Nursing leadership, nursing research (annotated bibliography),

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APA format

1) Minimum 23 pages  (No word count per page)- Follow the 3 x 3 rule: minimum of three paragraphs per page

You must strictly comply with the number of paragraphs requested per page.

.

           Part 1: minimum  4 pages

           Part 2: minimum  6 pages

           Part 3: minimum  4 pages

           Part 4: minimum  4 pages

           Part 5: minimum  1 page (20 hours)

           Part 6: minimum  1 page (20 hours)

           Part 7: minimum  3 pages (20 hours)

Submit 1 document per part

2)¨******APA norms

         All paragraphs must be narrative and cited in the text- each paragraph

         The writing must be coherent, using connectors or conjunctive to extend, add information, or contrast information. 

         Bulleted responses are not accepted

         Don’t write in the first person 

         Don’t copy and paste the questions.

         Answer the question objectively, do not make introductions to your answers, answer it when you start the paragraph

Submit 1 document per part

3)****************************** It will be verified by Turnitin (Identify the percentage of exact match of writing with any other resource on the internet and academic sources, including universities and data banks) 

********************************It will be verified by SafeAssign (Identify the percentage of similarity of writing with any other resource on the internet and academic sources, including universities and data banks)

4) Minimum 3 references (APA format) per part not older than 5 years  (Journals, books) (No websites)

Part 1:  Minimum 8 references (APA format) per part not older than 5 years  (Journals, books) (No websites)

Part 2:  Minimum 8 references (APA format) per part not older than 5 years  (Journals, books) (No websites)

Part 3:   References (APA format)  should only refer to the  6 attached articles 

Part 4:   References (APA format)  should only refer to the  6 attached articles  

All references must be consistent with the topic-purpose-focus of the parts. Different references are not allowed.

5) Identify your answer with the numbers, according to the question. Start your answer on the same line, not the next

Example:

Q 1. Nursing is XXXXX

Q 2. Health is XXXX

6) You must name the files according to the part you are answering: 

Example:

Part 1.doc 

Part 2.doc

__________________________________________________________________________________

Part 1: Nursing Leadership (40 hours)

Topic: Creating a No Bullying Unit Environment

Issue: Bullying in nursing

Your role: Nurse Leader 

Purpose: Addressing and solving the topic

From your role:

1. Introduce the issue (One paragraph)

2. Describe two scholarly pap3rs that addressed the issue (two paragraphs: One paragraph for the perspective and One paragraph for the proposal)

a. Describe the perspective from the scholarly pap3rs about the issue

b. Describe the proposal to solve the issue from each scholarly pap3r

3. Describe three implications of the issue for nurse leaders (Two paragraphs)

4. Describe how the issue impacts 3 (three) nurse activities (Two paragraphs)

5. Describe how the nurse leader should address the issue (One paragraph)

6. Desing and describe one proposal to solve the issue (One paragraph)

7. Describe the outcomes of the proposal (One paragraph)

8. Describe the benefits of solving the problem for (One paragraph):

a. Patients

b. Nurses

c. System health care

9. Conclusion (One paragraph)

Part 2: Nursing Leadership (60 hours)

Topic:   Future of Nursing Leadership.

1. Introduction (One paragraph)

2. From an academic perspective, How should future Nursing Leaders prepare themselves? (Two paragraphs)

3. From a clinic and practice perspective, How should future Nursing Leaders prepare themselves? (Two paragraphs)

4. What are the practices expected of an ideal nurse leader (Three paragraphs: One paragraph for patients, One paragraph for nurses, One paragraph for System Health )

a. What expect the patients?

b. What expect the nurses?

c. What expect the System Health?

5. Describe three specifics aspect that differentiates a nurse leader from an ideal nursing leader (Three paragraphs: One paragraph for each differentiating aspect)

6. How does the ideal nurse leader contribute to the future of Nursing Practice?  (Two paragraphs)

7. How do you plan to contribute to the future of Nursing Practice?  (Two paragraphs)

8. What do you expect in the future of Nursing Practice?  (Two paragraphs)

9. Conclusion (One paragraph)

10. Recommendations (One paragraph)

Part 3: Nursing Research (40 hours)

Annotated bibliography (APA format)

PICOT question:

it is unknown if implementing an educational program about administering IV antibiotics to nurses will reduce Iv antibiotic errors in geriatric patients compared with the error rate before the training within one month of the implementation of the educational program.

Annotated bibliography (Mandatory)

Use only the six (6) attached documents to make an annotated bibliography.

A half page for each article (Two articles per page)

Answer points 2 and 6 for each document attached in a single paragraph in narrative format.

1. Introduction to the topic and describe the annotated bibliography’s importance (One paragraph)-  No per each article

According to the six (6) research pap3er attached:

2. Describe the purpose of the article in dimple words of each article

3.  Describe the research question if applied 

4.  Briefly describe the scientific method used in each article

5.  Summarize the results of each article

6.  Summarize the conclusion  of each article
 

7. Conclusion from the Annotated bibliography, including the six articles’ findings (Two paragraphs)- No per each article

Part 4: Nursing Research (60 hours)

Annotated bibliography (APA format)

PICOT question:

  

Will falls in patients with medical equipment/support in med-surge settings be reduced after nurses participate in a fall prevention program in comparison with the amount of falls before the educational program in ten weeks?

Annotated bibliography (Mandatory)

Use only the six (6) attached documents to make an annotated bibliography.

A half page for each article (Two articles per page)

Answer points 2 and 6 for each document attached in a single paragraph in narrative format.

1. Introduction to the topic and describe the annotated bibliography’s importance (One paragraph)-  No per each article

According to the six (6) research pap3er attached:

2. Describe the purpose of the article in dimple words of each article

3.  Describe the research question if applied 

4.  Briefly describe the scientific method used in each article

5.  Summarize the results of each article

6.  Summarize the conclusion  of each article
 

7. Conclusion from the Annotated bibliography, including the six articles’ findings (Two paragraphs)- No per each article

Part 5: Pathophysiology (20 hours)

 

Sixty-two–year-old James White is accompanied to the clinic today by his wife and son. James has had increasing problems with his memory for the past several months and has rapid mood swings for no apparent reason. His wife says that “he’ll go outside in the garden without his clothes on, and his speech is difficult to understand.” His son reports that at times James flaps his arms a lot and notices that he is unable to cut his food or tie his shoes. James was diagnosed with heart failure approximately 6 months ago.

1. How would you explain to the White family what is occurring with James? (One paragraph)

2. What treatment modalities would be appropriate for James at this time? (One paragraph)

3. What are the outcomes expected from treatment? (One paragraph)

Part 6: Health Promotion  (20 hours) 

 

 

Health promotion initiative:   

 Infection Prevention and Spread in Patients with Foley Catheters
 

Implementation of standardized catheter removal protocols increases compliance with the best care practice. Lastly, streamlining communication improves clinician discussion when caring for a patient using a foley catheter. Also, it improves the handover process. The expected outcomes are; a decline in CAUTI prevalence rate, high compliance with CDC guidelines for preventing CAUTI, and improved communication between clinicians 

1. Describe three possible settings/community locations to implement your health promotion initiative and explain why? (Two paragraphs)

2. Share the advantages and disadvantages of each setting to meet your goals (One paragraph)

Part 7: Advanced pathophysiology (20 hours)

  

Answer in paragraph format each of the questions that are indicated. That is, you must objectively answer each of the questions in the order indicated.

Cardiovascular diseases are…….Coronary artery disease (CAD) is…….. Cardiac arrhythmia is ……

 

  

One paragraph

1. Skin functions

2. Layers of skin. 

a. Which layer is produced Keratin and melanin?

3. Which are dermal appendages?

4. Which system regulates blood supply to the skin?

One paragraph

5. Eccrine vs Apocrine glands: 

a. Location

b. Differences

c. Functions.

6. Primary vs secondary skin lesions. 

a. Examples of each group.

7. Mention al primary skin lesions and describe it.

One paragraph

8. Describe all Skin Cancers and features for each.

9. What is pressure injury? 

a. Describe stages of it.

One paragraph

10. What is a keloid and why it occurs?

11. Mention inflammatory disorders of the skin and concept for each of it.

One paragraph

12. Psoriasis and features of it.

13. Acne Vulgaris and features of it.

14. Hidradenitis Suppurative and features of it.

One paragraph

15. Acne rosacea and features of it.

16. Lupus Cutaneous and features of it.

17. Folliculitis vs Furuncles

One paragraph

18. Celullitis vs erysipelas. 

a. Etiology 

b. Clinical features.

19. HSV-1 vs HSV-2

20. Shingles vs Chickenpox (Varicella Zoster Virus)

One paragraph

21. Tnieas fungal Infections: types depending on location.

22. Urticaria: why occur?, Lesions and symptoms.

23. What is actinic Keratosis? 

One paragraph

24. What is the ABCDE rule for suspected skin lesions for Melanoma assessment?

25. Kaposi Sarcoma, what isthis type of lesion and in which type of patients is present?

26. Paronychia vs Onychomycosis

Association of Adverse Events With Antibiotic Use
in Hospitalized Patients
Pranita D. Tamma, MD, MHS; Edina Avdic, PharmD, MBA; David X. Li, BS;
Kathryn Dzintars, PharmD; Sara E. Cosgrove, MD, MS

A ntibiotic use is common in the inpatient setting.Approximately 50% of hospitalized patients receive atleast 1 antibiotic during their hospital stay,1 with an es-
timated 20% to 30% of inpatient days of antibiotic therapy con-
sidered unnecessary.2-6 The reasons for antibiotic overuse are
myriad, including administration of antibiotics for nonbacte-
rial or noninfectious syndromes, treatment of conditions
caused by colonizing or contaminating organisms, and dura-
tions of therapy that are longer than indicated. Unnecessary
use of antibiotics is particularly concerning because antibiot-
ics may be associated with a number of adverse drug events
(ADEs), including allergic reactions, end-organ toxic effects,

subsequent infection with antibiotic-resistant organisms, and
Clostridium difficile infections (CDIs).7-12

Estimates of the incidence of antibiotic-associated ADEs
in hospitalized patients are generally unavailable. Previ-
ously, Shehab and colleagues13 conducted a retrospective analy-
sis of ADEs among patients presenting to emergency depart-
ments and found that antibiotics were implicated in 19% of all
emergency department visits for ADEs. It is unclear whether
these data are generalizable to hospitalized patients for a num-
ber of reasons: (1) acutely ill hospitalized patients may be pre-
disposed to certain ADEs, such as antibiotic-associated neph-
rotoxic effects, particularly those admitted with acute renal

IMPORTANCE Estimates of the incidence of overall antibiotic-associated adverse drug events
(ADEs) in hospitalized patients are generally unavailable.

OBJECTIVE To describe the incidence of antibiotic-associated ADEs for adult inpatients
receiving systemic antibiotic therapy.

DESIGN, SETTING, AND PARTICIPANTS Retrospective cohort of adult inpatients admitted to
general medicine wards at an academic medical center.

EXPOSURES At least 24 hours of any parenteral or oral antibiotic therapy.

MAIN OUTCOMES AND MEASURES Medical records of 1488 patients were examined for 30
days after antibiotic initiation for the development of the following antibiotic-associated
ADEs: gastrointestinal, dermatologic, musculoskeletal, hematologic, hepatobiliary, renal,
cardiac, and neurologic; and 90 days for the development of Clostridium difficile infection or
incident multidrug-resistant organism infection, based on adjudication by 2 infectious
diseases trained clinicians.

RESULTS In 1488 patients, the median age was 59 years (interquartile range, 49-69 years),
and 758 (51%) participants were female. A total of 298 (20%) patients experienced at least
1 antibiotic-associated ADE. Furthermore, 56 (20%) non–clinically indicated antibiotic
regimens were associated with an ADE, including 7 cases of C difficile infection. Every
additional 10 days of antibiotic therapy conferred a 3% increased risk of an ADE. The most
common ADEs were gastrointestinal, renal, and hematologic abnormalities, accounting for 78
(42%), 45 (24%), and 28 (15%) 30-day ADEs, respectively. Notable differences were
identified between the incidence of ADEs associated with specific antibiotics.

CONCLUSIONS AND RELEVANCE Although antibiotics may play a critical role when used
appropriately, our findings underscore the importance of judicious antibiotic prescribing to
reduce the harm that can result from antibiotic-associated ADEs.

JAMA Intern Med. 2017;177(9):1308-1315. doi:10.1001/jamainternmed.2017.1938
Published online June 12, 2017.

Author Affiliations: Division of
Pediatric Infectious Diseases,
Department of Pediatrics, Johns
Hopkins University School of
Medicine, Baltimore, Maryland
(Tamma); Department of Pharmacy,
Johns Hopkins Hospital, Baltimore,
Maryland (Avdic, Dzintars); Division
of Infectious Diseases, Department of
Medicine, Johns Hopkins University
School of Medicine, Baltimore,
Maryland (Li, Cosgrove).

Corresponding Author: Pranita D.
Tamma, MD, MHS, Division of
Pediatric Infectious Diseases,
Department of Pediatrics,
Johns Hopkins University
School of Medicine,
200 N Wolfe St, Ste 3149,
Baltimore, MD 21287
([email protected]).

Research

JAMA Internal Medicine | Original Investigation

1308 JAMA Internal Medicine September 2017 Volume 177, Number 9 (Reprinted) jamainternalmedicine.com

© 2017 American Medical Association. All rights reserved.

Downloaded From: https://jamanetwork.com/ on 08/01/2022

failure for non–antibiotic-related reasons; (2) hospitalized pa-
tients are frequently administered intravenous antibiotic
therapy, often at high doses, which may have different ad-
verse event profiles than the oral regimens more commonly
prescribed in the outpatient setting14; (3) hospitalized pa-
tients are commonly administered multiple medications con-
currently, causing a potentially synergistic increase in the risk
of ADE development15; and (4) hospitalized patients are more
likely to be elderly or have multiple medical conditions, re-
sulting in impaired drug elimination and an increased risk of
ADE development.16,17 Previous studies evaluating antibiotic-
associated ADEs in the inpatient setting have used adminis-
trative databases and have not accounted for antibiotic-
associated ADEs that occurred after hospital discharge.18,19

Additionally, they have limited their evaluation of ADEs to
single antibiotic classes or single infectious syndromes.18-21 A
comparative analysis of the incidence of ADEs across all classes
of antibiotics has yet to be performed. Therefore, in the pre-
sent study, we sought to describe the incidence of antibiotic-
associated ADEs for adult inpatients receiving systemic anti-
biotic therapy while hospitalized in general medicine wards.

Methods
Setting and Patients
This study was conducted at the Johns Hopkins Hospital, a 1194-
bed tertiary care facility in Baltimore, Maryland. This study was
approved by the Johns Hopkins University School of Medicine
Institutional Review Board, with a waiver of informed consent
due to the retrospective nature of the study. The data were ret-
rospectively collected on patients 18 years and older admitted
to 4 general medicine services between September 2013 and
June 2014.6 All patients who received antibiotics for at least 24
hours were included. Exclusion criteria included prophylactic
antibiotic use with no clear stop dates, antibiotics used for non-
infectious indications (eg, rifaximin for hepatic encephalopa-
thy, erythromycin for intestinal motility), topical or inhaled
antibiotics, and antituberculosis regimens.

Data Collection and Definitions
Demographic data, preexisting medical conditions, antibi-
otic regimens, and ADEs were collected via patient medical rec-
ord review. Both inpatient and outpatient medical records were
reviewed to obtain follow-up data for patients in the Johns
Hopkins Health System. In addition, the Epic Care Everywhere
Network, a secure health information exchange, was ac-
cessed to view patient data from a large number of health care
facilities throughout the United States.22 This enabled the iden-
tification of patients presenting to outside emergency depart-
ments, hospitals, or primary care clinics with antibiotic-
associated ADEs, if these facilities were in the Epic system.

All antibiotic regimens were adjudicated for appropriate-
ness and associated ADEs by at least 2 infectious diseases phy-
sicians or pharmacists (P.D.T., E.A., K.D., and S.E.C.). Days of
therapy (DOTs) were defined as the number of days from
antibiotic initiation until the completion of antibiotic courses.
A single DOT was recorded for each individual antibiotic

administered to a patient on a given calendar day. Unneces-
sary antibiotic days were defined as DOTs that were not clini-
cally indicated based on recommendations in the Johns
Hopkins Hospital Antibiotic Guidelines.23 For calculations of
overall rates of ADEs, the denominator included all patients
receiving antibiotics (n = 1488). For calculations involving a
single antibiotic, the denominator included only patients
receiving that particular antibiotic.

Avoidable ADEs were defined as the proportion of overall
ADEs that occurred in patients for whom antibiotic therapy was
considered not indicated. Nonindicated antibiotic regimens did
not include patients with prolonged durations of therapy be-
cause our goal was to determine the incidence of adverse re-
actions for patients for whom no antibiotic therapy was nec-
essary. For example, if a patient received ciprofloxacin for 15
days for pyelonephritis when 7 days would have been suffi-
cient and the patient developed tendinitis on day 16, one would
be unable to attribute the adverse event to the 7 indicated days
of ciprofloxacin use or the additional 8 days of unnecessary
ciprofloxacin use. We also did not consider overly broad spec-
trum antibiotic therapy prescribed for valid indications as not
indicated because of the impossibility of knowing whether the
patient would or would not have developed an ADE with a nar-
rower choice, particularly in the same class of antibiotics.

Criteria used to define antibiotic-associated ADEs are sum-
marized in Table 1. These definitions were derived from avail-
able literature, package inserts, and/or consensus opinions prior
to any data collection related to the present work. Patients were
observed for 30 days from the date of antibiotic initiation for
most ADEs (gastrointestinal, dermatologic, musculoskeletal,
hematologic, hepatobiliary, renal, cardiac, and neurologic
events) and for 90 days from the date of antibiotic initiation
for CDI and the development of multidrug-resistant organ-
ism (MDRO) infections not previously identified. All ADEs other
than CDI or incident MDRO infections were censored at 30 days
due to concerns for underestimating the incidence if a longer
evaluation period was used because these ADEs generally
occur during exposure to particular antibiotics or shortly there-
after. In contrast, data suggest that CDI and the emergence of
MDRO infections can become clinically apparent several weeks
to months after discontinuing antibiotic therapy.26,27

Key Points
Question What is the likelihood of developing antibiotic-
associated adverse drug events (ADEs) for hospitalized patients
receiving antibiotic therapy?

Findings In this cohort study, medical records of 1488 adult
inpatients were examined for 30 days after antibiotic initiation for
the development of the following antibiotic-associated ADEs:
gastrointestinal, dermatologic, musculoskeletal, hematologic,
hepatobiliary, renal, cardiac, and neurologic; and 90 days for the
development of Clostridium difficile infection or incident
multidrug-resistant organism infection. Twenty percent of patients
experienced at least 1 antibiotic-associated ADE.

Meaning These findings underscore the importance of judicious
antibiotic prescribing to reduce the harm that can result from
antibiotic-associated ADEs.

Adverse Events and Antibiotic Use in Hospitalized Patients Original Investigation Research

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All potential ADEs were adjudicated in the context of the pa-
tient’s medical history and clinical course to ensure that each
event was likely to have been antibiotic associated, both to rule
out alternative explanations and to appropriately categorize
ADEs. Each ADE was then attributed to a single antibiotic, based
on the likelihood of that antibiotic causing the specific ADE and
the temporal relationship of the antibiotic’s administration to the
ADE. For example, acute kidney injury in a patient receiving van-
comycin and cefepime would have been attributed to vancomy-
cin use only. This step was performed to avoid overestimating
the incidence of ADEs because most patients in our cohort re-
ceived multiple antibiotics during their hospital stays. However,
because virtually all antibiotics can cause CDI or the emergence
of MDRO infections, the development of either of these 90-day
ADEs was attributed to all preceding antibiotic used.

Statistical Analysis
Rates per 10 000 person-days and 95% confidence intervals
were calculated for each ADE and antibiotic class. For 30-day
ADEs, the numerator was the number of ADEs attributed to
each antibiotic or class of antibiotics. The denominator was the
person-time at risk for all patients who received that particu-
lar antibiotic or class of antibiotics, computed as the time, in
days, from antibiotic initiation to the ADE for patients who ex-
perienced the ADE, with censoring at 30 days for patients who
did not experience the ADE. The proportion of 30-day anti-
biotic-associated ADEs per antibiotic or antibiotic class and the
proportion of patients receiving a particular antibiotic or
antibiotic class who developed a 30-day ADE were also calcu-

lated. For 90-day ADEs, the numerator accounted for all pre-
ceding antibiotics rather than only a single antibiotic. The de-
nominator was the person-time at risk for all patients who
received antibiotics, computed as the time, in days, from
antibiotic initiation to ADE onset, with censoring at 90 days.
Hazard ratios were calculated to identify the incremental risk
of an ADE conferred by each additional day of antibiotic use.
All analyses were performed using Stata 13 (StataCorp).

Results
Antibiotic Regimens
Of the 5579 patients admitted to the 4 included medicine wards
during the study period, 1488 (27%) patients received anti-
biotics for at least 24 hours and were included in the analysis.
Previous work describes the demographic data, preexisting
medical conditions, sources of infection, and “appropriate-
ness” of antibiotic use of the included population in more
detail.6 In brief, the median age was 59 years (interquartile
range [IQR], 49-69 years) and 758 (51%) participants were
female. The most common underlying medical conditions were
diabetes (491 [33%]), structural lung disease (327 [22%]), and
congestive heart failure with an ejection fraction of less than
40% (178 [12%]). The median length of hospital stay was 4 days
(IQR, 2-9 days). The most common indications for antibiotic
therapy were urinary tract infections (179 [12%]), skin and
soft-tissue infections (119 [8%]), and community-acquired
pneumonia (104 [7%]).

Table 1. Criteria Used for Antibiotic-Associated Adverse Drug Events

Adverse Drug Event Definition
Within 30 d of Antibiotic Initiation

Non–Clostridium
difficile–associated diarrhea

>3 Loose stools per day associated with antibiotic administration and documented as “diarrhea” in the medical record,
in the absence of laxative use or preexisting enteritis. Patients with a positive C difficile PCR test result were excluded
from this category

Nausea and vomiting Nausea and vomiting associated with antibiotic administration, in the absence of an alternate explanation

Hematologic Anemia (hemoglobin level <10 g/dL), leukopenia (white blood cell count <4500 cells/μL), or thrombocytopenia (platelet
count <150 × 103/μL) with levels below patient’s baseline and in the absence of bleeding or myelosuppressive therapies

Hepatobiliary Cholestasis (total bilirubin level >3 mg/dL) or transaminitis (aspartate transaminase or alanine transaminase level
>3 times patient’s baseline) in the absence of existing hepatobiliary disease or recent biliary instrumentation

Renal Increase in serum creatinine level >1.5 times patient’s baseline in the absence of precipitating factors for acute kidney
injury such as sepsis or the receipt of intravenous contrast or other nephrotoxic agents24

Neurologic Altered mental status, peripheral neuropathy, or seizures in the absence of preexisting neurologic conditions,
substance-related toxic effects, or infectious syndromes

Dermatologic Rash, including hives, nonhives rashes, and red man syndrome, temporally associated with antibiotic administration
with resolution on antibiotic discontinuation; excluding vancomycin-associated red man syndrome

Cardiac QTc >440 ms in males or >460 ms in females in the absence of preexisting arrhythmias, based on ≥2 electrocardiograms

Anaphylaxis Acute onset of respiratory compromise, hypotension, or end-organ dysfunction within minutes after initiation
of antibiotic administration, in the absence of an alternative explanation

Myositis Increase in creatine phosphokinase level >5 times patient’s baseline, in the absence of existing myopathy or statin use

Within 90 d of Antibiotic Initiation

C difficile infection Clinical signs and symptoms consistent with C difficile infection in the setting of a positive C difficile PCR test result
and the absence of laxative use

Infection with
MDR organism25

Infection with any of the following organisms, in a patient without a history of colonization or infection with the same
organism: methicillin-resistant Staphylococcus aureus; vancomycin-resistant enterococci; carbapenem-resistant
Enterobacteriaceae; MDR Acinetobacter; MDR Pseudomonas; or a gram-negative organism with a greater than 2-fold
increase in the minimum inhibitory concentration of an antibiotic compared with the initial infection

Abbreviations: MDR, multidrug-resistant; PCR, polymerase chain reaction.

SI conversion factors: To convert hemoglobin to grams per liter, multiply by 10.0; to convert white blood cell count to ×109 per liter, multiply by 0.001; to convert
platelet count to ×109 per liter, multiply by 1.0; to convert bilirubin to micromoles per liter, multiply by 17.104.

Research Original Investigation Adverse Events and Antibiotic Use in Hospitalized Patients

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The most frequently prescribed antibiotics were third-
generation cephalosporins (607 [41%] regimens), parenteral
vancomycin (544 [37%] regimens), and cefepime (414 [28%]
regimens) (Table 2). The majority of patients (1176 [79%]) re-
ceived more than 1 antibiotic during the hospitalization. The
median DOTs per patient was 7 days (IQR, 4-14 days). A total
of 324 unique ADEs occurred; 298 (20%) patients experi-
enced at least 1 antibiotic-associated ADE. The overall rate of
antibiotic-associated ADEs was 22.9 per 10 000 person-days.

Every additional 10 antibiotic DOTs conferred a 3%
increased risk of an ADE. A total of 236 (73%) antibiotic-
associated ADEs occurred during hospitalization and the re-
maining 88 (27%) occurred after hospital discharge including
33 (18%) 30-day ADEs, 11 (20%) CDIs, and 44 (52%) MDRO in-
fections. The study investigators determined that 287 (19%)
of antibiotic regimens were not clinically indicated, most com-
monly because of treatment of asymptomatic bacteriuria or
treatment of noninfectious lower respiratory tract conditions
(eg, aspiration pneumonitis, congestive heart failure).6 Of the
287 nonindicated antibiotic regimens, 56 (20%) were associ-
ated with an ADE.

30-Day ADEs
Of the 324 overall ADEs, 186 (57%) were 30-day ADEs. The me-
dian time to development of a 30-day ADE was 5 days (IQR,
3-8 days). The median times to 30-day ADEs for the various
organ systems were as follows: cardiac, 11 days (IQR, 4-18 days);
gastrointestinal, 5 days (IQR, 2-9 days); hematologic, 12 days
(IQR, 6-24 days); hepatobiliary, 8 days (IQR, 4-12 days); renal,
5 days (IQR, 2-10 days); and neurologic, 3 days (IQR, 2-4 days).
The most common ADEs were gastrointestinal, renal, and he-
matologic abnormalities, accounting for 78 (42%), 45 (24%),
and 28 (15%) 30-day ADEs, respectively (Table 2). Table 3 and
Table 4 outline the proportions of 30-day ADEs attributable
to specific antibiotics or antibiotic classes and the proportion
of patients receiving a specific antibiotic or antibiotic class who
developed 30-day ADEs, respectively.

Aminoglycosides, parenteral vancomycin, and trimetho-
prim-sulfamethoxazole were associated with the highest rates
of nephrotoxic effects at 21.2 (95% CI, 12.5-66.0), 12.1 (95% CI,
7.7-19.0), and 13.2 (95% CI, 5.9-29.3) episodes per 10 000 per-
son-days, respectively (Table 2). Two patients experienced QTc
prolongation—1 receiving azithromycin and 1 receiving cipro-
floxacin after 4 and 18 days of therapy, respectively. Seven pa-
tients (6.7 [95% CI, 2.7-12.0] episodes per 10 000 person-
days) receiving cefepime developed neurotoxic effects,
including encephalopathy or seizures. Less frequent 30-day
ADEs, all occurring in single patients, included cefepime-
associated anaphylaxis, piperacillin-tazobactam–associated
drug fever, daptomycin-associated myositis, ciprofloxacin-
associated tendinitis, trimethoprim-sulfamethoxazole–
associated pancreatitis, linezolid-associated peripheral
neuropathy, vancomycin-associated hives, and a trimethoprim-
sulfamethoxazole–associated nonhives rash.

90-Day ADEs
There were 138 ADEs occurring within 90 days, accounting for
43% of all ADEs. Of these 138 ADEs, 54 (39%) were CDI and 84

(61%) were MDRO infections. The median time to develop-
ment of a 90-day ADE was 15 days (IQR, 4-34 days). The rate
of CDI was 3.9 (95% CI, 3.0-5.2) per 10 000 person-days for pa-
tients receiving antibiotics, corresponding to 54 (4%) study pa-
tients developing CDI within 90 days of antibiotic initiation.
The antibiotics most frequently associated with CDI were third-
generation cephalosporins (present in 28 [52%] regimens pre-
ceding CDI), cefepime (26 [48%] regimens), and fluoroquino-
lones (19 [35%] regimens).

The rate of emergence of incident MDRO infections was
6.1 (95% CI, 4.9-7.6) per 10 000 person-days, corresponding
to 84 [6%] study patients developing an infection with a new
MDRO within 90 days of antibiotic initiation. Subsequent gram-
positive resistance was observed in 60 (4%) patients, at a rate
of 4.8 (95% CI, 3.7-6.1) cases per 10 000 person-days. Forty
(67%) of the MDRO c ases were related to vancomyc in-
resistant enterococci infections. Gram-negative resistance
occurred less frequently at a rate of 1.7 (95% CI, 1.2-2.6) cases
per 10 000 person-days, or in 30 (2%) patients, with extended-
spectrum β-lactamase production being the most common
resistance mechanism identified.

Clinically Significant ADEs
Antibiotic-associated ADEs were then categorized into clini-
cally significant and non–clinically significant categories. Only
1 category was selected per patient, with the more severe cat-
egory selected when multiple categories were met. A total of
314 (97%) of the 324 antibiotic-associated ADEs were consid-
ered clinically significant because of the following reasons: new
hospitalization(s) (n = 10 [3%]), prolonged hospitalization
(n = 77 [24%]), additional clinic or emergency department vis-
its (n = 29 [9%]), and additional laboratory tests, electrocar-
diograms, or imaging (n = 198 [61%]). There were no deaths
attributable to any antibiotic-associated ADE.

Discussion
We found that 20% of hospitalized patients receiving at least
24 hours of antibiotic therapy developed an antibiotic-
associated ADE. Moreover, 20% of ADEs were attributable to
antibiotics prescribed for conditions for which antibiotics were
not indicated. Every 10 DOTs conferred an additional 3% risk
of an ADE. Our findings underscore the importance of avoid-
ing unnecessary antibiotic prescribing to reduce the harm that
can result from antibiotic-associated ADEs.

Previous studies on antibiotic-associated ADEs in the in-
patient setting have largely been limited to single infectious
syndromes or single antibiotic classes.18-21,28 For example, Lin
and colleagues18 evaluated the incidence of antibiotic-
associated ADEs using an administrative database of hospi-
talized patients with pneumonia. They found that even though
less than 1% of patients developed ADEs, the presence of an
antibiotic-associated ADE was an independent predictor of
prolonged hospital lengths of stay and total hospital charges.
Werner et al20 evaluated the frequency of adverse events re-
lated to unnecessary fluoroquinolone use in hospitalized
patients based on medical record review. They found that

Adverse Events and Antibiotic Use in Hospitalized Patients Original Investigation Research

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.

Research Original Investigation Adverse Events and Antibiotic Use in Hospitalized Patients

1312 JAMA Internal Medicine September 2017 Volume 177, Number 9 (Reprinted) jamainternalmedicine.com

© 2017 American Medical Association. All rights reserved.

Downloaded From: https://jamanetwork.com/ on 08/01/2022

approximately 40% of days of fluoroquinolone therapy were
unnecessary and 27% of regimens were associated with ad-
verse events including gastrointestinal events (14%), MDRO
colonization (8%), and CDI (4%). Finally, Macy and Contreras19

evaluated the incidence of cephalosporin-associated ADEs
using an administrative database and found that the most
frequently reported serious ADEs were CDI, occurring in ap-
proximately 1% of patients.

We believe that our study enhances these investigations
in a number of ways. First, unlike previous studies, we evalu-
ated antibiotic-associated ADEs that occurred in both the in-
patient setting as well as the outpatient setting after hospital
discharge, enabling us to produce a more global picture of the
overall incidence of antibiotic-associated ADEs.13,18,19,29 Our
previous work suggests that approximately 40% of antibiot-
ics prescribed for hospitalized patients represent antibiotics
prescribed at the time of hospital discharge that are to be con-
tinued after leaving the hospital.6 We believe that it is impor-

tant to include these antibiotic days in estimates of antibiotic-
associated adverse events for hospitalized patients. Second,
in our cohort, infectious diseases physicians and pharma-
cists reviewed all patient medical records to identify ADEs and
to determine whether they were most likely attributable to re-
cent or current antibiotic use using strict, predefined criteria.
In contrast, previous studies have generally used administra-
tive databases, in which relevant events are commonly mis-
coded and through which attributable risk cannot always be
assigned.13,18 Furthermore, we did not limit our evaluation to
specific antibiotic classes but, rather, included all antibiotic
classes.

Limitations
Our study has a number of limitations. This was a single-
center study at an academic hospital with a medically com-
plex patient population. Replication of our results at other in-
stitutions and in other patient populations is necessary to

Table 3. Proportion of 30-Day Antibiotic-Associated Adverse Drug Events in 1488 Hospitalized Patients Receiving Systemic Antibiotic Therapya

Antibiotic Agent

No. of
Patients
Receiving
Agent

No. (%)

Cardiac
Gastro-
intestinalb Hematologic

Hepato-
biliary Renal Neurologic

Other
Eventsc

β-Lactamsd 1187 0 59 (5.0) 27 (2.3) 6 (0.5) 17 (1.4) 10 (0.8) 2 (0.2)

Ampicillin 63 0 2 (3.2) 1 (1.6) 1 (1.6) 1 (1.6) 0 0

Amoxicillin-
clavulanate

102 0 3 (2.9) 0 0 0 0 0

Ampicillin-
sulbactam

52 0 1 (1.9) 0 0 2 (3.8) 0 0

Oxacillin 33 0 4 (12.1) 1 (3.0) 2 (6.0) 0 0 0

Piperacillin-
tazobactam

315 0 16 (5.1) 4 (1.3) 1 (0.3) 1 (0.3) 1 (0.3) 1 (0.3)

Cefazolin 79 0 0 1 (1.3) 0 2 (2.5) 0 0

Ceftriaxone 607 0 14 (2.3) 11 (1.8) 3 (0.5) 5 (0.8) 1 (0.2) 0

Cefpodoxime 89 0 2 (2.2) 0 0 0 0 0

Cefepime 414 0 10 (2.4) 6 (1.4) 0 6 (1.4) 7 (1.7) 1 (0.2)

Ertapenem 85 0 3 (3.5) 0 0 0 0 0

Meropenem 80 0 4 (5.0) 3 (3.8) 0 0 1 (1.3) 0

Non–β-lactams

Aminoglycosides 32 0 0 0 0 2 (6.3) 0 0

Azithromycin 400 1 (0.3) 1 (0.3) 0 4 (1.0) 0 0 0

Clindamycin 193 0 3 (1.6) 0 0 0 0 0

Daptomycin 8 0 0 0 0 0 0 1 (12.5)

Doxycycline 57 0 2 (3.5) 0 0 0 0 0

Fluoroquinolones 394 1 (0.3) 5 (1.3) 1 (0.3) 3 (0.8) 1 (0.3) 1 (0.3) 1 (0.3)

Linezolid 23 0 0 0 0 0 1 (4.3) 0

Metronidazole 175 0 1 (0.6) 0 0 0 1 (0.6) 0

Trimethoprim-
sulfamethoxazole

155 0 5 (3.2) 0 0 6 (3.9) 0 1 (0.6)

Intravenous
vancomycin

544 0 2 (0.4) 0 0 19 (3.5) 0 2 (0.4)

Any antibiotics 1488e 2 (0.1) 78 (5.2) 28 (1.9) 13 (0.9) 45 (3.0) 13 (0.9) 7 (0.5)
a The following regimens are included in the overall rates and resulted in no

30-d adverse drug events: penicillin (21), amoxicillin (47), dicloxacillin (1),
cephalexin (44), second-generation cephalosporins (38), ceftazidime (6),
ceftaroline (8), aztreonam (22), fosfomycin (10), nitrofurantoin (26),
tigecycline (3), oral vancomycin (84).

b Includes nausea, emesis, non–Clostridium difficile–associated diarrhea.
c Other adverse drug events include cefepime-associated anaphylaxis (1),

piperacillin-tazobactam–associated drug fever (1), ciprofloxacin-associated
tendinitis (1), daptomycin-associated myositis (1), trimethoprim-
sulfamethoxazole–associated pancreatitis (1), vancomycin-associated hives (1),
and trimethoprim-sulfamethoxazole-associated nonhives rash (1).

d Some patients received more than 1 β-lactam antibiotic.
e Most patients (1176 [79%]) received more than 1 antibiotic.

Adverse Events and Antibiotic Use in Hospitalized Patients Original Investigation Research

jamainternalmedicine.com (Reprinted) JAMA Internal Medicine September 2017 Volume 177, Number 9 1313

© 2017 American Medical Association. All rights reserved.

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enhance the generalizability of our findings. This would also
allow for ADE estimates for antibiotic agents not included on
our hospital formulary. Furthermore, because prescriptions of
some antibiotics were so infrequent (eg, penicillin, ceftaro-
line fosamil, tigecycline), accurate estimates of some drug-
specific ADEs could not be calculated. Our approximations of
antibiotic-associated ADEs are likely underestimations for a
number of reasons. First, our hospital has had a robust anti-
biotic stewardship program since 2002 that remained active
during the study period, likely reducing overall antibiotic pre-
scriptions, durations of antibiotic therapy, and consequently
antibiotic-associated ADEs. Second, we were unable to evalu-
ate data from patients who had follow-up medical care out-
side the Epic Care Everywhere network, for example those who
presented to primary care clinicians, emergency depart-
ments, or urgent care centers not using the Epic electronic
medical record system.22 Of note, only 119 (8%) patients were
considered lost to follow-up with no subsequent inpatient or

outpatient visits documented in the Epic Care Everywhere net-
work. Additionally, it is plausible that a portion of patients in
this cohort may have previously experienced serious antibiotic-
associated ADEs, leading to future avoidance of these agents
(eg, hives from penicillin use as a child), also potentially
underestimating the incidence of antibiotic-associated ADEs.
Finally, we did not include excessively prolonged durations of
antibiotic therapy or inappropriately broad antibiotic use
toward our calculation of avoidable antibiotic-associated ADEs,
likely underestimating this value.

Conclusions
In summary, antibiotic-associated ADEs are common among
inpatients receiving antibiotics, some of which may be avoid-
able with more judicious use of antibiotics. The frequency of
antibiotic-associated ADEs may not be recognized by clini-

Table 4. Proportion of 1488 Patients Receiving Systemic Antibiotic Therapy Who Developed Adverse Drug Events (ADEs) Within 30 Daysa

Antibiotic Agents

No. (%)

Total ADEs Cardiac
Gastro-
intestinalb Hematologic

Hepato-
biliary Renal Neurologic

Other
Eventsc

Any β-lactamd 121 (65.1) 0 59 (75.6) 27 (96.4) 6 (46.2) 17 (37.8) 10 (76.9) 2 (28.6)

Ampicillin 4 (2.2) 0 2 (2.6) 1 (3.6) 0 1 (2.2) 0 0

Amoxicilin-
clavulanate

3 (1.6) 0 3 (3.8) 0 0 0 0 0

Ampicillin-
sulbactam

3 (1.6) 0 1 (1.3) 0 0 2 (4.4) 0 0

Oxacillin 7 (3.8) 0 4 (5.1) 1 (3.6) 2 (15.4) 0 0 0

Piperacillin-
tazobactam

24 (12.9) 0 16 (20.5) 4 (14.3) 1 (7.7) 1 (2.2) 1 (7.7) 1 (14.3)

Cefazolin 3 (1.6) 0 0 1 (3.6) 0 2 (4.4) 0 0

Ceftriaxone 34 (18.3) 0 14 (17.9) 11 (39.3) 3 (23.1) 5 (11.1) 1 (7.7) 0

Cefpodoxime 2 (1.1) 0 2 (2.6) 0 0 0 0 0

Cefepime 30 (16.1) 0 10 (12.8) 6 (21.4) 0 6 (13.3) 7 (53.8) 1 (14.3)

Ertapenem 3 (1.6) 0 3 (3.8) 0 0 0 0 0

Meropenem 8 (4.3) 0 4 (5.1) 3 (10.7) 0 0 1 (7.7) 0

Non–β-lactams

Aminoglycosides 2 (1.1) 0 0 0 0 2 (4.4) 0 0

Azithromycin 6 (3.2) 1 (50.0) 1 (1.3) 0 4 (30.8) 0 0 0

Clindamycin 3 (1.6) 0 3 (3.8) 0 0 0 0 0

Daptomycin 1 (0.5) 0 0 0 0 0 0 1 (14.3)

Doxycycline 2 (1.1) 0 2 (2.6) 0 0 0 0 0

Fluoroquinolones 13 (7.0) 1 (50.0) 5 (6.4) 1 (3.6) 3 (23.1) 1 (2.2) 1 (7.7) 1 (14.3)

Linezolid 1 (0.5) 0 0 0 0 0 1 (7.7) 0

Metronidazole 2 (1.1) 0 1 (1.3) 0 0 0 1 (7.7) 0

Trimethoprim-
sulfamethoxazole

12 (6.5) 0 5 (6.4) 0 0 6 (13.3) 0 1 (14.3)

Intravenous
vancomycin

23 (12.4) 0 2 (2.6) 0 0 19 (42.2) 0 2 (28.6)

All antibioticse 186 (100) 2 (100) 78 (100) 28 (100) 13 (100) 45 (100) 13 (100) 7 (100)
a The following regimens are included in the overall rates and resulted in no

30-d adverse drug events: penicillin (21), amoxicillin (47), dicloxacillin (1),
cephalexin (44), second-generation cephalosporins (38), ceftazidime (6),
ceftaroline (8), aztreonam (22), fosfomycin (10), nitrofurantoin (26),
tigecycline (3), oral vancomycin (84).

b Includes nausea, emesis, non-Clostridium difficile–associated diarrhea.
c Other ADEs include cefepime-associated anaphylaxis (1), piperacillin-

tazobactam–associated drug fever (1), ciprofloxacin-associated tendinitis (1),
daptomycin-associated myositis (1), trimethoprim-sulfamethoxazole–
associated pancreatitis (1), vancomycin-associated hives (1), and
vancomycin-associated nonhives, non–red man syndrome rash (1).

d Some patients received more than 1 β-lactam antibiotic.
e Most patients (1176 [79%]) received more than 1 antibiotic.

Research Original Investigation Adverse Events and Antibiotic Use in Hospitalized Patients

1314 JAMA Internal Medicine September 2017 Volume 177, Number 9 (Reprinted) jamainternalmedicine.com

© 2017 American Medical Association. All rights reserved.

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cians because ADEs have varied manifestations, clinicians may
be unaware of the risks associated with specific antibiotic
agents, or because they may occur after patients are dis-
charged from the hospital. Our findings provide quantitative

data about the risk of ADEs that clinicians should consider
when weighing decisions to initiate or discontinue antibiotic
therapy and lend further credence to the importance of anti-
biotic stewardship to optimize patient safety.

ARTICLE INFORMATION

Accepted for Publication: April 6, 2017.

Published Online: June 12, 2017.
doi:10.1001/jamainternmed.2017.1938

Author Contributions: Dr Tamma had full access to
all of the data in the study and takes responsibility
for the integrity of the data and the accuracy of the
data analysis.
Study concept and design: Tamma, Avdic, Li,
Cosgrove.
Acquisition, analysis, or interpretation of data: All
authors.
Drafting of the manuscript: Tamma, Avdic, Li,
Dzintars.
Critical revision of the manuscript for important
intellectual content: Avdic, Li, Dzintars, Cosgrove.
Statistical analysis: Tamma, Li.
Obtained funding: Tamma, Avdic, Cosgrove.
Administrative, technical, or material support: Avdic,
Dzintars.
Supervision: Dzintars, Cosgrove.

Conflict of Interest Disclosures: None reported.

Funding/Support: This study was made possible
by an investigator-initiated grant from Pfizer
Independent Grants for Learning and Change and
The Joint Commission.

Role of the Funder/Sponsor: The funders had no
role in the design and conduct of the study;
collection, management, analysis, and
interpretation of the data; preparation, review, or
approval of the manuscript; and decision to submit
the manuscript for publication.

Additional Contributions: We thank Yuan Zhao,
MPH, Johns Hopkins University, and John Keenan,
MD, Johns Hopkins University, for their assistance
with data collection. Dr Keenan received a portion
of his salary from Pfizer/The Joint Commission.

REFERENCES

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Emerging Infections Program Healthcare-
Associated Infections and Antimicrobial Use
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2. Hecker MT, Aron DC, Patel NP, Lehmann MK,
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3. Camins BC, King MD, Wells JB, et al. Impact of an
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5. Cosgrove SE, Seo SK, Bolon MK, et al; CDC
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6. Tamma PD, Avdic E, Keenan JF, et al. What is the
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7. Bell BG, Schellevis F, Stobberingh E, Goossens H,
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8. Hensgens MP, Goorhuis A, Dekkers OM, Kuijper
EJ. Time interval of increased risk for Clostridium
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9. Liu NW, Shatagopam K, Monn MF, et al. Risk for
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10. Kuster SP, Rudnick W, Shigayeva A, et al;
Toronto Invasive Bacterial Diseases Network.
Previous antibiotic exposure and antimicrobial
resistance in invasive pneumococcal disease:
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11. Alshammari TM, Larrat EP, Morrill HJ, Caffrey
AR, Quilliam BJ, LaPlante KL. Risk of hepatotoxicity
associated with fluoroquinolones: a national
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12. Torres MJ, Blanca M, Fernandez J, et al; ENDA;
EAACI Interest Group on Drug Hypersensitivity.
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13. Shehab N, Patel PR, Srinivasan A, Budnitz DS.
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2008;47(6):735-743.

14. File TM Jr, Segreti J, Dunbar L, et al.
A multicenter, randomized study comparing the
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acquired pneumonia. Antimicrob Agents Chemother.
1997;41(9):1965-1972.

15. Hammond DA, Smith MN, Li C, Hayes SM,
Lusardi K, Bookstaver PB. Systematic review and
meta-analysis of acute kidney injury associated
with concomitant vancomycin and
piperacillin/tazobactam. Clin Infect Dis. 2017;64(5):
666-674.

16. Martin RM, Biswas PN, Freemantle SN, Pearce
GL, Mann RD. Age and sex distribution of suspected

adverse drug reactions to newly marketed drugs in
general practice in England: analysis of 48 cohort
studies. Br J Clin Pharmacol. 1998;46(5):505-511.

17. Pretorius RW, Gataric G, Swedlund SK, Miller JR.
Reducing the risk of adverse drug events in older
adults. Am Fam Physician. 2013;87(5):331-336.

18. Lin RY, Nuruzzaman F, Shah SN. Incidence and
impact of adverse effects to antibiotics in
hospitalized adults with pneumonia. J Hosp Med.
2009;4(2):E7-E15.

19. Macy E, Contreras R. Adverse reactions
associated with oral and parenteral use of
cephalosporins: a retrospective population-based
analysis. J Allergy Clin Immunol. 2015;135(3):
745-52.e5.

20. Werner NL, Hecker MT, Sethi AK, Donskey CJ.
Unnecessary use of fluoroquinolone antibiotics in
hospitalized patients. BMC Infect Dis. 2011;11:187.

21. Blumenthal KG, Kuhlen JL Jr, Weil AA, et al.
Adverse drug reactions associated with ceftaroline
use: a 2-center retrospective cohort. J Allergy Clin
Immunol Pract. 2016;4(4):740-746.

22. Epic Care Everywhere Network.
https://www.epic.com/CareEverywhere/. Accessed
December 6, 2016.

23. Johns Hopkins Medicine Antibiotic Guidelines
2015-2016. http://www.hopkinsmedicine.org/amp.
Accessed February 5, 2017.

24. Goldstein SL, Kirkendall E, Nguyen H, et al.
Electronic health record identification of
nephrotoxin exposure and associated acute kidney
injury. Pediatrics. 2013;132(3):e756-e767.

25. Centers for Disease Control and Prevention.
Antimicrobial resistant phenotype definitions.
https://www.cdc.gov/nhsn/pdfs/ps-analysis
-resources/phenotype_definitions.pdf. Accessed
January 26, 2017.

26. Anand A, Bashey B, Mir T, Glatt AE.
Epidemiology, clinical manifestations, and outcome
of Clostridium difficile-associated diarrhea. Am J
Gastroenterol. 1994;89(4):519-523.

27. Gerding DN, Olson MM, Peterson LR, et al.
Clostridium difficile-associated diarrhea and colitis
in adults: a prospective case-controlled
epidemiologic study. Arch Intern Med. 1986;146(1):
95-100.

28. Johannes CB, Ziyadeh N, Seeger JD, Tucker E,
Reiter C, Faich G. Incidence of allergic reactions
associated with antibacterial use in a large,
managed care organisation. Drug Saf. 2007;30(8):
705-713.

29. Meropol SB, Localio AR, Metlay JP. Risks and
benefits associated with antibiotic use for acute
respiratory infections: a cohort study. Ann Fam Med.
2013;11(2):165-172.

Adverse Events and Antibiotic Use in Hospitalized Patients Original Investigation Research

jamainternalmedicine.com (Reprinted) JAMA Internal Medicine September 2017 Volume 177, Number 9 1315

© 2017 American Medical Association. All rights reserved.

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Quantitative Exploration of Medication Errors among Older People: A Systematic Review

Running Title: Medication Errors in Older People: A Systematic Review

Shahrzad Salmasi1, Barbara C. Wimmer2, Tahir Mehmood Khan3,4, Rahul P. Patel2, Long Chiau Ming2,5

1Faculty of Pharmaceutical Sciences, Collaboration for Outcomes Research and Evaluation (CORE), University of British Columbia, Vancouver, Canada

2Pharmacy, School of Medicine, University of Tasmania, Hobart, Tasmania, Australia

3School of Pharmacy, Monash University Malaysia, Sunway City, Selangor, Malaysia

4The Institute of Pharmaceutical Sciences (IPS), University of Veterinary & Animal Sciences (UVAS), Lahore, Pakistan

5School of Pharmacy, KPJ Healthcare University College, Nilai, Negeri Sembilan, Malaysia.

E-mail:

Shahrzad Salmasi: [email protected]

Barbara C Wimmer: [email protected]

Tahir M Khan: [email protected]

Rahul P Patel: [email protected]

Corresponding author:

Dr Long Chiau Ming

Email: [email protected]

1. School of Pharmacy, KPJ Healthcare University College, Lot PT 17010, Persiaran Seriemas Kota Seriemas,71800 Nilai,Negeri Sembilan, Malaysia. Tel: +606-7942653; Fax:+606-794 2669

2. Unit for Medication Outcomes Research and Education, Pharmacy, University of Tasmania, Private Bag 26, Hobart, 7001, Tasmania, Australia. Tel: +603 32584775. Fax: +603 32584602

Abstract

Background: Medication Errors (ME) in older people are of importance due to global ageing patterns. Following on from aging-related changes in pharmacokinetics, pharmacodynamics, and the potential presence of multiple co-morbidities treated with polypharmacy, older people are highly vulnerable to the effect and consequences of MEs.



Objective: The primary outcome was to systematically review studies on the incidence and categories of medication errors (ME) in older people. Secondary outcomes included economic and clinical consequences of ME in older people, risk factors for ME in older people, and medications involved.




Methods: A comprehensive, electronic search was conducted using PubMed, EBSCOhost, OvidMedline and Proquest central databases for studies evaluating ME in older people published in peer-reviewed journals before November 2017. A secondary manual search was also conducted by checking the bibliographies of included studies to identify other relevant studies. There was no limitation imposed on the language, time of publication or the setting in which the study was carried out. The quality of identified studies was assessed based on 17 criteria adopted from Alsulami et al and Metsälä et al. The results were categorized using the phases of medication use when the error was detected or occurred.

Results: Eighteen studies met the inclusion criteria with a total of 467,193 participants from 11 countries. Identified MEs were administration errors (n=7, 1.2%-59.0%), prescribing errors (n=7, 1.6%-49.7%), transcribing errors (n=5, 15.0%-70.2%), reconciliation errors (n=4, 5.0%-53.6%), and dispensing errors (n=2, 2.0%-14.0%). People with polypharmacy had the highest tendency of MEs. Three studies reported severe clinical consequences from MEs ranging from 2.9% to 13.0%. The main category of medications involved in MEs were cardiovascular medications (n=15); nervous system medications (n=11); and medications for the alimentary tract and metabolism (n=8).

Conclusions: Administration and prescribing errors were the most frequently reported MEs in older people. Medication classes that were most commonly reported in the context of MEs in older people were cardiovascular medications and nervous system medications. We identified polypharmacy as a risk factor for MEs, which was found to correlate with the number of MEs in many stages of medication use. A lack of studies from Asia, Latin America and Africa highlights the need of future research in these regions.

PROSPERO registration number: CRD42016042975.

Keywords: Patient safety; nursing homes; medication error; medical error, measurement/epidemiology; human error

Key points:

1. Prescribing and administration errors are the most extensively studied errors in older people.

2. The highest medication error rate reported among older people was 70.2% for transcribing error.

3. Cardiovascular and nervous system medications were the most commonly reported therapeutic classes associated with medication errors in older people. The main risk factor associated with medication errors was the number of medications taken.

INTRODUCTION


Medication errors (MEs) can be defined as “any preventable event that may cause or lead to inappropriate medication use or patient harm while the medication is in the control of the health care professional, patient, or consumer” [1]. MEs cause between 44,000 and 98,000 deaths each year in United States of America (USA) hospitals, leading to an economic cost of $6-29 billion for such errors [2, 3].

MEs in older people are of importance due to global ageing patterns [4]. Medication is often the easiest and most effective treatment modality, but older people are highly vulnerable to the effect and consequence of MEs due to aging-related organ functions decline, multiple co-morbidity and polypharmacy. Polypharmacy can be defined as unnecessary medication use, use of any inappropriate medication, or the use of more medications than medically indicated [5-7].

A number of systematic reviews focusing on MEs have been reported. Alsulami et al systematically reviewed ME studies in the Middle East [8], and Salmasi et al wrote a systematic review on MEs in Southeast Asia [9]. Population-specific reviews have also been done: Krzyzaniak et al [10] focused on MEs in neonates, while Ghaleb et al [11] and Miller et al [12] performed systematic reviews to study MEs in pediatrics. There has only been one systematic review that reported MEs exclusively in the older people, however that systematic review by Metsala et al was limited to MEs occurring in acute care settings [13]. The primary objective of this review was to systematically review studies on the incidence and categories of MEs in older people in any setting.

METHODS

The study protocol for this systematic review has been registered and published in the international prospective register of systematic reviews (PROSPERO) with the registration number CRD42016042975.

Search strategy


A comprehensive, electronic search was conducted for studies published before November 2017 using PubMed, EBSCOhost, OvidMedline and Proquest central databases. A secondary manual search was conducted by checking the bibliographies of included studies (refer to supporting information S1 PRISMA Checklist). Detailed steps performed during the literature search are presented using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flowchart (Figure 1).

Search terms used:

Keywords related to “prescribing error”, “administration error”, “transcribing error”, “medication safety”, “reconciliation error”, “wrong time”, “wrong medication”, “wrong regimen”, “wrong dose”, “wrong patients”, “preparation error” as well as MeSH terms related to “patient safety”, “nursing homes”, “medication error” combined with “elderly” or “old” “older” or “geriatric” or “senior citizen” were used.

Study selection:




Original peer-reviewed research studies were eligible if they comprised MEs in people aged 55 years and older. The United Nations use 60 years as the cut-off point to define older people [14]. The World Health Organization (WHO) has however used the cutoff of 55 years to define older people in many of its projects [15]. We chose the more conservative cutoff point of 55 to ensure no relevant study was excluded. Studies focusing on MEs caused by patients themselves, such as self-medication, were excluded. Studies were only included if they were designed to assess MEs. There was no limitation imposed on the language, time of publication or the setting in which the study was carried out. Unpublished or grey literature were not included.

Studies that reported MEs as a secondary or additional outcome and those not specifically designed to assess and analyze MEs were excluded. Moreover, the prescribing of Beers medication was not considered a ME. Beers criteria classify medications with a high risk of adverse reactions that are potentially inappropriate for older people [16]. While prescribing potentially inappropriate medications is discouraged and may lead to adverse drug reactions, their prescribing is not considered a ME and their evaluation was, hence beyond the scope of our study. Two reviewers (SS and TMK) independently screened titles and abstracts, followed by full texts of relevant articles. Any disagreements were resolved through discussion.

Data extraction

Two authors (SS and LCM) independently extracted data from each included trial, using a specially designed pre-piloted data extraction form on Microsoft Excel. Any disagreement was resolved by seeking the opinion of the third author (TMK). Respective authors were contacted if any additional information (age, sample size, or number of cases reviewed) was missing.

Outcomes measured

Primary outcome: incidence and categories of MEs in older people.

Secondary outcomes: economic and clinical consequences of ME in older people, reasons behind ME in older people and medications involved in MEs.

Quality assessment

The quality of the identified studies was assessed based on 17 quality assessment criteria adopted from Alsulami et al [8] and Metsälä et al [13]. For full checklist and results of quality assessment see Table 1. Two authors (SS, LCM) critically appraised all included studies, any disagreement was discussed until consensus was reached. Two points were assigned to items that were fully satisfied, one point was given for each checklist item that was partly satisfied. No points were given for items that did not apply and one point was deducted for items that were applicable but not met. The total point received were calculated and presented in Table 1.

Studies that scored less than 12 points (satisfied at least one-third of the 17 assessment criteria; n=6 criteria) were considered poor quality, 12-23 marks were considered average quality (satisfied at least two-thirds of the 17 assessment criteria; n=12 criteria), and studies that scored more than 23 marks were considered as good quality (satisfied more than two-thirds of the 17 assessment criteria). Below are the assessment criteria:

1. Aims/objectives of the study clearly stated.

2. Study background and theoretical framework are clearly defined.

3. Definition of what constitutes an ME.

4. Error categories specified.

5. Error categories defined.

6. Presence of a clearly defined denominator.

7. The design is clearly stated.

8. Data collection method described clearly.

9. Setting in which study conducted described.

10. Sampling and calculation of sample size described.

11. Describes any efforts to address potential sources of bias.

12. Answers the research questions logically.

13. Reliability measures.

14. Measures in place to ensure that results are valid.

15. Limitations of study listed.

16. Mention of any assumptions made.

17. Ethical approval.

Data synthesis and analysis


The included studies used different methodologies, making it difficult to compare between the error outcomes. Therefore, MEs were categorized by the phases of healthcare provision in which they were reported: dispensing, prescribing, transcribing, and administration [17, 18]. A summary of the analysis of MEs is presented in supporting information S2. The following definitions were used in categorizing the MEs:

Medication administration errors: ‘‘any difference between what the patient received or was supposed to receive and what the prescriber intended in the original order” [19].

Prescribing error: error in the process of prescribing the medication that leads to (or has the potential to lead to) patient harm [9].

Transcribing error: error which is “due to data entry error that is commonly made by the human operators” [20, 21].

Reconciliation error: error occurring during an organized interview process to document a comprehensive medication history prior to a patient’s admission [22].

Quantitative analysis was performed using Stats Direct software. In this report, the number of time each ME subcategory was reported is indicated using “n”. Please note that “n” does not represent the number of included articles reporting an error because certain articles reported more than one studies that assessed certain errors in different settings.

RESULTS

Study characteristics


In total, 18 studies met the inclusion criteria. The total number of participants across the 18 studies were 475,867. Included studies were published over a period of 12 years from 2004 [23] to 2016 [24]. Participants’ mean age was ≥80 years in nine studies [17, 24-31], 70-80 years in five studies [18, 32-35], and 65-70 years in three studies [19, 23, 36]. Countries of origin were the USA [25, 31, 34, 35], France [17, 18, 27], Belgium [28, 30], England [19, 37], Canada [32], Indonesia [33], Israel [36], Malaysia [23], the Netherlands [29], Spain [24], and Sweden [26]. All studies were in English except for one [17], which was in French, and translated by a professional translator. Detailed characteristics of included studies are summarized in supporting information S3.

Quality of the included studies

Table 1 summarizes the quality assessment of included studies for the 17 quality assessment criteria. For detailed explanation of the quality assessment, please refer to the methods section. Two studies [17, 26] (11.1%) were categorized as poor quality, nine [18, 19, 24, 28, 32, 34-37] (50.0%) as moderate quality and seven studies [23, 25, 27, 29-31, 33] (38.9%) as high quality. Van den Bemt et al [29] had the highest quality score (31 points), meeting 16 out of the 17 quality assessment criteria.

All studies met criteria 1 and 2 (clear objective stated and clearly defined background). However, criteria 3, 10, 11 and 16 (definition of what constitutes a ME, mention of any assumptions made, sampling and calculation of sample size described, and description of any efforts to address potential sources of bias) were poorly met. This is important for future research because without this information, comparison between studies will be not feasible.

Table 1: Quality assessment of the included studies.

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

Total score

van den Bemt et al, 2009 [29]

**

**

**

**

**

**

**

**

**

**

**

**

**

**

**

**

31

Verrue et al, 2010 [30]

**

**

**

**

**

**

**

**

**

*

**

**

**

**

X

**

28

Young et al, 2008 [31]

**

**

**

**

**

**

**

**

*

**

**

**

**

**

**

27

Beckett et al, 2012 [25]

**

**

**

**

**

**

*

**

**

**

**

**

**

*

**

26

Abdullah et al, 2004 [23]

**

**

**

**

**

**

*

**

**

**

*

**

25

Quelennec et al, 2013 [27]

**

**

**

**

**

**

**

**

**

**

**

**

**

**

25

Ernawati et al, 2014 [33]

**

**

**

**

**

*

**

**

**

**

**

**

**

**

24

Kelly et al, 2012 [19]

**

**

**

**

**

**

**

**

*

**

*

*

**

**

22

Moro et al, 2016 [24]

**

**

**

**

**

**

**

**

**

**

**

**

**

22

Cornish et al, 2005 [32]

**

**

**

**

*

**

**

**

**

**

**

**

**

21

Ben-Yehuda et al,2011 [36]

**

**

*

**

**

*

**

**

**

**

**

**

**

X

21

Szczepura et al, 2011 [37]

**

**

**

**

*

**

**

**

**

**

**

**

18

Raimbault et al, 2013 [18]

**

**

**

**

**

**

**

*

**

**

**

15

Steinman et al, 2014 [34]

**

*

**

*

**

**

X

**

**

**

**

**

15

Somers et al, 2013 [28]

**

*

**

*

**

**

**

**

**

**

**

14

Picone et al, 2008 [35]

*

**

**

**

*

**

**

**

**

**

**

14

Midlov et al, 2005 [26]

**

**

**

*

**

**

**

**

**

9

Cecile et al, 2009 [17]

**

**

**

*

**

**

**

**

6

**Satisfies assessment criteria

*Partly satisfies assessment criteria

– Does not satisfy assessment criteria

X Assessment criteria do not apply

Overall ME rates reported:

MEs were reported based on the phase of healthcare provision in which they were detected, which was specified in all but two studies [17, 18]. Seven studies [19, 29-31, 33, 35, 37] reported administration error rates (1.2% [37] to 59.0% [33]).

Seven studies [18, 23, 28, 33-36] evaluated prescribing error. The error frequency ranged between 1.6% [35] and 49.7% [34]. One study, however, did not report the overall prescription error rate [18].

Five studies evaluated transcribing errors. Overall, reported transcribing error rates ranged from 15.0% to 70.2% [23, 26, 33, 35, 36]. Meanwhile, four included studies reported reconciliation errors (rate ranged from 5.0% to 53.6%) [24, 25, 27, 32]. Only two studies [33, 35] evaluated dispensing errors. Dispensing errors comprise discrepancies between the medication dispensed or supplied with the medication ordered or written on the prescription [9]. The rate of this ME was reported between 2.0% and 14.0%.

Below, the reported ME rates for each ME category are summarized.

Reconciliation errors


Incorrect dose/route/frequency were the most frequently reported subcategories of reconciliation errors. “Omission” accounted for the bulk of reconciliation errors with 87.9% [27], 46.4% [32], 40.5% [25], and 35.0% [24]. The second highest rate of error incidence in this category was “incomplete prescription reconciliation” (40.0%) [24].

Administration errors





The most frequently reported subcategories of administration errors were: “wrong drug/dosage form” (n=8) [19, 30, 31, 33], “wrong time” (n=7) [19, 29-31, 33, 37], “wrong dose/route/frequency” (n=6) [19, 30, 31, 33], followed by “omission” (n=5) [19, 29-31, 33, 35]. The highest incidence of error during administration belonged to “wrong time” (72.1%) [19], “wrong technique” (73.0%) [29] and “wrong documentation” (64.0%) [33].

One documented reason for the high rate of “wrong time” errors could be that the timing on medication charts might not be practical or compatible with nursing staff shift schedules (10 pm dose to be administered, in a setting where caregivers finish working at 8pm). Therefore, a customized drug administration timing adjusted to shift rotation could facilitate administering medication at the correct time by the nursing staff [38]. Similarly, for older people residing in a care facility, omissions might happen at the time of shift rotation if staff communication is suboptimal [39]. This scenario is different among older people living with family because health literacy, intentional and non-intentional adherence to medication could influence their medication adherence [40].

Prescribing or Dispensing errors

The most frequently reported subcategories of prescribing error were: “improper administration instructions” (n=8) [18, 28, 36], “drug interaction/contraindication” (n=8) [18, 28, 33, 34, 36], “wrong dose” (n=6) [18, 28, 33, 34, 36], and “over/under prescribing” (n=5) [18, 28, 33]. The highest rate of error during prescribing was “wrong dose” reported by Ben Yehuda et al to be 49% [36] whereas the highest incidence of dispensing error was based on “labeling errors” (22.0%) [33].

Transcribing errors


“Wrong drug/dosage form” (n=3) [26, 33, 36], and “wrong patient particulars” (n=3) [26, 33, 36] were the most frequently reported transcribing error subcategories. One study did not provide a detailed list of transcribing errors except for miswriting of diagnosis which was reported to be the most frequent transcribing error, with 277 cases (73.8%) [23].

Midlov et al focused on transcribing errors that occur during a patient’s transition between primary healthcare and hospital [26]. The authors found that medications were often erroneously added when patients left the hospital, because the changes decided upon by physicians in the hospital were not transcribed.

Economic consequences of MEs


One study estimated the cost of prescribing and transcribing errors among older people at an outpatient pharmacy in Malaysia[23]. The projected total drug and humanistic (labour) cost of MEs per year was estimated to be 28,022.50 USD[41]. However, because no other study estimated the associated ME costs, comparisons were not possible.

Clinical consequences of MEs

Eight studies rated the clinical consequences of MEs [19, 24, 25, 27, 29-32]. The classification systems and criteria used to categorize the clinical consequences of MEs differed substantially between studies. One study adopted the classification from the National Coordinating Council for Medication Error Reporting and Prevention (NCCMERP) [24], which categorizes MEs into nine categories (A-I) according to their clinical importance [42]. Two studies [19, 32] categorized MEs as having minor, moderate and severe clinical consequences, while the remaining five studies [25, 27, 29-31] used a narrative approach to report the clinical consequences of the MEs without the use of any specific classification system.

Medications involved

Below is a summary of medications commonly involved in MEs, by therapeutic class. The percentage in the brackets represents the proportion of studies that reported the association of these therapeutic classes with MEs. A detailed list of the medications involved in MEs in older people is presented in supporting information S2.

· Cardiovascular medication [17-19, 23, 25-32, 34, 35] (83.3%).

· Nervous system medication [17-19, 24-28, 32, 34, 35] (73.3%).

· Medications for the alimentary tract and metabolism [18, 19, 24, 26-28, 33, 34](53.3%).

· Analgesics [17, 19, 29, 30, 35, 37] (33.3%).

· Anti-infectives [17, 19, 23, 28, 33, 35] (33.3%).

· Diabetic medications [17, 23, 31, 33, 35] (27.8%).

· Mineral and vitamin supplements (e.g., vitamin D, calcium and iron) [18, 24, 25, 28] (22.2%).

· Hormones [25, 29, 34] (16.7%).

Analgesics, minerals and vitamins were mainly associated with omission errors that means they were indicated but not prescribed/administered [18, 28-30]. Cardiovascular medications were mostly associated with “wrong-dose” errors [29-31, 34], specifically warfarin was reported in this context [30, 31].

Factors contributing to MEs


Medication errors are usually not a result of a failure of an individual but a symptom of system failure . In March 2017, the WHO launched its Third Global Patient Safety Challenge with the aim of reducing preventable MEs by 50% in the next five years through addressing weaknesses in healthcare systems [15]. It was therefore necessary to assess the health care system factors contributing to MEs. Healthcare system factors contributing to MEs in older people were: polypharmacy [17, 23, 24, 27, 34-36], , inappropriate administration scheduling [19, 31], understaffing [29, 35], similar packaging [30], stress and time constraints [37], lack of staff training [23], medications associated with complex tasks (crushing)[29], and interruptions during ward rounds [37].

Seven studies [17, 23, 24, 27, 34-36] found a correlation between the number of medications taken and MEs. The highest rate of MEs was found in older people who received more than nine medications (32.1%) [23, 36]. Furthermore, the odds of a ME increased by 5.0% for each additional medication the patient received [35]. When taking nine or more medications there was a significantly increased risk if a transcribing error (OR 2.58 [95% CI 1.02, 6.51]) [36].

The number of medications prescribed to an older person was the strongest and most consistent predictor of prescribing problems. The rate of each subcategory of prescribing problem was approximately 10 times higher in patients with eight or more medications than in patients with one to three medications [34]. Moreover, the number of reconciled medications was found to correlate with reconciliation errors rates (R = 0.276, p = 0.002) [24].

DISCUSSION

The Institute of Medicine, in its report on the quality of healthcare “To Err is Human”, called for a more systematic approach to preventable events such as MEs [43]. To our knowledge, this systematic review is the first to summarize studies on MEs in the older people in all settings (teaching hospital, general hospital, outpatient pharmacy, nursing home and residential care).


Overall, the range of the MEs rates reported was very wide. This is likely due to heterogeneity of the studies in terms of the setting, method of data collection and reporting.

Identified MEs were administration errors (n=7, 1.2%-59.0%), prescribing errors (n=7, 1.6%-49.7%), transcribing errors (n=5, 15.0%-70.2%), reconciliation errors (n=4, 5.0%-53.6%), dispensing errors (n=2, 2.0%-14.0%). People with polypharmacy had the highest tendency of MEs. Prescribing, and administration errors were the most extensively studied errors in older population (58.0% of the included studies). Transcribing, reconciliation, and dispensing errors were the least extensively studied errors (20.0%, 17.0% and 8.0% of the included studies, respectively).

Medication classes most frequently involved in MEs were cardiovascular medications and nervous system medications which were reported by 83.3% and 73.3% of the included studies, respectively. The high frequency of cardiovascular medications involved in MEs because these are the most commonly prescribed medications in older people since cardiovascular diseases occur at exponentially increasing rates with advancing age [44]. The second most frequently cited medication class involved in MEs was nervous system medications such as benzodiazepines. Most studies did not report the percentage of the errors each medication class was responsible for. However, five studies [26-28, 32, 35] reported that nervous system medications were associated with more MEs than any other medication class, making up 26.0% [28], 25.9% [32], 22.0% [27], and 20.2% [35] of the total errors reported, respectively. In the study by Moro et al, however, nervous system medications were responsible for 18.0% of the reported MEs, ranking second after alimentary tract medications [24]. The association of this medication class with MEs could be related to their complex dosing and administration schedules. Considering the importance of medications such as benzodiazepines in older people in the context of potentially inappropriate medications, this finding should be investigated further in the future [45].

The majority of MEs were rated to have minor or moderate clinical consequences, however, different tools were used by different studies to make this classification. None of the included studies reported any MEs with fatal consequences. With regards to monetary consequences, no conclusion could be drawn because only one study [23] calculated the costs associated with MEs.

The main risk factor for MEs was the number of medications taken [17, 23, 24, 27, 34-36]. This is important because it has been suggested that people older than 75 years will have polypharmacy (defined as five or more medications) for more than half of their remaining life [46]. In the context of our findings, this fact highlights potential benefits of medication reconciliation, especially for older people with multiple medications [38].

Strengths and Limitations



Strengths comprise the comprehensive search without limitations on language, setting or publication dates. One limitation the authors faced was that in most studies the denominator of the samples was not reported. Additionally, high data heterogeneity and different data reporting, interpretation and classification systems precluded a meta-analysis. The systematic review was further limited by differences in defining MEs and adverse drug reactions by different authors and in different countries. Furthermore, assessment of the error measurement and reporting methods were not performed in this study due to lack of standardized guidelines for error measurement.

There were no reported studies on MEs in older people in African countries, Latin America, Australia and Oceania. Medication error studies were only available in 6 European countries (the Netherlands, Sweden, Spain, Belgium, England and France), out of the 43. Similarly in Asia, MEs were only studied in three countries out of 47 countries [47].

Future research


While the variation in error measurement and reporting limited out ability to meta-analysize the data, this is an important issue that needs to be studied independently and in more depth in the future. Also, cardiovascular and nervous system medications were the most commonly associated medications with MEs in older people. Hence, these two therapeutic classes should be studied more extensively with regards to their association with MEs in older people.

Moreover, there is a lack of studies from Asia, Latin America and Africa. More studies need to be conducted in these regions due to differences in demographics, disease, medication-use patterns and healthcare systems, the results reported by developed countries may not be applicable to developing countries in Asia and Africa.

Conclusion

In conclusion, prescribing and administration errors were the most extensively studied errors in older people. Cardiovascular and nervous system medications were the most commonly reported therapeutic classes associated with MEs in older people. The review also identified ME risk factors that were characteristic to older people such as polypharmacy. This systematic review identified a lack of studies on MEs in older people, especially in the African and Asian regions. Older people are specifically susceptible to MEs, hence more attention needs to be paid to older people when evaluating MEs.

Conflict of Interest: The authors have declared that no competing interests exist.

Financial Disclosure: The authors received no specific funding for this work.

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LEGENDS

Figure 1. PRISMA diagram demonstrating the search strategy and results

S1. PRISMA Checklist. PRISMA 2009 Checklist.

S2. Summary of the main outcomes of included studies

S3. Characteristics of the included studies

27

Lyons I, et al. BMJ Qual Saf 2018;27:892–901. doi:10.1136/bmjqs-2017-007476892

Original research

► Additional material is
published online only. To view
please visit the journal online
(http:// dx. doi. org/ 10. 1136/
bmjqs- 2017- 007476).

For numbered affiliations see
end of article.

Correspondence to
Professor Bryony Dean Franklin,
Centre for Medication Safety
and Service Quality, Imperial
College Healthcare NHS Trust/
UCL School of Pharmacy,
London, W6 8RF, UK;
bryony. [email protected] nhs. net

Received 9 October 2017
Revised 12 March 2018
Accepted 24 March 2018
Published Online First
7 April 2018

To cite: Lyons I, Furniss D,
Blandford A, et al.
BMJ Qual Saf
2018;27:892–901.

Errors and discrepancies in the
administration of intravenous
infusions: a mixed methods
multihospital observational study

imogen lyons,1 Dominic Furniss,1 ann Blandford,1 gillian chumbley,2
ioanna iacovides,3 li Wei,4 anna cox,1 astrid Mayer,5,6 Jolien Vos,1
galal h galal-edeen,1,7 Kumiko O schnock,8,9 Patricia c Dykes,9,10
David W Bates,8,9 Bryony Dean Franklin4,11

ABSTRACT
Introduction Intravenous medication administration
has traditionally been regarded as error prone, with high
potential for harm. A recent US multisite study revealed few
potentially harmful errors despite a high overall error rate.
However, there is limited evidence about infusion practices
in England and how they relate to prevalence and types of
error.
Objectives To determine the prevalence, types and severity
of errors and discrepancies in infusion administration in
English hospitals, and to explore sources of variation,
including the contribution of smart pumps.
Methods We conducted an observational point prevalence
study of intravenous infusions in 16 National Health
Service hospital trusts. Observers compared each infusion
against the medication order and local policy. Deviations
were classified as errors or discrepancies based on their
potential for patient harm. Contextual issues and reasons
for deviations were explored qualitatively during observer
debriefs.
Results Data were collected from 1326 patients and
2008 infusions. Errors were observed in 231 infusions
(11.5%, 95% CI 10.2% to 13.0%). Discrepancies were
observed in 1065 infusions (53.0%, 95% CI 50.8% to
55.2%). Twenty-three errors (1.1% of all infusions) were
considered potentially harmful; none were judged likely to
prolong hospital stay or result in long-term harm. Types and
prevalence of errors and discrepancies varied widely among
trusts, as did local policies. Deviations from medication
orders and local policies were sometimes made for efficiency
or patient need. Smart pumps, as currently implemented,
had little effect, with similar error rates observed in infusions
delivered with and without a smart pump (10.3% vs 10.8%,
p=0.8).
Conclusion Errors and discrepancies are relatively
common in everyday infusion administrations but most
have low potential for patient harm. Better understanding
of performance variability to strategically manage risk
may be a more helpful tactic than striving to eliminate all
deviations.

InTRoduCTIon
Intravenous medication administration
is complex, and data suggest that errors

are common. For example, a systematic
review of nine studies across various
stages of intravenous medication prepa-
ration and administration reported errors
in 73% of intravenous doses.1 However,
published error rates vary widely, from
18% to 173% of intravenous doses in
studies using structured observation of
medication administration.2

Amidst concerns over safety, technol-
ogies such as ‘smart pumps’ have been
advocated. These incorporate dose error
reduction software to check programmed
infusion rates against preset limits within a
customisable drug library. However, dose
limits can be over-ridden, and evidence
regarding their impact is mixed.3 4 While
unintended infusion overdoses repre-
sent a major safety concern, there are
many factors that affect infusion admin-
istration, and smart pumps are just one
possible solution.

A recent multisite US study using
structured observation reported a high
prevalence of intravenous infusion admin-
istration errors and procedural failures,
even with the use of smart pumps, yet few
potentially harmful errors.4 Building on
this and an earlier US study,5 we therefore
wanted to conduct a similar study in the
UK with a larger sample size6 to confirm
or refute these findings in a different
context in which smart pumps are less
common. In contrast to previous studies,
we also wanted to incorporate a Safety II
approach to interpret our findings.7 This
approach moves away from the tradi-
tional focus of classifying all deviations as
errors and blaming the human for unre-
liable processes. Instead it encourages

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893Lyons I, et al. BMJ Qual Saf 2018;27:892–901. doi:10.1136/bmjqs-2017-007476

Original research

consideration of deviations in terms of performance
variability, how to understand and manage this vari-
ability, and that the human component can make posi-
tive contributions to safety.7 8 Our objectives were to
determine the prevalence, types and severity of errors
and discrepancies in intravenous infusions in England
and to explore sources of variation, including the
potential contribution of smart pumps, using a Safety
II approach.

MeThodS
Study design
We used a point prevalence observational study of intra-
venous infusions in a sample of hospitals, followed
by debriefs with staff at each site to gather additional
context. Although we built on previous studies,4 5 we did
not consider all deviations from the medication order
or local policy to be errors: minor or intentional devi-
ations were classed as discrepancies. The study protocol
was published previously6 and the study was approved
by a National Health Service (NHS) Research Ethics
Committee (14/SC/0290).

Study setting and sample
We used a purposive sampling strategy to select 16
NHS trusts in England, aiming for a diverse range of
organisations in terms of type, size, location, patient
safety metrics and use of infusion devices and smart
pump technology.6 Online supplementary appendices
1 and 2 summarise the recruitment process and char-
acteristics of each participating trust. We conducted
observations in three clinical areas (general medicine,
general surgery and critical care) in 13 trusts; in eight
of these we also conducted observations in paediatrics
and oncology day care. Two specialist children’s hospi-
tals collected paediatric data only. One further trust
collected oncology day care data at three hospital sites.
We aimed to include a sample of 2100 infusions across
all participating sites to give a CI around a 10% error
rate of 8.7%–11.3%.6

data collection
Data were collected between April 2015 and December
2016. At each trust, two observers (usually a nurse and a
pharmacist) employed in the organisation were trained
by the research team to collect data. This training
included highlighting the types of deviations to look
for, conducting observations in the presence of the
research team where possible and using sample cases to
facilitate discussion about classification of deviations
identified. Observers were also requested to identify
and familiarise themselves with relevant local policies
and guidelines prior to data collection. Observers then
spent 1 weekday or equivalent collecting data in each
clinical area. One clinical area could comprise one or
more wards. Observers aimed to collect data on all
intravenous infusions being administered at the time

of data collection, including drugs, fluids, blood prod-
ucts and nutrition. Bolus doses were excluded, except
where a prescribed bolus was given as an infusion, or
vice versa. Completed infusions were excluded even if
still attached to the patient. Patients were not observed
if they were in isolation due to infection risks, were
receiving care that would have required interruption
or were off the ward.

Observers compared each medication being admin-
istered against the prescription and local policies/
guidance,6 and consulted clinical staff if needed to
understand any deviations. Data were recorded using
a standardised paper form and subsequently uploaded
to a secure web-based tool.9 No patient identifiable
data were recorded. Suspected errors were raised with
clinical staff so they could be corrected if needed; local
reporting practices were then followed.

Identifying and assessing deviations
We recorded any deviations from a prescriber’s
written or electronic medication order, the hospital’s
intravenous policy and guidelines, or the manufactur-
er’s instructions. We included the administration of
medication to which the patient had a documented
allergy or sensitivity, but did not assess other aspects of
the clinical appropriateness of the medication order.
We also collected data on policy violations and proce-
dural or documentation deviations that may increase
the likelihood of medication administration errors
occurring. These included patients not wearing an
identification wristband with the correct information,
medication or infusion administration sets not being
labelled in accordance with hospital policy and failure
to document the administration of medication in line
with policy. Finally, we encouraged observers to record
any other irregularities, anomalies or workarounds
related to the administration. Some of these were
grouped together for analysis and formed new catego-
ries. Online supplementary appendix 3 presents defi-
nitions of deviation types.

Local observers rated each deviation using an adap-
tation of the National Coordinating Council for Medi-
cation Error Reporting and Prevention (NCCMERP)
severity index.10 Ratings were based on the likelihood
of the deviation resulting in patient harm if it had not
been intercepted, and were used to classify the devia-
tions as discrepancies (rated A1 or A2) or errors (rated
from Cto I) (online supplementary appendix 4).6 Based
on these ratings we developed and clarified our clas-
sifications, recognising that deviations could be either
errors or discrepancies, either in medication adminis-
tration or in the associated procedural and documen-
tation requirements (figure 1). We report separately
on a comparison between the NCCMERP ratings and
an alternative severity classification method based on
expert judgement.11

Observers at each trust documented brief descrip-
tions of any deviations identified and provided further

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894 Lyons I, et al. BMJ Qual Saf 2018;27:892–901. doi:10.1136/bmjqs-2017-007476

Original research

qualitative insights during semistructured debriefs
once data collection was complete.

data management and analysis
Clinicians within the research team reviewed devia-
tions that had uncertain classifications, for example,
where local observers highlighted that they found
categorisation difficult and where observers had clas-
sified similar deviations differently. Clinicians within
the research team also reviewed each error rated cate-
gory D (‘likely to have required increased monitoring
and/or intervention to preclude harm’) and above.
Minor changes were made to classifications of type
and severity of error as needed.

Error and discrepancy rates were calculated as the
proportion of infusions with at least one error or
discrepancy using total opportunities for error (total
number of doses administered, plus any omitted doses)
as the denominator. Results are presented according
to overall error and discrepancy rates, and individual
types of errors and discrepancies, grouped into medi-
cation administration deviations, and procedural and
documentation deviations. Variations in deviation
rates between clinical areas, delivery modes and infu-
sion types were explored descriptively with their 95%
CIs, and Χ2 tests where appropriate. Qualitative data
were analysed inductively.

ReSulTS
Overall, 6491 patients were present in the clinical
areas observed, of whom 1545 (23.8%) were receiving
and/or prescribed an intravenous infusion at the time
of data collection. Data were collected from 1326

(85.8%) patients, who were administered and/or
prescribed 2008 infusions.

Frequency, types and potential severity of errors and
discrepancies
Overall, 240 errors and 1491 discrepancies were
identified across 2008 intravenous infusions. Table 1
presents the numbers and percentages of infusions and
patients affected. Table 2 shows the types of devia-
tions observed and their likely harm. Ninety per cent
of observed errors were considered unlikely to cause
harm despite reaching the patient (NCCMERP cate-
gory C). Twenty-two errors (9.5%) were category
D, and one (0.4%) category E; these 23 potentially
harmful errors represent 1.1% of infusions. Examples
in each severity category are presented in table 3.

Medication administration deviations
Overall, 427 (21.3%) infusions involved at least one
medication administration error (n=211) or discrep-
ancy (n=257). The most frequent types of deviation
concerned rates and unauthorised medications.

Rate deviations
Overall, 152 infusions (7.6%) were being adminis-
tered at a different rate from that prescribed; 77 were
classified as errors (rated ≥C) and 75 as discrepancies
(rated A1 or A2). A large proportion involved order
changes that had not been correctly documented
and infusions titrated based on the patient’s clinical
need or fluid allowance without such titration being
prescribed. Three deviations involved prescribed

Figure 1 Classification of deviations, errors and discrepancies.

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895Lyons I, et al. BMJ Qual Saf 2018;27:892–901. doi:10.1136/bmjqs-2017-007476

Original research

boluses administered as infusions, and one was a
prescribed infusion given as a bolus.

About 31% of rate errors occurred in infusions
delivered via gravity (without using a pump), despite
accounting for just 8% of infusions. Of the 12 most
serious rate errors (rated D), eight were administered
via gravity; these included red blood cells, vancomycin,
paracetamol and piperacillin/tazobactam. Many medi-
cation orders specified a duration rather than rate (eg,
over 8 hours). In one case an infusion was observed
running at a very high rate to ‘catch up’—1 L of Plas-
malyte 148 had been prescribed over 24 hours; at the
time of observation, 27 hours after the start time, the
rate was set at 500 mL/hour.

Unauthorised medication
Eighty-nine infusions did not have a corresponding
medication order. Thirteen were flushes that did
not require a medication order according to local
policy. Therefore, 76 infusions (3.8%; 75 errors, one
discrepancy) were judged to be unauthorised. Almost
half were fluids used to flush the line, commonly in
oncology settings, including sodium chloride 0.9%
(n=29), dextrose (1), Plasmalyte (2) and heparin
(3). A further seven infusions were sodium chloride
0.9% administered at low rates to keep the vein
open. Twenty infusions were unauthorised repeats of
previously prescribed maintenance fluids. Four were
administered based on verbal orders that had not
been documented at the time of observation. Of the
remaining 10 unauthorised infusions, seven involved
maintenance fluids and three were drugs (calcium foli-
nate, remifentanil, insulin). The remifentanil infusion
had been prescribed and subsequently discontinued,
but not represcribed after a decision to resedate the
patient.

Procedural and documentation deviations
Overall, 961 infusions (47.9%) had at least one proce-
dural or documentation error (n=24) or discrepancy
(n=1219). Table 2 shows the frequency and severity of
different types of procedural and documentation devi-
ations. Non-compliance with hospital requirements
for labelling infusion administration sets was most
common. Procedural or documentation errors mostly
involved unlabelled syringes, or infusions where the
label was significantly inaccurate. For example, a
patient prescribed 60 mg pamidronate was being
administered an infusion labelled as 30 mg, but staff
confirmed the patient had received the correct dose.

While some of the discrepancies identified in our
study were deviations from protocols that may have
been intentional workarounds, this was not always
the case. Some were minor, non-clinically significant
variations from what was prescribed that did not meet
our definition of a medication administration error
(eg, small deviations in flow rate or concentration,
or minor delays to maintenance fluids’ start or finish T

ab
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896 Lyons I, et al. BMJ Qual Saf 2018;27:892–901. doi:10.1136/bmjqs-2017-007476

Original research

times due to being interrupted to administer intrave-
nous antibiotics), and some were minor documenta-
tion discrepancies.

Sources of variation in error and discrepancy rates
Error rates among trusts ranged from 2.7% to 24.4%,
and discrepancy rates from 13.5% to 100% of infu-
sions, with no evidence of a relationship between
error and discrepancy rates (figure 2). Procedural or
documentation deviations ranged from 9.9% to 100%
of infusions across trusts, reflecting wide variation in
hospital policies and how they were enacted in prac-
tice. Some trusts had stringent policy requirements (eg,
trust K) whereas others did not (eg, trust J); some had
requirements that staff were unaware of in practice
(eg, trusts D and P).

Variation was also evident among clinical areas
and different infusion types (online supplementary
appendix 5). Infusions observed in critical care had a
lower error rate (7.0%); the error rate for paediatric
areas was similar to that for adult non-critical care

areas. Patient-controlled analgesia pumps and syringe
drivers had the lowest error rates at 6.4% and 5.1%,
respectively, with infusions delivered via gravity the
highest (21.5% of 163 infusions). Error rates also
varied by type of medication; maintenance fluids (eg,
sodium chloride 0.9%) had a high error rate (18.5%)
compared with drugs (6.9%), blood products (9.1%)
and parenteral nutrition (2.9%).

Eleven of 16 hospitals (69%) used smart pumps
(ie, an infusion pump with a drug library and/or dose
error reduction software enabled) in at least one clin-
ical area. However, just 640 (32%) infusions were
administered using a smart pump (online supplemen-
tary appendix 5). Infusions delivered using smart
pumps had similar error rates to those using other
pumps (10.3% vs 10.8%; p=0.8). No appropriate
entry was available in the drug library for one-third
of infusions administered using a smart pump. Of 424
infusions with a library entry available, the library
was used in 356 (84%) cases. There was no significant
difference in error rates for doses given via a drug

Table 2 Number, frequency and potential severity of each type of deviation

Type of deviation

Errors Discrepancies

NCCMERP severity rating n (% of 2008
infusions)

NCCMERP severity
rating n (% of 2008

infusions)C D E A1 A2

Medication administration deviations
Rate deviation 65 12 – 77 (3.8) 48 27 75 (3.7)
Unauthorised medication 72 3 – 75 (3.7) – 1 1 (0.0)
Administration start time discrepancy 13 – – 13 (0.6) 31 8 39 (1.9)
Incomplete or delayed completion 10 – – 10 (0.5) 4 27 31 (1.5)
Expired drug 11 – – 11 (0.5) 1 1 2 (0.1)
Dose discrepancy 5 2 – 7 (0.3) 6 6 12 (0.6)
Wrong drug/fluid/diluent 11 – – 11 (0.5) 1 1 2 (0.1)
Omitted medications (not administered at time of

data collection)
2 3 – 5 (0.2) 1 6 7 (0.3)

Roller clamp positioned incorrectly or inappropriately 1 – – 1 (0.0) – 10 10 (0.5)
Concentration discrepancy – – 1 1 (0.0) 7 2 9 (0.4)
Drug library not used or incorrectly used (in the case

of smart pumps)
– – – – – 67 67 (3.3)

Allergy oversight – – – – 2 – 2 (0.1)
All medication administration deviations 190 20 1 211 101 156 257
Procedure or documentation deviations
Infusion administration set not tagged/labelled

correctly
– – – – – 537 537 (26.8)

Documentation of the administration 1 – – 1 (0.0) – 334 334 (16.6)
Additive label missing or incorrect 16 1 – 17 (0.8) 2 200 202 (10.1)
Patient identification* 6 – – 6 (0.3) – 110 110 (5.5)
Documentation of the medication order – – – – 7 31 36 (1.8)
All procedure or documentation deviations 23 1 – 24 9 1212 1219
Miscellaneous 4 1 – 5 (0.2) 4 9 13 (0.6)
All deviations 217 22 1 240 114 1377 1491
*Deviations are counted per infusion; this figure includes patient identification deviations (ie, no name band) applied to all infusions for those patients.
There were 88 patient identification discrepancies, counting each once per patient.
NCCMERP, National Coordinating Council for Medication Error Reporting and Prevention.

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library versus those given without (online supple-
mentary appendix 5). Discrepancy rates were higher
in infusions delivered using smart pumps (61.7% of
640 infusions) compared with those without smart
features (46.4% of 1202 infusions, p<0.001). Sixty-
seven discrepancies were identified in the use of a
smart pump drug library: 61 where the drug library
was bypassed completely and six where the wrong
entry was selected. However, differences in discrep-
ancy rates were more commonly linked with policy
requirements for labelling infusions and administra-
tion sets at different sites; when discrepancies related
to use of a drug library are excluded, the discrepancy
rate remains higher in infusions delivered via smart
pump (59.2% of 640 infusions).

Qualitative insights
Information provided by observers revealed some
reasons for deviations. Some were simple slips or
lapses such as confusing diluents and forgetting
to open roller clamps to start the infusion; others
involved lack of knowledge of policy requirements.
Staff also reported deliberate deviations that would
benefit patients but conflicted with official rules
and formal procedures, for example, giving patients
fluids that had not yet been prescribed when a doctor
was unavailable (unauthorised fluids) and keeping
lines patent by switching to a low infusion rate in
anticipation of another infusion being needed (rate
deviation). There were several instances of inaccu-
rate prescriptions that were ‘corrected’ and admin-
istered by nurses without getting the order changed
prior to administration. However, in one case the
administering nurse incorrectly assumed an unusual
prescription was wrong (table 3—piperacillin/tazo-
bactam).

In some instances, nursing staff actively tried to
balance risk and efficiency rather than follow proce-
dures mechanistically. For example, staff reported
stopping infusions (delay in completion) when patients
left the ward for investigations so a nurse did not have
to accompany the patient when staffing resources
were stretched. In addition, some nurses objected to
spending time labelling administration sets and writing
batch numbers on additive labels for short infusions
that would soon be discarded.

Observers at some trusts reported that collecting
the study data provided insights into the reasons for
some deviations and helped them identify solutions.
For example, at one site where poor compliance with
documentation of medication administration was
recorded, the trust subsequently purchased handheld
computers to allow staff to access electronic records in
closer proximity to patients.

dISCuSSIon
We found that 1 in 10 intravenous infusions involved
an error, and one in two involved a discrepancy.
However, few were considered likely to cause patient
harm. There was considerable variability in errors,
discrepancies, policies and practices among trusts. Our
mixed methods approach offers insights into some
reasons for this variability. Nurses can be a source of
resilience, compensating for deficiencies and vulner-
abilities in the system; however, this same adaptive
capacity can also lead to unsatisfactory outcomes.12
Informed by Safety II, 7 8 our findings suggest the need
to question traditional notions of ‘error’ and the goal
of eliminating all errors and discrepancies. Instead we
reflect on a broader notion of deviations, highlight
positive contributions to efficiency and safety that go
beyond compliance and explore strategic interventions
to manage performance variability.

Table 3 Examples of observed deviations in the administration
of intravenous infusions

Severity
category Examples

E ► Patient was administered 2 g vancomycin diluted in 250 mL of
sodium chloride 0.9%. The drug should have been diluted in
500 mL of sodium chloride 0.9% (concentration error: severity
category E) and administered over at least 240 min. The drug
was observed running too fast via gravity feed (rate error: D).
The chart had not been signed to confirm the administration had
been double-checked as required (documentation discrepancy:
A2). The patient suffered from pain and red lumps along arm.

D ► Piperacillin/tazobactam was prescribed to be given over 3 hours.
However, it was given as a bolus over 3–5 min, which is the
most common way to administer this antibiotic. The nurses
presumed the doctors had made a mistake and corrected it.
However, this had been prescribed intentionally after discussions
with the consultant, with microbiology, with pharmacy and the
drug manufacturer due to the patient’s poor renal function. This
clinical decision was recorded in the patient’s notes but nursing
staff had not reviewed these.

► 40 mmol of potassium chloride rather than the prescribed
20 mmol was administered together with 10 mmol magnesium
sulfate in sodium chloride 0.9% at 1000 mL/hour.

C ► 1 L sodium chloride 0.9% with potassium chloride 0.15% was
prescribed over 12 hours. The documented start time was 23:25.
When observed at 13:00 the following day the infusion was not
running and approximately 150 mL remained. The infusion should
have been complete but the pump was not plugged in and the
battery was empty.

► A medication order for 20 mcg fentanyl stated diluent as
dextrose 5%, however the drug was prepared and administered
in sodium chloride 0.9%.

A2 ► Electronic prescription specified 1 L of sodium chloride 0.9%
over 8 hours. Started at 02:00 thus due to finish 10:00 but at
09:25 there was still 500 mL to run. The infusion was paused
at the time of observation as the patient was receiving an
intermittent amoxicillin infusion.

► Hartmann’s solution had been selected in the smart pump’s drug
library but the infusion being administered was sodium chloride
0.9% (at the correct rate prescribed).

A1 ► The prescribed rate was 250 mL/hour for 123 mg paclitaxel in
250 mL sodium chloride 0.9%. However, the final reconstituted
volume was 290.5 mL, which was being infused at 290 mL/hour
to give the same rate of administration as prescribed.

► Administration of piperacillin/tazobactam was delayed by
approximately 30 min.

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Original research

disentangling errors, discrepancies and harm
Overall, we found a lower error rate (11.5%) than
that reported in much research into intravenous
medication error (range 35%–85.9%).13–15 Some of
this difference can be explained by methodological
differences, for example, inclusion of bolus doses and
preparation errors in other studies. The difficulties in
comparing error rates between studies using different
methods and definitions, in different contexts, have
been well documented.15 16 Comparing studies using
similar methods,4 5 we found broadly comparable rates
of potentially harmful errors, with errors rated D or
above in 1.1% of infusions in our study, and 0.4%4
and 3.8%5 elsewhere. We also identified similar error
types, with the most common medication adminis-
tration errors being rate deviations and unauthor-
ised medications, and the most common procedural
and documentation deviations concerning labelling
of medication and administration sets. However, our
overall error rate remains lower than in these studies,
probably due to our more nuanced distinction between
errors and discrepancies.

While several studies consider the potential harm
associated with errors and some distinguish between

medication administration errors and procedural
failures or policy violations,4 13 we are not aware of
previous studies that sought to understand the context
of the deviation by distinguishing errors and discrepan-
cies. Researchers and practitioners may have differing
views on what constitutes an error,17 with a range of
situations identified that clinicians may not consider
errors.18 19 These judgements are largely ignored in
definitions of errors adopted in most previous studies.
Separation of discrepancies and errors in our study
allowed us to better capture the complexities of current
intravenous practices, and may be more acceptable to
clinicians who feel that the realities of practice mean
that policies cannot always be adhered to.

Previous studies have highlighted the importance
of procedural failures and policy violations in identi-
fying system weaknesses that may create latent condi-
tions for patient harm.5 In this study, we recognise
that both medication administration and procedural/
documentation deviations occur on a spectrum from
minor discrepancies to serious errors with potential
for harm. While severe errors naturally attract greater
attention, and are often the focus for intervention, a

Figure 2 Variation in error and discrepancy rates between National Health Service (NHS) trusts.

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899Lyons I, et al. BMJ Qual Saf 2018;27:892–901. doi:10.1136/bmjqs-2017-007476

Original research

Safety II perspective encourages us to look at ‘normal’
discrepancies to identify potential system weaknesses.
According to Safety II, people make adjustments to
respond to the demands of the situation and compen-
sate for system weaknesses. We identified several
cases where these adjustments avoided or mitigated
potential harm. However, these same adaptive mech-
anisms can also lead to unsatisfactory outcomes, as
identified in one instance in this study. A challenge
for safety management is that everyday discrepancies
appear trivial but can contribute to rarer and more
serious incidents.20 Our approach to distinguishing
discrepancies and errors may help clinicians to reflect
on different kinds of deviations, consider which are
important and identify discrepancy patterns that may
be concerning.

Policy and practice gaps
Much of the variability among trusts related to gaps
between policy and practice. Better understanding of
the reasons behind such performance variability is neces-
sary to target interventions that improve safety. Proce-
dural and documentation deviations may not always
represent poor practice but rather a poor fit between
official policy and everyday practice due to situational
constraints. In some cases, policies that better reflect
existing practice may be more beneficial in managing
risk to both patients and staff than enforcing compli-
ance with existing policy. For example, policies allowing
administration of flushes without a medication order in
specific circumstances or for specific patient groups,
already in place in many trusts, could be introduced at
hospitals where unprescribed flushes are accepted local
practice by clinical staff but are technically unauthorised.
National standardisation may be helpful for whether or
not small volume flushes need to be prescribed and if
so how, labelling requirements for intravenous infusions
and giving sets, and requirements for double-checking.

Implications for practice: strategic interventions and
smart pumps
Appreciating the nuances of frequency, types and
severity of deviations occurring in different contexts
moves us beyond interventions focused on improving
compliance and eliminating error, towards more stra-
tegic interventions to proactively manage risk. Care is
rarely delivered in ideal circumstances and a more prag-
matic and practical approach, incorporating a wider
range of strategies, is needed.8 Strategic decisions to
live with certain deviations might be made if efforts to
resolve them are likely to distract from other aspects
of patient care, or not translate into gains for patient
safety. More work is needed to understand if and how
routine performance variability in intravenous infusions
can spiral into rare and unsatisfactory outcomes, what
conditions contribute to poor outcomes and which
interventions should be prioritised to prevent harm
rather than only reducing discrepancies.

Smart pumps are one possible intervention to improve
safety in intravenous infusion administration. Similar
to previous US studies,4 5 we found that smart pumps,
as currently implemented in English hospitals, do not
seem to reduce the risk of error in everyday practice.
Although smart pumps may have a role in preventing
more severe and rare errors, our relatively limited
observation periods did not identify these. In addition,
greater attention to the configuration and usability of
pumps is required: a third of smart pumps used in our
study offered no advantage over standard pumps due
to incomplete drug libraries. Using smart pumps as part
of an integrated system with bar code scanning and
interfacing with electronic systems could guard against
a broader range of deviations. Although the costs
and benefits of implementing such a system have not
yet been established,4 5 such approaches have become
standard practice in the USA as both were included in
the government’s Meaningful Use programme, which
provides financial incentives to promote the use of
health information technologies to improve quality.
Such configurations are rare in English hospitals; no
participating trusts used bar code administration, and
only a minority had trust-wide electronic prescribing
and medication administration records. The high error
rate associated with infusions delivered without a pump
in our study suggests that efforts to reduce reliance on
gravity feed, where it is difficult to control the delivery
rate, may be a more immediate and achievable priority
than the expansion of smart pump technology.

Strengths and limitations
This was a large multisite study, incorporating hospi-
tals with widely differing medication processes and
systems, reflecting the diversity of intravenous infusion
practices within the English NHS. Adopting a mixed
methods approach provided a rich understanding of
intravenous medication errors and the contexts in
which they occur. There are advantages and disadvan-
tages of using local observers versus observers from
a research team. Employing local data collectors may
have allowed less conspicuous observation and reduced
the likelihood of nurses modifying their behaviour on
observation days. However, using local staff may have
resulted in some interobserver variability or institu-
tional blindness to local poor practice. Variability was
minimised as much as possible by using two observers
from different professional backgrounds at each site
where possible, providing training, and subsequent
review of data by the multidisciplinary research team.
Resource limitations and confidentiality agreements
precluded measurement of interobserver reliability
across sites.

Other limitations are acknowledged. The timing
of data collection at each trust depended on local
approvals and staff availability; both daily and
seasonal variation in staffing levels and workload
may have affected deviation rates. We focused on

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900 Lyons I, et al. BMJ Qual Saf 2018;27:892–901. doi:10.1136/bmjqs-2017-007476

Original research

infusions running at the time of observation and will
therefore have underestimated the overall medication
administration error rate; observation of prescribing,
dispensing, preparation and setting up infusions is
likely to have revealed further errors.21 Errors already
identified and corrected by smart pumps or a double
check by another staff member prior to our obser-
vations would also not be captured using our meth-
odology. Ward managers were aware the study was
investigating medication administration errors and
discrepancies, so it is possible that nurses changed
their behaviour on observation days. However, obser-
vation dates were not publicised in advance and nurses
were not directly observed, thus the impact is likely
minimal. Finally, our study was not powered to test
for associations between pump and infusion types and
error rates; our findings instead highlight areas for
further investigation.

ConCluSIon
Overall, we identified errors in 1 in 10 infusions, but
very few were likely to result in patient harm. Smart
pumps, as currently implemented, seemed to have little
effect, with similar error rates observed in infusions
delivered with and without a smart pump. Measuring
the prevalence, types and severity of errors and discrep-
ancies can provide valuable insights for reflection.
However, this needs to be coupled to causal accounts
and contextual understanding of local hospital poli-
cies, cultures, customs and practices. Not all deviations
from medication order or policy are bad; many arise
as nurses actively manage safety and productivity pres-
sures. This study suggests there is a need to shift the
focus away from the goal of eliminating deviations to
enable strategic intervention to manage infusion risk
in the context of everyday performance variability
and working conditions. Future work should explore
where efforts should be targeted to prevent harm
rather than only reducing discrepancies.

Author affiliations
1UCL Interaction Centre, University College London, London, UK
2Pain Management Centre, Imperial College Healthcare NHS Trust, London, UK
3Institute of Educational Technology, Open University, Milton Keynes, UK
4Research Department of Practice and Policy, UCL School of Pharmacy, London,
UK
5UCL Medical School, University College London, London, UK
6Royal Free London NHS Foundation Trust, London, UK
7Faculty of Computers and Information, Cairo University, Cairo, Egypt
8Brigham and Women’s Hospital, Boston, Massachusetts, USA
9Harvard Medical School, Boston, Massachusetts, USA
10Department of Medicine, Brigham and Women’s Hospital, Boston,
Massachusetts, USA
11Centre for Medication Safety and Service Quality, Imperial College Healthcare
NHS Trust, London, UK

Contributors As per previous submission.

Funding This work is supported by the National Institute
for Health Research (NIHR) grant [12/209/27], from the
Health Services and Delivery Research (HS&DR) stream. The
research is also supported by the NIHR Imperial Patient Safety
Translational Research Centre. The views expressed are those

of the authors and not necessarily those of the NHS, the NIHR
or the Department of Health.

Competing interests None declared.

Patient consent Not required.

Ethics approval NHS Research Ethics Committee (14/SC/0290)

Provenance and peer review Not commissioned; externally
peer reviewed.

Open access This is an open access article distributed
in accordance with the terms of the Creative Commons
Attribution (CC BY 4.0) license, which permits others to
distribute, remix, adapt and build upon this work, for
commercial use, provided the original work is properly cited.
See: http:// creativecommons. org/ licenses/ by/ 4. 0/

© Article author(s) (or their employer(s) unless otherwise
stated in the text of the article) 2018. All rights reserved.
No commercial use is permitted unless otherwise expressly
granted.

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901Lyons I, et al. BMJ Qual Saf 2018;27:892–901. doi:10.1136/bmjqs-2017-007476

Original research

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  • Errors and discrepancies in the administration of intravenous infusions: a mixed methods multihospital observational study
    • ABSTRACT
    • Introduction
    • Methods
      • Study design
      • Study setting and sample
      • Data collection
      • Identifying and assessing deviations
      • Data management and analysis
    • Results
      • Frequency, types and potential severity of errors and discrepancies
        • Medication administration deviations
          • Rate deviations
          • Unauthorised medication
        • Procedural and documentation deviations
      • Sources of variation in error and discrepancy rates
      • Qualitative insights
    • Discussion
      • Disentangling errors, discrepancies and harm
      • Policy and practice gaps
      • Implications for practice: strategic interventions and smart pumps
      • Strengths and limitations
    • Conclusion
    • References

Journal of

Clinical Medicine

Article

Determinants of In-Hospital Mortality in Elderly Patients Aged
80 Years or above with Acute Heart Failure: A Retrospective
Cohort Study at a Single Rural Hospital

Yusuke Watanabe 1,*, Kazuko Tajiri 2 , Hiroyuki Nagata 1 and Masayuki Kojima 3

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Citation: Watanabe, Y.; Tajiri, K.;

Nagata, H.; Kojima, M. Determinants

of In-Hospital Mortality in Elderly

Patients Aged 80 Years or above with

Acute Heart Failure: A Retrospective

Cohort Study at a Single Rural

Hospital. J. Clin. Med. 2021, 10, 1468.

https://doi.org/10.3390/jcm10071468

Academic Editor: Nuria Farre

Received: 11 February 2021

Accepted: 23 March 2021

Published: 2 April 2021

Publisher’s Note: MDPI stays neutral

with regard to jurisdictional claims in

published maps and institutional affil-

iations.

Copyright: © 2021 by the authors.

Licensee MDPI, Basel, Switzerland.

This article is an open access article

distributed under the terms and

conditions of the Creative Commons

Attribution (CC BY) license (https://

creativecommons.org/licenses/by/

4.0/).

1 Department of Internal Medicine, Hitachiomiya Saiseikai Hospital, 3033-3 Tagouchichou, Hitachiomiya,
Ibaraki 319-2601, Japan; [email protected]

2 Department of Cardiology, Faculty of Medicine, University of Tsukuba, Tsukuba 305-8577, Japan;
[email protected]

3 Department of Surgery, Hitachiomiya Saiseikai Hospital, Hitachiomiya 319-2256, Japan;
[email protected]

* Correspondence: [email protected]; Tel.: +81-295-52-5151; Fax: +81-295-52-5725

Abstract: Heart failure is one of the leading causes of mortality worldwide. Several predictive risk
scores and factors associated with in-hospital mortality have been reported for acute heart failure.
However, only a few studies have examined the predictors in elderly patients. This study investigated
determinants of in-hospital mortality in elderly patients with acute heart failure, aged 80 years or
above, by evaluating the serum sodium, blood urea nitrogen, age and serum albumin, systolic blood
pressure and natriuretic peptide levels (SOB-ASAP) score. We reviewed the medical records of
106 consecutive patients retrospectively and classified them into the survivor group (n = 83) and the
non-survivor group (n = 23) based on the in-hospital mortality. Patient characteristics at admission
and during hospitalization were compared between the two groups. Multivariate stepwise regression
analysis was used to evaluate the in-hospital mortality. The SOB-ASAP score was significantly better
in the survivor group than in the non-survivor group. Multivariate stepwise regression analysis
revealed that a poor SOB-ASAP score, oral phosphodiesterase 3 inhibitor use, and requirement of
early intravenous antibiotic administration were associated with in-hospital mortality in very elderly
patients with acute heart failure. Severe clinical status might predict outcomes in very elderly patients.

Keywords: acute heart failure; elderly patients; SOB-ASAP score; phosphodiesterase 3 inhibitor; antibiotics

1. Introduction

Heart failure is one of the most common diseases worldwide and generally affects the
elderly [1–3]. Elderly patients with heart failure are likely to have many comorbidities [2].
The prevalence of heart failure is on the rise due to the rapidly aging population [3,4]; in
2019, the estimated number of individuals aged 65 years or above in Japan was approx-
imately 36 million (28.4% of the total population). Heart failure is the leading cause of
mortality in Japan. Although several novel medications have been developed [5], thera-
peutic strategies for improving patients’ prognoses are yet to be identified.

Previous studies have suggested that risk score systems are useful for predicting
prognosis in inpatients and outpatients with heart failure [6–8]. Other studies have reported
factors leading to in-hospital mortality, such as acute kidney injury, new-onset atrial
fibrillation, and nutritional index [9–11]. However, most of these studies have focused
on relatively younger populations than the Japanese elderly population, and very few
studies have focused on the very elderly population [12,13]. The population of hospitalized
patients with acute heart failure is aging, even in rural areas. Recently, a novel scoring
system, the serum sodium, blood urea nitrogen, age and serum albumin, systolic blood
pressure and natriuretic peptide level (SOB-ASAP) score, was developed in Japanese

J. Clin. Med. 2021, 10, 1468. https://doi.org/10.3390/jcm10071468 https://www.mdpi.com/journal/jcm

J. Clin. Med. 2021, 10, 1468 2 of 10

registries [14]. The SOB-ASAP score ranges from 0 to 14; the highest score indicates a high
in-hospital mortality rate [14].

This study aimed to reveal other determinants of in-hospital mortality in very el-
derly patients (aged 80 years or older) with acute heart failure by evaluating their SOB-
ASAP score.

2. Materials and Methods

This single-hospital retrospective observational study was conducted at the Hita-
chiomiya Saiseikai Hospital, Japan. We reviewed the medical records of all consecutive
patients with heart failure admitted to our hospital between January 2017 and December
2019. The inclusion criteria were as follows: (1) hospitalized patients aged ≥80 years and
diagnosed with heart failure, (2) clinical status corresponding to heart failure, according to
the Framingham criteria [15], and (3) left ventricular function assessed with echocardiog-
raphy, at least. The exclusion criteria were as follows: (1) brain natriuretic peptide (BNP)
level <100 pg/mL or unknown, (2) readmission of the same patient with acute heart failure,
(3) no diagnosis of acute heart failure, and (4) requiring transfer to a tertiary hospital. We
divided the participants into two groups based on the prevalence of in-hospital mortality:
the survivor group and the non-survivor group.

This study was approved by our institutional review board (ID 20-06) and was con-
ducted in accordance with the Declaration of Helsinki for experiments involving humans.
The requirement for written informed consent was waived by our institutional review
board due to the retrospective nature of the study.

In echocardiography, data acquisition was performed by an expert. The variables mea-
sured and derived using echocardiography were determined as follows: two-dimensional
left ventricular ejection fraction (LVEF) was computed from the calculated left ventricular
end-diastolic and end-systolic volumes. Valvular heart disease was defined as moderate to
severe valvular disease (according to current guidelines [16–18]) or a history of valvular
surgery or cardiac surgery. Wall motion abnormality was defined as localized abnormal
wall motion, such as akinesis, hypokinesis, and dyskinesis.

Hypertension was defined as the use of medication for hypertension and/or a
history of hypertension before admission. Dyslipidemia was defined as a triglyceride
level ≥150 mg/dL, low-density lipoprotein cholesterol level ≥140 mg/dL, high-density
lipoprotein cholesterol level ≤40 mg/dL, the use of medication for dyslipidemia, or a
history of dyslipidemia. Diabetes mellitus was defined as a hemoglobin A1c level ≥6.5%
(National Glycohemoglobin Standardization Program value), the use of medication for
diabetes mellitus, or a history of diabetes mellitus. Chronic obstructive pulmonary
disease (COPD) was defined as the use of medical treatment for COPD and/or a history
of COPD before admission. We calculated the estimated glomerular filtration rate (eGFR)
from the serum creatinine levels, age, weight, and sex using the following formula:
eGFR (mL/min/1.73 m2) = 194 × s-Cr (−1.094) × age (−0.287) × 0.739 (if female) [19].
Worsening renal function was defined as an increase in the serum creatinine level
to >0.3 mg/dL [20]. The SOB-ASAP score was calculated according to the previously
published formula [14].

Statistical Analyses

All statistical analyses were performed using SPSS 26.0 for Windows (SPSS, Chicago,
IL, USA).

Continuous data are expressed as mean ± standard deviation (SD). Normality was
tested using the Shapiro–Wilk test. Normally distributed continuous variables were com-
pared between the two groups using the unpaired Student’s t-test. Continuous variables
were compared using the Mann–Whitney U-test. Categorical variables were expressed as
numbers and percentages and were compared using the Pearson’s χ2 test or the Fisher’s
exact test. Multivariate stepwise regression analysis was used to evaluate the in-hospital
mortality in elderly patients (aged ≥ 80 years) with acute heart failure; the included vari-

J. Clin. Med. 2021, 10, 1468 3 of 10

ables were found to be significant (p < 0.1) using a univariate logistic regression analysis.
We analyzed the relationship between LVEF and the in-hospital mortality by constructing a
receiver operating characteristics (ROC) curve and calculating the area under the curve. The
area under the curve was 0.66 (95% confidence interval (CI): 0.53–0.79, p = 0.018). The sensi-
tivity and specificity for an LVEF of 49.6% were 60.2% and 39.1%, respectively. Therefore, an
LVEF ≥ 50% was analyzed in the univariate analysis. Meanwhile, the variables included in
the SOB-ASAP scoring system, such as the systolic blood pressure and BNP, were excluded
from the multivariate model. A p-value < 0.05 was considered statistically significant.

3. Results

A total of 106 patients (36.8% men, mean age: 89.8 ± 4.5 years) were included in the
study (survivor group: n = 83; non-survivor group: n = 23) (Figure 1).

Figure 1. Study flow chart. BNP: brain natriuretic peptide.

Table 1 shows the comparison of the baseline characteristics and medication usage at
admission between the two groups. The systolic blood pressure was significantly higher in
the survivor group than in the non-survivor group (139 ± 33 mmHg vs. 119 ± 20 mmHg,
p = 0.011). A systolic blood pressure of ≤100 mmHg, indicating an unstable hemody-
namic status, was more prevalent in the non-survivor group than in the survivor group
(26.1% vs. 8.4%, p = 0.022). The SOB-ASAP score was significantly better in the survivor
group than in the non-survivor group (4.3 ± 2.3 vs. 6.8 ± 2.7, p < 0.001). Mineralocorti-
coid receptor antagonist usage was significantly lower in the survivor group than in the
non-survivor group (10.8% vs. 30.4%, p = 0.028).

J. Clin. Med. 2021, 10, 1468 4 of 10

Table 1. Comparison of the baseline characteristics and medication usage at admission between the survivor and non-
survivor groups.

Survivor Group
(n = 83)

Non-Survivor Group
(n = 23)

p-Value

Age, years 89.5 ± 4.6 91.0 ± 4.2 0.17
Male sex, n (%) 31 (37.3) 8 (34.8) 0.82

Height, cm 147 ± 10 149 ± 9 0.34
Body weight, kg 49.8 ± 10.6 46.4 ± 11.0 0.087

Systolic blood pressure, mmHg (n, %) 139 ± 33 119 ± 20 0.011
Diastolic blood pressure, mmHg (n, %) 78.5 ± 23.1 72.0 ± 16.0 0.35

Heart rate, beats/minute (n, %) 89 ± 26 93 ± 31 0.41
Respiratory rate, breaths/minute (n, %) 21 ± 6 19 ± 4 0.13

Systolic blood pressure ≤ 100 mmHg, n (%) 7 (8.4) 6 (26.1) 0.022
Hypertension, n (%) 76 (91.6) 21 (91.3) 0.62
Dyslipidemia, n (%) 21 (25.3) 5 (21.7) 0.48

Diabetes mellitus, n (%) 25 (30.1) 6 (26.1) 0.71
Atrial fibrillation/atrial flutter, n (%) 46 (55.4) 16 (69.6) 0.22

Pacemaker implantation, n (%) 13 (15.7) 1 (4.3) 0.14
Chronic obstructive pulmonary disease, n (%) 7 (8.4) 2 (8.7) 0.62

eGFR < 60 mL/min/1.73 m2, n (%) 61 (73.5) 16 (69.6) 0.71
Ambulance transport to emergency department,

n (%)
16 (19.3) 6 (26.1) 0.33

NYHA functional classification at admission 0.32
3, n (%) 27 (32.5) 5 (21.7)
4, n (%) 56 (67.5) 18 (78.3)

SOB-ASAP score, (n, %) 4.3 ± 2.3 6.8 ± 2.7 <0.001
Medication usage at admission

ACE-I and/or ARB, n (%) 47 (56.6) 9 (39.1) 0.14
β blockers, n (%) 27 (32.5) 7 (30.4) 0.85

Calcium channel blockers, n (%) 35 (42.2) 7 (30.4) 0.31
Loop diuretics, n (%) 47 (56.6) 17 (73.9) 0.13

Mineralocorticoid receptor antagonists, n (%) 9 (10.8) 7 (30.4) 0.028
Thiazides, n (%) 2 (2.4) 2 (8.7) 0.21
Tolvaptan, n (%) 6 (7.2) 3 (13.0) 0.30
Digitalis, n (%) 4 (4.8) 1 (4.3) 0.70

PDE3-inhibitor, n (%) 1 (1.2) 3 (13.0) 0.031
Statins, n (%) 12 (14.5) 3 (13.0) 0.58

Oral anti-diabetes mellitus agents, n (%) 12 (14.5) 2 (8.7) 0.37
Anti-platelets, n (%) 18 (21.7) 8 (34.8) 0.20

Anti-coagulants, n (%) 27 (32.5) 5 (21.7) 0.32

Categorical variables are expressed as numbers and percentages. Continuous variables are expressed as mean ± SD. ACE-I: angiotensin-
converting enzyme inhibitor; ARB: angiotensin II receptor blocker; eGFR: estimated glomerular filtration rate; GWTG-HF: Get with the
Guideline-Heart Failure; NYHA: New York Heart Association, PDE3: phosphodiesterase 3; SOB-ASAP: SO, serum sodium; B, blood urea
nitrogen; A, age and serum albumin; S, systolic blood pressure; and P, natriuretic peptide levels.

Table 2 shows the differences in the baseline laboratory data and echocardiographic
parameters between the two groups. The serum sodium levels were significantly higher in the
survivor group than in the non-survivor group (139 ± 5 mEq/L vs. 136 ± 5 mEq/L, p = 0.025).
The C-reactive protein level was significantly lower in the survivor group than in the non-
survivor group (1.5 ± 2.3 mg/dL vs. 5.1 ± 7.2 mg/dL, p = 0.0073). The BNP level was signifi-
cantly lower in the survivor group than in the non-survivor group (646.9 ± 586.9 pg/mL vs.
1170.7 ± 1018.8 pg/mL, p = 0.0033). The LVEF value was significantly better in the survivor
group than in the non-survivor group (52.8 ± 17.5% vs. 42.1 ± 19.9%, p = 0.018).

J. Clin. Med. 2021, 10, 1468 5 of 10

Table 2. The comparison of baseline laboratory data and echocardiographic parameters between the survivor and non-
survivor groups.

Survivor Group
(n = 83)

Non-Survivor Group
(n = 23)

p-Value

Laboratory data

Total protein, g/dL (n, %) 6.6 ± 0.7 (80, 96.4) 6.4 ± 0.8 (22, 95.7) 0.22
Serum albumin, g/dL (n, %) 3.4 ± 0.5 3.1 ± 0.7 0.10
Total bilirubin, g/dL (n, %) 0.79 ± 0.51 (82, 98.8) 0.76 ± 0.40 (22, 95.7) 0.10

Aspartate aminotransferase, U/L (n, %) 37 ± 32 83 ± 152 0.70
Alanine aminotransferase, U/L (n, %) 23 ± 17 51 ± 93 0.99

Serum sodium, mEq/L (n, %) 139 ± 5 136 ± 5 0.025
Serum potassium, mEq/L (n, %) 4.2 ± 0.7 4.4 ± 1.0 0.17

Blood glucose, mg/dL (n, %) 139 ± 44 (81, 90.4) 151 ± 55 (21, 91.3) 0.12
Blood urea nitrogen, mg/dL (n, %) 26.5 ± 16.5 29.1 ± 16.6 0.29

Serum creatinine, mg/dL (n, %) 1.24 ± 0.76 1.25 ± 0.60 0.53
Estimated glomerular filtration rate,

mL/min/1.73 m2 (n, %)
47.2 ± 23.3 43.4 ± 20.5 0.59

C-reactive protein, mg/dL (n, %) 1.5 ± 2.3 5.1 ± 7.2 0.0073
Hemoglobin, g/dL (n, %) 10.9 ± 2.0 11.0 ± 1.9 0.81

Brain natriuretic peptide, pg/mL (n, %) 646.9 ± 586.9 1170.7 ± 1018.8 0.0033
Echocardiography results

Left ventricular ejection fraction, (%) 52.9 ± 17.5 42.1 ± 19.9 0.018
Interventricular septal thickness, mm 9.7 ± 1.7 (82, 98.8) 9.6 ± 2.9 (22, 95.7) 0.36

Left ventricular end-diastolic diameter, mm 44.9 ± 8.8 45.6 ± 11.6 0.95
Left ventricular end-systolic diameter, mm 32.4 ± 9.4 36.3 ± 12.6 0.30

Posterior left ventricular wall thickness, mm 9.8 ± 1.9 (88, 98.8) 10.0 ± 2.2 (22, 95.7) 0.71
Left ventricular end-diastolic volume, mL 95.9 ± 44.3 103.7 ± 60.9 0.98
Left ventricular end-systolic volume, mL 47.3 ± 32.4 65.6 ± 51.2 0.28

Left atrial diameter, mm 43.1 ± 9.4 (82, 98.8) 41.8 ± 8.2 0.56
Aortic diameter, mm 29.7 ± 4.2 (80, 96.4) 31.8 ± 5.2 0.078

Valvular heart disease, n (%) 74 (89.2) 22 (95.7) 0.31
Wall motion abnormality, n (%) 9 (10.8) 4 (17.4) 0.30

Categorical variables are expressed as numbers and percentages. Continuous variables are expressed as mean ± standard deviation (SD).

Table 3 shows the comparison of treatment strategies and subsequent outcomes during
hospitalization between the two groups. The prevalence of intravenous administration of
diuretics within 48 h of hospitalization was significantly higher in the survivor group than
in the non-survivor group (80.7% vs. 56.5%, p = 0.017). The prevalence of intravenous cate-
cholamine support requirement and intravenous administration of antibiotics within 48 h
of hospitalization was significantly lower in the survivor group than in the non-survivor
group (1.2% vs. 13.0%, p = 0.031; 14.5% vs. 34.8%, p = 0.033, respectively). Intravenous
catecholamine support requirement, intravenous administration of antibiotics, and non-
invasive positive pressure ventilation support during the entire period of hospitalization
were more prevalent in the non-survivor group than in the survivor group (3.4% vs. 30.4%,
p < 0.001; 18.0% vs. 52.2%, p < 0.001; and 5.6% vs. 21.7%, p = 0.029, respectively). Worsening
of renal function was less frequent in the survivor group than in the non-survivor group
(21.3% vs. 60.9%, p < 0.001).

J. Clin. Med. 2021, 10, 1468 6 of 10

Table 3. Comparison of treatment and outcomes during hospitalization between the survivor and non-survivor groups.

Survivor Group
(n = 83)

Non-Survivor Group
(n = 23)

p-Value

Details of treatment within 48 h of hospitalization

Intravenous diuretic administration, n (%) 67 (80.7) 13 (56.5) 0.017
Intravenous carperitide administration, n (%) 1 (1.2) 0 (0.0) 0.78

Tolvaptan introduction, n (%) 5 (6.0) 0 (0.0) 0.29
Intravenous nitric acid administration, n (%) 11 (13.0) 1 (4.3) 0.21

Digoxin administration, n (%) 3 (3.6) 2 (8.7) 0.30
Intravenous catecholamine support requirement, n (%) 1 (1.2) 3 (13.0) 0.031

Oral PDE3-inhibitor and/or catecholamine addition n (%) 0 (0.0) 1 (4.3) 0.22
Intravenous antibiotic administration, n (%) 12 (14.5) 8 (34.8) 0.033

NPPV support requirement, n (%) 4 (4.8) 3 (13.0) 0.17
Morphine use, n (%) 2 (2.4) 0 (0.0) 0.61

Details of treatment and results during the entire period of hospitalization

Intravenous diuretic administration, n (%) 74 (83.1) 19 (82.6) 0.58
Intravenous carperitide administration, n (%) 1 (1.1) 0 (0.0) 0.80

Tolvaptan introduction, n (%) 11 (12.4) 6 (26.1) 0.099
Intravenous nitric acid administration, n (%) 13 (14.6) 1 (4.3) 0.17

Digoxin administration, n (%) 5 (5.6) 2 (8.7) 0.44
Intravenous catecholamine support requirement, n (%) 3 (3.4) 7 (30.4) <0.001

Oral PDE3-inhibitor and/or catecholamine
administration, n (%)

3 (3.4) 2 (8.7) 0.27

Intravenous antibiotic administration, n (%) 16 (18.0) 12 (52.2) <0.001
NPPV support requirement, n (%) 5 (5.6) 5 (21.7) 0.029

Morphine use, n (%) 1 (1.1) 2 (8.7) 0.11
Maximum serum creatinine during hospitalization,

mg/dL (n, %)
1.47 ± 0.96 2.03 ± 1.10 0.0089

Worsening renal function, n (%) 19 (21.3) 14 (60.9) <0.001

Categorical variables are expressed as numbers and percentages. Continuous variables are expressed as mean ± SD. NPPV: noninvasive
positive pressure ventilation; PDE3: phosphodiesterase 3.

Table 4 shows the results of the univariate logistic regression analysis and the multi-
variate stepwise regression analysis for predicting in-hospital mortality. Only variables
that had significant differences (p-value < 0.1), except for age and male sex, are shown
in the results of the univariate logistic regression analysis (Supplemental Table S1). The
multivariate stepwise regression analysis model showed that a poor SOB-ASAP score (per
point increase; odds ratio (OR): 1.449, 95% CI: 1.159–1.812, p = 0.0010), oral phosphodi-
esterase 3 inhibitor usage at admission (OR: 14.276, 95% CI: 1.119–182.170, p = 0.041), and
intravenous antibiotic administration within 48 h of hospitalization (OR: 3.887, 95% CI:
1.142–13.224, p = 0.030) were significantly associated with in-hospital mortality.

Table 4. Results of the univariate logistic regression analysis and the multivariate stepwise regression analysis for predicting
in-hospital mortality.

Univariate Analysis OR 95% CI p-Value

Age (per year increase) 1.077 0.969–1.197 0.17
Male sex 0.897 0.340–2.352 0.82

Systolic blood pressure (per mmHg increase) 0.975 0.956–0.993 0.0086
SOB-ASAP score (per point increase) 1.455 1.194–1.774 <0.001

Mineralocorticoid receptor antagonist use at admission 3.597 1.167–11.090 0.026
Phosphodiesterase 3 inhibitor use at admission 12.300 1.214–124.581 0.034

Serum albumin (per g/dL increase) 0.462 0.204–1.044 0.063
Aspartate aminotransferase (per U/L increase) 1.007 0.999–1.015 0.079
Alanine aminotransferase (per U/L increase) 1.012 0.998–1.025 0.083

Serum sodium (per mEq/L increase) 0.917 0.838–1.004 0.060

J. Clin. Med. 2021, 10, 1468 7 of 10

Table 4. Cont.

Univariate Analysis OR 95% CI p-Value

Serum potassium (per mEq/L increase) 1.716 0.926–3.182 0.086
C-reactive protein (per mg/dL increase) 1.267 1.087–1.486 0.0036

Brain natriuretic peptide (per pg/mL increase) 1.001 1.000–1.001 0.0080
Left ventricular end-systolic volume (per mL increase) 1.012 1.000–1.023 0.046

Left ventricular ejection fraction ≥50% 0.446 0.173–1.147 0.094
Aortic diameter (per mm increase) 1.101 0.997–1.216 0.058

Intravenous diuretic administration within 48 h of hospitalization 0.310 0.116–0.834 0.020
Catecholamine support requirement within 48 h of hospitalization 12.300 1.214–124.581 0.034
Intravenous antibiotic administration within 48 h of hospitalization 3.156 1.100–9.052 0.033

Multivariate Analysis OR 95% CI p-Value

SOB-ASAP score (per point increase) 1.449 1.159–1.812 0.0010
Phosphodiesterase 3 inhibitor use at admission 14.276 1.119–182.170 0.041

Intravenous antibiotic administration within 48 h of hospitalization 3.887 1.142–13.224 0.030

CI: confidence interval; GWTG-HF: Get with the Guideline-Heart Failure; NPPV: noninvasive positive pressure ventilation; NYHA: New
York Heart Association; OR: odds ratio; SOB-ASAP: SO, serum sodium; B, blood urea nitrogen; A, age and serum albumin; S, systolic blood
pressure; and P, natriuretic peptide levels.

4. Discussion

The three main findings of the present study are as follows: (1) the SOB-ASAP score
can predict in-hospital mortality even in very elderly patients with acute heart failure,
and (2) in addition to the SOB-ASAP score, use of oral phosphodiesterase 3 inhibitors
at admission, and requirement of intravenous antibiotic administration within 48 h of
hospitalization were important factors for predicting in-hospital mortality secondary to
acute heart failure.

The SOB-ASAP score, which can predict the clinical outcomes of patients with acute
heart failure, was found to be useful and practical. Several previous studies have performed
risk assessments for patients with heart failure, including assessments with the Get with
the Guideline-Heart Failure (GWTG-HF) risk score that was adopted globally to anticipate
the outcomes of acute heart failure [21]. Although the SOB-ASAP score was validated in
accordance with previous risk scores such as the GWTG-HF risk score, the SOB-ASAP score
includes novel serum parameters such as BNP and N-terminal pro-BNP (NT-pro BNP),
which were not considered in the previous studies [14]. Therefore, the SOB-ASAP score may
predict the outcomes of hospitalized patients with acute heart failure. Furthermore, one of
the greatest advantages of the SOB-ASAP score is that it predicts the clinical outcomes of
patients with acute heart failure during the very acute phase of hospitalization [14]. The
present study suggests the usefulness of a novel risk scoring system even in very elderly
patients with acute heart failure, which could be valuable for physicians treating patients
with heart failure.

The present study also underscores the clinical impact of treatment with oral phospho-
diesterase 3 inhibitors at admission. Phosphodiesterase 3 inhibitors are often required in
patients with heart failure having a severe clinical status [22]. One study showed that despite
their hemodynamically beneficial effects, long-term therapy with oral phosphodiesterase
3 inhibitors could increase the morbidity and mortality of patients with severe chronic heart
failure [23]. In other words, patients treated with oral phosphodiesterase 3 inhibitors are in
a worse clinical situation. Therefore, in-hospital mortality could be frequently observed in
patients with acute heart failure requiring oral phosphodiesterase 3 inhibitors.

The association between intravenous antibiotic administration within 48 h of hospi-
talization and worse clinical outcomes should be discussed further. The present study
showed that patients who required intravenous antibiotic administration in the early phase
of hospitalization were often suspected of being affected with pneumonia, because pa-
tients with worse clinical outcomes had higher serum C-reactive protein levels as well as
symptoms similar to that of pneumonia. Furthermore, a previous study showed that the

J. Clin. Med. 2021, 10, 1468 8 of 10

coexistence of comorbidities, such as pneumonia, could increase the risk of mortality in the
elderly [24,25]. The requirement of intravenous antibiotic administration in the early phase
of hospitalization could lead to acute infections such as pneumonia, and could therefore
affect the clinical outcomes of elderly patients with heart failure.

Our study has several limitations. First, because this was a single-center retrospective
observational study, there is a risk of selection bias. Second, although both left and
right cardiac function may affect the clinical prognosis [26,27], the present study did not
comprehensively assess the cardiac function. Moreover, the present study did not show the
etiology of heart failure. Furthermore, the prognosis of patients with heart failure having a
preserved ejection fraction (HFpEF) was as bad as that of patients with heart failure having
a reduced ejection fraction (HFrEF). Additionally, the prevalence of HFpEF was high in
the elderly patients with heart failure [28,29]. Therefore, the relationship between LVEF
and prognosis should be carefully interpreted. Third, the frailty and nutritional status
of patients could affect their prognosis [30,31]; however, we could not obtain sufficient
information on the baseline frailty and nutritional status due to the severity of acute heart
failure and its emergent clinical setting. Fourth, the severity of acute heart failure itself
might affect the selection of treatment. For example, in some cases, physicians may hesitate
to administer intravenous diuretics due to unstable hemodynamics. Finally, the present
study was observational in nature and had a relatively small study population; therefore,
it can be considered as a pilot study whose results need to be confirmed prospectively in
further extensive multicenter studies.

In conclusion, a poor SOB-ASAP score, oral phosphodiesterase 3 inhibitor use at ad-
mission, and requirement of early intravenous antibiotic administration were significantly
associated with in-hospital mortality in elderly patients (aged ≥ 80 years) with acute heart
failure. Recognizing patients with severe disease and high SOB-ASAP scores, which is a
novel risk scoring system, could help physicians to treat patients with heart failure.

Supplementary Materials: The following are available online at https://www.mdpi.com/article/10
.3390/jcm10071468/s1, Table S1: Univariate logistic regression analysis to predict in-hospital mortality.

Author Contributions: Conceptualization, Methodology, Original draft preparation, Data curation,
and writing: Y.W. Editing, Supervision, Reviewing Writing, and Investigation: K.T. Supervision and
Editing: H.N. Supervision and Reviewing: M.K. All authors have read and agreed to the published
version of the manuscript.

Funding: This research received no external funding.

Institutional Review Board Statement: The study was conducted according to the guidelines of the
Declaration of Helsinki and was approved by the Institutional Review Board of the Hitachiomiya
Hospital (ID 20-06).

Informed Consent Statement: Patient consent was waived due to the retrospective nature of
the study.

Data Availability Statement: The datasets generated and/or analyzed during the current study are
not publicly available because the study dataset contains potentially identifying clinical information,
but are available from the corresponding author upon reasonable request.

Acknowledgments: We are grateful to the staff of the clinical laboratory department at the Hita-
chiomiya Saiseikai Hospital for their support.

Conflicts of Interest: The authors declare no conflict of interest. The funders had no role in the design
of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or
in the decision to publish the results.

J. Clin. Med. 2021, 10, 1468 9 of 10

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  • Introduction
  • Materials and Methods
  • Results
  • Discussion
  • References

Harbin et al. BMC Geriatrics (2022) 22:458
https://doi.org/10.1186/s12877-022-03161-w

R E S E A R C H

Barriers and facilitators of appropriate
antibiotic use in primary care institutions
after an antibiotic quality improvement
program – a nested qualitative study
Nicolay Jonassen Harbin1*, Morten Lindbæk1 and Maria Romøren2

Abstract
Background: Antibiotic prescribing by physicians in primary care institutions is common and affected by several fac-
tors. Diagnosis and treatment of infections in a nursing home (NH) resident is challenging, with the risk of both under-
and overtreatment. Identifying barriers and facilitators of appropriate antibiotic prescribing in NHs and municipal
acute care units (MACUs) is essential to ensure the most adequate antibiotic treatment possible and develop future
antibiotic stewardship programs.

Methods: After implementing a one-year antibiotic quality improvement program, we conducted six semi-struc-
tured focus group interviews with physicians (n = 11) and nurses (n = 14) in 10 NHs and 3 MACUs located in the
county of Østfold, Norway. We used a semi-structured interview guide covering multiple areas influencing antibiotic
use to identify persistent barriers and facilitators of appropriate antibiotic prescribing after the intervention. The inter-
views were audio-recorded and transcribed verbatim. The content analysis was performed following the six phases of
thematic analysis developed by Braun and Clarke.

Results: We identified thirteen themes containing barriers and facilitators of the appropriateness of antibiotic use
in primary care institutions. The themes were grouped into four main levels: Barriers and facilitators 1) at the clinical
level, 2) at the resident level, 3) at the next of kin level, and 4) at the organisational level. Unclear clinical presentation
of symptoms and lack of diagnostic possibilities were described as essential barriers to appropriate antibiotic use.
At the same time, increased availability of the permanent nursing home physician and early and frequent dialogue
with the residents’ next of kin were emphasized as facilitators of appropriate antibiotic use. The influence of nurses
in the decision-making process regarding infection diagnostics and treatment was by both professions described as
profound.

Conclusions: Our qualitative study identified four main levels containing several barriers and facilitators of appropri-
ate antibiotic prescribing in Norwegian NHs and MACUs. Diagnostic uncertainty, frequent dialogue with next of kin
and organisational factors should be targeted in future antibiotic stewardship programs in primary care institutions. In
addition, for such programs to be as effective as possible, nurses should be included on equal terms with physicians.

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Open Access

*Correspondence: [email protected]

1 Antibiotic Center for Primary Care, Department of General Practice, Institute
of Health and Society, University of Oslo, Postboks 1130 Blindern, 0317 Oslo,
Norway
Full list of author information is available at the end of the article

Page 2 of 15Harbin et al. BMC Geriatrics (2022) 22:458

Background
Antimicrobial resistance is an increasing challenge
worldwide [1], and the call for prudent use of antibiotics
is in demand to slow down and reverse further resistance
development [2]. Previous studies have shown that 1/2 to
more than 3/4 of nursing home (NH) residents receive
one or more courses of antibiotics during a calendar year
[3–6]. Bacterial infections requiring antimicrobial treat-
ment has a high prevalence in long-term care residents
compared to elderly living at home [7], many of them
deemed inappropriate [8–10].

Prescribing antibiotics can be classified either as medi-
cally or ethically appropriate based on the circumstances
of the specific antibiotic-requiring infection. Medically
appropriate antibiotic use typically covers the clinical,
microbiological, pharmacokinetic and dynamic aspects
of the specific cases. Simultaneously, antibiotic treatment
among old and frail NH residents is primarily about pro-
longing life, which raises the question of whether anti-
biotic treatment is appropriate or inappropriate from
an ethical perspective. Ethical questions make infection
diagnostics and treatment a more significant challenge
for NH physicians and nurses, as multiple comorbidities,
polypharmacy, speech and hearing disabilities, cogni-
tive debilitation, and atypical symptom manifestation of
infections is more common in the NH population [11–
15]. Limited diagnostic on-site possibilities at the NHs
further complicate diagnosis and treatment of infections
[16]. Next of kin is usually more involved in promoting
NH residents’ interests and demands than in their earlier
adult life. Although the Norwegian health law demands
more next of kin involvement when residents cannot
consent, the providing physician has to make final deci-
sions in cases involving consent incompetence [17].
Besides apparent advantages and benefits of next of kin
involvement, this guardianship role may lead to tension,
disagreement and conflict between relatives and health
care professionals regarding infection treatment [18, 19].

Although the final decision to prescribe antibiot-
ics or not is taken by one or several medical physicians,
the decision-making of prescribing is multifactorial and
complex. Previous studies have identified several factors
influencing antibiotic prescribing in hospitals and gen-
eral practice, for example, physician-specific and patient-
related factors, availability of diagnostic tools and local
antibiotic resistance data, patient satisfaction and cul-
tural and organizational factors [20–31]. Many of the fac-
tors identified in general practice and hospitals may apply

for NHs, and some issues are specific to NHs affecting
antibiotic prescribing. Studies on antibiotic prescribing
decisions in NHs and older aged patients have identified
the availability of evidence-based guidelines, physicians’
habits, perceived risks of antibiotic prescribing, the influ-
ence of other health care professionals, and residents’
current clinical situation and medical history as impor-
tant factors influencing antibiotic treatment duration and
the decision-making whether or not to prescribe antibi-
otics [16, 32–36].

Responding to the emerging antimicrobial resist-
ance threat, the Norwegian Government published its
“National Action Plan against Antibiotic Resistance in
the Health Services” in 2016 [37]. As part of the plan, the
Antibiotic Centre for Primary Care launched the “RASK”
intervention in the county of Østfold, a quality improve-
ment programme aiming to optimize treatment of infec-
tions and improve antibiotic prescribing in Norwegian
NHs and municipal acute care units (MACUs) [38]. The
intervention aimed to increase the knowledge regarding
appropriate antibiotic treatment and increase the aware-
ness of the institutions’ antibiotic prescribing patterns.

Previous Norwegian studies have found a wide vari-
ation in total antibiotic use between Norwegian NHs,
indicating a potential for improving antibiotic prescrib-
ing in this sector [39, 40]. In addition, we have identified
only one previous Norwegian qualitative study on fac-
tors influencing antibiotic treatment in NH residents,
who primarily investigated the ethical problems related
to intravenous antibiotic administration perceived by
NH nurses [18]. Further studies, investigating the cur-
rent topic on a broader level is warranted. Therefore, this
focus group study aimed to in-depth explore both physi-
cians’ and nurses’ perceptions of persisting barriers and
facilitators of appropriate antibiotic use in Norwegian
NHs and MACUs after the implementation of a struc-
tured antibiotic improvement program.

Methods
This article conforms to the “Standards for Reporting
Qualitative Research (SRQR): 21-items checklist” [41].

Study setting
The current study was initiated after completing the
“RASK” intervention in Østfold county, located in the
South-Eastern part of Norway, which lasted from Octo-
ber 2016 to October 2017. In Norway, NHs may be clas-
sified as long-term, short-term or mixed (both long- and

Keywords: Nursing home, Municipal acute care unit, Antibiotic stewardship program, Barriers, Facilitators, Urinary
tract infection, Life-prolonging treatment

Page 3 of 15Harbin et al. BMC Geriatrics (2022) 22:458

short-term) based on the residency. In addition to ordi-
nary NHs, we have municipal acute care units (MACUs)
to alleviate the use of hospital services. Although classi-
fied as a part of the NH sector, MACUs differ from tra-
ditional NHs in that the patients live at home and are
admitted due to acute onset disease by general practi-
tioners during regular working hours and out-of-hours.
When the patients have been treated, they are usually
discharged home.

We invited all 37 NHs and MACUs in the county to the
intervention, resulting in 34 institutions participating in
the project. NH and MACU physicians, nurses and other
healthcare professionals from included institutions were
then invited to a one-day conference with professional
presentations and workshops on infections and appro-
priate use of antibiotics. All participating institutions
received a report presenting their antibiotic use based
on sales statistics from supplying pharmacies, compared
to other participating institutions in the county. After
the starting conference, participants were instructed to
arrange educational activities on the same topics for their
colleagues and set a goal for their institution during the
one-year project period. In addition, the institutions were
asked to register bi-monthly point prevalence surveys
on antibiotic use and indication, and tailor-made clini-
cal checklists were offered as tools to be used during the
intervention year. Follow-up conferences were held after
six and 12 months, and participating institutions received
new antibiotic reports for further academic audit and
feedback. All physicians and nurses working in the NHs
or MACUs that took part in the intervention were invited
orally at the final “RASK” conference to participate in
the current study, and in addition they were personally
invited by email or telephone. Willing informants were
included until we decided that a saturation point had
been reached. The saturation point was assessed continu-
ously by comparing the current interview with summa-
ries and transcripts of previous interviews, and decided
upon when no new themes and no additional information
on pre-existing themes occurred. We conducted six focus
group interviews between October 2017 and December
2018 with 11 physicians and 14 nurses from 13 institu-
tions. The participants did not work in the same institu-
tion, except from one interview where one physician and
three nurses were employed at the same MACU ward.
Nine physicians and six nurses had participated at one
or more conferences during the intervention year, and all
participants were familiar with the programme through
the antibiotic reports, educational material, and the use
of intervention tools at the institutions. Each focus group
consisted of three to six participants, a size range decided
upon to obtain interactive group discussions during
the interviews and to increase the involvement level for

each participant. Four of the interviews were conducted
with both physicians and nurses mixed to explore the
dynamics between the two occupational groups. The two
last interviews were conducted with only physicians in
one interview and only nurses in the other to see if we
received other information when the groups were inter-
viewed separately.

Researcher characteristics
NJH is a part time NH physician working at a short-term
NH in one of the municipalities that participated in the
“RASK” intervention. In addition, he was the respon-
sible coordinator for the “RASK” intervention in the
county of Østfold. NJH had no experience in qualitative
research prior to conducting the current study. ML is a
long-time GP and a researcher in the field of antibiotic
prescribing in general practice and NHs, and had the
overall leadership responsibility for the “RASK” interven-
tion in Østfold. MR is a GP and a long-time researcher
in the field of NH medicine and general practice. Both
ML and MR have extensive prior experience and train-
ing in conducting qualitative research. All authors share
a common interest in quality improvement in primary
care institutions, and factors affecting antibiotic prescrib-
ing in particular. Based on the authors background, one
could imagine that the informants would formulate their
answers based on what they thought was expected to be
answered. However, we perceived the discussions in the
interviews as open and rich, and that the health person-
nel talked uncensored about their thoughts, experiences
and dilemmas in their clinical work. The prior knowledge
of the organizational structure and clinical everyday life
rather was an advantage in penetrating and understand-
ing the informants’ stories and perceptions.

Data collection
The interview duration varied from 56 minutes to 87 min-
utes, with a mean overall duration of 75 minutes. NJH was
the main interviewer in all six interviews, while ML and
MR participated as co-interviewers in one and five inter-
views, respectively. We used a semi-structured interview
guide that NJH, MR, and ML developed. The interview
guide contained four main topics; 1) factors influencing
physicians’ antibiotic prescribing, 2) factors influencing
physicians’ choice to deviate from antibiotic guidelines,
3) influence of nurses on physicians’ antibiotic prescrib-
ing and 4) what ethical dilemmas physicians and nurses
experience regarding antibiotic treatment. The inform-
ants were provided with written information about the
main topics of the study by email in advance. All inter-
views were started by shortly describing the main top-
ics, followed by encouraging the informants to describe
two experienced cases where antibiotic treatment had

Page 4 of 15Harbin et al. BMC Geriatrics (2022) 22:458

been initiated; one where there had been no doubt and
the other where there had been hesitations regarding the
treatment. The main topics were then presented to the
informants step-wise through the interviews to initiate
discussions in the group. The informants were moderated
if they deviated greatly from the topics. When saturation
on the relevant topics became evident, the interviewers
moved on to the next topic in the interview guide. The
interviewers also engaged informants who were not as
involved in the discussions and complemented with in-
depth questions along the way as needed.

Data analysis
The interviewers discussed the interviews immedi-
ately after completion of each interview, and a sum-
mary for each interview was written and discussed
further by email. All interviews were audio-recorded
and transcribed verbatim. We based the analyses on the
six phases of thematic analysis developed by Braun and
Clarke [42], primarily with a inductive and semantic
approach: 1) familiarizing with the depth and breadth of
the content by reading repeatedly through the interviews
to gain a general impression, 2) generating initial codes
for the entire material using both theory and data-driven
approaches, 3) searching for themes and re-sorting the
initial codes into potential themes, 4) reviewing potential
themes at the level of the coded data extracts and creat-
ing a candidate thematic map and secondly considering
the validity of individual themes and the candidate the-
matic map in relation to the data set, 5) further defining,
refining and naming the themes and identifying barriers
and facilitators of appropriate antibiotic use, 6) identify-
ing, defining and naming overarching levels, and further
group the themes at the appropriate level, 7) produc-
tion of the article including illustrative extracts from the

material that captures the essence of the points demon-
strated. NJH transcribed the interviews and performed
the initial coding and analysis of the content. MR and ML
further evaluated the transcribed data material, as well
as the initial coding of the content. All authors partici-
pated substantially in the process of searching, defining,
reviewing and naming relevant themes and in the article
production. The qualitative data analysis software pro-
gram NVIVO 12 was used for analyses and data manage-
ment [43].

Ethical approval
All participants provided written consent prior to the
interviews. We replaced any names and places with num-
bers and characters in the transcribed text to protect the
anonymity of the participants. The Regional Commit-
tees for Medical and Health Research Ethics of South-
East Norway granted ethics approval for the study (ref.:
2017/1711), and the Norwegian Centre for Research Data
approved data protection (55,887 / 3 / LAR).

Results
The demographic characteristics of the informants are
presented in Table 1.

We identified thirteen themes grouped into four main
overarching levels affecting antibiotic use during the
analysis, ranging from individual to external and sys-
temic factors (Fig. 1). Most of the barriers and facilitators
described by the informants applied to both NHs and
MACUs. We have chosen to use the term NH further
in the article when discussing factors that apply to both
types of institutions, while we specify when factors were
applicable only to NHs or MACUs.

Table 1 Characteristics of the study informants

Demographics Physicians (n = 11) Nurses (n = 14) Overall (n = 25)

Sex Female 7 13 20

Male 4 1 5

Age Mean (range) 42 (32 – 64) 43 (25 – 62) 43 (25 – 64)

Years clinical experience Mean (range) 14 (4 – 37) 16 (2 – 41) 15 (2-41)

Type of facility Nursing home 7 10 17

Municipal acute care unit 4 4 8

Speciality Nursing home General practitioner (1) Geriatric and palliative medicine (1) –

Internal medicine (2) Rehabilitation medicine (1)

In specialisation (3) Registered nurse (8)

No specialisation (1)

Municipal acute care unit General practitioner (1) Acute geriatric medicine (3) –

In specialisation (3) Registered nurse (1)

Page 5 of 15Harbin et al. BMC Geriatrics (2022) 22:458

Barriers and facilitators at the clinical level
Unclear clinical presentation
Unclear clinical manifestations caused by infections,
especially in cognitively impaired residents, were
regarded as major contributors to diagnostic uncertainty
and difficult treatment decisions. Some physicians high-
lighted the difficulty of distinguishing viral from bacterial
respiratory tract infections, due to a perception that frail
and old residents with viral respiratory tract infections
often present with typical hallmarks of bacterial infec-
tions like fever, crackles over the lungs and increased
C-reactive protein concentrations. Identifying bacterial
aetiology was pointed out as a relevant challenge, espe-
cially during flu seasons, which often led to uncertainty
among physicians regarding the initiation of antibiot-
ics. In such cases, the resident’s general condition was
described as decisive for whether antibiotic treatment
should be initiated. Several physicians described that
they had a lower threshold for starting antibiotic treat-
ment in residents with a chronic obstructive pulmonary
disease when in doubt about the microbiological cause
of the respiratory infection. Diagnosis and treatment
of urinary tract infection (UTI) was perceived as chal-
lenging, especially in demented residents, due to non-
specific symptoms, poor anamnesis and high prevalence
of asymptomatic bacteriuria, leading to a high level of
uncertainty. Both physicians and nurses described sev-
eral approaches to uncertain UTI situations, including
watchful waiting, intravenous fluid therapy and antibiotic
prescribing to be on the safe side. With uncertain focus of

infections, several of the physicians and nurses described
that broad-spectrum antibiotics were often prescribed
to cover both the airways and urinary tract system. One
of the physicians claimed that in cases where residents
presented with new-onset non-specific symptoms, like
confusion and agitation, it was better to try a short-term
course of antibiotics than more side-effect burdened
medications.

Physician, male, 35 – 39 years: “They do not have the
clear urinary tract infection symptoms. They can be
agitated and have a positive urine stick. Instead of
starting up with haloperidol or something similar, it
is after all a bit better to give a course of pivmecilli-
nam to check if a urinary tract infection is the cause.
Therefore, you treat a little more on vague indica-
tions.”

Lack of diagnostic possibilities
Lack of diagnostic possibilities was described as a gen-
eral barrier for both the diagnostic process and for the
choice of antibiotic by both professions. On-site x-ray
was an opportunity they missed, mainly when dealing
with emerging cases of respiratory infections to avoid
unwanted and burdensome referrals to the local hospital.
One physician described a case that involved a resident
who had experienced several respiratory infections, lead-
ing to multiple antibiotic treatments. After referring the
resident to an x-ray investigation at the hospital, lung
cancer was identified. The informant emphasized that

Fig. 1 Overarching levels (in the circle) and associated themes affecting antibiotic prescribing by physicians nursing homes

Page 6 of 15Harbin et al. BMC Geriatrics (2022) 22:458

the resident could have been spared from many antibiotic
courses if inhabiting an on-site x-ray at the NH. The lack
of diagnostic possibilities were also described as a barrier
for narrow-spectrum antibiotics, as it often led to a “bet-
ter safe than sorry” approach.

Physician, male, 35 – 39 years: “We are first-line
service, so we do not have all the diagnostic tools.
When you get a case with no clear clinical focus, and
you have not performed a good advance care plan-
ning, I feel a bit trapped. I do not want to refer the
patient to the hospital, but still you want to feel that
what we do is justifiable. Then it happens that you
end up with broad spectrum (antibiotics), and it is
often with a bit of distaste, right?!”

Among the nurses, a primary concern was an often pro-
longed time from sampling to blood biochemistry and
bacteriological cultivation results. This was regarded as
a barrier to treating infections in accordance with the
National guidelines for antibiotic use and, potentially,
leading to decisions not to prescribe the recommended
first-line antibiotics.

Knowledge and awareness
The physicians and nurses pointed to a shortcoming of
knowledge, mainly amongst auxiliary nurses and regis-
tered nurses, regarding indication, sampling and inter-
pretation of point-of-care test results as a persistent
and major barrier to appropriate antibiotic treatment of
residents. Not interpreting the test results alongside the
clinical signs and symptoms was described as a recurrent
problem in the diagnostic process.

Physician, male, 40 – 44 years: “The next day the
C-reactive protein has risen, but the fever has gone
down and the patient is out of bed. Then there are
some who think that the antibiotics does not work
… and then… then you have to quickly sign up for a
course and start paying attention.”

Both professions emphasized increased knowledge
regarding the correct use of diagnostic tests as one of the
most important measures of the intervention. In particu-
lar, the indication and interpretation of urine dipstick and
C-reactive protein tests were mentioned.

To increase awareness among healthcare profession-
als, concerning own antibiotic prescribing practices and
the development of antimicrobial resistance (locally and
globally) was described as an additional intervention
measure to facilitate prudent antibiotic use.

Physician, female, 40 – 44 years: I gave the introduc-
tory antimicrobial resistance lecture, from the first
conference meeting, to my nurses. When they saw

the maps changing color throughout Europe, from
mainly green to mainly red countries, there was a
gasp from the assembly. Therefore, I think with good
and correct knowledge it at least makes it easier and
safer for me to explain and justify my choices to my
colleagues.

Strategies for coping with uncertainty
The physicians and nurses mentioned several strategies to
counteract diagnostic uncertainty and thereby facilitate
appropriate antibiotic use. Watchful waiting, often com-
bined with intravenous fluid treatment, was described as
a commonly used strategy, especially when dealing with
suspected but uncertain UTI cases. Utilization of a urine
culture to avoid unnecessary antibiotic treatment was
additionally lifted as a strategy when encountering non-
specific UTI symptoms.

Physician, male, 35 – 39 years: “When speaking of
UTIs, which is where perhaps the most disagreement
is, I think if I am in doubt “yes, we’ll send it for cul-
ture”. It takes a few days or a week until the culture
is ready, and by that time the resident has become
better or has developed more clear symptoms. Then
I gain some time on it, and can postpone or avoid
antibiotics.”

Some nurses and physicians described the clinical
checklist for suspected UTIs, offered to the participat-
ing institutions as part of the intervention, as a valuable
and effective tool in reducing the number of antibiotic
treatments in pending cases of UTIs. One perceived rea-
son for this was that the threshold for sampling urinary
dipstick tests increased amongst both auxiliary and reg-
istered nurses, leading to fewer tests being presented to
the physician for evaluation. Finally, a referral system to
the local hospital for diagnosis, treatment decision and
level of care, informally called a “diagnostic loop referral”,
was highlighted as an additional strategy when dealing
with diagnostic uncertainty. This system was mainly uti-
lized by the informants working at MACUs, and to some
extent by the NH informants.

Barriers and facilitators at the resident level
One of the physicians described the balancing act of anti-
biotic treatment in NH residents, and hence life-prolong-
ing treatment, as operating in “gray areas”.

Resident autonomy and consent competence
Most of the nurses and physicians described an increased
focus on assessing consent competence in NHs in
recent years. In addition, several of the physicians and
nurses emphasized the importance of the patients’

Page 7 of 15Harbin et al. BMC Geriatrics (2022) 22:458

voice regarding antibiotic treatment, even if cognitively
impaired and apparently consent incompetent.

Nurse, female, 35 – 39 years: “We have demented
residents who say: “No, I am now so ill that this is
not compatible with life”. And it’s a bit like, what do
you express in your own illness when you are there?
We have demented pneumonia patients who can
answer us: “Yes, thank you. It’s nice that the doctor
has been here, but I will not take any pills”. Then you
have those who want treatment for all it is worth.”

Both professions expressed that if a consent-compe-
tent resident, and to some extent consent-incompetent
residents, express a specific wish not to be treated with
antibiotics in case of a life-threatening infection, the
residents wish was usually respected. Nevertheless,
some nurses described that it was not unusual that phy-
sicians still initiated antibiotic treatments against the
residents wish not to receive treatment. Several factors
were perceived as barriers to good judgment and deci-
sions regarding antibiotic treatment in end-of-life situa-
tions. These included poor advance care planning, lack of
residents own voice, cognitive impairment, and residents
changing their minds regarding antibiotic treatment dur-
ing an ongoing infection. Nevertheless, according to both
nurses and physicians, such cases often culminated in
antibiotic treatments.

Physician, male, 35 – 39 years: “Then you have that
“fresh product” as you mentioned earlier, where you
have a patient who earlier said it does not want any
life-prolonging treatment. Then the patient gets an
infection and then they want treatment, and then
they get (antibiotic) treatment.”

Quality of life, frailty and short life expectancy
One decisive factor that was perceived as crucial regard-
ing life prolonging treatment or not, including antibiotic
treatment, was residents’ quality of life. Several different
factors influencing quality of life were mentioned, such as
familiar joys, a wish to experience important events (the
next Olympics, a wedding, etc.), or simply to enjoy good
food. When evaluating the quality of life, the physicians
and nurses expressed that this was an assessment prefera-
bly done by residents themselves. In cases with an absent
resident voice, both professions described that they usu-
ally involved next of kin to elicit information regarding
the resident’s earlier preferences. If the involvement of
the next of kin did not provide adequate information, the
choice of treatment was to be decided by the responsi-
ble physician. One physician described that degree of
cognitive impairment, pain and agitation were the most
essential prerequisites for assessing the quality of life in

residents unable to communicate themselves. There was
a a general agreement among both nurses and physicians
throughout the interviews that antibiotic treatment at the
expense of residents’ quality of life was considered uneth-
ical and inappropriate.

Physician, male, 35 – 39 years: “If the measure you
take to live longer takes away the quality of life….”

Physician, male, 40 – 44 years: “Then it may not be
the right measure.”

One physician shared that many antibiotic treatment
courses in NHs are both medically and ethically inappro-
priate, as it often prolongs residents’ suffering. Accord-
ing to the same physician, the reason for this, and hence
being a barrier to proper antibiotic treatment in these
situations, was that physicians refuse to decide to refrain
from treatment as it is perceived as unpleasant. Further-
more, that the prescriber should assess the level of frailty
and underlying disorders before initiating life-prolonging
antibiotic therapy and reflect on the life situation the
resident eventually would return to, given a successful
treatment. Achieving this, according to the same physi-
cian, would facilitate both the medically and ethically
appropriateness of antibiotic therapy in NH residents.
The same physician also applied this to residents experi-
encing recurring bacterial infections and in cases where
the preferred antibiotics lacked effect, leaving the ques-
tion of whether to change to broader spectrum antibiot-
ics or not.

Physician, male, 40 – 44 years: “You have the option
to start with penicillin, then it does not work so
you add gentamycin, and if that does not work you
switch to cefotaxim. If you choose that road, it is
clearly not the right way to go with someone that
frail in the first place. Although you might do it cor-
rect medically, you are ethically completely out of
your mind.”

Antibiotic treatment of palliative and pre-terminal
residents with short life expectancies generated mixed
responses. Several physicians expressed a tendency to
treat palliative care residents with antibiotics primarily
with a symptom-based, not life-prolonging, approach to
relieving pain and discomfort associated with the infec-
tion. On the other hand, the majority of both nurses and
physicians described a clear reluctance towards treating
pre-terminal patients with antibiotics, including treat-
ment to relieve symptoms.

Physician, female, 35 – 39 years: “It seems directly
unethical really. If you think they will die in a short
time, giving antibiotics, I do not know. There are also

Page 8 of 15Harbin et al. BMC Geriatrics (2022) 22:458

side effects. I cannot see many situations where it
can be justified.”

Barriers and facilitators at the next of kin level
Drivers for testing and treatment
Despite health personnel considering the treatment
medically and ethically inappropriate, influence and
pressure for antibiotic treatment from residents’ next
of kin were described as a persistent barrier towards
correct antibiotic use in NHs. Both the physicians and
nurses expressed that diagnostic and antibiotic treatment
should be based on residents’ wishes and medical deci-
sions made by physicians. However, several informants
from both professions were inclined to give in to non-
coherent wishes and pressure from the next of kin. Lack
of residents’ own voice, and cases where residents’ ear-
lier wishes prior to the incapacity were unknown, were
described as potential conflict-generating situations.
Some nurses even described cases where residents clearly
had expressed specific treatment wishes, but through
persuasion by next of kin had chosen to change their
position regarding treatment per the relatives’ wishes.

Nurse, female, 60 – 62 years: “This man, at that
time, he said clearly and unequivocally: “it is I who
decide”. Then the relatives persuaded him when we
were not present. Therefore, I think there is a lot of
hassle with family members.”

Disagreements and conflicts
Disagreement between health care professionals and
next of kin was widely discussed in several interviews
as a common challenge concerning antibiotic treat-
ment. Regarding frail elderly residents, the nurses and
physicians described relatives who exhibit unrealistic
expectations of the treatment effect of antibiotics and
do not understand why diagnostic testing needs a clini-
cal indication. Fear of negative coverage in the local
newspaper or filing complaints to the municipality’s
management department were reasons described for
giving in to pressure from next of kin. Another reason
for succumbing to the wishes of residents’ next of kin
was the experience that this approach generated less
work for the physician, as dealing with disagreements
and conflicts were time-consuming and tiring. When
exposed to strong disagreements regarding antibiotic
treatment, some expressed that they simply chose to
follow the wishes of next of kin to avoid conflicts. One
physician explained that in cases where family mem-
bers demanded antibiotic treatment in apparent uneth-
ical or medically futile situations, he often decided to
treat with a narrow-spectrum antibiotic knowing that

it would have no effect at all on the infection. Oth-
ers described compromise-based approaches, which
resulted in an antibiotic treatment attempt of two or
three days, with subsequent termination of the treat-
ment if the resident did not show signs of improvement.

Nurse, female, 60 – 64 years: “But the grandson of
the resident, who himself was a doctor, would not
give up. Therefore, we talked with our physician and
expressed that this was not correct. Then we decided
to prescribe antibiotics for two or three days and
then discontinue the treatment.”

Some of the nurses further expressed an impression
that residents’ relatives over the years increasingly have
gained power concerning diagnostic procedures and ini-
tiating antibiotic treatment.

Nurse, female, 45-49 years: “Whom are we actually
treating? Are we treating the resident or the rela-
tives?”

Dialogue and advance care planning
Early stage dialogue with residents’ next of kin, often con-
nected with advance care planning, was highlighted as
facilitators for achieving ethically and medically correct
antibiotic treatment of NH residents. Perceived benefits
of early dialogue included building trust relationships,
maturing and curbing relatives for future deteriorations
in health and deciding level of antibiotic treatment prior
to these events. Professional experience of healthcare
workers, continuity in terms of full-time employment of
physicians, and collaboration and agreement between
health care professionals on complex issues regarding
antibiotic treatment were described as important facili-
tators for trust building with next of kin. Although next
of kin was generally described as needing repeated real-
ity-oriented conversations concerning conflicting issues,
such dialogues were considered an essential measure for
ethically and medically correct antibiotic treatment.

Nurse, female, 60 – 64 years: “The patient has a seri-
ous illness not yet diagnosed, which the hospital has
chosen not to investigate any further. Therefore, if
we do not talk openly about this the relatives might
wonder why in the world we do not treat their dad,
right?! Such cases need clarification.”

Advance care plans, applying primarily for long-term-
care NHs, were generally seen as valuable, reassuring and
important by both physicians and nurses when dealing
with new-onset infectious conditions, mainly concerning
whether the resident should receive antibiotic treatment
or not.

Page 9 of 15Harbin et al. BMC Geriatrics (2022) 22:458

Barriers and facilitators at the organisational level
Barriers and facilitators in nursing homes
Deficient staffing resources, especially concerning physi-
cians, were described as an important barrier in terms of
optimizing diagnostics and antibiotic treatment of resi-
dents. By having frequent access to the permanent NH
physician, who inhabits knowledge of the residents and
their medical history, this was perceived as a benefit for
the residents themselves and facilitate both medically
and ethically appropriate use of antibiotics.

Physician, male, 40 – 44 years: “By being present
every day, I think you get to use antibiotics in a
much better way compared to arriving at a NH to
attend an ill resident you do not know from before.
Then it is much easier to think, “yes we’ll start anti-
biotic treatment because he is ill.”

Both professions described the collaboration between
nurses and physicians as non-problematic in terms of
antibiotic treatment. Some physicians emphasized that
due to the intervention, the collaboration worked better
because the nurses to a lesser extent conducted point-
of-care testing on their own initiative. Likewise, some
physicians also highlighted decreased pressure from the
nurses to initiate antibiotic treatment during and after
the intervention, further adding to better collaboration
between the two professions. Both professions pointed
to the crucial role of nurses regarding the diagnostic pro-
cess, where several of the physicians expressed that the
nurses literally acted as their “eyes and ears” in many
clinical decisions.

Physician, female, 40 – 44 years: “We are very
dependent on the nurses, it is therefore very impor-
tant that they have a competent clinical view and
that the collaboration works well.”

Similarly, the nurses perceived their role in clinical deci-
sion-making processes as significant, and thus having
a major impact on physicians’ clinical decisions. One
physician pointed out that if a nurse wanted a resident
treated with antibiotics, the nurse would have no prob-
lem convincing the physician into treating the resident.

Physician, male, 35 – 39 years: “Yes, so it is how they
(the nurses) describe it. They will get a cure for uri-
nary tract infection if they want. They can report
that the patient is more restless, has frequent urina-
tion and so on.”

Some physicians and nurses described two potential bar-
riers of appropriate antibiotic use regarding the nurse
role. First, different nurses may have consistently different
interpretations and reports of clinical observations. Sec-
ondly, nurses’ accuracy in relation to adherence regarding

dosing intervals of oral antibiotics was described as often
inaccurate, while with intravenous antibiotics the adher-
ence to the intervals was usually accurate. Some of the
nurses confirmed this, and described that one possible
reason may be that residents treated with oral antibiot-
ics are not considered as ill as those receiving intravenous
antibiotics.

Challenges specific for municipal acute care units
One issue that applied explicitly to MACUs was that the
diagnosis given in referral letters from general practition-
ers (GPs) and emergency physicians (OOHS) often was
perceived as deliberately incorrect. Several of the MACU
nurses and one MACU physician expressed a suspicion
that the referring physicians often used wrong referral
diagnosis as a shell hide for the real reason for admit-
tance. UTIs and dehydration were mentioned as fre-
quently used diagnoses to justify admissions to MACUs,
while the real reasons for referral often were perceived as
pressure from the patient’s relatives or the home nurse
service regarding inclining difficulties living at home
due to age, cognitive impairment and frailty. Referrals to
MACUs often include an antibiotic initiation plan when
the admission diagnosis is an infection and is usually not
re-evaluated until the MACU physician returns to the
ward. Several of the MACU nurses looked upon this as
a barrier of correct antibiotic treatment, as many of the
referred UTI cases were actual cases of asymptomatic
bacteriuria not requiring antibiotic treatment.

Nurse, female, 25 – 29 years: “We get patients
referred with a plan, like an antibiotic regimen. But
the real reason for admission is that relatives are
going on holiday … they take a urine sample, find
something on the dip stick and then they are admit-
ted to us.”

Treatment initiated by out‑of‑hours service
The nurses generally expressed that OOHS was some-
thing they strived to avoid using as far as possible, as
contacting the OOHS was tantamount to calling in a
treatment order.

Nurse, female, 35 – 39 years: “You call in an order,
and you get what you ask for.”

Regarding antibiotic treatment, several of the nurses
and physicians in the interviews shared the opinion that
OOHS physicians had a lower threshold for initiating
broad-spectrum antibiotics. Lack of knowledge con-
cerning resident history and lack of clinical examination
of residents as the treatment decision often happens by
telephone consultation were described as main barriers

Page 10 of 15Harbin et al. BMC Geriatrics (2022) 22:458

towards appropriate antibiotic use when initiated by the
OOHSs.

Physician, male, 30 – 39 years: “I think that the
OOHS physicians do not know the residents very
well, and to them an ill resident is an ill resident.
They do not think about what kind of quality of life
this patient already has. So they are faster to start
treatment, and perhaps more broad-spectrum and
more intravenous (treatment) than we might have
done. Because they do not see the whole picture.”

To avoid involving the OOHSs, some physicians pointed
out they had agreements with their NHs to be available
on phone outside working hours while others did not
follow such practice as it resulted in too many inquiries
after hours.

Treatment initiated during hospital admissions
Several of the physicians and nurses shared thoughts and
frustration regarding overtreatment of NH residents ini-
tiated during hospital stays. Palliative care and other resi-
dents with short life expectancy and reduced quality of
life returning to the NHs with ongoing antibiotic treat-
ment that clearly would outlive the resident itself, were
perceived as particular problematic cases.

Physician, female, 50-54 years: “When is enough,
enough? One resident returned from the hospital
with a gallbladder infection with intravenous anti-
biotics and nutrition, but the resident was over
ninety years old with severe heart failure. Then you
feel trapped with how long are you going to hold on,
when are you supposed to stop the treatment? I felt
the hospital over-treated the resident.”

In general, the physicians described that they seldom
challenged or re-evaluated hospital-initiated treatment,
even in cases where antibiotic treatment clearly was
questionable. Only if antibiotic treatments were excess
broad-spectrum, further degraded residents’ quality of
life or were obviously medically futile, some physicians
expressed that they might contact hospital colleagues to
discuss the treatment. Perceived barriers to challenging
hospital-initiated treatments included respecting hospi-
tal physicians being specialists, better diagnostic possi-
bilities at the hospital and difficulties defending change of
treatment towards residents’ next of kin.

Physician, female, 40 – 44 years: “Yes, so I know a
little about a lot, they know a lot about less. It is
natural that they should be better than me at this
I think. If I am very stunned, I call to ask of course.
However, to change (the treatment)? Then it has to
be completely outrageous.”

Discussion
We identified four overarching levels covering thirteen
themes affecting the appropriateness of antibiotic use in
primary care institutions: Barriers and facilitators 1) at
the clinical level, 2) at the resident level, 3) at the next
of kin level, and 4) at the organisational level (Fig.  1).
Our main finding was the unclear clinical presentation
of symptoms and lack of diagnostic possibilities as per-
sistent barriers of appropriate antibiotic use after the
quality improvement programme. Increased knowledge
and awareness, appropriate use of point-of-care tests,
increased availability of the permanent NH physicians
and early and frequent dialogue with the residents’ next
of kin were important facilitators of appropriate antibi-
otic use.

Corresponding well with a previous Dutch study [16],
we found that unclear clinical presentations greatly con-
tribute to diagnostic uncertainty. Correct diagnosis of
infections with an emphasis on distinguishing asympto-
matic bacteriuria (ABU) from cystitis, was a major educa-
tional focus of the intervention. Although the informants
described an improvement regarding these issues after
the intervention, they still expressed a clinical reality
where unclear clinical symptom presentations played a
significant role as a barrier towards medically appropri-
ate antibiotic use. In line with a previous NH interview
study [33], the informants expressed that non-specific
functional and behavioral changes often were wavered
in the clinical assessment of suspected UTI cases. When
suspecting a UTI, both based on specific and non-spe-
cific UTI symptom presentation, a further examination
by urine dipstick analysis and urinary culture is standard
practice. Taking into account the findings of Sundvall
et  al. [44] that positive urine cultures were as common
in NH residents with as without non-specific symptoms,
the continued need for education on correct clinical
assessment of UTIs in NH residents must be emphasized.
Several informants highlighted the clinical UTI checklist
on observed signs and symptoms as an effective facilita-
tor for increasing the threshold for a sampling of urinary
dipstick tests. Especially the nurses valued the checklist
and described an observed decrease in the number of
sampled urinary tests and antibiotic use for suspected
UTIs after the checklist implementation. Two recent
studies utilising checklists for signs and symptoms of sus-
pected UTIs in NH residents reported improvements in
the use of UTI antibiotics [45, 46]. Based on the findings
in these studies and our study, clinical checklists as diag-
nostic guiding tools appear to be an effective and easy to
implement measure facilitating appropriate antibiotic use
in NH residents.

Lack of on-site diagnostic tools and resources was
perceived as a persistent barrier in achieving medically

Page 11 of 15Harbin et al. BMC Geriatrics (2022) 22:458

optimal antibiotic treatment and has previously been
described [16, 34]. The nurses expressed frustration of
the delay in obtaining laboratory test results, especially
from urine cultures. The physicians did not mention this
particular issue as a major clinical challenge to the same
extent. One reason may be that the National Guidelines
for antibiotic use in NHs recommend three empirical
first-line antibiotics for UTIs, providing the physicians
with different antibiotic choices in case of treatment fail-
ure [47]. The description of utilizing urine cultures as a
facilitator to buy time and thereby avoid immediate anti-
biotic initiation when exposed to uncertain UTI cases
is to our knowledge not described before. Alongside
increased knowledge regarding clinical and laboratory
test evaluation, the informants emphasized increased
awareness concerning their own antibiotic use through
workshops as an important facilitator in achieving medi-
cally appropriate antibiotic use. This academic detailing
approach has previously been shown to facilitate reduc-
tion and appropriateness of antibiotic use in both general
practice and NHs [46, 48]. We, therefore, encourage such
an approach when planning future NH antibiotic stew-
ardship programs.

Awareness and emphasis on patient autonomy and
consent-competence were described as important facili-
tators for ethically and medically appropriate antibiotic
prescribing. The informants shared the opinion that
consent-competent residents, able to express treatment
desires, should be the major guiding factor in treatment
decision-making. This finding somewhat contradicts
the findings of Klomstad et.al. where the patients’ indi-
vidual preferences seemed to have a more peripheral
role in the decision-making regarding life-prolonging
treatment [49]. In contrast, lack of residents ability to
express themselves, due to hearing or speech difficulties,
worsened general condition and cognitive impairment,
and residents’ ambivalence regarding treatment, were
described as persistent barriers to appropriate antibiotic
use. When one or more of these factors are present, one
consequence may be that adequate anamnesis is made
more difficult, in turn leading to difficulties and uncer-
tainty regarding correct medical diagnostics and antibi-
otic treatment. Another possible consequence may be
that the patient’s desire for treatment remains unknown
to the responsible physician, which increases the pos-
sibility for initiating ethically debatable antibiotic treat-
ment. These barriers are not easily solved and rest mainly
on individual assessments by health care professionals
responsible for the treatment. Nevertheless, we believe
that these barriers can be improved by increasing the
clinical knowledge regarding infection diagnostics and
thus promoting confidence when exposed to unclear and
demanding situations. Regular colleague forums and the

opportunity to confer with other colleagues on-site or via
telephone would most likely strengthen decision-making
in similar cases. In addition, advance care planning, cov-
ering antibiotic treatment clarification, was described as
a key facilitator for appropriate life-prolonging treatment
when dealing with uncertainty generating resident fac-
tors. These findings correspond well with other studies
reporting that advance care plans often are appreciated
and has a central role in the decision-making process in
NHs, including infection treatment [16, 50].

Antibiotic therapy in palliative medicine is an area per-
meated by ethical issues without a single correct answer.
Although most informants shared the agreement that one
should avoid antibiotic treatment in residents with obvi-
ous short life expectancies, some informants expressed
willingness to treat palliative care residents with antibi-
otics to relieve discomfort associated with infections.
This tendency corresponds well with the findings of a
recent North American descriptive survey, where most
participating NHs reported that end-of-life residents
likely would receive antibiotics if UTI was suspected
[51]. Therefore, future antibiotic stewardship programs
should address these issues in an attempt to make NH
and MACU physicians better prepared in such situations.
The main message of such an approach should always be
to consider restraining from antibiotic treatment if the
residents’ quality of life most likely will be worsened by
the treatment, or if the antibiotic treatment most cer-
tainly will be medically futile.

The nurses frequently described next of kin’s expecta-
tions as one of the most considerable barriers towards
achieving medically and ethically appropriate antibiotic
treatment. The decision-making influence from next
of kin is well known from previous NH studies [52, 53].
Antibiotic treatment in such cases often conflicts with
good clinical practice, highlighting the need for better
interaction and information exchange towards residents’
next of kin. Giving in to pressure as it is less time-con-
suming, and fear of complaints and unpleasant media
coverage are previously described reasons for giving in to
pressure from next of kin [52, 53]. Advance care plans,
including early-stage and repeated dialogue with next of
kin, were regarded as facilitators for avoiding disagree-
ment and conflicts. Based on a previous Norwegian NH
study, there is further room for improvement by increas-
ing the proportion of conducted advance care plans in
NH residents [49]. Focus on readily available and clear
advance care plans familiar to the NH healthcare profes-
sionals, should therefore be a priority in future antibiotic
stewardship programs.

However, situations presenting contradictions between
treatment decisions and one’s own work ethic and known
good clinical practice may not be mitigated by advance

Page 12 of 15Harbin et al. BMC Geriatrics (2022) 22:458

care plans, dialogue with next of kin, increased clini-
cal knowledge and collegial conferring alone. Increasing
the professional knowledge and experience of care givers
in the field of ethical issues in NHs through education,
guidelines and ethical reflection groups, may contribute
to health personnel becoming more robust in the face
of such challenging situations. During the opening con-
ference of the intervention, a professional presentation
alongside a workshop covering ethical aspects of antibi-
otic treatment in NH residents were held in this regard.
Although not mentioned by the informants during the
interviews, in demanding ethical cases where the above
components fall short as to solve the issue, a clinical eth-
ics committee may be contacted for advice and guidance
in specific cases. All major health trusts in Norway and
some municipalities have a clinical ethics committee
which may be contacted by NHs when needed.

Lack of permanent physicians and infrequent regu-
lar medical visits is a common everyday situation, espe-
cially for small NHs in Norway [18] and abroad [54].
The informants in our study highlighted the increase
of these two factors as key in facilitating optimal use of
antibiotics, as it would lead to a better knowledge of resi-
dents’ medical history and settled advance care plans. In
addition, this would further reduce the involvement of
OOHSs, which by the informants would reduce the like-
lihood of unnecessary and broad-spectrum antibiotic
prescribing.

Our findings regarding the influence of nurses in the
diagnosis and treatment of infections are by no means
unique [16, 33, 34]. Given the amount of time nurses
interact with residents compared to physicians, it is natu-
ral that physicians trust and emphasize the reports from
this occupational group, highlighting the importance of
adequate and sound clinical observations and evaluations
from the nurses. However, the large variation in the qual-
ity of observations and reporting from different nurses
is worrying, potentially leading to both over- and under-
prescribing of antibiotics. Furthermore, the descriptions
about the inaccuracies of the nurses regarding oral anti-
biotic dosing intervals can, in a worst-case scenario, lead
to inadequate effect of antibiotic regimens. These barri-
ers demonstrate that antibiotic stewardship in NHs, to be
as effective as possible, should include nurses on an equal
footing with physicians.

MACUs are a relatively new service in the Norwegian
health service, and research in the field is so far scarce.
In the current study, the informants expressed a suspi-
cion that several of the referral diagnoses stated by GPs
and OOHS physicians are used as cover for other condi-
tions or situations less suitable for admittance to MACU
wards. By exploiting the large incidence of asymptomatic
bacteriuria in the elderly as a gateway to MACUs, this

increases the risk of unnecessary antibiotic prescribing.
Cumbersome and defiant collaboration between MACU
employees and GPs regarding admittance to MACU’s,
as well as vague admission criteria as perceived by GPs,
have previously been described by Johannessen et.al [55].
Together with our findings, this further strengthens the
need for better collaboration between the various pri-
mary health care services and more explicit admission
criteria to MACUs to achieve the best possible use of
antibiotics.

Previous Norwegian studies have shown that hospital-
initiated antibiotic treatment in some instances should be
challenged, including the spectrum of the initiated anti-
biotic treatment and the outlined treatment duration [56,
57]. Despite addressing this issue during the intervention
meetings, where the participants were encouraged to
evaluate critically, and if indicated challenge hospital ini-
tiated antibiotic regimens, the informants still described
a reality lacking such an initiative. The barriers described
as driving this reluctance; feeling of being less of a spe-
cialist and differences in diagnostic opportunities, may
be improved by increasing the clinical and theoretical
knowledge and competence in NH physicians as well as
to facilitate for easier conferring between NH- and hos-
pital physicians. Together with the findings of a previous
Norwegian study, which describe communication failure
at all stages of the patient pathway in the collaboration
between NHs and hospitals [58], this area calls for fur-
ther focus in future antibiotic stewardship programs.

Strengths and limitations
The main strength of the study is the investigation of not
only physicians’ perspectives, but also perspectives of
NH nurses given their obviously significant role in the
antibiotic decision-making. Furthermore, the inform-
ants’ wide range in age and working experience resulted
in rich and varied feedback that broadly and realistically
embraces the everyday clinical life in Norwegian primary
care institutions.

As a limitation applicable to most qualitative research,
this study cannot firmly conclude to what extent each
identified barrier and facilitator affects antibiotic pre-
scribing in NHs and MACUs. In order to present pre-
cise assumptions around the magnitude of each factor,
future observational and quantitative studies are war-
ranted. Another possible limitation of the study may be
the composition of informants in the first four inter-
views, in which both physicians and nurses participated
together. This may have resulted in some informants
being reluctant to express themselves credibly and truth-
fully about their own role and concerning the other
occupational group present during the interviews. Based
on this potential limitation, we conducted the two last

Page 13 of 15Harbin et al. BMC Geriatrics (2022) 22:458

interviews with only physicians present in one and only
nurses in the other one, without observing any appar-
ent differences in the feedback or dynamics compared
to the first four interviews. We therefore believe that
if such impact has found place during the mixed inter-
views, it has been of minor relevance to the results of the
study. There might have appeared changes in the inves-
tigated field in 4 years’ time between data collection and
publication of the results. However, we have not identi-
fied any new relevant guidelines or published literature
from Norwegian NHs addressing the area of interest in
the time period between data collection and publication.
We, therefore, believe our results and conclusions stands
viable and firmly and adds valuable knowledge to a field
where prior research is scarce. Lastly, when interpreting
the results of the study, it is important to remember that
our findings are based on descriptions and perceptions of
the physicians and nurses, and thus lacking the views and
experiences of residents, next of kin, other health care
professionals from other health services and the manage-
ment representatives from the institutions.

Conclusions
After the completion of a one-year antibiotic quality
improvement intervention, our focus group study reveals
a wide variety of persistent barriers influencing antibi-
otic prescribing in the participating NHs and MACUs.
Unclear clinical presentation of symptoms, lack of diag-
nostic possibilities and pressure from next of kin were
perceived as major barriers to appropriate antibiotic use.
On the other hand, increased knowledge and awareness,
appropriate use of point-of-care tests, increased availabil-
ity of permanent NH physicians and early and frequent
dialogue with the residents’ next of kin were important
facilitators of appropriate antibiotic use. The influence of
nurses in the decision-making process was by both pro-
fessions described as profound. We encourage targeting
these factors in future antibiotic stewardship programs
to achieve the most adequate antibiotic treatment possi-
ble. Future studies should lean towards quantitative and
observational methods to gain more knowledge of how to
overcome barriers and contribute to practice- and imple-
mentation developments to ensure optimal antibiotic
prescribing to elderly patients.

Abbreviations
NH: Nursing home; MACU : Municipal acute care unit; UTI: Urinary tract infec-
tion; OOHS: Out-of-hours services; GP: General practitioner.

Acknowledgements
The authors thank the physicians and nurses who participated in the inter-
views and shared their views and experiences.
The authors thank Jon Birger Haug and Siri Jensen for valuable comments and
evaluation of the manuscript.
This work was performed on the TSD (Tjeneste for Sensitive Data) facilities,

owned by the University of Oslo, operated and developed by the TSD service
group.
at the University of Oslo, IT-Department (USIT ). (tsd- [email protected] usit. uio. no).

Authors’ contributions
All authors contributed to conception and design of the present study and
collection of the data; all authors contributed to the data analysis and the
interpretation of the data; NJH drafted the article; all authors revised the article
critically for important intellectual content and approved the final draft.

Funding
This work was supported by the Norwegian Research Fund for General
Practice. The funding organization had no influence on study design, data col-
lection, data analysis, and data interpretation, and did not play a role in writing
the manuscript and in the decision to submit the manuscript for publication.

Availability of data and materials
The datasets used and/or analysed during the current study are available from
the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate
The Regional Committees for Medical and Health Research Ethics of South-
East Norway granted ethics approval for the study (ref.: 2017/1711), and the
Norwegian Centre for Research Data approved data protection (55887 / 3 /
LAR). Written informed consent was obtained from all participants prior to
conducting the interviews, and participation was voluntary. To protect the
anonymity of the participants, any names and places in the transcribed text
were replaced with numbers and characters. All methods were performed in
accordance with the relevant guidelines and regulations.

Consent for publication
Not applicable.

Competing interests
The authors declare that they have no competing interests.

Author details
1 Antibiotic Center for Primary Care, Department of General Practice, Institute
of Health and Society, University of Oslo, Postboks 1130 Blindern, 0317 Oslo,
Norway. 2 Centre for Medical Ethics, Institute of Health and Society, Faculty
of Medicine, University of Oslo, Oslo, Norway.

Received: 20 February 2022 Accepted: 24 May 2022

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RESEARCH ARTICLE

A structured training program for health

workers in intravenous treatment with fluids

and antibiotics in nursing homes: A modified

stepped-wedge cluster-randomised trial to

reduce hospital admissions

Maria Romøren1,2*, Svein Gjelstad2, Morten Lindbæk2

1 Department of Administration Vestfold Hospital Trust, Tønsberg, Norway, 2 Department of General
Practice Institute of Health and Society, University of Oslo, Blindern, Oslo, Norway

* [email protected]

Abstract

Objectives

Hospitalization is potentially detrimental to nursing home patients and resource demanding

for the specialist health care. This study assessed if a brief training program in administrat-

ing intravenous fluids and antibiotics in nursing homes could reduce hospital transfers and

ensure high quality care locally.

Design

A pragmatic and modified cluster randomized stepped-wedge trial with randomization on

nursing home level.

Participants

330 cases in 296 nursing home residents from 30 nursing homes were included. Cases

were patients provided intravenous antibiotics or intravenous fluids, in nursing home or hos-

pital. Primary outcome was localization of treatment, secondary outcomes were number of

days treated, days of hospitalization among admitted patients, type of antibiotics used and

30-day mortality.

Intervention

The nursing homes sequentially received a one-day educational program for the health

workers including theory and practical training in intravenous treatment of dehydration and

infection, run by two skilled nurses. After completing the training program, the nursing

homes had competence to provide intravenous treatment locally.

PLOS ONE | https://doi.org/10.1371/journal.pone.0182619 September 7, 2017 1 / 21

a1111111111

a1111111111

a1111111111

a1111111111

a1111111111

OPEN ACCESS

Citation: Romøren M, Gjelstad S, Lindbæk M
(2017) A structured training program for health

workers in intravenous treatment with fluids and

antibiotics in nursing homes: A modified stepped-

wedge cluster-randomised trial to reduce hospital

admissions. PLoS ONE 12(9): e0182619. https://

doi.org/10.1371/journal.pone.0182619

Editor: Terence J Quinn, University of Glasgow,

UNITED KINGDOM

Received: September 21, 2016

Accepted: July 19, 2017

Published: September 7, 2017

Copyright: © 2017 Romøren et al. This is an open
access article distributed under the terms of the

Creative Commons Attribution License, which

permits unrestricted use, distribution, and

reproduction in any medium, provided the original

author and source are credited.

Data Availability Statement: All data files are

available from the Dryad database (http://dx.doi.

org/10.5061/dryad.4sd8p). All other relevant data

are within the paper and Supporting Information

files.

Funding: The 3iV project received funding grants

from the South-Eastern Norway Regional Health

Authority and the University of Oslo, Norway. The

funders had no role in study design, data collection

Results

The intervention had a highly significant effect on treatment in nursing homes (OR 8.35,

2.08 to 33.6; P<0.01, or RR 2.23, 1.48 to 2.56). The number treated in nursing homes was
stable over time; the number treated in hospital gradually decreased (chi square for trend

P< 0.001).
Among patients receiving intravenous antibiotics in the nursing homes, 50 (46%) died

within 30 days, compared to 30 (36%) treated in the hospital (P = 0.19). Among patients

receiving intravenous fluids locally, 21 (19%) died within 30 days, compared to 2 (8%) in the

hospital group (P = 0.34). Mortality was associated with reduced consciousness and ele-

vated c-reactive protein.

Conclusions

A brief educational program delivered to nursing home personnel was feasible and effective

in reducing acute hospital admissions from nursing homes for treatment of dehydration and

infections.

Introduction

In the Norwegian population of 5.2 million inhabitants, there are 900 nursing homes and over

41 000 nursing home beds, and approximately 45% of all deaths occur here [1,2]. Nursing

home residents are characterized by high age, frailty, chronic diseases and deficits in activities

of daily living, and many have moderate to severe cognitive impairment, in Norway more than

half [3–5]. Bacterial infections and dehydration contribute substantially to acute deterioration

in nursing home residents, but treatment strategies and treatment goals is individual, multifac-

torial and context dependent [6]. Nursing home acquired infections has been a much studied

topic, in particular the most common infections pneumonia and urine tract infections. Imple-

menting diagnosis and treatment algorithms and guidelines for these conditions in long term

care facilities have proved effective in improving quality of care; in some, but not all studies

also with a reduction in hospital transfers [7–10].

Hospitalization from nursing homes is similarly complex; and transfer rates vary substan-

tially between institutions and geographical areas [11, 12]. The need for intravenous treatment

may be the only reason why many nursing home patients are transported to a hospital [13].

Hospitalization for acute care is considered potentially detrimental to the patient and resource

demanding for the specialist health care [14]. Further high quality studies of interventions to

reduce hospital admissions from nursing homes have been requested [11, 12].

As a response to these challenges, the local hospital and the Teaching Nursing Home in

Vestfold county decided to conduct and evaluate an intervention to increase the competence

in administrating intravenous fluids and antibiotics in all nursing homes in the county. The

evaluation was designed as a pragmatic and modified stepped-wedge cluster randomised

trial [15]. The number of nursing homes was high, making the stepped-wedge design with

sequential rollout both feasible given the available resources, and reasonably efficient. The aim

of the evaluation was to assess if a structured training program in administrating intravenous

fluids and antibiotics on-site can reduce the number of hospital admissions among nursing

home residents. Secondary outcomes presented are average length of treatment, 30-day mor-

tality and number of days in hospital both before and after intervention; as well as these

Intravenous treatment in nursing homes

PLOS ONE | https://doi.org/10.1371/journal.pone.0182619 September 7, 2017 2 / 21

and analysis, decision to publish, or preparation of

the manuscript.

Competing interests: The authors have declared

that no competing interests exist.

comparisons for treatment in nursing homes versus hospital; including appropriateness of

antibiotic selection.

Method

The study is reported in accordance with the Consort 2010 extension to cluster randomised

trials and the suggested modifications to the Consort 2010 cluster extension for reporting of

stepped wedge cluster randomised trials (Fig 1) [15]. Trial registration (12/1/09): Clinical-

Trials.gov NCT01023763. The registration was delayed one month after study onset due to

practical reasons. The authors confirm that all ongoing and related research within the trial is

registered.

Participants and setting

Eligible units were all 34 nursing homes in Vestfold County, Norway. Four declined to partici-

pate, two because the nursing home leaders perceived low need for intravenous treatment

among their residents, two because they used the hospital in the neighboring county. The 30

participating nursing homes had 12–124 beds (median 41), in total 1379 beds. They had one to

eight departments, and either one type of beds or a combination of beds: for rehabilitation,

short term and long term care, palliative care and special departments for patients with

dementia. Mean man-years for nurses in the nursing homes was 14.1 (range 3.5–40.2), mean

man-years for nursing assistants were 26.2 (range 5 to 105).

We used 50 beds as a cut off and defined nine nursing homes as large, 21 as small. Two of

the large nursing homes received the intervention as a pilot project to assess the training mate-

rial, equipment etc. They were not randomized and did not serve as controls pre-intervention.

These two and three other nursing homes had a certain competence and routine in adminis-

trating intravenous treatment before the project started, such as in the palliative units.

There is one hospital in the county: a local public hospital, Vestfold Hospital Trust. All

nursing home patients in need of hospitalization are admitted to this hospital, and all admis-

sions in this study were to the Medical department.

Trial design and randomization

We conducted a pragmatic and modified stepped wedge cluster randomized trial with ran-

domization on the nursing home level, each nursing home representing one cluster. The

design involves random and sequential crossover of clusters from control to intervention until

all clusters are exposed. Data collection continues throughout the study so that each cluster

contributes observations under both control and intervention observation periods [15, 16].

We selected a stepped wedge design in order to retain the power of randomization while offer-

ing all facilities enrolled in the trial exposure to what was expressed to be a desirable interven-

tion and to enable delivery of the intervention to these facilities by a small study team. The

modification refers to including the pilot sites in the intention to treat-analysis.

The formal trial period was from 1
st

of November 2009 to the 31
th

of December 2011. The

intervention was implemented in the 30 nursing homes in accordance to the randomization

plan from 11
th

of November 2009 to 1
st

of November 2011, resulting in a random and sequen-

tial crossover of clusters from control group pre-intervention to intervention group after

implementation (Fig 2). The patient-level inclusion and data collection continued during the

same period (first patient was included 17
th

of November 2009, last patient included 19
th

of

December 2011) so that each nursing home except the pilot nursing homes potentially could

contribute with cases under both control and intervention periods.

Intravenous treatment in nursing homes

PLOS ONE | https://doi.org/10.1371/journal.pone.0182619 September 7, 2017 3 / 21

Fig 1. CONSORT 2010 checklist of information to include when reporting a cluster randomised trial. Suggested

modifications to the CONSORT 2010 cluster extension for reporting of stepped wedge cluster randomised trials.

https://doi.org/10.1371/journal.pone.0182619.g001

Intravenous treatment in nursing homes

PLOS ONE | https://doi.org/10.1371/journal.pone.0182619 September 7, 2017 4 / 21

The randomization was stratified based on nursing home size and followed two computer

based lists, one with the seven large and one with the 21 small nursing homes. In order to get a

balanced randomization, we randomised three small nursing homes and then one large nurs-

ing home consecutively. The date of inclusion of the pilot sites was defined as onset of the

study (day 0). The intention was to include the remaining nursing homes one by one, giving

29 steps. The randomization list was open to the intervention team, and the two nurses who

ran the training program cooperated so that each of them included every second nursing

home consecutively according to the list. In two instances, they made appointments with their

respective nursing homes on the same day, resulting in two sites being transitioned simulta-

neously (step 13 and 23).

The study was not designed to have a fixed time between the steps. The intervention was

carried out in ordinary nursing homes with normal operation and activity, and the time to the

next step was determined by when it was feasible for each nursing home to receive two ore

more days of education within the frames of day-to-day care. For example, the educational

program could not be run during holidays with less staff and few of the permanent employees

on duty.

The median length of the steps was 14 days (0–171 days). The trial design is presented in

Fig 2.

Intervention and training

The intervention was a structured educational program in intravenous treatment of dehydra-

tion and infections for all health workers in the nursing homes (registered and enrolled

nurses and nurse assistants with and without formal education). Two nurses from the

Fig 2. Modified stepped-wedge design with 30 clusters (nursing homes). Each cluster receive the intervention at baseline. The median

length of the steps (intervals between each crossover) was 14 days (0–171 days).

https://doi.org/10.1371/journal.pone.0182619.g002

Intravenous treatment in nursing homes

PLOS ONE | https://doi.org/10.1371/journal.pone.0182619 September 7, 2017 5 / 21

Vestfold Hospital Trust ran the training program simultaneously in half of the nursing

homes each. They did not receive specific training for the purpose, but both had solid experi-

ence in intravenous treatment to elderly. The exact timing of the training, also representing

the switch from control to intervention period, and subsequently the length of time between

each nursing home switch, was determined by the capacity of the nurses and the specific

nursing home.

The training lasted one day, was held in the nursing home, and included theory of preven-

tion, presentation, diagnosis and treatment of dehydration and infections (based on Power-

Point presentations) and practical training in peripheral intravenous therapy skills and

procedures (using intravenous training arms). It was repeated one to three times in each site,

to ensure participation for all relevant personnel. The number of nursing staff trained was not

registered systematically, but the nursing home- and ward managers reported that all or the

majority of their employees participated. The few nurses or nursing assistants who did not

manage to participate (mainly due to part-time contracts and shift work which is very com-

mon in Norwegian nursing homes) were offered to visit the Simulation Centre at the hospital

for practical training. Two of the researchers contacted the nursing homes monthly for assis-

tance and support regarding treatment or data collection in the study period and were in addi-

tion available for questions on a daily basis.

In nursing homes that had completed the training program (intervention period), and had

sufficient expertise and capacity, patients in need of intravenous fluids or antibiotics were

treated locally; otherwise they were hospitalized. The control group received “standard prac-

tice”, i.e. patients were hospitalized by the nursing home doctor for intravenous treatment. As

described, a few of the larger nursing homes provided intravenous treatment before the project

started, explaining why a number of patients were treated locally in the control period.

Recruitment and data collection

Inclusion of patients: A case was defined as a patient provided intravenous treatment in either

nursing homes or hospital. We defined two groups: 1. Patients provided intravenous antibiotics
for pneumonia, urinary tract infection or skin infection, with or without additional intrave-

nous fluids, and 2. Patients provided intravenous fluids: in conjugation with an infection (with
or without oral antibiotics); due to reduced intake of fluids; due to hypotension; as a part of

terminal care etc. Inclusion criteria for patients admitted to the hospital was that they could

have been diagnosed and treated at the nursing home given necessary competence and avail-

able personnel and equipment. Patients with septicemia and patients in need of hospitalization

for additional diagnostics or treatment, were not included in the study.

Demographic and clinical data collected is listed in Table 1. Demographic data were age,

gender, co-existing diseases and Barthel Index of Activities of Daily Living 14 days before dis-

ease onset Clinical data were recorded in 30 days: at enrollment (day 1 in the treatment course)

and at given days during the course of the acute illness: diagnosis, vital signs (blood pressure,

pulse, temperature, respiratory rate), c-reactive protein (CRP) value, food and fluid intake,

consciousness, delirium assessed with Confusion Assessment Method (CAM).Direct and indi-

rect complications related to the acute disease as well as type of intravenous fluids or antibiot-

ics were also registered.

In each of the nursing homes as well as in each hospital department, one or several nurses

served as primary contact (PC) for the study team. These were responsible for including and

registering information about the patients receiving intravenous treatment in standardized

data collection forms. The nursing homes were followed closely by the study team, both

regarding the local intravenous treatment and the patient inclusion and data collection. The

Intravenous treatment in nursing homes

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Table 1. Characteristics of patients provided intravenous antibiotics or fluids in nursing homes and hospital, by control and intervention group.

Values are numbers (percentages) unless stated otherwise. Calculation of p-values was done by independent samples T-test (two-sided) for comparing

means, and two-sided chi-square test for comparing differences in counts.

Control Intervention Total P-values

Nursing

home

(n = 38)

Hospital

(n = 64)

Total

(n = 102)

Nursing

home

(n = 184)

Hospital

(n = 44)

Total

(n = 228)

n = 330 Control vs.

intervention

Nursing

home vs.

hospital

Mean age (range) 79,6

(52–95)

81,8

(38–98)

81,0

(38–98)

81,0

(45–99)

83,9

(71–93)

81,6

(45–99)

81,4 0.02 0.11

Median age 81.0 85.0 84.0 83.0 85.5 84.0 84.0 0.02 0.11

Women 28 (73) 41 (64) 69 (69) 98 (53) 21 (48) 119 (52) 188 (57) <0,01 0.91
Barthel Index of ADL

(n = 74/133)

Mean

Median

Range

6,2

6.0

(0–20)

6,6

5.0

(0–20)

6.5

5.0

(0–20)

0.72 N/A

Number regular

medications

(mean) 7,9 8,4 8,2 8,6 9,0 8,7 8,5 0.31 0.80

Co-existing diseases

Apoplexia (n = 271) 5 (32) 20 (33) 25 (32) 32 (22) 12 (27) 44(23) 69 (26) 0.11 0.18

COPD (n = 271) 3 (21) 16 (25) 19 (24) 28 (19) 14 (33) 42 (22) 61 (23) 0.59 0.08

Angina pectoris

(n = 270)

7 (50) 17 (27) 24 (31) 33 (22) 18 (41) 51 (26) 75 (28) 0.43 0.14

Heart failure (n = 270) 4 (29) 22 (35) 26 (34) 35 (24) 27 (61) 62 (32) 88 (33) 0.80 <0.01
Diabetes (n = 271) 1 (7) 15 (24) 16 (21) 21 (14) 7 (16) 28 (14) 44 (16) 0.20 0.12

Cancer (n = 270) 3 (21) 10 (16) 13 (17) 62 (42) 12 (27) 74 (38) 87 (32) <0,01 <0.01
Diagnosis in patients

treated with i.v.

antibiotics

Pneumonia 13 (65) 26 (54) 39 (57) 63 (70) 21 (58) 84 (67) 123 (63) 0.20 0.06

Pneumonia & urinary tract infect. 3 (15) 13 (27) 16 (24) 7 (8) 8 (22) 15 (12) 31 (16) 0.04 <0.01
Upper urinary tract

infection

3 (15) 7 (15) 10 (15) 10 (11) 6 (17) 16 (13) 26 (13) 0.70 0.46

Other infections* 1 (5) 2 (4) 3 (4) 10 (11) 1 (3) 11 (9) 14 (7) 0.27 0.09

Diagnosis in patients treated

with i.v. fluids

Infection (with/wthout registered

reduced intake, hypotension etc)

13 (72) 10 (63) 23 (68) 66 (70) 6 (75) 72 (71) 95 (70) 0.75 0.71

No infection (reduced

intake, hypotension etc.)

5 (28) 6 (38) 11 (32) 28 (30) 2 (25) 30 (29) 41 (30) – –

Clinical status on

enrollment (day 1)

Systolic BP (mean/

median)

120/109 138/130 132/125 122/120 140/137 127/124 125/123 0.06 <0.01

Pulse (mean/median) 92/99 93/88 93/88 84/86 90/85 86/85 87/85 0.30 0.05

Respiratory rate (mean/median) 18/18 22/22 21/20 21/20 23/20 21/20 21/20 0.72 0.24

Temp (mean/median) 37.5/37.2 37.6/37.7 37.6/37.6 37.5/37.2 37.3/37.3 37.5/37.3 37.5/37.4 0.46 0.31

Septicemia score > 2 1 (3) 4 (6) 5 (5) 7 (4) 3 (7) 10 (4) 15(5) 0.84 0.24
Reduced consciousness 22 (58) 18 (28) 40 (39) 83 (45) 15 (43) 98 (43) 138 (42) 0.52 <0.01
CRP-value (mean/

median)

79/63 132/132 116/124 108/97 152/178 119/101 111/101 0.55 <0.01

Reduced food intake 35 (92) 54 (84) 89 (87) 164 (89) 39 (89) 203 (89) 292 (89) 0.64 0.35

Reduced fluid intake 34 (90) 57 (89) 91 (89) 165 (90) 39 (89) 204 (90) 295 (89) 0.94 0.84

Delirium 4 (11) 15 (23) 19 (19) 27 (15) 7 (16) 34 (15) 53 (16) 0.43 0.17

*Skin, gastrointestinal and unspecified infections

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PCs were contacted for a follow-up by telephone on a regular basis. In addition, the study

team was available for support to the nursing homes and on e-mail and telephone on a daily

basis. The nursing homes received a follow-up visit some months after the intervention, a few

were visited several times. Complete patient inclusion was easier to control at the hospital.

Twice weekly, a list of admissions to the Medical Department was provided, and the study

team ensured inclusion of all patients filling the inclusion criteria.

Outcome measures

Outcomes were measured in individual residents. The unit of analysis was the treatment level,

whereas the cluster level was the nursing homes, serving as the unit of allocation and interven-

tion. The primary outcome measure was number of patients treated with intravenous antibiot-

ics and/or fluids in a participating nursing home or in Vestfold Hospital Trust. Secondary

outcome measures were number of days treated, number of days of hospitalization among the

admitted patients, type of antibiotics used, and mortality within 30 days. The antibiotic selec-

tion was compared with the national guidelines for antibiotic use in nursing homes and in hos-

pital [17, 18]. Information on other health care related treatment outcomes collected will be

reported elsewhere.

Statistical analysis

IBM SPSS
1

statistics program and STATA 12 were used for statistical analyses. The logistic

regression analyses were performed as multilevel models with nursing homes as clusters (ran-

dom intercept). Comparison of means were analysed by independent samples T-test (two-

sided alpha). The Stata function “CLTEST” was used to perform cluster-adjusted Chi-square

tests (P-value from the group adjustment Chi-2) for comparing differences in counts. All anal-

yses were conducted on an intention-to-treat-basis. The nursing homes in the pilot study were

included in the analyses to increase the sample size. Identical analyses were also performed

without the two pilot sites. In all the logistic regression analyses, the identity of the nursing

home was used as the cluster identification (random intercept). In the bivariate and multivari-

ate logistic regression analysis, the dependent outcome variable described whether the patient

was treated in a nursing home or in the hospital. The associations are presented in odds ratios

(OR) and for the main outcome an estimated relative risk (RR) [19]. Independent variables

were age, gender, number of regular drugs, Barthel Index and the co-existing diseases and the

measures of clinical status on day 1 listed in Table 1, intravenous fluids or antibiotics provided

and intervention or control period. Variables not significantly associated with location of treat-

ment in bivariate analysis were not included in multivariate analysis (except gender). The vari-

ables CRP and blood pressure (BP) were grouped into tertiles; the level of consciousness was

dichotomized to “awake” or “reduced consciousness or somnolence”. To assess comparability

between patient groups, we used the chronic diseases recorded in the collection forms, and the

number of regular medications, as a proxy for the patients’ general health status.

The time variation variable, describing how many nursing homes that were included at the

time of each patient event, was recoded into a six-category variable, as the original variable had

30 different categories that would make the resulting results more difficult to interpret.

We used a significance level of p < 0.05 for all analyses. Explanatory variables with a value

of p > 0.2 in a bivariate multilevel regression were excluded from the multivariate model, with

exception of gender. In the multilevel logistic regression models we used nursing home as the

cluster level, and calculated the intra cluster correlation coefficient (ICC), using the STATA

function “estat icc”.

Intravenous treatment in nursing homes

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Few patients were included more than once: 273 patients (92%) were included once,19

patients (6.4%) twice, 2 patients (1%) three times, 1 patient (0.3%) 6 times and 1 patient (0.3%)

7 times. Allowance for repeated measures on individuals was therefore not included in the

analysis.

Sample size estimation

There was no previous research on nursing home patients in need of hospitalization for intra-

venous treatment in this setting. The power calculation was based on assumptions and discus-

sions with health workers and administrators in the field. As some nursing homes already

provided intravenous treatment, we estimated that 10% of the patients were treated locally at

baseline. We further estimated a 25% reduction of hospital admissions of patients in need of

intravenous treatment, from 90% to 65%. We used a two-sided alpha level of 0.05 and a beta of

0.80. We assumed a cluster-coefficient of 0.10. The calculation gave an estimate of 56 patients

in each group. With a calculated drop out proportion of 10%, the estimated number of patients

needed to treat increased to 65 patients in each group, totally 130 patients, or 4.3 patients from

each of the 30 nursing homes. The original power calculation was for a standard RCT, allow-

ance for the number of steps and allowance for any repeated measures on individuals was not

included in this sample size calculation.

Patient involvement

Patients were not involved in the design, development of outcome measures, recruitment to or

conduct of the study, but patients’ priorities, experiences, and preferences was indirectly taken

into account. The Teaching Nursing Home played an important role in planning and imple-

mentation of the project, and nurses from all nursing homes were involved in planning the

study, recruitment of patients and collection of data. The results is planned to be disseminated

to the participating nursing homes and the hospital through seminars and workshops for the

health personnel and administrators. We also aim to make the results known to lay people

through mass media.

Ethical considerations

The Regional Committee for Medical Research Ethics verbally communicated the approval of

the collaborative research project after a committee meeting 19
th

October 2009, confirmed by

letter the 13
th

November 2009 (reference no. 2009/1584a-1). Their assessment of the burden of

the intervention on patients concluded that the intervention was beneficial to nursing home

patients. Written informed consent was obtained from all patients. In patients lacking deci-

sion-making capacity, written consent was collected from next of kin.

Results

Numbers analyzed

296 patients with 330 treatments were included during the 26-month period; Fig 3 displays the

participant flow for the study.

Table 2 gives the number of patients treated locally or admitted to hospital in each nurs-

ing home before and after intervention. Intention to treat analysis was conducted for the 2

pilots and the 28 nursing homes randomized into the intervention. The two pilots and four

Intravenous treatment in nursing homes

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additional nursing homes had no intravenous treatments registered in the control period;

four nursing homes had no treatments registered after the intervention.

Despite tight follow-up by the research team, we discovered that not all patients treated

locally were included in the study. Reasons given by the PCs for not including patients were

mainly lack of time or lack of dedication among the staff to adhere to the data collection. We

do not know the exact number of patients that were treated in the nursing homes or if the

non-inclusion varied throughout the period. We have no reason to believe that patients not

included in the study differed from patients included.

Fig 3. Flowchart showing nursing home and patient recruitment. Patients that did not fill the inclusion

criteria, or patients who by mistake were eligible, but not included, were not registered. All eligible patients

consented to participate and no patients were excluded. None of the included patients were lost during the 30

days follow up; death in the period was regarded as an outcome.

https://doi.org/10.1371/journal.pone.0182619.g003

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Participant characteristics

Table 1 displays participant characteristics at the time of inclusion. The patients in the control

and intervention group were similar in most of the characteristics except a higher proportion

of women in the control group; a higher proportion of patients with cancer in the intervention

group and a higher proportion of combined pneumonia and UTI in the control group.

Among patients treated with intravenous antibiotics, pneumonia was the dominating diagno-

sis: 57% (95% confidence interval 45 to 69%) before and 67% (58 to 75%) after the interven-

tion, P = 0.12). Among patients treated with intravenous fluids before the intervention, 23

(68%, 51 to 84%) had an infection and 11 (48%, 26 to 70%) were treated with oral antibiotics;

Table 2. Number of patients provided intravenous treatments in nursing home or hospital and treatments per 100 beds per month in each of the

30 nursing homes in Vestfold, Norway in the study period 2009–2011.

Control period Intervention period Total

Hospital Nursing home Treatmentsper

100beds/month

Hospital Nursing home Treatments per

100beds/month

Nursing

home no.

Number of

beds

No. iv

ab

No. iv

fluids

No. iv

ab

No. iv

fluids

No. iv

ab

No. iv

fluids

No. iv

ab

No. iv

fluids

1 124 0 0 0 0 – 3 1 14 11 0.90 29

2 122 0 0 0 0 – 5 1 42 40 2.77 88

3 19 0 0 0 0 0 1 0 0 6 1.42 7

4 22 0 0 0 0 0 0 0 1 3 0.76 4

5 48 0 0 0 0 0 3 0 4 5 1.04 12

6 38 0 0 1 0 0.66 1 0 1 4 0.72 7

7 12 1 0 0 0 2.08 1 0 0 1 0.76 3

8 68 1 0 0 0 0.29 5 0 0 3 0.56 9

9 26 5 0 0 1 4.62 3 1 4 1 1.65 15

10 16 1 0 0 0 1.04 1 0 0 1 0.63 3

11 69 2 2 3 0 1.69 2 0 3 2 0.51 14

12 28 3 1 0 1 1.79 1 0 1 1 0.67 8

13 20 0 0 0 1 0.45 0 1 0 0 0.33 2

14 16 3 0 0 0 1.56 0 1 4 1 2.68 9

15 86 1 0 2 1 0.39 4 0 1 1 0.50 10

16 18 0 0 0 2 0.93 0 0 0 1 0.40 3

17 32 2 2 0 1 1.30 0 0 8 1 2.01 14

18 58 3 0 0 0 0.34 1 0 0 4 0.78 8

19 64 0 0 0 0 0 0 0 1 0 0.14 1

20 52 4 5 0 0 1.15 0 0 0 0 0 9

21 33 0 0 1 0 0.19 1 0 1 0 0.61 3

22 20 4 0 1 2 2.19 1 2 0 2 2.50 12

23 76 3 1 0 0 0.33 1 0 0 1 0.26 6

24 25 2 1 0 0 0.71 1 0 0 0 0.44 4

25 48 0 1 2 0 0.37 0 0 0 0 0 3

26 56 3 0 10 3 1.59 0 1 5 3 2.01 25

27 46 2 2 0 0 0.48 1 0 0 1 0.54 6

28 38 2 1 0 0 0.44 0 0 0 0 0 3

29 55 4 0 0 0 0.32 0 0 0 1 0.61 5

30 44 2 0 0 6 0.76 0 0 0 0 0 8

Sum 1 379 48 16 20 18 0.86 36 8 90 94 0.87 330

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after the intervention, 72 (71%, 62 to 80%) had an infection (P = 0.746), and 21 (57%, 45 to

69%) were treated with oral antibiotics (P = 0.44).

Comparability between patients treated locally and patients admitted to hospital is neces-

sary for the comparison of clinical outcome in the two treatment levels. The major difference

was that 110 of 222 (50%, 43 to 56%) of the patients treated in the nursing home and 84 of

108 (78%, 70 to 86%) patients treated in the hospital were provided intravenous antibiotics

(P<0.001). Further, among patients receiving intravenous antibiotics, 21 (25%, 16 to 34%) had

a combined pneumonia and urinary tract infection in the hospital versus 10 (9%, 4 to 15%) in

the nursing homes (P<0.001). The proportion of patients with heart failure was lower in the

nursing home group than in the hospital group (24%, 17 to 31% versus 46%, 36 to 55%,

P<0.001), while cancer was more frequent (40%, 32 to 47% versus 21%, 13 to 28%, P<0.001).

Of the vital signs on treatment day 1, the systolic blood pressure was lower in the nursing

home group (mean 123 mmHg, 118 to 127 mmHg, versus 135 mmHg, 129 to 141, P<0.001);

the pulse was lower (mean 85 (82 to 88) versus 90 (86 to 94), P<0.001); a higher proportion

had a reduced level of consciousness (47% (41 to 54%) versus 31% (22 to 39%), P<0.01) and

CRP was lower (mean 100 (88 to 112) versus 130 (113 to 148), P<0.001).

Primary outcome: Location of intravenous treatment

In the majority of the nursing homes, few patients received intravenous treatment—regardless

of location: median 0.47 patients were treated per 100 beds per month (range 0–4.6) before the

intervention and median 0.62 patients were treated per 100 beds per month (range 0–2.8) after

the intervention (Table 2). The proportion of patients treated in the nursing home increased

from 37% (28 to 47%) in the control period to 81% (76 to 86%) in the intervention period

(P<0.05) (Table 3). The proportion of patients treated with intravenous fluids in the nursing

homes increased from 53% (35 to 71%) to 92% (87 to 97%), P<0.001, whereas the proportion

of patients treated with intravenous antibiotics in the nursing homes increased from 29% (18

to 41%) to 71% (63 to 79%), P<0.001. The two pilot nursing homes had the highest number

of patients treated locally. When we excluded these two nursing homes, the proportion of

patients treated locally with intravenous fluids increased from 53% (35 to 71%) to 88% (78 to

97%) after intervention (P<0.001), and the proportion of patients treated with intravenous

antibiotics increased from 29% (18 to 41%) to 55% (42 to 68%) (P<0.005).

Table 3. Number of patients receiving intravenous antibiotics and fluids in hospital versus nursing home in the intervention and control group.

Values are numbers (percentages). The calculated p-values are adjusted for clustering at the nursing home level.

Control Intervention P-values

n (%) n (%)

Patient provided antibiotics

Nursing home 20 (29) 90 (71)

Hospital 48 (71) 36 (29)

Total 68 (100) 126 (100) <0.05
Patients provided intravenous fluids

Nursing home 18 (53) 94 (92)

Hospital 16 (47) 8 (8)

Total 34 (100) 102 (100) <0.05
All patients treated

Nursing 38 (37) 184 (81)

Hospital 64 (63) 44 (19)

Total 102 (100) 228 (100) <0.05

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Fig 4 shows the development of number and location of iv-treatments over time. The

number treated in nursing homes is stable over time (linear trend -0.04, P = 0.97), while the

number treated in hospital gradually reduced through the project period (linear trend -2.38,

P = 0.02). The difference between these two groups is significant (chi square for trend

P< 0.001). We found a similar trend without the pilot sites included (S1 Fig)

The multivariate analysis adjusting for covariates confirmed that there was a highly signifi-

cant effect of the intervention on treatment in nursing homes (OR 8.35 (2.08 to 33.6), P<0.01,

corresponding to RR 2.23, 1.48 to 2.56 (Table 4). Congestive heart failure and the clinical vari-

ables high blood pressure and CRP in the upper tertile associated significantly with admission

to hospital. The nursing home group level ICC was estimated to 0.51 (0.26 to 0.76). The results

were similar without the pilots included (S1 Table).

Secondary outcomes: Course of disease and antibiotic use

Number of days of hospitalization among the admitted patients was mean 7.3 days (median 6,

range 1–35) before the intervention and mean 7.1 days (median 5, range 1–30) after the inter-

vention, (P = 0.9). Patients provided intravenous antibiotics were treated mean 7.3 days

(median 6.0, range 1–29) before and mean 8.2 days (median 7.0, range 1–36) after the inter-

vention (P = 0.30). Patients provided intravenous fluids were treated mean 3.8 days (median

3.5, range 1–11) before and mean 4.4 days (median 3.0, range 1–30) after the intervention

(P = 0.43).

Nursing home versus hospital treatment

The patients were treated with intravenous antibiotics mean 7.5 days (median 6, range 1–25)

in the nursing homes, mean 8.4 days (median 6, range 1–36) in the hospital (P = 0.21). Among

patients receiving intravenous antibiotics in the nursing homes, 50 (45% (36 to 55%)) died

within 30 days, compared to 30 (36%, 25 to 46%) treated in the hospital (P = 0.17).

Patients provided intravenous fluids were treated mean 4.7 days (median 4, range 1–30) in

the nursing homes, mean 2.2 days (median 2, range 1–5) in the hospital (P = 0.01). Among

patients receiving intravenous fluids locally, 21 (19%, 95% CI 11 to 26%) died within 30 days,

compared to 2 (8%, 95% CI 0 to 20%) in the hospital group (P = 0.22).

Fig 4. Number of patients receiving intravenous antibiotics and fluids in nursing home versus hospital in the study period, per 3 months.

https://doi.org/10.1371/journal.pone.0182619.g004

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Multilevel logistic regression analysis revealed that treatment with intravenous antibiotics

rather than fluids, reduced level of consciousness, elevated CRP-value and age <70 were asso-

ciated with 30-day mortality (Table 5). Treatment located in nursing home or in hospital was

not associated with increased mortality. In identical analysis on the subgroup receiving intra-

venous antibiotics, reduced level of consciousness and age <70 was associated and elevated

CRP-value was insignificantly associated with 30-day mortality. In the analysis on the sub-

group receiving intravenous fluids, no factors was significantly associated with 30-day

mortality.

Antibiotic choice

The choice of intravenous antibiotics differed in the nursing homes compared to the hospital

(Table 6). For pneumonia, 47 (62%, 51 to 73%) of 76 nursing home patients were given cepha-

losporins alone or in combinations, 18 (38%, 24 to 53%) of 47 patients treated in the hospital

(P = 0.01). For urine tract infections, 12 (92%, 76 to 100%) of 13 nursing home patients were

given cephalosporins, 11 (85%, 34 to 64%) of 13 patients treated in the hospital (P = 0.54). The

antibiotic choice was also broad spectrum among the 52 patients who were provided intrave-

nous fluids and oral antibiotics, but numbers were too small to compare choices in nursing

homes versus hospital. Phenoxymetylpenicillin was provided to only 6 (12%, 3 to 21%) of 52

patients, all with a respiratory tract infection (Table 6).

Implementation of intravenous treatment in the nursing homes

Over 90% of the health personnel (nurses and nursing assistants) in the 30 nursing homes

received the intervention. Feedback during the training, follow-up meetings and evaluations

Table 4. Associations of demographic and clinical variables with intravenous treatment in the nursing home. Multilevel logistic regression model

with nursing home as cluster (random intercept).

Factors Bivariate analysis Multivariate analysis (N = 249)

OR (95% CI) P-value OR (95% CI) P-value

Intervention 5.60 2.79 to 11.2 <0.01 8.35 2.08 to 33.6 <0.01
Intravenous antibiotics 0.18 0.09 to 0.36 <0.01 0.89 0.31 to 2.54 0.82
Gender 0.69 0.38 to 1.23 0.21 0.95 0.39 to 2.29 0.90

Reduced consciousness 3.21 1.71 to 6.05 <0.01 2.12 0.84 to 5.38 0.11
Systolic blood pressure at onset (tertiles)

<115 mmHg Reference Reference
115 to 138 mmHg 0.65 0.31 to 1.37 0.26 0.84 0.27 to 2.56 0.75

>138 mmHg 0.33 0.16 to 0.67 <0.01 0.33 0.11 to 2.56 0.04
CRP at onset (tertiles)

<65 Reference Reference
65 to 156 0.78 0.36 to 1.67 0.52 0.75 0.24 to 2.33 0.62

>156 0.25 0.11 to 0.57 <0.01 0.20 0.06 to 0.73 0.02
Congestive heart failure 0.20 0.09 to 0.42 <0.01 0.15 0.06 to 0.42 <0.01
Number of nursing homes in intervention (time factor)

1 to 5 Reference Reference

6 to 10 0.57 0.21 to 1.54 0.27 0.67 0.11 to 3.94 0.66

11 to 15 1.30 0.49 to 3.43 0.60 1.74 0.31 to 9.73 0.53

16 to 20 0.45 0.15 to 1.29 0.14 0.53 0.09 to 3.05 0.48

21 to 25 4.46 1.11 to 17.9 0.04 6.59 0.58 to 75.5 0.13

26 to 30 3.83 1.27 to 11.5 0.02 2.47 0.35 to 17.5 0.36

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was positive. Among advantages described, were that the patients were treated in surroundings

and by personnel familiar to them—by personnel knowing them well; and the general phrase:

“That hospitalization was avoided”. Among disadvantages described were practical difficulties

with placing and keeping the PVC and confrontation with ethical dilemmas with end-of-life

treatment. As a solution to the former, the ambulance service offered to assist in the practical

problems with the PVC when necessary. All nursing homes were actively planning to continue

providing intravenous treatment in the future.

Discussion

The principal finding of this trial were that a structured training program in administrating

intravenous fluids and antibiotics was highly effective in reducing the number of hospital

admissions for dehydration and infections among nursing home residents. Hospitalization of

the acute ill and frail elderly patient in many cases lead to a worsening of functional abilities,

even though the specific condition for which the patient is transferred may improve [20, 21].

The research literature on hospitalization from nursing homes is extensive, but it is difficult to

generalize on the extent of avoidable complications of hospital transfers such as delirium and

pressure ulcers [11]. However, given that the patient can receive the same treatment and care

Table 5. Associations of demographic and clinical variables with 30-day mortality in patients provided intravenous treatment in nursing homes

and hospital. Multilevel logistic regression model with nursing home as cluster (random intercept).

Bivariate analysis Multivariate analysis (n = 249)

OR (95% CI) P-value OR (95% CI) P-value

Intervention 1.49 0.88 to 2.51 0.14 1.22 0.50 to 3.05 0.66

Nursing home treatment 1.12 0.68 to 1.84 0.67 1.43 0.64 to 3.23 0.39

Intravenous antibiotics 3.54 2.05 to 6.11 <0.01 2.79 1.23 to 6.30 0.01
Female 1.10 0.69 to 1.76 0.69 1.03 0.56 to 1.90 0.92

Age

<70 Reference Reference
70 to 79 0.31 0.13 to 0.70 <0.01 0.17 0.57 to 0.52 <0.01
80 to 89 0.42 0.20 to 0.88 0.02 0.37 0.13 to 1.04 0.06

>90 0.37 0.16 to 0.88 0.02 0.37 0.12 to 1.14 0.08
Congestive heart failure 0.22 0.72 to 2.09 0.46 1.41 0.72 to 2.77 0.32

Reduced consciousness 2.14 1.31 to 3.47 <0.01 2.61 1.41 to 4.83 <0.01
Systolic blood pressure at onset (tertiles)

<115 mmHg Reference Reference
115 to 138 mmHg 0.87 0.50 to 1.53 0.63 1.28 0.61 to 2.68 0.52

>138 mmHg 0.71 0.39 to 1.27 0.25 0.93 0.43 to 2.00 0.86
CRP at onset (tertiles)

<65 Reference Reference
65 to 156 1.28 0.67 to 2.44 0.46 0.86 0.39 to 1.93 0.72

>156 2.98 1.59 to 5.57 <0.01 1.84 0.82 to 4.15 0.14
Number of nursing homes in intervention (time factor)

1 to 5 Reference Reference

6 to 10 0.53 0.22 to 1.25 0.15 0.54 0.17 to 1.68 0.29

11 to 15 1.41 0.65 to 3.06 0.38 1.86 0.64 to 5.42 0.26

16 to 20 0.70 0.33 to 1.47 0.34 0.67 0.24 to 1.89 0.45

21 to 25 0.76 0.31 to 1.87 0.56 0.95 0.25 to 3.57 0.94

26 to 30 0.73 0.35 to 1.52 0.40 0.71 0.22 to 2.32 0.57

https://doi.org/10.1371/journal.pone.0182619.t005

Intravenous treatment in nursing homes

PLOS ONE | https://doi.org/10.1371/journal.pone.0182619 September 7, 2017 15 / 21

in the nursing home, to avoid the burden and complications of relocation is obviously benefi-

cial to the patients.

The total number of patients provided intravenous treatment fell during the project period:

the proportion of patients treated in hospital reduced during the intervention while the num-

ber treated in nursing homes was stable. Of the factors contributing to the overall reduction is

an unplanned effect of the intervention: The nursing home staff described an increased aware-

ness and increased use of advanced care planning, as well as more informal general and case

specific discussions of ethical aspects and actual need of intravenous treatment and of hospital-

ization; leading to a more prudent consideration of curative or supportive treatment of the

patients. The proportion of patients provided intravenous fluids was higher in the nursing

homes than in the hospital, indicating that the need was higher and threshold lower for provid-

ing intravenous fluids than for parenteral antibiotic treatment locally. Length of intravenous

treatment, days of hospitalization among the admitted patients and 30-day mortality before

and after the intervention, was similar. 30-day mortality was not associated with location of

treatment, but the study was underpowered to conclude on mortality among patients provided

intravenous treatment in nursing homes versus hospital. Factors associated with increased

30-day mortality were treatment with intravenous antibiotics rather than fluids, CRP > 165

and reduced consciousness, all being factors serving as a proxy for severity of disease; also

found elsewhere [14, 22]; and age <70. In the nursing home population, biological age is not a

predictor of prognosis, but a higher mortality in the youngest residents is likely because these

are often patients with cancer in palliative units or patients with severe and invalidating

diseases.

Table 6. Choice of antibiotics in nursing homes versus hospital to patients provided intravenous and oral antibiotics, by diagnosis.

Iv antibiotics in nursing homes (n = 110) Iv treatment in hospital (n = 84) Total

RTI RTI + UTI UTI Other* RTI RTI+UTI UTI Other*

Benzylpenicillin 26 (34) 1 (10) 0 2 (18) 23 (49) 4 (19) 0 0 56 (29)

Broad spectrum penicillin 1 (1) 1 (10) 0 0 3 (6) 1 (5) 2 (15) 0 8 (4)

Cefalosporins 43 (57) 8 (80) 12 (92) 7 (64) 17 (36) 12 (57) 10 (77) 1 (33) 110 (57)

Other iv antibiotics** 2 (3) 0 1 (8) 0 0 1 (5) 0 0 4 (2)

Combinations*** 4 (5) 0 0 2 (18) 4 (9) 3 (14) 1 (8) 2 (67) 16 (8)

Total 76 (100) 10 (100) 13 (100) 11 (100) 47 (100) 21 (100) 13 (100) 3 (100) 194 (100)

Oral antibiotics in nursing homes (n = 44) Oral antibiotics in hospital (n = 8) Total

RTI RTI + UTI UTI Other* RTI RTI+UTI UTI Other*

Phenoxymetylpenicillin 6 (30) 0 0 0 0 0 0 0 6 (12)

Broad spectrum penicillin 10 (50) 1 (33) 8 (50) 2 (40) 1 (50) 0 2 (40) 0 24 (46)

Ciprofloxacin 1 (5) 0 4 (25) 0 0 1 (100) 3 (60) 0 9 (17)

Doksycyclin 3 (15) 0 0 0 0 0 0 0 3 (6)

Nitrofuradantin 0 0 2 (13) 0 0 0 0 0 2 (4)

Trimetoprim +/- sulfa 0 1 (33) 1 (6) 0 1 (50) 0 0 0 3 (6)

Other oral antibiotics**** 0 1 (33) 1 (6) 3 (60) 0 0 0 0 5 (10)

Total 20 (100) 3 (100) 16 (100) 5 (100) 2 (100) 1 (100) 5 (100) 0 52 (100)

*Other: skin, gastrointestinal and unspecified infections;
**Other iv antibiotics: ciprofloxacin (n = 1), meropenem (n = 3);

***Combinations: cefotaksim + benzylpenicillin/metronidazol/meropenem/klindamycin (n = 9), gentamicin + benzylpenicillin/ampicillin (n = 5), klindamycin

+ benzylpenicillin (n = 2);

****Other oral antibiotics: cefotaksim (n = 1), erythromycin (n = 1), metronidazol (n = 2), vancomycin (n = 1).

https://doi.org/10.1371/journal.pone.0182619.t006

Intravenous treatment in nursing homes

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The Norwegian guidelines for empirical treatment of pneumonia state that benzylpenicillin

is the first-line antibiotics for empirical treatment in both nursing homes and hospital [17, 18].

Two thirds of the parenteral antibiotics used in this study was broad-spectrum, and the major-

ity of patients in nursing homes and in hospital were given 3
rd

generation cephalosporins. A

safe and effective strategy for antibiotic use involves prescribing antibiotics only when it is

needed and selecting appropriate and effective medicines with the narrowest spectrum of anti-

microbial activity. The spread of MRSA in nursing homes has been reported in a number of

countries including Norway [23]; and infections caused by ESBL-producing bacteria is a rising

problem [24–26]. The emergence of resistant bacteria argues for careful prescription of antibi-

otics as well as restricting transfer of patients between nursing homes and hospital when it is

not necessary.

The principal strength of this study is its size and design: the stepped wedge cluster ran-

domized trial is a pragmatic study design, which can enable research on planned service deliv-

ery interventions without compromising with the concerns of the stakeholders, in this case,

the rollout of an educational program planned by the regional hospital. The design allowed for

implementation approximately as planned as well as a randomized evidence of effectiveness.

The intervention rolled out as planned without unexpected challenges and the education was

provided to almost all personnel in the nursing homes. We included all cases of intravenous

treatment in which hospital admissions could be avoided, both patients with serious infections

and cases of dehydration; and the follow up for all the patients for 30 days made it possible to

assess a prognosis. The study nursing homes were the vast majority of public and private

nursing homes in one county, and probably without relevant differences from Norwegian

nursing homes in general. The intervention itself can be repeated without large investments or

resources; it did not require more equipment than a training arm and intravenous therapy

supplies and was carried out by two nurses.

The study’s main limitation was the difficulties collecting data. Not all patients treated

locally were included in the study and the data collection forms were incomplete for a number

of patients. We have no reason to believe that patients not included in the study differed from

patients included, or that the main results could have been altered, but it may have lead to an

underestimate of the need for intravenous treatment among nursing home patients. We have

no reason to believe that a systematic change in under-reporting over time has lead to a fictive

time trend of reduced intravenous treatments throughout the study period. A second limita-

tion was that although we through the inclusion criteria aimed to ensure comparability

between the patients treated in nursing homes and the patients admitted to hospital, the two

groups are not identical. We assume that in the study as well as in clinical practice, there is a

trend towards more seriously ill patients being hospitalized, shown by the higher proportion

of patients with congestive heart failure, high blood pressure and high CRP in the hospital

group. However, among patients given intravenous treatment locally, there will be some that

are provided intravenous treatment as palliative care in a terminal phase who would not been

hospitalized for the same treatment. How this affects the outcomes of the study is difficult to

assess, but may have contributed to a higher mortality in the nursing home group. A further

limitation is that the two pilot nursing homes had no observational time, and due to low turn-

over of intravenous treatment, eight additional nursing homes had data for one level only,

resulting in a certain loss of power. Last, the original power calculation was for a standard ran-

domized controlled trial, allowance for the number of steps and allowance for any repeated

measures on individuals was not included in this sample size estimate.

This study is the first to evaluate the effect of a training program in intravenous treatment

in nursing homes using a stepped-wedge design. The composition of the nursing home popu-

lation, and views and traditions on optimal care, treatment strategies and treatment intensity

Intravenous treatment in nursing homes

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among nursing home residents, vary across countries [6], making comparisons with other

studies, recommendations for further research as well as policy recommendations challenging.

Different aspects of the topic “hospitalization from nursing homes” have been elucidated in

the research literature the last decades [11]. We have only identified two studies using the

stepped wedge approach in the nursing home settings, none on intravenous treatment or on

reducing hospitalization [27, 28]. Several interventions to structure or standardize clinical

practice have been evaluated [12]. In Canada, Loeb et al. found that a clinical pathway for on-

site treatment of pneumonia and other lower respiratory tract infections in nursing homes

resulted in comparable clinical outcomes and reduced hospitalizations and health care costs

[9]. A multifaceted intervention study to implement guidelines in the USA did not affect hos-

pitalization rates for nursing home-acquired pneumonia [10]. A previous USA-based study

found that an education intervention directed at guidelines on antibiotic treatment in nursing

homes was feasible and increased adherence to treatment guidelines, but had no effect on hos-

pitalization or 30-day mortality [7]. The effect on hospitalization of the training program

implemented among nursing home personnel in this study may be partly explained by elevated

medical competence in the nursing homes: both an increased theoretical knowledge of both

prevention and treatment of infections and dehydration, and competence in an essential prac-

tical treatment procedure; partly by the described increased awareness regarding advance care

planning.

Due to demographic changes and an intensified effort in community care of the elderly

[29], residents in European nursing homes have over the past decades become increasingly

frail, often with multiple active diagnoses [30], and the situation is similar in Norway. In addi-

tion, in 2012, a political reform was introduced in Norway, aiming at treatment on lowest

effective level of care, including an increased focus on the interaction between hospitals and

nursing homes. Following, the burden of disease in the nursing homes have increased, making

it necessary for the nursing homes to increase their medical competence [31]. However, the

need for intravenous treatment among nursing home patients is limited. Pre-intervention,

many of the long term facility leaders and -workers were skeptic to the intervention, arguing

that it would be too resource demanding. It became apparent through the project period that

the need for intravenous treatment was low in the majority of nursing homes; exceptions were

short term, palliative and intensive care units. After intervention, 22 of 30 nursing homes had

fewer than 10 patients per 100 beds per year receiving intravenous treatment, and all nursing

home leaders confirmed that local intravenous treatment in most facilities was feasible without

large reallocations of existing resources. Further, the hospital reports obvious benefits of the

intervention: less pressure from hospitalizations and more effective discharges as the nursing

homes can continue initiated intravenous treatment to stabilized patients.

Health care policies around the globe are seeking ways to increase efficacy and reduce strain

on specialist health care, and reducing emergency admissions is often accentuated as the key

to achieve this [12]. Increased evidence on interventions reducing hospital admissions from

nursing homes have been explicitly requested [12]. This study fills some of the evidence-pol-

icy-gap and can contribute to inform current policies and future reforms. Our study demon-

strated that it is feasible to do a pedagogic intervention by use of a stepped wedge design. The

significant effect of the structured training program in intravenous treatment in nursing

homes makes the intervention almost directly recommendable for nursing homes in Norway.

We clearly recommend evaluating this intervention adapted to nursing homes in other settings

and other countries, as one strategy to reduce hospital admissions. Future research should also

incorporate barriers and facilitators for local management of nursing home patients both on

individual and structural level.

Intravenous treatment in nursing homes

PLOS ONE | https://doi.org/10.1371/journal.pone.0182619 September 7, 2017 18 / 21

Supporting information

S1 Fig. Number of patients receiving intravenous antibiotics and fluids in nursing home

versus hospital in the study period, per 3 months. Pilot sites not included.

(JPG)

S1 Table. Associations of demographic and clinical variables with intravenous treatment

in the nursing home. Multilevel logistic regression model with nursing home as cluster (ran-

dom intercept). Pilot sites not included.

(DOC)

S1 Appendix. Project protocol.

(DOCX)

S2 Appendix. Research form. Basic form for all patients.

(DOC)

S3 Appendix. Research form. Form for patients treated with iv antibiotics in hospital.

(DOC)

S4 Appendix. Research form. Form for patients treated with iv antibiotics in nursing homes.

(DOC)

S5 Appendix. Research form. Form for patients treated wit iv fluids in hospital.

(DOC)

S6 Appendix. Research form. Form for patients treated wit iv fluids in nursing homes.

(DOC)

S7 Appendix. Consent form.

(DOC)

S8 Appendix. TIDieR-checklist.

(DOCX)

Acknowledgments

We would like to thank all participating patients; health personnel and leaders in the nursing

homes and the hospital; and the research team members for their contributions to the study.

Author Contributions

Conceptualization: Maria Romøren, Morten Lindbæk.

Data curation: Maria Romøren.

Formal analysis: Maria Romøren, Svein Gjelstad, Morten Lindbæk.

Funding acquisition: Maria Romøren, Morten Lindbæk.

Investigation: Maria Romøren.

Methodology: Maria Romøren, Svein Gjelstad, Morten Lindbæk.

Project administration: Maria Romøren, Morten Lindbæk.

Resources: Maria Romøren, Morten Lindbæk.

Software: Maria Romøren, Svein Gjelstad, Morten Lindbæk.

Intravenous treatment in nursing homes

PLOS ONE | https://doi.org/10.1371/journal.pone.0182619 September 7, 2017 19 / 21

Supervision: Morten Lindbæk.

Validation: Maria Romøren, Svein Gjelstad, Morten Lindbæk.

Visualization: Maria Romøren, Morten Lindbæk.

Writing – original draft: Maria Romøren.

Writing – review & editing: Maria Romøren, Svein Gjelstad, Morten Lindbæk.

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© The Author(s) 2017. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved.
For permissions, please e-mail: [email protected]

1075

Research Article

Fall Risk, Supports and Services, and Falls Following a
Nursing Home Discharge
Marwa Noureldin, PharmD, MS, PhD,1,* Zachary Hass, MS, PhD,2
Kathleen Abrahamson, PhD, RN,2,3 and Greg Arling, PhD2,3
1Department of Pharmaceutical Sciences, College of Pharmacy, Natural and Health Sciences, Manchester University, Fort
Wayne, Indiana. 2School of Nursing, Purdue University, West Lafayette, Indiana. 3Center on Aging and the Life Course,
Purdue University, West Lafayette, Indiana.

*Address correspondence to: Marwa Noureldin, PharmD, MS, PhD, College of Pharmacy, Natural and Health Sciences, Manchester University,
10627 Diebold Rd, Fort Wayne, IN 46845. E-mail: [email protected]

At the time of manuscript submission, the corresponding author was working at Purdue University School of Nursing.

Received May 10, 2017; Editorial Decision Date July 18, 2017

Decision Editor: Rachel Pruchno, PhD

Abstract
Background and Objectives: Falls are a major source of morbidity and mortality among older adults; however, little is
known regarding fall occurrence during a nursing home (NH) to community transition. This study sought to examine
whether the presence of supports and services impacts the relationship between fall-related risk factors and fall occurrence
post NH discharge.
Research Design and Methods: Participants in the Minnesota Return to Community Initiative who were assisted in achiev-
ing a community discharge (N = 1459) comprised the study sample. The main outcome was fall occurrence within 30 days
of discharge. Factor analyses were used to estimate latent models from variables of interest. A structural equation model
(SEM) was estimated to determine the relationship between the emerging latent variables and falls.
Results: Fifteen percent of participants fell within 30 days of NH discharge. Factor analysis of fall-related risk factors pro-
duced three latent variables: fall concerns/history; activities of daily living impairments; and use of high-risk medications.
A supports/services latent variable also emerged that included caregiver support frequency, medication management assist-
ance, durable medical equipment use, discharge location, and receipt of home health or skilled nursing services. In the SEM
model, high-risk medications use and fall concerns/history had direct positive effects on falling. Receiving supports/services
did not affect falling directly; however, it reduced the effect of high-risk medication use on falling (p < .05).
Discussion and Implications: Within the context of a state-implemented transition program, findings highlight the import-
ance of supports/services in mitigating against medication-related risk of falling post NH discharge.

Keywords: Home and community-based services, Caregivers, Structural equation modeling, Nursing home transition, High-risk medica-
tions, Medication management

Background
It is estimated that a quarter to a third of adults aged
65  years and older fall annually (American Geriatrics
Society/British Geriatrics Society, 2011; Centers for Disease

Control and Prevention [CDC], 2017; Marrero, Fortinsky,
Kuchel, & Robison, 2017). Falls are the leading cause of
injury-related mortality and a well-studied source of sig-
nificant morbidity and diminished quality of life among

The Gerontologist
cite as: Gerontologist, 2018, Vol. 58, No. 6, 1075–1084

doi:10.1093/geront/gnx133
Advance Access publication September 4, 2017

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older adults (American Geriatrics Society/British Geriatric
Society, 2011; CDC, 2017; Lim, Hoffmann, & Brasel,
2007). Falls are also a major contributor of trauma-related
hospitalizations for older adults, ranging from fractures to
brain injury (Moncada, 2011), with costs of fall-related
treatments totaling more than $31 billion annually (CDC,
2017). Risk factors associated with falls have been exten-
sively studied and falls have been described as multifactor-
ial events resulting from both patient-specific (intrinsic) as
well as environmental (extrinsic) factors (Bueno-Cavanillas,
Padilla-Ruiz, Jimenez-Moleon, Peinado-Alonso, & Galvez-
Vargas, 2000; Ganz, Bao, Shekelle, & Rubenstein, 2007;
Marrero et al., 2017; Moncada, 2011). In addition to being
a major cause for hospitalization, falling among older
adults is also a predictor for both nursing home (NH)
admission and readmissions (American Geriatrics Society/
British Geriatric Society, 2011; Howell, Silberberg, Quinn,
& Lucas, 2007; Lim et  al., 2007). Although incidence of
falls among older adults and risk factors leading to these
events have been examined in multiple settings (Bueno-
Cavanillas et al., 2000; Ganz et al., 2007; Lim et al., 2007;
Phelan, Mahoney, Voit, & Stevens, 2015), few studies have
explored falls as an outcome during an older adult’s tran-
sition from a NH to the community (Howell et al., 2007;
Marrero et al., 2017).

NH Transitions

Transition from a NH to the community presents unique
challenges. NHs provide care to a range of individuals based
on their needs; short-stay residents (less than 100 days) are
typically admitted following an acute-care hospitalization,
whereas long-stay residents receive care for prolonged dis-
ease or disability. A  recent analysis indicated that a large
proportion (40%) of previously community dwelling indi-
viduals discharged to a NH following acute hospitaliza-
tion did not return to the community, or they returned but
were eventually readmitted to a NH (Hakkarainen, Arbabi,
Willis, Davidson, & Flum, 2016). Studies examining tran-
sition-related outcomes have focused on NH readmission
or hospitalizations (Howell et  al., 2007; Robison, Porter,
Shugrue, Kleppinger, & Lambert, 2015; Wysocki et  al.,
2014). Wysocki and colleagues (2014) reported that dually
eligible older adults who transitioned from the NH into
the community had an increased risk of hospitalizations
compared to NH residents. On the other hand, Bogaisky
and Dezieck (2015) reported that NH residents had 41%
higher risk of 30-day rehospitalization compared to adults
discharged to the community.

State-Implemented Transition Programs and Falls

Over the last several decades, federal and state policymak-
ers have advanced initiatives to assist individuals with long-
term care needs to transition from long-term care settings
to the community and to remain in the community after

a transition (Bardo, Applebaum, Kunkel, & Carpio, 2014;
Fries & James, 2012; Reinhard, 2010). These initiatives
have mainly focused on Medicaid paying or dual Medicare/
Medicaid paying residents through the Money Follows
the Person (MFP) programs. Some studies have explored
readmission outcomes associated with NH to community
transition within the context of these state-implemented
transition programs (Howell et  al., 2007; Marrero et  al.,
2017; Robison et al., 2015). Howell and colleagues (2007)
examined New Jersey’s nursing home transition program
participants and found that falls within 8 to 10 weeks of a
NH to community transition were a significant predictor of
long-stay NH readmissions. Another study evaluating the
Connecticut Money Follows the Person (MFP) program
examined fall incidence at two time points post NH dis-
charge (6 and 12 months) and reported that 25% of par-
ticipants fell in the first 6 months following a NH transition
and 25% fell between 6 and 12  months (Marrero et  al.,
2017). Predictors of falling at 12 months included previous
falls, depressive symptoms, unmet medical care needs, and
older adult physical/verbal mistreatment.

Services and Supports

A major component of state-implemented transition pro-
grams is the provision of home and community-based ser-
vices (HCBS), including both health-related and personal
care services to ease transitions and assist individuals in
maintaining independence in the community (Centers for
Medicare and Medicaid Services [CMS], 2016; Reinhard,
2010). Although some studies have examined transition
outcomes in the context of these state-implemented transi-
tion programs, these studies have not examined specifically
the impact of home and community service accessibility
on transition-related outcomes, including falls. In addi-
tion, these transition studies have not fully explored the
impact of caregiver availability and support on fall occur-
rence among older adults. Hoffman and colleagues (2017)
reported that receiving high levels of informal caregiving
(≥14 hours a week) was associated with reduced fall risk
among community dwelling older adults. Older adults who
had physical limitations and cognitive impairments and
who were receiving high levels of informal care experienced
the greatest reduction in the risk of falling (Hoffman et al.,
2017).

The purpose of our study was to examine whether the
presence of supports and services impacts the relation-
ship between factors typically associated with falls and the
occurrence of falls within 30-days post-discharge from the
NH. This time-frame is a critical period when older adults
are re-adjusting to their community setting and can be at an
increased risk for falls (Davenport et al., 2009). This study
examines the relationship within the context of state-imple-
mented transition program aimed at assisting private-pay
NH residents. As previously mentioned, studies examin-
ing NH to community transitions have mainly focused on

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the Money Follows the Person initiatives that are targeted
toward Medicaid populations and there is a lack of knowl-
edge about programs tailored to other populations (Bardo
et al., 2014; Howell et al., 2007; Marrero et al., 2017).

Study Context

The Minnesota Return to Community Initiative (RTCI) is a
state-implemented transition program that assists private-
pay NH residents to transition into the community. It pro-
vides a context for us to explore fall occurrence during a
transition and to investigate the role of HCBS and various
supports in fall prevention. Administered by the Minnesota
Department of Human Services, RTCI targets transition-
related assistance to NH residents who have a preference
for discharge, fit a discharge “target” profile (Arling, Kane,
Cooke, & Lewis, 2010), and have been in the NH for at
least 60 days (Minnesota Board on Aging, 2017). RTCI has
a staff of Community Living Specialists (CLS) that assists
in care planning and offers information about community
services and other resources to older adults and their fami-
lies both during the NH stay and after discharge. However,
they do not provide specific interventions or services related
to falls.

Conceptual Framework

Previous literature on fall-related risk factors and fall pre-
vention helped guide this study’s conceptual framework.
As formerly mentioned, falls can result from both patient-
specific factors as well as environmental factors. Patient-
specific factors include age, gender, having a history of falls,
having certain musculoskeletal or neurologic conditions,
depression, being cognitively impaired, and experiencing
problems with balance (Bueno-Cavanillas et  al., 2000;
Moncada, 2011). Environmental factors include presence
of home safety issues, use of certain high-risk medications
or multiple medications, and having impaired abilities to
perform activities of daily living (Bueno-Cavanillas et  al.,
2000; Ganz et  al., 2007; Moncada, 2011). Interventions
recommended in fall prevention guidelines are focused on
screening for older adults at high risk for falls and modify-
ing some of their risk factors (American Geriatrics Society/
British Geriatric Society, 2011; Moncada, 2011; Phelan
et  al., 2015). Current guidelines recommend multifac-
eted interventions for fall prevention, including providing
patient education, assessing and modifying medication
regimens, ensuring a safe home environment, and enroll-
ing older adults in physical therapy and exercise programs
among other strategies (American Geriatrics Society/British
Geriatric Society, 2011). However, there has been less focus
on how other types of strategies, such as caregiver assis-
tance, use of durable medical equipment, or use of HCBS-
based services, can modify fall risk, especially following a
transition from the NH to the community setting.

In our conceptual framework, we hypothesize that fall-
related risk factors, including previous history of falls in
the NH, concerns related to balance, falling, or the home
environment, activities of daily living (ADL) deficits, and
use of potentially inappropriate medications will contrib-
ute to falls among NH residents transitioning into the com-
munity. We also hypothesize that HCBS as well as various
informal supportive strategies will have a moderating effect
and ameliorate the impact of fall-related risk factors on fall
occurrence. Modeling the effects of supports and services
on falls is complex. We expect individuals with greater fall
risk, e.g., ADL impairment, history of falls, or high-risk
medication use will receive more supports and services.
Consequently, a simple bivariate model might result in the
counterintuitive finding that greater supports and services
contribute to falls. We employed a structural equation
model (SEM) to test our conceptual framework because
this approach can be more effective at addressing direct,
indirect, and moderating effects of both fall-related risk
factors and supports and services. A figure of the concep-
tual framework is included in the Supplementary Figure 1.

Design and Methods

Study Sample
The analytic sample included NH residents who were tran-
sitioned from the NH to the community by the Minnesota
RTCI between April 2014 and October 2016 (N  =  1,459).
Data came from the comprehensive Community Planning
Tool (CPT), completed by CLS prior to discharge for all NH
residents who participated in RTCI. The CPT is a compre-
hensive assessment and includes demographic information,
medical diagnoses, health, functional, and cognitive status of
the residents, medication use and medication management,
discharge location, as well as caregiver availability and fre-
quency of assistance. The CLS personnel use various sources
to collect information for the CPT, including Minimum Data
Set (MDS) assessments, NH charts, and NH resident and fam-
ily caregivers. CLS staff conduct follow-up interviews with
older adults (in person or by phone) at 3, 10, and 30  days
post-discharge. The follow-up assessments provide informa-
tion regarding fall occurrence and health care utilization.

Variables

Study variables were derived from the CPT and follow-up
assessments. The outcome variable of interest was occurrence
of falls within 30 days of discharge, dichotomously coded (yes/
no). Independent variables included age, gender, presence of
at least one musculoskeletal condition (arthritis, hip fracture,
osteoporosis, etc.), or presence of at least one neurological
condition (dementia, stroke, seizures, etc.). Medical diagnoses
were collected from MDS assessments and were based on NH
records. Additional variables included presence of moderate-
to-severe cognitive impairment (moderate-to-severe score

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≤12, cognitively intact 13–15), based on the Brief Interview
for Mental Status (BIMS; Saliba et al., 2012) and presence of
moderate-to-severe depression based on the Patient Health
Questionnaire-9 (PHQ-9 score; moderate-to-severe score
≥10, mild to no depression score 0–9; Kroenke, Spitzer, &
Williams, 2001). Prior history of NH falls (yes/no) as well as
resident concerns at discharge regarding falling in the com-
munity (yes/no) and concerns about balance/vertigo affect-
ing daily activities (yes/no) were also included in the analysis.
Home environmental safety issues were defined as older adult
concern about getting around within at least one of seven
areas in the home, including the basement, bathroom, bed-
room, kitchen, laundry room, stairs, and entrances/exits
(yes/no). Functional variables included three items assessing
whether assistance is sometimes needed with ADLs, specific-
ally toileting, walking, and bed mobility (yes/no). Toileting
was defined as getting to and on the toilet, adjusting clothes,
and cleaning after toilet use. Walking referred to the ability
to walk short distances around the house. Bed mobility was
defined as sitting up in bed or moving around in bed. Use of
medications considered inappropriate or high risk in the eld-
erly was obtained from medication lists provided to the CLS
staff by the NH at discharge. Medications were categorized
as psychotropics, analgesics, and anticholinergics (American
Geriatric Society, 2015). Psychotropics encompassed use of
antidepressants, hypnotics or sedatives, and anti-psychotics;
analgesics included use of opioid medications; and varying
types of medications with known anticholinergic effects that
can lead to dizziness comprised the third category. Variables
related to various supports and services included assistance
with medication management (independent, somewhat
dependent, or dependent); older adult use of durable medical
equipment (yes/no); receipt of at least one of the following
HCBS: skilled nursing, home health, or personal care assis-
tants; discharge location (alone vs with someone else), and
caregiver frequency of support (once weekly or less vs daily
or several times a week).

Data Analysis

Descriptive statistics provide an overview of RTCI partici-
pant characteristics and 30-day post-discharge outcomes.
In the SEMs, we tested the relationships between: (a) fall-
related risk factors and receipt of supports and services, (b)
fall-related risk factors and the occurrence of falls, and (c)
moderating effect of supports and services on the relation-
ship between fall-related risk factors and the occurrence of
falls. The SEM approach allows us to model latent con-
structs from observed measures and to examine complex
relationships between observed variables and latent con-
structs simultaneously (Lei & Wu, 2007; Weston & Gore,
2006). Data management, descriptive statistics, and prelim-
inary regression analyses were conducted using SAS version
9.3 (SAS Institute, Cary, NC), whereas factor analysis and
SEM were conducted using Mplus version 7.4 (Muthen &
Muthen, Los Angeles, CA).

In developing the SEM models, we first conducted
bivariate logistic regression analyses to examine associa-
tions between variables identified in the study’s conceptual
framework with the outcome of falls, to provide preliminary
assessment of the relationships, and to assist in SEM model
specification. Next, exploratory factor analyses (EFAs) and
confirmatory factor analyses (CFAs) were used sequentially
to estimate individual latent variable models (measurement
models). Initially, we hypothesized the presence of two latent
constructs, supports and services, and fall-related risk fac-
tors. Results of factor analyses indicated that fall-related risk
factors were better represented by three constructs instead of
one: fall concerns and fall history, ADLs impairment, and use
of high-risk medications. Finally, two SEM models were esti-
mated, one without interactions and one with interactions,
including the support and services and fall risk constructs as
well as the outcome of falls. We tested all direct and indirect
effects and interaction terms between each fall-related risk
construct and the supports and services construct; however,
for parsimony, the final model included only the significant
interaction term. Model co-variates for the full SEM model
included age (>85  years vs ≤85  years), gender, diagnosis
with at least one musculoskeletal condition, diagnosis with
at least one neurological condition, depression, and cogni-
tive status. Results from the model without interactions are
included in the Supplementary Figure 2.

SEM model fit is typically assessed based on several indi-
ces including the comparative fit index (CFI), the root mean-
square error of approximation (RMSEA), and the maximum
likelihood χ2 test (Lei & Wu, 2007; Weston & Gore, 2006).
The χ2 test is a measure of how well the models fit the observed
data with a nonsignificant χ2 indicating good fit; however, it
is extremely sensitive to large sample sizes (Weston & Gore,
2006). The CFI is an incremental fit index that measures
improvement in fit with values more than 0.9 or 0.95 indi-
cating improved fit. The RMSEA is an index that corrects
for model complexity with values less than 0.06 indicating
good fit between the hypothesized model and sample data
(Lei & Wu, 2007; Weston & Gore, 2006). Model fit indices
were used to assess the individual latent variable models and
SEM model with no interaction terms. Due to the dichoto-
mous nature of some variables in the SEM model, Mplus uses
maximum likelihood to estimate a model with interaction
terms. This estimation technique does not provide traditional
fit statistics. We compared our SEM models using the receiver
operating curve (ROC) to assess which model was the most
predictive of falls (closer to 1.0 indicates more predictive
accuracy). The research was approved by the Institutional
Review Board at Purdue University.

Results

Descriptive and Bivariate Associations
Fifteen percent of RTCI participants (N = 1,459) who
transitioned from the NH to the community fell within
30 days of discharge. An overview of RTCI participant

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characteristics is presented in Table 1. The mean age of par-
ticipants was 79.6 years, 59.5% were female and 57.4%
were married. The majority (92.8%) had been admitted to
the NH from an acute-care hospital and 16.6% had expe-
rienced a fall in the NH prior to discharge. Based on the
BIMS, 11.7% of participants had moderate-to-severe cog-
nitive impairment. In terms of assistance with ADLs, 69.8%

needed some assistance with walking, 12% needed some
assistance with toileting, and 9.7% needed some assist-
ance with moving within bed. A majority (54.1%) of par-
ticipants were using psychotropic medications and almost
40% were using analgesics prior to NH discharge. In terms
of medication management, 54.7% indicated some level
of assistance needed (somewhat dependent or dependent).

Table 1. Participant Demographics and Key Variables

Total % (N) Fall % (N) No fall % (N)

Variables N = 1,459 N = 219 N = 1,240

Age (mean ± standard deviation) 79.6 ± 9.8 78 ± 10.1 79.9 ± 9.7
Female 59.5% (868) 47.7% (106) 61.6% (762)c

Married 57.4% (835) 50.2% (111) 58.7% (724)c

Prior nursing home stay in previous 2 years 61.5% (894) 60.6% (134) 61.6% (760)
Admission from acute hospital 92.8% (1,354) 92.3% (205) 92.9% (1,149)
Mean length of stay 76.7 ± 92.9 78.2 ± 109.9 76.4 ± 89.5
Medical conditions
Depression (moderate to severe)a 8.2% (119) 11.7% (26) 7.5% (93)c

Diabetes 32.6% (476) 35.6% (79) 32.1% (397)
Heart disease 47.4% (692) 46.4% (103) 47.6% (589)
Musculoskeletal conditions (arthritis, osteoporosis) 49.5% (722) 43.7% (97) 50.5% (625)c

Neurological conditions (dementia, stroke) 33.9% (494) 51.4% (114) 30.7% (380)c

Cognitive impairmentb (moderate to severe) 11.7% (170) 16.8% (37) 10.8% (133)c

Functional variables (sometimes need assistance)
ADL-toileting 12.0% (175) 15.8% (35) 11.3% (140)c

ADL-walking 69.8% (1,018) 68.9% (153) 69.9% (865)
ADL-bed movement 9.7% (141) 11.3% (25) 9.4% (116)
Previous fall in nursing home 16.6% (242) 28.8% (64) 14.4% (178)c

Fear of falling in the community 50.4% (735) 56.8% (126) 49.2% (609)c

Concern with vertigo/balance 41.8% (610) 55.4% (123) 39.4% (487)c

Concern with home safety 35.6% (520) 39.6% (88) 34.9% (432)
Use of durable medical equipment 31.7% (462) 31.5% (70) 31.7% (392)
High-risk medication use
Psychotropics 54.1% (789) 68.0% (151) 51.6% (638)c

Analgesics 39.5% (577) 37.4% (83) 39.9% (494)
Anticholinergics 10.8% (158) 10.4% (23) 10.9% (135)
Medication management
Independent 45.2% (660) 36.9% (82) 46.7% (578)
Somewhat dependent 36.9% (539) 41.0% (91) 36.2% (448)
Dependent 17.8% (260) 22.1% (49) 17.1% (211)c

Caregiver support
Once weekly or less 24.1% (352) 19.4% (43) 25.0% (309)c

Weekly or more frequently 75.9% (1107) 80.6% (179) 75.0% (928)
Post-discharge living arrangement
Alone 30.2% (441) 18.9% (42) 32.3% (399)
With family 49.8% (727) 59.9% (133) 48.0% (594)c

Assisted living 19.9% (291) 21.2% (47) 19.7% (244)
Use of HCBS-based services
Skilled nursing 48.3% (704) 46.8% (104) 48.4% (599)
Home health aides 50% (729) 53.6% (119) 49.3% (610)
Personal care assistants 1.9% (27) 2.7% (6) 1.7% (21)

Note: ADL = activities of daily living; HCBS = home and community-based services.
aBased on PHQ-9(score ≥ 10 = moderate to severe).
bBased on BIMS (score of ≤ 12 = moderate to severe).
cBivariate association (fall/did not fall) significant at alpha = .1.

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Three quarters of participants (75.9%) had caregiver sup-
port daily or multiple times a week, and most were living
with a spouse, other relative or significant other (69.8%).
At discharge, 48.3% accepted skilled nursing services and
50% accepted home health aide services.

Bivariate analyses indicated statistically significant
associations (alpha < .10) between falls and several of the
variables considered in our conceptual framework, includ-
ing health and functional variables as well as medication-
related variables and caregiver support (Table 1).

EFA and CFA for the Fall-Related Risk Factors

EFA with the fall-related risk variables, suggested three latent
constructs: fall concerns/fall history, ADLs impairment, and
use of high-risk medications. CFA was used to fit the three
latent variables for the SEM models. The first item of each
latent variable was set to 1 to allow for model estimation.
For the fall concerns/fall history latent variable, four indica-
tors loaded significantly, including concern with home safety
(1.00), previous NH fall (1.03), fear of falling in the commu-
nity (2.17), and concerns with vertigo/balance (3.10). For the
ADLs impairment latent variable, three indicators loaded sig-
nificantly including needing some assistance within bed move-
ment (1.00), with toileting (0.40), and walking (−0.31). For
the use of high-risk medications latent variable, three indica-
tor variables loaded significantly, including use of analgesics
(1.00), anticholinergics (0.90), and psychotropics (1.13).

Each of the three latent variable models had good fit to
the data individually. We combined the three latent vari-
ables into one model to examine how well they fit the data
collectively. Figure  1 shows standardized parameter esti-
mates and correlations between latent variables in the com-
bined model. The combined model also had good model

fit with a χ2(32) = 78.44, p < .01; CFI = .94, RMSEA = .03
(90% confidence interval [CI] = 0.02, 0.04).

EFA and CFA for the Support and Services
Construct

In the EFA, we found that five indicators of supports and
services loaded significantly onto a single-latent construct.
We conducted CFA for these variables and the latent vari-
able supports and services (Figure 2). The first item (receiv-
ing at least one HCBS) was set to 1. The loadings were 0.96
for use of durable medical equipment, 2.46 for caregiver
support frequency, 2.61 for medication management assis-
tance, and 3.04 for discharge location. The latent variable
was influenced mainly by discharge location, medication
management assistance, and caregiver support. This latent
variable had good model fit with a χ2(5) = 10.36, p = .07;
CFI = .99; RMSEA = .03 (90% CI = 0.00, 0.05).

SEM Model

We estimated two SEM models: one model without inter-
action terms and the second model with the addition of
interaction terms. The initial model indicated that con-
structs of ADL impairment and use of high-risk medica-
tion were positively related to supports and services, while
supports and services had no significant effect on falls
at 30  days (Supplementary Figure  2 and Supplementary
Table 1). Next, we tested the same conceptual model with
interaction terms between supports and services and each
of the fall-related risk constructs. Nonsignificant interac-
tion terms were then dropped and a more parsimonious
model was tested. This final model was similar to the ini-
tial model except for the inclusion of an interaction term

.93***

.38 ***

.31***
.65*** .41

***

.23

.39 .16

.52***
.30***

.46***

-.29 ***
.94***

High risk
medication

use

Analgesics Anticholinergics Psychotropics

Bed
mobility

Toileting Walking

Fall
concerns/fall

history

Home safety
concern

Previous
nursing home

fall

Fear of falls
Vertigo/balance

concern

Activities of
daily living

impairments

Figure 1. Confirmatory factor analysis for fall-related risk factor latent variables. Standardized coefficients are presented. Correlations between latent
variables are also presented. χ2(32) = 78.44, p < .01; CFI = .94, RMSEA = .03 (90% confidence interval = 0.02, 0.04). ***p < .001. CFI = comparative fit
index; RMSEA = root mean-square error of approximation.

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between the latent variables of supports and services with
use of high-risk medications (Figure 3). To evaluate the two
SEM models (with and without the interaction term), we
compared C-statistics from the ROC for each model. Based
on the ROC, the model with the interaction term predicted
falling within 30  days of post-discharge more accurately
than the model with no interactions, with a C-statistic of
0.757 versus 0.719, respectively.

Results from the final model indicated a significant posi-
tive effect of the falls concern/falls history latent variable
on falls, a significant positive effect of use of high-risk med-
ications on falls, and a significant positive effect of ADL
impairments on receiving supports and services (Figure 3).
In addition, the interaction between supports and services
and use of high-risk medications was negatively associated
with falling (p  =  .03). Given a specific level of high-risk
medication use, as receipt of supports and services increase,
the risk of falling decreases. In addition, being female was

negatively associated with falling while having at least one
neurological condition had a significant positive effect on
falling. Unstandardized and standardized model coeffi-
cients for direct effects are presented in Table 2.

Discussion
This is one of few studies examining fall outcomes within
30  days of older adults transitioning from the NH to the
community within the context of a state-implemented tran-
sition program. Previous studies have typically examined
fall incidence during NH stays or during/after hospitali-
zations. Among this study’s participants, 15% fell within
30 days of NH discharge, which is lower than reported fall
rates for both NH and community dwelling older adults
(American Geriatrics Society/British Geriatric Society, 2011;
CMS, 2015). Marrero and colleagues (2017)reported that
among older adults transitioning from the NH to the com-
munity, 25% experienced a fall within the first 6  months
of discharge. This study’s participants were specifically tar-
geted for assistance through the RTCI based on health and
functional characteristics (Arling et al., 2010), which may
partially explain the lower fall rate. However, RTCI offered
information about community resources and was not an
intervention specifically aimed at fall prevention.

Factor analysis and structural equation modeling pro-
vided a unique and innovative approach to examining risk
factors related to falling post NH discharge. Fall-related risk
has been typically examined as a unidimensional construct
with a fall score derived through conventional regression
analysis, and fall screening and prevention guidelines typi-
cally list risk factors for assessment without discriminating
among types of risk (American Geriatrics Society/British
Geriatric Society, 2011; Moncada, 2011; Phelan et al., 2015).

.22**

-.24

.02

.20***

Fall
concerns/fall

history

Activities of
daily living

impairments

High risk
medication

use

Supports
and

services

Falls within
30 days

Age Female

Depression
Cognitive
impairment

Musculoskeletal
disease

Neurological
condition

.93***

-.17** .26

.04

-.04
.15***

-.12 ***

-.05

Figure 3. Falls SEM. The three fall risk factor latent variables are correlated (not shown for simplicity). Standardized coefficients presented. Because
of the interaction term, Mplus did not provide fit statistics. Significance bolded. **p < .05, ***p < .001. SEM = structural equation model.

.76 ***.25***

Supports and
services

Use of HCBS
(home health,
skilled nursing,

etc.)

Durable
medical

equipment
use

Caregiver
support

frequency

Medication
management

assistance

Discharge
location

.24 *** .62 ***

.65 ***

Figure  2. Confirmatory factor analysis for supports and services
latent variable. Standardized coefficients presented. χ2(5)  =  10.36,
p = .07; CFI = .99; RMSEA = .03 (90% confidence interval = 0.00, 0.05),
***p < .001. CFI = comparative fit index; HCBS = home and community-
based services; RMSEA = root mean-square error of approximation.

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Our study moves the discussion forward by examining how
various fall risk factors are related to each other as well as to
the receipt of supports and services. We found three clinically
meaningful fall-related risk constructs represented by the
latent variables: fall concerns and fall history; ADL impair-
ments; and use of high-risk medications. The fall concerns/
fall history latent variable is comprised of older adults’ con-
cerns with balance, fear of falling, and concern with home
safety along with previous NH fall history. The ADL impair-
ments latent variable indicates that three ADL impairments
are related, some difficulty with toileting, with walking,
and with bed mobility. Likewise, the high-risk medication
latent variable highlights three medication classes related
to falling with psychotropic medications having a higher
loading than the other two. The three latent variables were
significantly correlated and had good model fit. Results of
the SEM model indicated that fall concerns/fall history and
use of high-risk medications had a significant positive direct
effect on falls, whereas ADL impairments were not signifi-
cantly related. These findings provide a unique view when
examining fall risk from a clinical perspective and further
strengthen empirical evidence for fall predictors in this older
adult population undergoing a care transition. For example,
older adults’ concerns about issues related to falling, such as
fear of falling or concerns with balance, can be vital consid-
erations when assessing fall risk. Results also highlight the
importance of high-risk medications, as a main contributor
to falls in the community after NH discharge. This finding
emphasizes the need for continued reviews of medications
lists by health care professionals and adjustment of medica-
tion regimens to minimize use of unnecessary and potentially
inappropriate medications in older adults.

Another key contribution of our findings is the role of
supports and services in ameliorating the effects of fall-
related risk factors. The latent variable for supports and
services included several items that had not been exten-
sively examined in the fall risk literature. Frequency of
caregiver support, assistance with medication manage-
ment, use of durable medical equipment, post-discharge
living arrangement, and receipt of home health or skilled
nursing services were all correlated within the latent vari-
able. Durable medical equipment use has been previously
considered as a risk factor for fall (Moncada, 2011) rather
than a potential support, and variables such as assistance
with managing medications had not been examined. This
finding brings forward a new perspective on the interrela-
tionship between different types of supports and services
and provides insight into the potential benefit of both fam-
ily and other informal supports in combination with HCBS
in transitioning from the NH.

We found that receipt of supports and services had
no significant direct effect on fall occurrence. This result
highlights the complexity of relationships between the fall-
related risk factors and support and services. In our study,
older adults who had some ADL impairments were more
likely to receive supports and services. Although this may
have led to a lack of significant relationship between ADL
impairments and falls, this finding is encouraging since it
indicates those who need assistance seem to be receiving
it among RTCI participants. More importantly, individu-
als who used high-risk medications and also received sup-
port tended to benefit from that support with a reduced
likelihood of falling. It is not clear if one component of
the supports and services latent variable is influencing this

Table 2. Structural Equation Model of Falls Within 30 Days Post-Discharge

Model with interaction

Variables Unst. C SE Std. C

Direct effects: falls
Fall concern/fall history 0.939** 0.376 0.203
Activities of daily living impairment −0.588 1.704 −0.236
High-risk medication use 2.461*** 0.739 0.218
Supports and services 1.203 2.949 0.258
Neurological condition 0.628*** 0.170 0.147
Musculoskeletal condition −0.161 0.156 −0.040
Depression (moderate to severe) 0.155 0.255 0.021
Cognitive impairment (moderate to severe) 0.249 0.211 0.043
Female −0.477*** 0.155 −0.116
Age ≥ 85 years −0.189 0.171 −0.045
Support and services × high-risk medication use (interaction term) −4.525** 2.252 −0.174
Direct effects: supports and services
Fall concern/fall history — — —
Activities of daily living impairment 0.500*** 0.065 0.933
High-risk medication use — — —

Note: Unstd. C = unstandardized coefficient; SE = standard error; Std. C = standardized coefficient.
**p < .05, ***p < .01.

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relationship or if it is a combination of the assistance pro-
vided, including assistance with medication management.
Additional research is needed to further examine these sup-
portive strategies and evaluate how they might vary across
the older adult population and their potential impact on
health outcomes.

Limitations

There are several limitations to this study that should be
noted. First, the study sample was primarily short-stay
private-pay NH residents who had met specific targeting
criteria for discharge. As such, these results may not be
generalizable to Medicaid residents or private paying older
adults transitioning into the community but who do not fit
the RTCI targeting profile. Based on RTCI’s design, some
information was only collected prior to discharge, such
as type and number of high-risk medications taken. Since
medication lists tend to be dynamic in nature, participants’
medication lists may have changed within the first 30 days.
Additionally, not all fall-related risk factors were examined
due to the nature and type of data collected. For example,
gait and balance were not objectively assessed, and partici-
pants were only asked if they had concerns with balance
or vertigo.

Methodologically, this study has unique strengths
including the use of advance modeling (latent variables and
structural equation modeling) that go beyond regression
or hazards modeling commonly seen when studying fall
risk. Given the complexity and multifactorial nature of fall
occurrence and the dynamic relationships between various
factors, higher levels of modeling provide a broader pic-
ture of the factors associated with falls, both positively and
negatively. Moreover, other studies have focused on NH to
community transition among Medicaid populations, and
there is limited information on other populations, such
as the private-pay population, which comprises approxi-
mately a third of NH users (CDC, 2016).

Implications

Within the context of a state-implemented transition pro-
gram and using structural equation modeling, results indi-
cate that fall risk factors can be viewed as latent constructs
relating to older adults’ fall concerns and fall history, ADL
deficits, and use of high-risk medications. Supports and ser-
vices are essential when assessing fall risk. Although they
were not related directly to the occurrence of falls, they
moderated the relationship between using high-risk medi-
cations and falls. Individuals with greater fall risk due to
high-risk medications were less likely to fall if they had sup-
ports and services. This result points to the importance of
both informal supports and receipt of HCBS in influencing
older adult NH to community transition outcomes.

Results emphasize the importance of conducting fall
assessment and medication reviews in older adults who are
transitioning from an institutionalized to a community set-
ting similar to current guidelines for fall prevention in the
community (American Geriatrics Society/British Geriatric
Society, 2011; Casey et  al., 2016). Furthermore, it is also
essential for health care providers to recognize the role
older adults’ concerns and attitudes, such as concerns with
balance or with falling, can play in fall risk and address
these concerns in a patient-centered manner. From a policy
perspective, findings can help inform other state-imple-
mented transition programs aimed at achieving successful
NH to community transitions.

Supplementary Material
Supplementary data is available at The Gerontologist
online.

Funding
This work was supported by the Agency for Healthcare Research
and Quality [grant number R18HS020224]. The content is solely
the responsibility of the authors and does not necessarily represent
the official views of the Agency for Healthcare Research and Quality.

Conflict of Interest
None reported.

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International Journal of

Environmental Research

and Public Health

Article

Impact of Nurses’ Intervention in the Prevention of
Falls in Hospitalized Patients

Raimunda Montejano-Lozoya 1 , Isabel Miguel-Montoya 1, Vicente Gea-Caballero 1,* ,
María Isabel Mármol-López 1, Antonio Ruíz-Hontangas 1 and Rafael Ortí-Lucas 2

1 Escuela Enfermería La Fe, Valencia (Spain), adscript center of Universitat de Valencia, Research Group
GREIACC, Health Research Institute La Fe, 46026 Valencia, Spain; [email protected] (R.M.-L.);
[email protected] (I.M.-M.); [email protected] (M.I.M.-L.); [email protected] (A.R.-H.)

2 Public Health Department, Catholic University of Valencia, 46001 Valencia, Spain; [email protected]
* Correspondence: [email protected]

Received: 3 July 2020; Accepted: 18 August 2020; Published: 20 August 2020
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Abstract: Background: Clinical safety is a crucial component of healthcare quality, focused on
identifying and avoiding the risks to which patients are exposed. Among the adverse events that
occur in a hospital environment, falls have a large impact (1.9–10% of annual income in acute care
hospitals); they can cause pain, damage, costs, and mistrust in the health system. Our objective was to
assess the effect of an educational intervention aimed at hospital nurses (systematic assessment of the
risk of falls) in reducing the incidence of falls. Methods: this was a quasi-experimental study based
on a sample of 581 patients in a third level hospital (Comunitat Valenciana, Spain). An educational
program was given to the intervention group (n = 303), and a control group was included for
comparison (n = 278). In the intervention group, the nurses participated in a training activity on the
systematized assessment of the risk of falls. Analysis was undertaken using the Bayesian logistic
regression model. Results: a total of 581 patients were studied (50.6% male, 49.4% female), with an
average age of 68.3 (DT = 9) years. The overall incidence of falls was 1.2% (0.3% in the intervention
group and 2.2% in the control group). Most of the falls occurred in people ≥65 years old (85.7%).
The intervention group had a lower probability of falling than the control group (OR: 0.127; IC95%:
0.013–0.821). Neither the length of hospital stay, nor the age of the participants, had any relevant
effect. Conclusions: the systematic assessment of the risk of a patient falling during hospital processes
is an effective intervention to reduce the incidence of falls.

Keywords: accidental falls; hospitalization; patient safety; accident prevention; nursing
education research

1. Background

Clinical safety is a crucial component of healthcare quality that focuses on identifying and avoiding
the risks to which patients are exposed in their relationship with the healthcare system, and whose
materialization is known as Adverse Events (AEs) in the international literature. AEs cause significant
morbidity and mortality, and consequently trying to avoid them, or at least to reduce them, is a
priority for health institutions. Background information shows that almost half of falls are avoidable.
To achieve this, systems must be designed to make it easier to carry out processes properly [1,2].

Among the AEs that occur in a hospital environment, falls cause a significant impact, because it is
a type of accident that reflects system failures in organizational structures and processes. Studies have
shown that falls cost between 1.6% and 13.4% of the annual income in acute care hospitals [3–7].
Reported rates range from 1.3 to 8.9 falls/1000 inpatient days in acute care hospitals (30% of these
resulting in serious injury) [8–10]. Although they might not always provoke serious harm, there are

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Int. J. Environ. Res. Public Health 2020, 17, 6048 2 of 13

instances that require intervention as a result of the pain and suffering caused to the patient and
their relatives [3,6]. Costs resulting from falls alone have been reported at between 0.85% and
1.5% of the total health care expenses within the United States, Australia, the European Union,
and the United Kingdom [5]. According to the World Health Organization (WHO), these financial
costs are additional to the costs of damage to people and mistrust in the health system; therefore,
health institutions should seek to eradicate avoidable falls [4,11].

The literature shows that those who fall are people with limited mobility, an altered state of
consciousness, advanced age, and sensory deficits. When several risk factors are present at the same
time, the risk is much higher [7,12–15].

Many studies about falls agree that assessing their frequency and identifying risk factors helps to
prevent and/or reduce them [15–18]; thus, in a systematic review that included four meta-analyses on
19 studies on falls, it was shown that programs and interventions focused on hospitalized patients
reduce the relative risk of falls by up to 30% [19].

Several research studies have shown that the use of scales to identify patients with a high risk of falls
is effective, as it achieves a reduction in falls and a decrease in the injuries that result [3,13,15,16,20–22].
In the study by Kobayashi et al. [3], the risk of falls was evaluated using a Fall Assessment Score Sheet
at admission and during hospitalization. The authors showed that the incidence of serious events and
falls was significantly higher in patients with a higher risk of falling (p < 0.05). Bittencourt et al. [13]
carried out a transversal study in clinical and surgical stay units using sociodemographic and clinical
forms, as well as the MORSE scale, for data collection. They found a significant association (p < 0.001)
between high risk of falling and neurological clinical hospital stay, trauma surgery, and comorbidities
such as diabetes mellitus, systemic arterial hypertension, visual difficulty, dizziness, and fear of falling.
Severo et al. [15] developed and validated the SAK fall risk scale; the scale includes seven variables:
disorientation/confusion, frequent urination, walking limitations, lack of caregiver, postoperative
status, previous falls, and number of medications administered within 72 h prior to the fall. Finally,
Hernandez-Herrera et al. [16] designed a checklist of 60 intervention activities for “Fall Prevention”
(based on the Nursing Intervention Classification, NIC). The most frequently performed activities were
those related to a risk factor, transfer, and patient education.

The study of Pasa et al. [21] concludes that the use of the MORSE assessment scale to identify
patients at high risk of falling is effective. They also found an association between a greater number of
falls and patients staying longer in hospitals. The work of Hou et al. [22] shows the advantages of
applying a tool to identify patients at high risk of falling, which allows nurses to have more control
over them.

Nurses, as the professionals responsible for performing assessments upon admission to the hospital,
are in an optimal position to identify patients at risk and implement fall prevention programs. Involving this
group of professionals (including their leaders) in a culture of responsibility, and improving their training
in preventive programs, allows very positive results to be obtained [8,9,23,24].

1.1. Framework

Our theoretical framework was based on the systematized assessment of Virginia Henderson’s
model of care. This model is considered an axiom for nursing care. The author defines the individual as
a whole with fourteen basic needs; among them the need to protect the safety of the person (“to avoid
danger”, according to the author). This need, and more specifically the prevention of falls, is the
focus of our intervention. The fact of reducing or preventing falls is properly framed within the
improvement of patient safety. The role of the nurse, therefore, consists of helping the person to recover
their independence when they lack strength, knowledge or will, within this framework of improving
safety [25–27].

Int. J. Environ. Res. Public Health 2020, 17, 6048 3 of 13

1.2. Justification

Based on the dimension of the problem, as well as the consequences of falls (pain, injuries,
complications, costs, and increase in hospital stay), we consider it necessary to implement studies
with interventions, in order to increase the evidence available around what practices a nurse should
implement to reduce the problem.

We proposed as a study hypothesis: patients admitted to units whose nurses have been trained in
the systematic assessment of the risk of falls will fall less than those in units in which nurses have not
received specific training.

The question is whether the implementation of an advanced and systematized assessment by the
nurse following the patient’s admission to a hospital unit reduces the incidence of falls, compared to a
traditional assessment.

1.3. Objectives

The general objective was to assess the effect of an educational intervention aimed at hospital
nurses (systematic assessment of the risk of falls) in reducing the incidence of falls.

2. Methods

2.1. Study Design

This was a quasi-experimental study with a non-randomized control group.

2.2. Population

The study was carried out in 2015 in a third level hospital in the Comunitat Valenciana (Spain).
Four Care Units with the highest average patient stay were chosen in Neurology/Neurosurgery,
General Internal Medicine, Nephrology/Vascular Surgery, and Traumatology/Urology. Two groups
were formed (intervention and control), made up of two Care Units each, so that in both there were
patients from both medical and surgical specialties. The assignment of each group was random.

Finally, the intervention was performed in one of the groups (intervention group, formed by the
units of Nephrology/Vascular Surgery and Traumatology; the control group was formed by Internal
Medicine and Neurology/Neurosurgery). In this sense, the patients were not randomized, but taken
from the hospital units where the nurses were trained (or not).

In each group, it was stipulated that a necessary minimum sample size of 258 patients was required
for a confidence level of 95% and a statistical power of 80%, estimating an approximate incidence of
AEs of 16% in the control group and 8% in the intervention group.

Inclusion Criteria: patients who were admitted during the study period (Neurology/Neurosurgery,
General Internal Medicine, Nephrology/Vascular Surgery, and Traumatology/Urology units), with a
minimum stay of five days in the unit (this time allowance was estimated to be sufficient to produce
the AE object of study). The sample selection was carried out prospectively and consecutively after the
training activity, covering patients who met the inclusion criteria to reach the assigned number.

Exclusion Criteria: patients who had dementia or delirium were excluded.
A total of 593 patients were studied, of which 12 patients were excluded (four due to recording

errors, and eight who refused to participate in the study). No deaths or dropouts occurred during
the study.

2.3. Study Assessment Parameters

Independent variables:

• Sex (men, women);
• Age categorized (in years) and age groups (15–50, 51–64, 65–79, ≥80);

Int. J. Environ. Res. Public Health 2020, 17, 6048 4 of 13

• Nursing units (General Internal Medicine, Neurology and Neurosurgery, Traumatology and
Urology, Vascular Surgery and Nephrology);

• Group (control and intervention);
• Type of nurse assessment on admission (traditional method, systematized method);
• Assessment of the risk of falls on admission according to the Downton scale (yes/no) [28] (this scale

assesses factors related to the risk of falling, such as sensory deficits, mental state impairment,
wandering, and intake of medication whose side effects may influence the occurrence of falls);

• Length of hospital stay in days and in two categories (0–7 and ≥8 days);
• Degree of mobility (non or impaired, unaided in and outside of the room and bathroom);
• Surgical intervention (yes/no);
• Altered consciousness (yes/no);
• Nutritional status on admission according to the Mini Nutritional Assessment-Short Form

(MNA-SF) (risk and/or malnutrition and good nutritional status) [29];
• Supply of oxygen (yes/no);
• Has catheters (vascular access; nasogastric tubes; urinary catheterization) and categorized (does

not have catheters, has a catheter, and has two or more catheters).

2.4. Procedure

Before the start of the study, the necessary tools were developed for each phase of the project:
the protocol containing the data collection procedure for the evaluation team, the form with data
content to be filled in, and the systematic nurse assessment registry to deploy in the intervention units.

The study was carried out over 8 months, following three phases.
In the first phase (before the quasi-experimental study; this phase lasted two months), a pilot test

was carried out using a baseline test which allowed a diagnosis to be made and determined how the
information was to be collected to consolidated.

In the second phase (one month), the nurses were trained through programmed theoretical and
practical sessions, as well as training reinforcement sessions.

The intervention originally consisted of a formative activity directed to the nurses of the
intervention the group. A total of 33 professionals attended (84.6% of the total of nurses of the
intervention group). The training workshop was held with two theory and practice sessions of 4 h each,
offering the possibility to repeat the workshop upon the nurse´s request to reinforce aspects as necessary.
Before starting the formative activity, the attendees were requested to undertake a self-assessment
to estimate their level of knowledge about the relevant topics. At the end of the training, the same
self-assessment was repeated, resulting in a very positive comparison.

The formative activity focused mainly on the first stage of the nursing process: the assessment [24]
was framed in the Human Needs Model of Virginia Henderson, as it is considered the most appropriate
to the idiosyncrasies of the institution [24–26]. The systematized evaluation was a regulated process
that collected all patient information in a bio-psycho-social way (holistic image of the person). This was
undertaken at the patient’s admission and continued throughout the care process, which made it
possible to identify potential problems and risks and implement their care plan. In the control group,
a traditional assessment was undertaken that did not follow a standardized method, and it was
intuitive, improvised, and not systematically reflected in the patient’s clinical history.

Finally, the third phase was data collection (five months). This period was needed to reach the
pre-set sample.

After a systematic, exhaustive, and complete evaluation of the patients, carried out in the Hospital
units of the intervention group, the care plan was optimized (as a result of detecting risks that would
not have been detected with the usual evaluation). Afterwards, a follow-up process was initiated in
all the units. The established criteria were to conduct a review of the clinical history of the patient,

Int. J. Environ. Res. Public Health 2020, 17, 6048 5 of 13

followed by inspection and an interview with him/her and/or family and professionals responsible for
his/her care, asking about the incidence of falls.

Blinding was kept simple by not informing patients of the type of assessment received.

2.5. Statistical Analysis

Data were registered into a database and analyzed with the statistical program Statistical Package
for Social Science (SPSS) version 20.0 (IBM Corporation, Armonk, NY, USA) and R version 3.5.1.
(R Core Team, Vienna, Austria).

A descriptive study was performed by assessing the variables related to the total sample
and the established groups (control and intervention). The incidence of falls was assessed,
concerning the studied variables. The categorical variables are presented in frequencies and percentages,
and continuous variables in averages with standard deviations (SD).

Afterward, to assess the probability of falls between the two studied groups, a Bayesian logistic
regression model was used. An attempt was made to reduce overfitting by selecting the fewest number
of possible variables; the model was adjusted by entering, as confounding factors, the stay in days and
the age in years, calculated by the Odds Ratio (OR) with a Credible Interval (CI) of 95%.

2.6. Ethical Considerations

The study protocol was approved by the Research Ethics Committee of the Hospital,
before implementation of the study. All persons involved were informed and asked for voluntary
participation. The data obtained were handled following the law prevailing at that time: the Data
Protection Law 15/1999, and the Law 41/2002. Personal data were guarded carefully by the investigation
team. The researchers declare they have no ethical conflicts, nor have received any grant or economic
benefit for this study.

3. Results

3.1. Description of the Sample

The sample was a total of 581 patients (response rate = 97.97%), 50.6% men and 49.4% women,
with an average age of 68.3 ± 9 years. The control group was 278 patients distributed between the
General Internal Medicine unit (23.9%) and Neurology/Neurosurgery (23.9%). The intervention group
with a total of 303 patients from the Traumatology and Urology units (35.5%), as well as Vascular
Surgery and Nephrology (16.7%).

The average length of stay was 12.2 ± 9 days, and this was lower in the intervention group
(10.9 ± 7.5 days) than in the control group (13.7±0.2 days). Two-thirds (66.3%) of the patients belonging
to the intervention group were assessed in a systematic way, applying the Downton scale (assessment of
falls risk), compared to 2.9% in the control group (Table 1).

Int. J. Environ. Res. Public Health 2020, 17, 6048 6 of 13

Table 1. Sample description by Study Group.

Variables
Totals
n = 581
n (%)

Control Group
n = 278
n (%)

Intervention Group
n = 303
n (%)

Gender:
Men 294 (50.6) 135 (48.6) 159 (52.5)

Women 287 (49.4) 143 (51.4) 144 (47.5)
Mean Age ± Standard Deviation 68.3 ± 16.2 66.78 ± 17.08 69.67 ± 15.32

Age Group:
15–50 years 85 (14.6) 51 (18.3) 34 (11.2)
51–64 years 105 (18.1) 47 (16.9) 58 (19.1)
65–79 years 224 (38.6) 107 (38.5) 117 (38.6)
≥80 years 167 (28.7) 73 (26.3) 73 (26.3)

Nurse assessment on admission:
Traditional Method 372 (69) 269 (96.8) 103 (34)
Systematic method 209 (31) 9 (3.2) 200 (66)

Risk assessment of falls on
admission:

Yes 213 (36.7) 10 (3.6) 203 (67.0)
No 368 (63.3) 268 (96.4) 100 (33.0)

Average Hospital Stay
± Standard Deviation (days) 12.2 ± 9 13.71 ± 10.19 10.89 ± 7.49

Days interval:
0 to 7 days 205 (35.3) 76 (27.3) 128 (42.4)
≥8 days 376 (63.7) 202 (72.7) 174 (57.6)
Mobility

None (bed-to-armchair) 146 (25.1) 65 (23.4) 81 (26.7)
Unaided in room/bathroom 124 (21.3) 45 (16.5) 78 (25.7)
Unaided outside the room 311 (53.5) 167 (60.1) 144 (47.5)

Surgical intervention:
Yes 270 (46.5) 42 (15.1) 228 (75.2)
No 311 (53.5) 236 (84.9) 75 (24.8)

Altered consciousness:
Yes 59 (10.2) 41 (14.7) 18 (5.9)
No 522 (89.8) 237 (85.3) 285 (94.1)

Nutritional status:
Risk and/or malnutrition 272 (46.8) 150 (54) 122 (40.3)
Normal nutritional status 309 (53.2) 128 (46) 181 (59.7)

Supply of Oxygen:
Yes 119 (20.5) 50 (18) 69 (22.8)
No 462 (79.5) 228 (82) 233 (77.2)

Catheters (intravenous line,
gastric, bladder tube, drainage):

None 7 5 (1.8) 3 (1)
Has one catheter 263 205 (73.7) 96 (31.7)

Has 2 or more catheters 308 68 (24.5) 204 (67.3)

3.2. Incidence of Falls

Only 1.2% of the patients suffered any falls during the study period. Seven falls were reported:
1 in the intervention group and 6 in the control group, resulting in an incidence of 0.3% and 2.2%,
respectively. A higher number of falls were observed in men (85.7%), in persons older than 65 years
(85.7%), and in those who stayed more than 7 days in hospital (85.7%). The total number of people
who suffered a fall was autonomous in terms of mobility and having some type of catheter (Table 2).

Int. J. Environ. Res. Public Health 2020, 17, 6048 7 of 13

Table 2. Incidence of falls.

Variables
Falls

No
n (%)

Yes
n (%)

Gender
Men 288 (50.2) 6 (85.7)

Women 286 (49.8) 1 (14.3)
Age

15–50 years 85 (14.8) 0 (0)
51–64 years 104 (18.1) 1 (14.2)
65–79 years 221 (38.5) 3 (42.9)
≥80 years 85 (14.8) 3 (42.9)

Nursing Units
General Internal Medicine 135 (23.5) 4 (57.1)
Neurology/Neurosurgery 137 (23.9) 2 (28.2)

Traumatology/Urology 206 (35.9) 0 (0)
Vascular Surgery/Nephrology 96 (16.7) 1 (14.2)

Groups
Intervention 302 (52.6) 1 (14.3)

Control 272 (47.4) 6 (85.7)
Nurse assessment on admission

Traditional Method 208 (36.2) 1 (14.3)
Systematic method 366 (63.1) 6 (85.7)

Risk assessment of falls on admission
No 212 (36.2) 6 (85.7)
Yes 362 (63.8) 1 (14.3)

Hospital Stay (days)
0–7 days 204 (35.5) 1 (14.3)
≥8 days 370 (64.6) 6 (85.7)
Mobility

None (bed-to-armchair) 146 (25.4) 0 (0)
Unaided in room/bathroom 120 (20.9) 4 (57.1)
Unaided outside the room 308 (53.7) 3 (42.9)

Surgical intervention
Yes 264 (46) 1 (14.2)
No 310 (54) 6 (85.7)

Altered consciousness
Yes 59 (10.3) 0 (0)
No 515 (89.7) 7 (100)

Nutritional status on admission
Risk and/or malnutrition 267 (46.5) 5 (71.4)
Normal nutritional status 307 (53.5) 2 (28.6)

Supply of Oxygen
Yes 117 (20.4) 2 (28.6)
No 457 (79.6) 5 (71.4)

Catheter (intravenous, gastric/bladder,
drainage)

None 8 (1.4) 0 (0)
Has one catheter 294 (51.2) 7 (100)

Has 2 or more catheters 272 (47.4) 0 (28.6)

3.3. Regression Model

By using the logistic regression model, it was possible to demonstrate that patients in the
intervention group had a lower likelihood of falls than those in the control group (OR: 0.127; IC95%:
0.013–0.821). This hypothesis was reinforced with a probability of 0.99, associated with an evidence
ratio of 77.43. On the other hand, neither the length of hospital stay, nor the age of the participants in
the study had any relevant effect (Table 3).

Int. J. Environ. Res. Public Health 2020, 17, 6048 8 of 13

Table 3. Results of the logistic regression model.

Estimate Std. Error OR * Lower 95% Upper 95%

Intercept −6842 2581 0.001 0 0.088
Intervention Group −2062 1054 0.127 0.013 0.821

Stay −0.04 0.053 0.961 0.849 1044
Age 0.045 0.032 1,046 0.991 1119

WAIC 76,754 23,922

* OR: Odds Ratio.

Figure 1 shows the partial effect of the group regarding the probability of falls. The dots
represent the estimated average probability for each group, while the vertical lines indicate the interval
corresponding to that estimate. As can be seen, the probability of a fall in the intervention group was
lower than in the control group.

Int. J. Environ. Res. Public Health 2020, 17, x 8 of 13

Figure 1. Differences in the probability of fall between the two groups, intervention and control.

No significant association was found between the intrinsic risk factors and the incidence of falls.

4. Discussion

The total incidence of falls was 1.2%. This result was better than in other studies we consulted,
with falls affecting between 1.6% and 13.4% of the annual income in hospitals for acute patients [3–
7,30,31].

The characteristics of people who suffered a fall correspond in many ways with those described
in the reviewed literature. There is evidence that relates advanced age to falls [7,14,32–34]. In our
study, 85.8% of people that fell were 65 years and older, and 85.7% of those who fell were men; we
found similar percentages in a few studies [7,18].

We want to emphasize that all people who suffered falls in our study had a catheter; this is a
factor we did not find described by other authors. Regarding the average stay of the patient in the
hospital and its influence on the risk of suffering falls [12,13,22,35], 85.7% of falls occurred in patients
with stays longer than one week. Luzia et al. [7] reported that 63.2% of patients fall between the 10th
and 24th days of hospitalization.

Patients with some level of mobility suffer the most falls according to various authors
[12,15,18,22,32]; in our case all people who suffered a fall were autonomous or had a certain level of
mobility. This is in agreement with the work of Lopez-Soto et al. [36], which demonstrated that more
falls occur while patients are standing or sitting, when entering/leaving the room, and when getting
up or getting out of bed. A systematic review of Laguna et al. [37] concludes that the leading causes
of falls are related, in addition to age, to preoperative and postoperative status, neurological diseases,
and medication. It is known that surgical patients have a higher risk of falling [7,37,38]. In the studied
sample, the number of patients with the risk factor of surgical intervention was five times higher in
the intervention group; despite this, there was only one fall in surgical patients in the intervention
group, which reinforces the benefit of the educational program.

An altered state of consciousness, although it is an intrinsic risk factor identified frequently in
the consulted bibliography [7,13,16,30,32,39], was not associated with any falls in patients with this
type of problem in our study.

Figure 1. Differences in the probability of fall between the two groups, intervention and control.

No significant association was found between the intrinsic risk factors and the incidence of falls.

4. Discussion

The total incidence of falls was 1.2%. This result was better than in other studies we consulted,
with falls affecting between 1.6% and 13.4% of the annual income in hospitals for acute patients [3–7,30,31].

The characteristics of people who suffered a fall correspond in many ways with those described in
the reviewed literature. There is evidence that relates advanced age to falls [7,14,32–34]. In our study,
85.8% of people that fell were 65 years and older, and 85.7% of those who fell were men; we found
similar percentages in a few studies [7,18].

We want to emphasize that all people who suffered falls in our study had a catheter; this is a
factor we did not find described by other authors. Regarding the average stay of the patient in the
hospital and its influence on the risk of suffering falls [12,13,22,35], 85.7% of falls occurred in patients

Int. J. Environ. Res. Public Health 2020, 17, 6048 9 of 13

with stays longer than one week. Luzia et al. [7] reported that 63.2% of patients fall between the 10th
and 24th days of hospitalization.

Patients with some level of mobility suffer the most falls according to various authors [12,15,18,22,32];
in our case all people who suffered a fall were autonomous or had a certain level of mobility. This is in
agreement with the work of Lopez-Soto et al. [36], which demonstrated that more falls occur while
patients are standing or sitting, when entering/leaving the room, and when getting up or getting out of
bed. A systematic review of Laguna et al. [37] concludes that the leading causes of falls are related,
in addition to age, to preoperative and postoperative status, neurological diseases, and medication. It is
known that surgical patients have a higher risk of falling [7,37,38]. In the studied sample, the number
of patients with the risk factor of surgical intervention was five times higher in the intervention group;
despite this, there was only one fall in surgical patients in the intervention group, which reinforces the
benefit of the educational program.

An altered state of consciousness, although it is an intrinsic risk factor identified frequently in the
consulted bibliography [7,13,16,30,32,39], was not associated with any falls in patients with this type
of problem in our study.

The difference in falls incidence among the studied groups (0.3% in the intervention versus 2.3%
in the control group) led us to consider the beneficial effect produced by the systematic method of
assessment used by the majority of nurses in the intervention group who, in addition, applied Downton
scale [28] to detect the risk of patient falls on admission. The analysis of the intervention by logistic
regression revealed that a lower likelihood of falls in the intervention group was associated effectively
with the method of care in the units included in this group, with no other studied variables being
relevant. Our results are consistent with other studies that advocate for the benefits of using scales to
identify the risk of falls [3,13,15,16,20–22]. Likewise, the systematic review by Miake-Lye et al. [19]
expresses the benefits of programs that include interventions to identify risk factors associated with
falls in acute care environments. A study on the incidence of falls in hospitals and nursing homes
asserted that many patients suffer falls because they do not receive the appropriate preventive care [40].

Almost all studies on the incidence of falls that we reviewed were in agreement with the benefits
of applying preventive measures based on the risk identified and/or illness [13,15,16,18,20,22,30,32,39].
A systematic review by Avanecean et al. [35] indicated patient-centered interventions, in addition
to tailored patient education, may have the potential to be effective in reducing fall rates in acute
care hospitals.

With regard to the training process implemented, we observed that it was effective in achieving a
reduction in falls; this shows that the process of assessment and risk detection is not always optimal
(affecting the quality of care and patient safety), and that continuous and advanced training of nurses
is essential. This is consistent with similar studies in different settings [8,9,23,24,41,42]; AbuAlRub
and Abu Alhijaa [41] noted in their study with senior nurses that an advanced training intervention
improved outcomes and reduced adverse events, including falls. In addition, we found that advanced
training helps to detect patients at risk of falling, which allows specific strategies to be designed within
the care plan to reduce or control risk. Some studies have also concluded that preventive education for
cancer patients at risk of falling can reduce falls significantly [42].

This last reflection indicates that it is necessary to improve the clinical practice of nurses through
advanced training. To do this, we will plan new practice models that influence the elements that
increase the risk of falls, with evidence-based practices such as advanced and specific training in risk
assessment [43]. Systematic reviews affirm that it is necessary to increase the concern of professionals,
because this can reduce the risk of falls [44].

The implications of our study for professional practice include a reduction in the number of
patient falls as a result of protocolizing an advanced assessment that includes specific evaluation of the
risk of falls in hospitalized patients (such as having some type of catheter), as well as optimizing of
the plan of care to be more adapted to these detected risks. Following the results of this investigation,

Int. J. Environ. Res. Public Health 2020, 17, 6048 10 of 13

a Systematic Assessment Procedure has been implemented in all areas of the hospital, indicating that it
is seen as an excellent tool to reduce this adverse event and improve the quality of care.

It is, however, necessary to reflect on why not all nurses voluntarily adhere to this type of training
program, because based on the available evidence and the results of our study, it is effective in reducing
falls. The training level of nurses is an element that has generated ample evidence as a factor which can
allow for the improvement of patient outcomes [45]. We believe that all nurses in hospital units with
vulnerable patients should undergo such training, and that new and more extensive studies should
continue to be carried out that will allow them to broaden their knowledge of the problem. Similarly,
we consider it essential to explore new advanced training interventions focused on risks to patient
safety; this will allow for an increase in evidence supporting improved training interventions and
professional development.

5. Limitations

We believe that in this research the “Hawthorne effect” or “observer effect bias” could have
occurred. The nurses, both from the intervention units and those belonging to the control group,
could have changed their behavior in some way as a result of knowing that patients for whom they
were responsible were being monitored.

On the other hand, not all nurses in the intervention group received training in systematic
evaluation (84.6% of them were trained, and 66% of patients were evaluated), so there were patients
from those units who did not undergo a systematic assessment of the risk of falling.

The study focused on improving the assessment process of nurses, thus improving the detection
of patients at risk. Therefore, no exhaustive information was obtained about the pathological
processes of the patients; in particular, not enough information was obtained about the patients’
baseline characteristics, nor the effect of the different independent variables on the results, such as
surgical intervention.

Finally, the design of the study itself was a limitation, as we randomized the hospital units
(since the training intervention was aimed at the nurses of the unit), and not the patients, as subjects of
the study.

6. Conclusions

We found that the advanced training of nurses in fall prevention improves patient outcomes.
In our study, the patients to whom the intervention was applied were less likely to fall, regardless of
age and length of stay. The systematic assessment of the risk of a patient falling during the hospital
processes has proved to be an effective intervention to reduce the incidence of falls, especially in the
elderly, who have the most falls. It is, therefore, necessary to implement specific advanced training
for all nurses and not as a voluntary training program. There is a need to further improve the
evidence on clinical practices to ensure patient safety (such as fall risk prevention), especially with
experimental studies.

Author Contributions: Conceptualization, R.M.-L., I.M.-M. and R.O.-L.; methodology, I.M.-M., R.M.-L. and
R.O.-L.; software, M.I.M.-L. and V.G.-C.; validation, V.G.-C., M.I.M.-L. and A.R.-H.; formal analysis, I.M.-M.
and R.M.-L.; investigation, I.M.-M. and R.M.-L.; resources, R.O.-L.; data curation, V.G.-C., M.I.M.-L. and
A.R.-H.; writing—original draft preparation, I.M.-M., R.M.-L. and V.G.-C.; writing—review and editing,
all authors.; visualization, R.M.-L., R.O.-L. and V.G.-C.; supervision, R.O-L., V.G.-C., A.R.-H. and M.I.M.-L.;
project administration, V.G.-C. and M.I.M.-L. All authors have read and agree the published version of
the manuscript.

Funding: This research received no external funding.

Conflicts of Interest: The authors declare no conflict of interest.

Int. J. Environ. Res. Public Health 2020, 17, 6048 11 of 13

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© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access
article distributed under the terms and conditions of the Creative Commons Attribution
(CC BY) license (http://creativecommons.org/licenses/by/4.0/).

  • Background
    • Framework
    • Justification
    • Objectives
  • Methods
    • Study Design
    • Population
    • Study Assessment Parameters
    • Procedure
    • Statistical Analysis
    • Ethical Considerations
  • Results
    • Description of the Sample
    • Incidence of Falls
    • Regression Model
  • Discussion
  • Limitations
  • Conclusions
  • References

Implementation of a Fall Prevention
Toolkit on a Medical Surgical Unit

Item Type DNP Project

Authors Khandagale, Usha

Publication Date 2021-05

Abstract Problem: In-hospital falls result in patient harm which includes
minor injury, psychological distress and anxiety, and serious
injuries like fractures, head trauma, and even death. The Joint
Commission consistently ranks falls with serious injury as …

Keywords Tailoring Interventions for Patient Safety (TIPS); Accidental
Falls–prevention & control; Inpatients; Quality Improvement

Download date 02/08/2022 00:19:56

Link to Item http://hdl.handle.net/10713/15802

IMPLEMENTATION OF A FALL PREVENTION TOOLKIT 1

Implementation of a Fall Prevention Toolkit on a Medical Surgical Unit

Usha Khandagale

Under Supervision of

Brenda Windemuth

Second Reader

Kathleen Buckley

A DNP Project Manuscript

Submitted in Partial Fulfillment of the Requirements for the

Doctor of Nursing Practice Degree

School of Nursing, University of Maryland at Baltimore

May 2021

IMPLEMENTATION OF A FALL PREVENTION TOOLKIT 2

Abstract

Problem: In-hospital falls result in patient harm which includes minor injury, psychological

distress and anxiety, and serious injuries like fractures, head trauma, and even death. The

Joint Commission consistently ranks falls with serious injury as one of the top sentinel

events. An acute care medical surgical unit in a community-based hospital experienced an

increase in the number of falls with an overall fall rate higher than that of peer units.

Purpose: The purpose of this Quality Improvement (QI) project was to implement and

evaluate the benefits of, and staff adherence to, the use of Fall TIPS (Tailoring Intervention

for Patient Safety) toolkit to reduce falls on a medical surgical unit.

Methods: The Fall TIPS toolkit was designed to decrease the patient fall rate in hospitals and

engage patients and their families in a 3-step fall prevention process including performing a

fall risk assessment, creating a tailored fall prevention plan, and executing the plan regularly.

Implementation of a Fall TIPS toolkit with auditing transpired weekly over 10 weeks on a

medical surgical unit. Nurses’ adherence to the Fall TIPS protocol was measured weekly

during implementation.

Results: The results indicated that nurses’ adherence to use of the Fall TIPS toolkit averaged

78%. The run chart analysis of nurses’ adherence did not show any shifts or astronomical

datapoints, and the number of runs was consistent with random variation. However, there was

a 6-point upward trend in the data during weeks 2 to 7, indicating a special cause. Fall rates

during the first two months of implementation were 3.39 and 2.41 per 1000 patient-days

respectively, and dropped to zero during the third month.

Conclusion: Nurses’ adherence to a Fall TIPS toolkit was demonstrated on a medical

surgical unit, which likely resulted in a decreased patient fall rate during the final month of

the project. Additional time will be needed to determine if the practice changes and outcomes

are sustainable.

IMPLEMENTATION OF A FALL PREVENTION TOOLKIT 3

Introduction

Unfortunately, falling during hospitalization remains common. According to the

Agency of Health Care Research (AHRQ, 2019) falls occurred at a rate of 3-5 per 1000 bed-

days, and an estimated 700,000 to 1 million hospitalized patients fall annually in the United

States. More than one-third of in-hospital falls result in patient harm which includes minor

injury, psychological distress and anxiety, and serious injuries like fractures, head trauma,

and even death (AHRQ, 2019). The Joint Commission’s (2015) Sentinel Event database

consistently ranks falls with serious injury in the top 10. The 2017 Maryland Hospital Patient

Safety Program’s Annual Report showed that falls (27%) were a top-five most adverse

hospital event leading to death or serious disability (2017).

A medical surgical unit at a community-based hospital experienced an increased fall

rate, higher than that of peer units. The unit staff were asked about their view of why patients

fell in the unit. The staff responded that the patients’ falls were due to communication

problems of patients not calling for help when getting out of bed. The director of the unit also

reported that there was inadequate and incomplete information at the bedside and variability

among team members regarding the patients’ fall risk status and the plan to prevent falls.

The Centers for Medicare and Medicaid Services (CMS; 2019) considers falls to be

preventable. Therefore, they are no longer reimbursing costs associated with falls, deeming

them to be events that should not occur during hospitalization. Fall TIPS is a tailored

evidence-informed preventative bedside intervention tool to decrease falls in hospitalized

patients (Dykes et al., 2019). The purpose of this QI project was to implement and evaluate

the benefits of, and staff adherence to, Fall TIPS to reduce fall rates on a medical surgical

unit.

IMPLEMENTATION OF A FALL PREVENTION TOOLKIT 4

Literature Review

The evidence review supported an implementation of Fall TIPS program focused on

in-patient fall prevention, designed to implement patient safety, predominantly fall

prevention. The literature review emphasized the following themes that supported the Fall

TIPS protocol: (a) Fall TIPS lowered fall rates in hospitals; (b) patient, family, nursing, and

leadership engagement was key to effectiveness of Fall TIPS; and (c) exposure to Fall TIPS

positively influenced patient knowledge, skill, and confidence in managing their own health.

The need to implement patient safety and prevent falls is supported by various

studies. A randomized controlled trial by Dykes et al. (2010) revealed that Fall TIPS by

leveraging Health Information Technology significantly reduced falls by 25% in four acute

care hospitals on more than 10,000 patients, and was particularly effective in patients aged

sixty-five or older. Based on those results, Fall TIPS could prevent one fall per day, 7.5 falls

every month, and 90 falls per year in the intervention units. Dykes et al. (2012) used data

mining and modeling techniques to determine the factors related to falls on intervention units

when Fall TIPS was in place. The results revealed that a fall prevention toolkit rationale was

accurate to decrease falls, but strategies were required to improve patient and care team

adherence to the fall prevention intervention suggested by Fall TIPS. Both studies found that

the Fall TIPS intervention was associated with a significant reduction in the fall rate and

injury rate (Dykes et al., 2017, 2020).

When patient engagement was added to the Fall TIPS protocol and tools were

developed to encourage patient and family engagement, there was a decrease in fall and

injury rates demonstrating an increase in effectiveness of Fall TIPS intervention as patient

engagement increased (Dykes, et al., 2017, 2020). Both studies concluded that engaging

hospital staff and clinical leadership was vital in transforming the evidence-based care into

the clinical workflow. According to Duckworth et al. (2019), the three modalities of Fall

IMPLEMENTATION OF A FALL PREVENTION TOOLKIT 5

TIPS: Electronic Health Record (EHR) version, a laminated paper version, and the bedside

display version suggest that each fall TIP modality is effective at engaging patients in the 3-

step fall prevention process that includes:

1. Performing fall risk assessment.

2. Creating a tailored fall prevention plan.

3. Executing the tailored fall prevention plan regularly.

A mixed method study by Leung et al. (2017) found that fall risk and fall prevention icons for

a beside toolkit facilitated patient, family and care team engagement to accurately assess fall

risk and a tailored fall prevention plan, resulting in enhanced adherence to Fall TIPS and

reduced falls. A multisite qualitative study conducted by Carter et al. (2020) supported that

one of the barriers to Fall TIPS adoption was poor patient engagement routines among staff

resulting in limited patients’ active participation in fall prevention. Successful execution of

Fall TIPS adoption required staff engagement of patients. Both studies revealed that patient

engagement in the 3-step fall prevention process increased the effectiveness of Fall TIPS

intervention and fall prevention (Carter et al., 2020; Duckworth et al., 2019).

Both studies by Dykes et al. (2017) and Fowler and Reising (2021) included pre- and

post-survey results that showed that Fall TIPS adoption improved patients’ knowledge of the

falls risk factors and fall prevention plan. Improved patient knowledge resulted in a decrease

in fall rates. A multisite study by Christiansen et al. (2020) showed patient activation, which

refers to a patient’s understanding, ability, and self-confidence in overseeing his or her own

health, increased from pre-intervention to post-intervention at the three healthcare system

sites with the access to Fall TIPS. However, it was vital that care team members engaged

patients in their fall prevention plan to increase knowledge, confidence and skill.

Based on an evidence review, adoption of a Fall TIPS program on high fall-risk units

lowered fall rates; improved patient, family, nursing and leadership engagement in the 3-step

IMPLEMENTATION OF A FALL PREVENTION TOOLKIT 6

fall prevention strategies; and influenced patients’ confidence in managing their own health

(see Appendix A).

Theoretical Framework

Kurt Lewin’s Change theory was utilized to guide this quality improvement project.

There were three main stages to Lewin’s Change Theory: unfreezing, changing, and

refreezing (Lewin, 1947). Unfreezing included creating a motivation to change the current

practice and preparing for a change. According to Shirey (2013), a change agent is required.

For instance, a nurse leader seeing a problem, and activating others to see the need for

change. In the changing or moving stage, a comprehensive plan of action was created and

staff were willing to try out the action plan. Refreezing entailed sustaining the change so that

it became ingrained into the existing systems such as policies and practices.

The problem identified during the unfreezing stage was increased number of falls in

the medical surgical unit. The change needed was to implement Fall TIPS—a fall prevention

toolkit. The unfreezing stage consisted of identification of stakeholders who had a direct

impact on the success of the project, engaging stakeholders in adopting the Fall TIPS toolkit

(Falls TIPS Collaborative, n.d.), and sharing evidence-based findings on Fall TIPS with the

stakeholders and QI team during the Fall Task Force meetings and huddles. Motivation was

needed to change the current practice which lacked personalized fall risk assessment and a

fall prevention plan. This was accomplished by engaging patients and their families in their

personalized fall risk and fall prevention plans. The changing stage included the

implementation of Fall TIPS. During this stage the stakeholders, champions and unit staff

received education on implementation of Fall TIPS protocol. After training, the need for

change was created and staff training on the Fall TIPS protocol was accomplished. The 3rd

stage, refreezing, involved stabilization of the change when FALL TIPS became a standard

IMPLEMENTATION OF A FALL PREVENTION TOOLKIT 7

for the medical surgical population. The utilization of Lewin’s Change Theory was vital to

guiding the implementation of the QI project.

Methods

The purpose of this quality improvement project was to implement the Fall TIPS

(Tailoring Interventions for Patient Safety) toolkit, developed by the Falls TIPS Collaborative

at Brigham and Women’s Hospital and Harvard Medical School (Falls TIPS Collaborative,

n.d.). The project was carried out at a community-based hospital in a 32- bed acute care

medical surgical unit with patients having orthopedic, neurological and oncology conditions.

Inclusion criteria required that patients be hospitalized for at least one day and be alert and

oriented. A 66-member care team was involved in this project. Included were day and night

shift change champions (i.e., five Nurses, three Certified Nursing Assistants or CNA’s, one

Physical Therapist, one Occupational Therapist and two Housekeeping staff), 38-unit nurses

and 16 CNA’s.

The Fall TIPS readiness implementation checklist was used to guide hospital

leadership and staff to prepare for the implementation (see Appendix B). The practice change

was implemented by the nurses over 10 weeks following a 2-week period in which training

was completed (see Appendix C). A completed description of implementation of the Fall

TIPS process was shown in Table 1. A written commitment was obtained from change

champions for adoption; and spread of the new innovation as shown in Appendix D. The

lesson plan was executed for Fall TIPS education (see Appendix E). Pre-implementation

training on the Fall TIPS protocol occurred for day and night shift in twelve separate formal

presentations until the entire unit of 66 staff and stakeholders received education. Fall TIPS

training included: a PowerPoint presentation, handouts, educational binders, performing an

accurate Morse Fall Scale (MFS) assessment, the 3-step Fall prevention process, and one-to-

IMPLEMENTATION OF A FALL PREVENTION TOOLKIT 8

one case study review with role play of nurse-patient interaction. Nurses received the Fall

Prevention Knowledge Test (FPKT) (see Appendix F) to evaluate perceived knowledge in

fall prevention. The paired pretest and posttest FPKT were based on True and False response

with the coding option of 1 for the right and 0 for the wrong answer. Permission to utilize the

Fall TIPS toolkit was granted by the Fall TIPS study group as documented in Appendix G.

The practice change was initiated subsequent to 2-week training. Over the following

10 weeks, nurses utilized the laminated Fall TIPS poster (11×17 inches) to engage and

educate eligible patients and their families in the three-step fall prevention process (see

Appendix H). The poster was hung on the door across the patient’s bed for visibility. Nurses

updated the poster daily on the patient’s current status and reviewed the information on the

tool at least once per shift and as needed. The Fall TIPS Quality Audit Instruction was used

to guide the audit process (see Appendix I). Data was collected through observation by

change champions weekly using the Fall TIPS Quality Audit Tool, which measured the

nurse’s adherence to, and patients and families engagement in the fall risks and prevention

plan (see Appendix J). The paper pencil tool extracted anonymous data. The first 3 questions

require a yes/no response by the auditor. If there was a “no” response to any of the first 3

questions, then the auditor was asked if they had provided peer-to-peer feedback to the staff.

The 3 questions included the Fall TIPS poster hanging on the door across from the patient’s

bed with a correct date, while patient and family were required to verbalize fall risk factors

and the fall prevention plan. Peer-to-peer feedback was provided if any question was

answered “No”. The completed data was entered in the REDCap electronic data capture tools

hosted at University of Maryland, Baltimore. The monthly fall rate per 1000 patient-days was

tracked from Quality Services department.

The project leader retrieved the de-identified pretest and the posttest FPKT responses

from REDCap; and ensured that responses were matched by using paired t-test. Nurse’s

IMPLEMENTATION OF A FALL PREVENTION TOOLKIT 9

adherence to ensuring Fall TIPS toolkit was complete with correct date, risk factors and fall

prevention plan and family engagement on knowledge of fall risk and prevention was

calculated in percentages. A project summary was submitted to the University of Maryland

Baltimore Human Research Protections Office (HRPO) for a Non-Human Subjects Research

(NHSR) determination. The results of the Fall TIPS Quality Audit Tool was stored on an

internal password protected computer.

Results

The pre-implementation education on Fall TIPS protocol occurred in 12 separate face-

to-face formal sessions. A total of 43 nurses received education. Nurses received the FPKT to

evaluate their perceived knowledge in fall prevention. A paired t-test was utilized to assess

the nurses’ perceived knowledge in fall prevention pre- and post-education. The results from

the pre-test (M = 0.42, SD = 0.098) and post-test (M =0.42, SD =0.135) for the FPTK

indicated that the training resulted in no significant improvement in the nurse’s knowledge

t=0.00 p = 1.00.

The nurse’s adherence to fall TIPS on the 3 question yes/no response was analyzed on

a weekly basis as shown in the run chart in Figure 1. Change champions performed a total of

259 Fall TIPS Quality Audits. The 194 observations recorded on the Fall TIPS audit were

100% complete. The overall nurse’s adherence rate for the 10 weeks of implementation was

78%; the target goal was set at 100%. The preliminary adherence rate during the first three

weeks of implementation was 56%, 61.5% and 73.9% respectively and progressively

improved to 96% at the end of 10 weeks. Run chart analysis did not show any shifts or

astronomical datapoints, and the number of runs was consistent with random variation.

However, there was a 6-point upward trend in the data during weeks 2 to 7 demonstrating a

non-random pattern due to a special cause (see Figure 1).

IMPLEMENTATION OF A FALL PREVENTION TOOLKIT 10

The monthly pre- and post-implementation of fall rate per 1000 patient-days data was

tracked from the hospital Quality Services and analyzed in a run chart (Figure 2). Prior to

implementation the fall rates for the months of July and August were 2.19 and 4.59 per 1000

patient-days respectively. Fall rates during implementation in the months of October and

November were 3.39 and 2.41 per 1000 patient-days respectively. No falls occurred in the

month of December. Run chart analysis did not show runs, shifts or trends. However, there

was an astronomical point noted in the month of December when there were no falls.

Discussion

The aim of this project was to decrease falls by improving patient engagement in fall

risks and fall prevention plan with communication across care team members. Although all

the nurses were trained on the Fall TIPS protocol, their lack of improvement in scores on the

post-test may have been due to nurses’ fatigue. The project took place during the COVID-19

pandemic, and the medical surgical unit was experiencing increased patient acuity and

census, high staff turnover, and shortage of staff, and constant change. Competing demands

on nursing staff to complete annual competencies also created challenges and time

constraints on the implementation. The barrier of lack of awareness and familiarity to the new

protocol, despite being trained on Fall TIPS protocol, was addressed by the project leader and

nurse champions providing “Just-in-time” training sessions to all staff, to remedy concerns

and answer questions. This tactic was similar to one used by Dykes et al. (2017) who

developed and implemented the Fall TIPS toolkit.

Strategies to overcome the low adherence rate to the protocol during the first three

weeks of the project included, constant communication with the unit staff by spreading

awareness, removing knowledge barriers by small group discussion and one-on-one

education. Daily shift huddles, staff meetings, a fall prevention bulletin board, and study

IMPLEMENTATION OF A FALL PREVENTION TOOLKIT 11

references at both nurse’s stations offered verbal and visual occasions for communication

about falls. Engagement of leadership at the unit level improved awareness of the new

evidence. These approaches were comparable to those used by Carter et al. (2020) who

identified engagement of leadership commitment, staff and patients was key in transforming

effective adoption of Fall TIPS. Involving unit change champions to provide peer-feedback,

reeducation, and promoting consistent application and adoption of Fall TIPS improved

awareness.

The results indicated that the strategies and tactics used had a positive impact on the

nurses’ adherence to the Falls TIPS toolkit. The nurses reached their highest adherence rate

of 96% the first week of December. This may have been due to multiple reasons that included

the unit director requiring nurses to complete the Fall TIPS poster at the bedside during the

change of shift handoff. The Assistant Nurse Manager (ANM) and charge nurses also began

performing random spot checks daily by observation during each shift, for completion of the

Fall TIPS poster. The dramatic shift in the fall rate to no falls during the month of December

was also likely related to this high adherence rate. Other reasons that may have contributed

to these positive findings included the improvement of the fall communication among care

teams, patients and families. Nurses were in agreement that the Fall TIPS was an effective

prevention tool as it engaged patients and families in their prevention process. Patients

increased their rate for calling for assistance for getting out of bed or with toileting, due to

enhanced awareness of fall risks factors and the fall prevention plan. This result was

comparable to the findings by Fowler and Reising (2021) who suggested that with the Fall

TIPS adoption there was improved patients’ knowledge of their fall risk factors and fall

prevention strategies.

While there was a decline in the fall rate per 1000-patient days, from a high of 3.39 in

October to zero in December, more time is needed to determine if this decline will continue

IMPLEMENTATION OF A FALL PREVENTION TOOLKIT 12

beyond implementation. It is probable that an increase in the nurses’ adherence to the Fall

TIPS protocol affected the unit fall rates. The results were comparable to the previous studies

by Dykes et al. (2010) and Dykes et al. (2012), which demonstrated that the adoption of the

Fall TIPS toolkit as associated with a decrease in fall rates. All fall risks patients were put on

bed alarms as per hospital policy, which may have contributed to alarm fatigue and noise in

the environment and possibly resulted in falls. This concern resulted in the decision by the

project leader and stakeholders to not use bed alarms on every patient at risk for falls, which

is consistent to the approach taken by Dykes et al., (2018) in their implementation of the

toolkit. However, patients who were not reliable to call for help when required, were placed

on a bed alarm.

The findings of this QI project are not generalizable to other settings and are limited

to a single patient unit with medical surgical patients at the center. Due to the pandemic

nurses expressed fatigue due to constant new changes, which may have limited their

adherence to the fall prevention measures.

Conclusion

Overall, the Fall TIPS toolkit was beneficial and effective in enhancing the awareness

of unit staff on the medical surgical unit and increasing nursing adherence to fall prevention

measures. The Fall TIPS poster completion and engagement of patients and their families

appeared to have an impact on reducing patient falls for the final month of the project. The

project results also revealed increased engagement of patients and their families to identify

fall risk factors and related prevention plan.

There is an increased prospect for sustainability of the project. The stakeholders have

been involved from the start of the project and have shown great interest during the entire

implementation process. There was significant leadership support and nurses taking the role

of change champions by performing audits, providing peer-feedback, reeducating, and

IMPLEMENTATION OF A FALL PREVENTION TOOLKIT 13

promoting adoption and consistent application of Fall TIPS. The clinical nurse specialist

continues to perform periodic spot checks 3-4 times per week on the unit for adherence to the

Fall TIPS protocol. The unit secretaries are ensuring the availability of the Laminated Fall

TIPS posters in English and Spanish and dry-eraser markers. While these enhanced

engagements suggest a culture prepared to support a new evidence-based practice change,

additional time will be needed to determine if the practice changes and outcomes are

sustainable.

IMPLEMENTATION OF A FALL PREVENTION TOOLKIT 14

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Nursing, 30(1), 28–34.

IMPLEMENTATION OF A FALL PREVENTION TOOLKIT 16

Leung, W. Y., Adelman, J., Bates, D. W., Businger, A., Dykes, J. S., Ergai, A., Hurley, A.,

Katsulis, Z., Khorasani, S., Scanlan, M., Schenkel, L., Rai, A., & Dykes, P. C. (2017).

Validating fall prevention icons to support patient-centered education. Journal of

Patient Safety. 1-10. doi: 10.1097/PTS.0000000000000354

Lewin, K. (1947). Frontiers in group dynamics: concepts, method and reality in social

science; social equilibria and social change. Human Relations, 1, 5-41.

https://doi.org/10.1177/001872674700100103

Maryland Department of Health Office of Health Care Quality. (2017, June 30). Maryland

Hospital Patient Safety Program Annual Report Fiscal Year 2017.

https://health.maryland.gov/ohcq/docs/Reports/Maryland_Hospital_Patient_Safety_Pr

ogram_Report_FY17.pdf

Shirey, M. R. (2013). Lewin’s Theory of Planned Change as a strategic resource.

The Journal of Nursing Administration, 43(2), 69–72.

https://doi.org/10.1097/NNA.0b013e31827f20a9

The Joint Commission (2015, September 28). Sentinel alert even preventing falls and fall-

related injuries in health care facilities. https://www.jointcommission.org/-

/media/tjc/documents/resources/patient-safety-topics/sentinel-

event/sea_55_falls_4_26_16.pdf

IMPLEMENTATION OF A FALL PREVENTION TOOLKIT 17

Table 1

Description of Implementation Process of Fall TIPS toolkit

Motivating change • Engaged stakeholders in adopting the laminated paper Fall TIPS poster
as an evidence-based tool to decrease falls

• Presentation of the evidence was performed in Fall Task Force
meeting, leadership meeting and staff unit huddles

• Quality Services involved for monthly fall rate information

• Identified champions for day and night shift

Planning and set up • Set up for adoption and spread was performed by targeting patient
population in the medical surgical unit with high fall rate

• Supported secured from unit level leadership which included unit
director, ANM, and Charge Nurses

• Fall TIPS readiness implementation checklist was used to guide the
quality improvement project

• Utilized native communication such as staff meetings and morning and
evening huddles to spread the innovation

Education • Unit staff received pre-implementation training on Fall TIPS protocol
with Fall TIPS instruction sheet

• Nurses completed the Fall pre and post paired FPKT

• Nurses utilized the Laminated Fall TIPS poster to engage patients and
their families in the three-step fall prevention process

• Train-the-trainer sessions were utilized for new staff and staff
identified as having poor completion rate for Fall TIPS

• Fall TIPS information sheet was provided to patients

Establishing Care

goals
• Change champions performed audits to measure adherence rate and

patient compliance to Fall TIPS

• Change champions provided prompt feedback to nurses as needed post
audit

• Change champions were taught to assist with training

• Adherence to the Fall TIPS was performed by weekly spot checks in
the unit to observe whether Fall TIPS is complete with correct date,

risk factors and prevention plan

Continuous

monitoring and

feedback

• Continued the spread and utilization of Fall TIPS by engaging
leadership, unit director, ANM charge nurses and clinical nurse

specialist,

• Biweekly report shared with unit staff, director and committee leaders
on adherence to Fall TIPS protocol, patient/family engagement and fall

rates

• Staff meeting and huddle time was utilized to improve awareness and
adherence rate

IMPLEMENTATION OF A FALL PREVENTION TOOLKIT 18

Figure 1

Medical Surgical RN Compliance to Fall TIPS Run Chart

Median

Goal

0

20

40

60

80

100

120

S
e

p
t-1

2

S
e

p
t-1

9

O
c
t-3

O
c
t-1

0

O
c
t-1

7

O
c
t-2

4

O
c
t-3

1

N
o
v
-7

N
o
v
-1

4

N
o
v
-2

1

N
o
v
-2

8

D
e
c
-5

P
e

rc
e

n
ta

g
e

o
f
F

a
ll
T

IP
S

C
o

m
p

le
te

d

% of nurses compliant
with protocol

Medical and Surgical RN Fall TIPS Compliance

Values Median GoalPre-implementation Implementatoion

IMPLEMENTATION OF A FALL PREVENTION TOOLKIT 19

Figure 2

Fall Rate for the Medical Surgical Unit

Median

Goal0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

4.00

4.50

5.00

J
u
l-2

0

A
u

g
-2

0

S
e

p
-2

0

O
c
t-2

0

N
o
v
-2

0

D
e
c
-2

0
Fall Rate per 1000 Patient Days for Medical Surgical Unit

F
a

ll
R

a
te

p
e

r
1

0
0

0
P

a
ti

e
n

t
D

a
ys

f
o

r
M

e
d

ic
a

l
S

u
rg

ic
a

l
U

n
it

Implementation

IMPLEMENTATION OF A FALL PREVENTION TOOLKIT 20

Appendix A

Evidence Review Table that evaluates Fall TIPS and interventions among medical surgical patients
Carter E. J., Khasnabish, S., Adeleman, J. S., Bogaisky, M., Lindros, M. E., Alfieri, L., Scanlan, M., Hurley, A., Duckworth, M.,

Shelley, A., Cato, K., Shao P. Yu., Carroll, D., Jackson, E., Lipstiz, S., Bates, D. W., & Dykes, P. C. (2020). Adoption of a Patient-

Tailored Fall Prevention Program in Academic Health Systems: A Qualitative Study of Barriers and Facilitators. OMB Geriatrics,

4(2), 1-15 http://www.lidsen.com/journals/geriatrics/geriatrics-04-02-119

Level VI

Purpose/

Hypothesis

Design Sample Intervention Outcomes Results

“We aimed to

identify dominant

facilitators and

barriers to Fall TIPS

adoption”

A Multisite qualitative

study design

Sample Technique:

Convenient sampling

Eligible:

Staff N-71

Patients N=50 and

Family members N=7

Eligible participants:

Patients were

considered eligible if

they spoke English or

had a family member

who spoke English and

who were alert and

oriented.

Eligible patients were

chosen by healthcare

team.

They had to have no

prior relationship with

the study examiner.

Excluded: none

reported

Accepted:

A sum of 71 staff took

part in 11 focus groups.

There were 50 patients

and 7 family members

individually

Intervention Protocol:

Patients’ families were

interviewed

individually for 15-60

minutes.

The focus groups that

ranged from 3-10

participants interview

extended 30-60 minutes

Intervention fidelity:

Staff focus and patients

interview conducted in

2 phases

Phase 1- principal

barriers and facilitators

for Fall TIPS identified

Findings discussed with

major stakeholders to

examine for accuracy.

Phase 2 – Continued till

findings from phase 1

were validated or

rejected.

Two to three

investigators performed

the interviews and

focus groups at each

study.

Dependent variable:

Fall TIPS adoption

barriers and facilitators

Measures:

The dependent

variables were

measured

after participants

consented verbally,

audio recordings of

interviews were made.

Their responses were

transcribed verbatim by

an automated

transcription aid.

For transcription

validity, transcripts

were scrutinized by

both the study

coordinator and

investigator.

Researcher’s job

included mutual

identification of codes,

application of codes

and discussion of any

discrepancies to reach

an agreement.

Statistical results:

Interviews were

analyzed utilizing

Conventional Content

Analysis.

Coding was executed

within NVivo using

consensus approach.

Facilitator’s

identified to Fall TIPS

adoption included 1)

Staff understanding of

the previous limitation

of fall prevention

programs and

recognizing fall

prevention as a priority

2) Patients and their

families took part in the

fall prevention

3) Fall TIPS was

incorporated in staff

existing workflow.

Barriers to fall TIPS

adoption program

included

1) Poor engagement

practices among staff

resulted in limited

IMPLEMENTATION OF A FALL PREVENTION TOOLKIT 21

interviewed during the

study period.

Power Analysis: No

power analysis was

reported which

increased the risk of

making a Type II error.

Group Homogeneity:

The study participant

group homogeneity was

presented in table 2, for

demographics.

Investigators attended

continued accepted

education workshop

directed by two

qualitative research

experts.

Patient confidentiality

was maintained during

individual interviews.

Group exchange and

dialogue was promoted

in the staff focus

groups.

For ensuring validity of

the results, researchers

peer debriefed biweekly

to seek objectivity of

findings, member

checking, involved

discussion of

qualitative findings

with patients and staff

for accuracy.

patients’ activation in

fall prevention

2) Using the one size

fits all viewpoint in fall

prevention

3) Patient’s willfulness

of not following the fall

plans.

Christiansen, T. L., Lipsitz, S., Scanlan, M., Yu, S. P., Lindros, M. E., Leung, W. Y., Adelman, J., Bates, D. W., & Dykes, P . C.

(2020). Patient Activation Related to Fall Prevention: A Multisite Study. The Joint Commission Journal on Quality and Patient

Safety, 46(3), 129–135. https://doi10.1016/j.jcjq.2019.11.010

Level IV

Purpose/

Hypothesis

Design Sample Intervention Outcomes Results

“The primary aim of

this study was to

determine if exposure

to the Fall TIPS

program influences

patient activation

related to fall

prevention”

Pre and post

implementation design, a

multi-site study

Sample Technique:

Simple random sample

technique

Eligible participants:

Adult patients, aged >

18 years admitted to the

study units for a

minimum of 24 hours.

Patients who were

mentally and physically

able to participate.

Participants were alert

and oriented, able to

speak English, gave

verbal consent to take

the survey, and

voluntarily participated.

Excluded: were 7

patients who did not

respond to the survey

Intervention Protocol:

Patient activation was

graded by surveying a

random sample of adult

patients before and after

employment of Fall

TIPS at three health

care system.

Intervention Fidelity:

Researchers used the

short form Patient

Activation Measure

(PAM– 13) adapted for

fall prevention.

The 13-item survey

assessed a patient

knowledge, skill, and

self-reliance in

managing his or her fall

prevention.

Dependent

Variable(s):

Patient activation refers

to a patient’s

knowledge, skills and

confidence in managing

his or her own health.

Measurement tool

(reliability), time,

procedure:

Patient’s activation was

measured by the

The PAM is a 13-item

(short form) assessed

patient activation in

four different levels.

Level 1 is the lowest

level of activation and

level 4 is the highest

Patients with a score of

1 are considered

Statistical

Procedures(s):

A reliability analysis

using Cronbach’ alpha

was used for reliability

analysis and showed

that scale is reliable (α

= 0.870 pre; α 0.870

post)

The robust ordinal t-test

revealed an increase in

PAM scores between

groups overall, with the

preintervention mean

scores at 63.82 (SD +

17.35)

The post intervention

means scores at 80.88

(SD + 17.48), p <

0.0001

IMPLEMENTATION OF A FALL PREVENTION TOOLKIT 22

(response rate of

98.0%).

Exclusion criteria:

Patients, who were not

mentally and physically

able to participate, who

were below 18 years of

age and discharged

before 24 hours after

admission.

Accepted: 343 patients

across three sites

n=158 preintervention;

n=185 postintervention.

Intervention: 343

patients were randomly

assigned.

Power Analysis: No

reported power

analysis, increasing the

risk of a Type II error.

Group Homogeneity:

The pre and post

intervention group

homogeneity is

presented in Table 1 &

2 which represents

descriptive statistics of

patients’ baseline

characteristics.

overwhelmed and

disengaged, in

managing their health.

The short form is both

valid and reliable

instrument.

The PAM 13 uses a 4-

point Likert scale (1=

strongly disagree and 4

= strongly agree).

Results:

Patient’s activation

increased from pre to

postintervention at all

sites Brigham and

Women’s Hospital

(BWH), p < 0.0001;

Montefiore Medical

Center (MMC), p <

0.0001 and

New York-

Presbyterians (NYP), p

= 0.0373

Duckworth, M., Adelman, J., Belategui, K., Feliciano, Z., Jackson, E., Khasnabish, S., Lehman, I.-F. S., Lindros, M. E., Mortimer,

H., Ryan, K., Scanlan, M., Berger Spivack, L., Yu, S. P., Bates, D. W., & Dykes, P. C. (2019). Assessing the Effectiveness of

Engaging Patients and Their Families in the Three-Step Fall Prevention Process Across Modalities of an Evidence-Based Fall

Prevention Toolkit: An Implementation Science Study. Journal of Medical Internet Research, 21(1), e10008.

https://doi.org/10.2196/10008

Level IV

Purpose/

Hypothesis

Design Sample Intervention Outcomes Results

IMPLEMENTATION OF A FALL PREVENTION TOOLKIT 23

“The purpose of this

study is to assess the

effectiveness for

engaging patients and

family in the 3-step

fall prevention process

(as defined by

patient/family

knowledge of their

personalized fall risk

factors and prevention

plan) of each of the

Fall TIPS modalities”

Single Qualitative

Descriptive Study

Sample Techniques:

Random sample of

Audits conducted by

Champions across all

data collection sites

6 Neurology units

7 medical or medical-

surgical units

Eligible Participants:

N=1209

Accepted:

1209 audits on patient

engagement

1401 audits for the

presence of the Fall

TIPS poster at the

bedside.

Inclusion Criteria:

Patients must be aged ≥

18 years, alert and

oriented or have a

family member present

and being involved in

the care, English or

Spanish speaking; and

Length of Stay (LOS)

in hospital > 24 hours.

Excluded criteria:

Patients who were < 18

years and not alert and

oriented and did not

have a family at the

bedside were excluded

from the study.

Power Analysis: No

power analysis was

reported which

increased the risk of

making a Type II error.

Intervention Protocol:

Engagement of patient

in the 3-step fall

prevention process

across the 3 Fall TIPS

modalities, patients

were questioned about

their knowledge of their

fall prevention plan.

Intervention Fidelity:

Each site incorporated

the Fall TIPS

prevention process into

practice,

built the clinical

decision support by Fall

TIPS into the electronic

health record (EHR)

Nurses completed the

fall TIPS risk

assessment and tailored

plan and recorded in

her at each site of data

collection.

The 3 modalities

utilized to present and

communicate the

patient’s falls risk

factors and fall

prevention plan

included

1. The laminated Fall
TIPS poster

2. Electronic Fall TIPS
poster

3. Paperless patient
safety bedside

display

Dependent variable:

Patients and family’s

knowledge about their

personal fall risks

factors and their fall

prevention plan around

the 3 Fall TIPS

modalities.

Protocol adherence

measured as the display

of fall prevention plan

at bedside

Measurement tool

(reliability), time,

procedure:

Random audits

performed to check the

effectiveness of

engaging patients in the

3-step fall prevention

across the 3 modalities

by asking does

patient/family know

their fall prevention

plan?

Radom audits were

performed to measure

protocol adherence by

checking if Fall TIPS at

the bedside

Nurse champion

selected patients for

audits.

Unannounced audit was

performed weekly.

Display of the

personalized fall

prevention plan at the

patient’s bedside was

Results:

Each Fall TIPS

modalities was

efficiently to assist

patient engagement in

the 3-step fall

prevention method

rate (> 80%) of

adherence for both

measures. i.e., of

patient engagement and

of adhering to protocol

of Fall TIPS.

Recommendations are

that all 3 modalities can

be incorporated in the

clinical workflow.

IMPLEMENTATION OF A FALL PREVENTION TOOLKIT 24

Group Homogeneity:

The sample population

consisted of a diverse

group of patients. At

Brigham’s and

Women’s Hospital

(BWH), Montefiore

Medical (MMC)

37.78% comprised of

Hispanics. Average age

groups of patients at the

3 study hospitals

(namely, BWH, MMC,

and New York

Presbyterian Hospital)

were 60.5, 60.1 and

63.3 years, respectively.

an indication of

adherence to the Fall

TIPS protocol

Dykes, P. C., Burns, Z., Adelman, J., Benneyan, J., Bogaisky, M., Carter, E., Ergai, A., Lindros, M. E., Lipsitz, S. R., Scan lan, M.,

Shaykevich, S., & Bates, D. W. (2020). Evaluation of a Patient-Centered Fall-Prevention Tool Kit to Reduce Falls and Injuries: A

Nonrandomized Controlled Trial. JAMA Network Open, 3(11), 1-10. https://doi.org/10.1001/jamanetworkopen.2020.25889

Level III

Purpose/

Hypothesis

Design Sample Intervention Outcomes Results

“The goal of the trial

was to assess whether

a fall-prevention tool

kit that engages

patients and families

in the fall-prevention

process throughout

hospitalization is

associated with

reduced falls and

injurious falls”.

A Nonrandomized

Controlled Trial with

pre- and post-

intervention study

Sampling Technique

Convenient sample

design at 14 medical

units including 3

academic medical

centers.

Eligible Participants:

N=37231

Eligible criteria:

All adult inpatients who

were hospitalized were

involved in the study.

Excluded: None

Sample size: N-37,231

pre-intervention 17948

and post intervention

19283

Intervention

Participants were

continuously engaged

by nurses in the 3-step

fall prevention process.

Intervention Fidelity

A laminated Fall TIPS

poster displayed at the

bedside

Nurses completed

poster with dry eraser

markers with patient

/families at admission

and during every.

The research team

assigned start dates to

each unit with the Fall

Dependent variables:

The two main outcomes

included overall rate of

patient falls per 1,000 s

and overall rate of falls

with injury per 1,000

days.

Measurement tool

(reliability) time,

procedure:

Nurse champions

completed

competencies training

and monitored fidelity

Unit nurse champions

measured compliance

to the Fall TIPS

A Poisson regression

tool used to establish

association between

intervention and the

rate of patient falls and

falls with injury per

1,000 days.

In addition, in

secondary analysis

adjusted Poisson

regression model was

used to assess changes

before and after

intervention included,

fall rates with

interaction involving

age groups and period,

IMPLEMENTATION OF A FALL PREVENTION TOOLKIT 25

Group Homogeneity

Demographic

characteristic of

patient’s was presented

in Table

Power Analysis:

No power analysis was

reported which

increased the risk of

making a Type II error.

TIPS modality along

with the constraints,

based on the 3

modalities.

Nurses identified the

patients Fall risk by

using the MFS and

linking the risk factors

with the suitable fall

prevention plan.

In the EHR-toolkit the

clinical decision

support spontaneously

printed appropriate

preventive

interventions.

Automatic displayed

screen saver at bedside,

were effective in testing

patient engagement in

the 3-step fall

prevention protocol

A 21-week pre-

intervention period

followed by 21-week

post intervention

period.

protocol including

patient engagement and

auditing 3 question

1) Is the Fall TIPS

poster complete and has

the correct information,

2) Can patient/family

verbalize fall risk

factors and

3) does the

patient/Family

verbalize the fall

prevention plan.

Nurses completed 5

random audits per

month with the Fall

TIPS Audit tool.

and interaction between

site and period.

An alpha level was set

at p<005.

There was an overall

15% adjusted decrease

in falls post

implementation of Fall

prevention toolkit

compared with

implementation (2.92

vs 2.49 falls per 1000

patient-days [(95% Cl,

2.06-3.00 fall per 1000

patient-days)].

An adjusted 34%

decreased injury rate

(0.73 vs 0.48 injurious

falls per 1000 patient-

days [95% Cl. 0.34 –

0.70 injurious falls per

1000 patient-days];

adjusted rate ratio 0.66;

95% Cl. 0.53-0.88; p=.

003).

Conclusion:

Implementation of Fall

prevention Tool kit was

related with a

significant decrease in

falls and related injury.

Citation: Dykes PC, Carroll DL, Hurley A, Lipsitz S, Benoit A, Chang F, … Middleton. (2010). Fall prevention in acute care

hospitals: a randomized trial. JAMA: Journal of the American Medical Association, 304(17), 1912–1918.

https://doi.org/10.1001/jama.2010.1567

Level II

Purpose/

Hypothesis

Design Sample Intervention Outcomes Results

“To investigate

whether a fall

Cluster randomized trial

design

Sampling Techniques:

Convenient sampling

Control Protocol: Dependent variable: Statistical results:

IMPLEMENTATION OF A FALL PREVENTION TOOLKIT 26

prevention tool kit

(FPTK) using health

information

technology (HIT)

decreases patient falls

in hospitals”.

from Medical units with

fall rates higher than

the mean for the

institution the year

before the study were

matched to units with

similar fall rates and

patient-days.
Eligible: N=10264

patients

Eligibility Criteria:

Units that matched and

were not involved

specifically in other fall

prevention

improvement projects

were deemed eligible.

Excluded: 8 units did

not meet eligibility

criteria.

Accepted: 10264

patients in the medical

units with high fall

rates. Randomization

located patients in the

in each of the control or

the intervention group.

Control: 5160 patients

in 4 units that received

standard care

Intervention: 5160

patients in 4 units that

received the

intervention

Power analysis: 10264

patients expected to

meet 80% power (with

α =.05) with fixed

effects size. Power

Control units received

routine care associated

with fall prevention

which included:

Completed MFS using

paper or electronic

forms

Placing high risk fall

sign above patients’ bed

with MFS scores > 45

Education of

patients/family on falls

with a booklet or

handout

Documenting plan on

electronic or paper

Intervention Protocol:

Included interventions:

Completed MFS

utilizing Fall

Prevention Toolkit

(FPTK)

Personalized bedside

posters were printed

spontaneously and

placed above patients’

beds

Educated patient/family

with tailored handout

Followed tailored plan

generated

spontaneously

generated by FPTK

from MFS assessment

Treatment Fidelity:

The research team

developed software for

the FPTK.

Falls per 1,000 patient-

days

Falls with injury per

1,000 patient-days in

the targeted units

Patient falls specified as

an unplanned descent to

the floor throughout the

hospitalization

Measurement tool

(reliability). Time,

procedure:

The dependable

variable measured by:

reporting patients falls

and falls with injury

recorded in an event

report system in the

units by nurse taking

care of the patient.

Incidents were

validated by hospital

quality personnel and

unit managers.

Valid Fall Risk

Assessment Scale

(MFA) identified

patient on high fall

risks.

Adherence to the Fall

prevention protocol was

measured by random

review of MFS

completion in control

groups and use of

FPTK components

including MFS

completion in the

intervention groups.

To examine the

difference in falls

throughout intervention

and control group the

priori Poisson

regression model

utilized that contained a

fixed effect and

intervention effects for

hospital.

Patient characteristic

was calculated utilizing

proportions, means with

standard deviation and

median with

interquartile ranges.

Covariate balance was

checked utilizing the

stratified Wilcoxon test

for continuous

confounders and fixed-

effects multinomial

logistic regression for

categorical confounders

A priori Poisson

regression model with

fixed effect and

intervention effect for

hospitals was utilized to

examine the difference

in falls throughout

intervention and control

groups.

The stratified Wilcoxon

test was used to check

the covariate balance.

Factors tested were

continuous confounders

and fixed-effects

IMPLEMENTATION OF A FALL PREVENTION TOOLKIT 27

analysis met to reduce

risk for type II error.

Group Homogeneity:

The Participants

characteristic of the

control and

interventional groups is

based on descriptive

statistics summarized in

table 2.

The FPTK (Fall

Prevention Toolkit)

incorporated the current

workflow patterns and

communication in the

Health Information

Technology (HIT)

operations.

According to the Morse

Fall Scale (MFS) risk

assessment completed

by the nurse, the FPTK

software generated

personalized fall

prevention

interventions per the

patient’s specific fall

risk.

The FPKT generated

bed posters include,

short text with

associated icons, care

plan, education

handouts, and all

patient specific

notifications to patients

to stakeholders.

The FPTK included a

compliance dashboard

to assist monitoring.

multinomial logistic

regression for

categorical

confounders.

There were lesser

patients with falls in the

intervention units

(n=67; range across

units 10-28) compared

with the control units

(n= 87; range across

units, 15-33).

A significantly lower

adjusted rate was found

in the intervention units

fall rate of 3.15 [95%

confidence interval

(Cl), 2.54 -3.90] per

1,000 patient-days). By

comparison the control

units’ results were 4.18

[95% Cl, 3.45-5.06] per

1,000 patient-days, with

rate variance of 1.03

(95% Cl, 0.57-2.01) per

1000 patient-days

(p=.04).

Patients aged 65 years

or older derived the

most benefit from the

FPTK Adjusted rate

difference, 2.08 [95%

Cl, 0.61-3.56] per 1,000

patient-days p=.003).

No significant effect

was noted in the injury

rates.

In the 8 study units,

including control and

IMPLEMENTATION OF A FALL PREVENTION TOOLKIT 28

intervention, there were

two 862 patient-days

periods.

Results showed that

the FPTK can prevent 1

fall per 862 patient-

days. Hence, the FPTK

could possibly prevent

approximately 90 falls

every year in

intervention units.

equating to 7.5 falls

every month and 1 fall

every 4 days.

Dykes, P. C, I-Ching, E. H., Soukup, J. R., Chang, F., & Lipsitz, S. (2012). A case control study to improve accuracy of an

electronic fall prevention toolkit. AMIA … Annual Symposium Proceedings. AMIA Symposium, 2012, 170–179. https://www-

ncbi-nlm-nih-gov.proxy-hs.researchport.umd.edu/pmc/articles/PMC3540550/

Level IV

Purpose/

Hypothesis

Design Sample Intervention Outcomes Results

“The purpose of this

case control study was

to use data mining and

modeling techniques

to identify the factors

associated with falls in

hospitalized patients

when the toolkit was

in place. Our ultimate

aim was to apply our

findings to improve

the toolkit logic and to

generate practice

recommendations”

A Case Control Study Sampling Technique

Cases included patients

with a fall on

intervention units at 4

partners HealthCare

acute care hospitals.

Controls randomly

selected from

intervention units

without a fall

Eligible Participants

Cases: Inpatients that

fell on the intervention

unit in an acute care

hospital where the Fall

TIPS toolkit (FTTK)

was in place for a 6-

month period. Cases

Intervention

Faller were matched

with similar controls in

regards to gender, age,

first MFS, length of

stay till the fall

Reviewed patients’

medical records and

incident report of falls

when FTTK in place

Checked for problems

with the FTTK software

to be corrected

Checked for the

intervention plan

suggested by FTTK

was correct and was

followed as by

Dependent variables:

Factors associated with

falls such as out of bed

with assist, 1 and 2-

person assist, Chair/Bed

alarm,

reorientation/frequent

checks, bed close to the

nursing station.

Measurement tool

(reliability). Time,

procedure:

A nurse investigator

extracted clinical data

for each case and

controls from the FTTK

database comprising

demographics, and

Morse Fall Scale (MFS)

Descriptive statistics by

employing two-by-two

tables were produced to

explain demographic

data of cases and

controls including

percentages in each

case/control group.

Conditional logistic

regression was used to

assess differences in

patients’ characteristic

for cases and control.

A priori variable

measured for

multivariate conditional

logistic regression

model comprised the

following significant

IMPLEMENTATION OF A FALL PREVENTION TOOLKIT 29

involved if they had 3

or more matches

Controls: Randomly

selected from patients

admitted to the

intervention units in the

same 6 months and did

not have a fall.

Controls were paired

for gender, age (within

5 years), first Morse

Fall Scale (MFS) total

score and length of stay

in the unit (within 24

hours) up to the time of

fall.

Excluded:

1 patient was excluded

due to incomplete data.

Sample size: N-192

88 patients age 64 and

younger

104 patients age 65 and

older

Power Analysis: No

power analysis was

reported which

increased the risk of

making a Type II error.

Group Homogeneity:

Cases and controls with

p value on table 4 for

demographics and

clinical characteristic

clinicians as

recommended by FTTK

Document prior fall,

out of bed with assist,

cane, bed/chair alarm,

1-person assist, 2-

person assist, frequent

checks/orientation, and

bed close to nursing

station.

total scores, nurse’s

interventions (proposed

by the FTTK of

patient’s risk report and

nurse’s knowledge

about the patient).

The nurse investigator

also collected the fall

incident data from

incident reporting

system, comprising unit

length of stay at the

time of fall.

A second investigator

confirmed extraction

for a random selection

of 10% of cases and

controls with agreement

> 90%.

intervention variables

(p<0.05).

All P values were two

tailed and a statistically

significant p value was

<0.05.

Falls: total falls 67 in

the intervention unit.

Of remaining cases: 48

had 3 or more matches

for gender, age (within

5 years), first Morse

Fall Scale (MFS) total

score and length for a

total sample size of

192.

Three research

questions answered,

The univariate

conditional logistic

regression analysis was

completed to answer all

3 questions.

Question One

Why did some patients

on the experimental

units fall with access to

the FTTK?

The univariate

conditional logistic

regression analysis

showed there was a

significant association

for the subsequent 7

interventions:

document prior fall out

of bed with assist

(p=.000)

IMPLEMENTATION OF A FALL PREVENTION TOOLKIT 30

bed/chair alarm

(p=.003)

1-person assist (p=.040)

2-person assist

(p=.006)

frequent

checks/reorientation

(p=.025)

bed close to nursing

station (p=.042)

frequent

checks/Reorientation

(p=.025)

The 7 variables were

entered into a

conditional logistic

equation and the

findings recommended

cases (fallers) were 5.7

times more likely than

matched controls (non-

fallers) among patients

requiring assistance

getting out of bed.

Question 2

What factors are linked

with falls associated

with younger patients?

The univariate

conditional logistic

regression analysis

showed significant

association for the

following 5

interventions,

out of bed with assist

(p=.010)

bed/chair alarm

(p=.003)

IMPLEMENTATION OF A FALL PREVENTION TOOLKIT 31

1-person assist (p=.034)

frequent

checks/reorientation

(p=.023)

bed close to nursing

station (p=.012)

Nevertheless, after

entering these variables

into the conditional

logistic regression

model and adjusting for

insurance and total

MFS before the fall,

none remained

significant.

Question 3

What factors are

associated with falls in

older patients?

The univariate

conditional logistic

regression analysis

showed significant

association for the

following 3

interventions:

ambulatory aid:

cane (p=.047)

out of bed (p=.004)

two-person assist

(p=.005)

Findings suggest cases

were significantly less

likely than matched

controls to be patients

who prior to fall did not

use a cane as an

ambulatory aid.

IMPLEMENTATION OF A FALL PREVENTION TOOLKIT 32

Fallers were also 10.1

times more liable than

matched controls before

the fall known to need

assistance getting out of

bed before the fall, and

14.26 times more liable

than non-fallers before

the fall to need 2 people

for assistance when

walking or getting out

of bed.

Results of evaluation

suggested that the

FTTK rational is

accurate but strategies

are needed to enhance

adherence with the fall

prevention intervention

proposals generated by

the electronic toolkit.

Dykes, P. C., Duckworth, M., Cunningham, S., Dubois, S., Driscoll, M., Feliciano, Z., Ferrazzi, M., Fevrin F.E., Lyons. S., Lindros

M. E., Monahan A., Paley M.M., Jean-Pierre S., Scanlan, M. (2017). Pilot testing Fall TIPS (Tailoring Interventions for Patient

Safety): a Patient-Centered Fall prevention Toolkit. The Joint Commission Journal on Quality and Patient Safety, 43(8), 403–413.

https://doi.org/10.1016/j.jcjq.2017.05.002

Level IV

Purpose/

Hypothesis

Design Sample Intervention Outcomes Results

Pilot testing the Fall

TIPS (Tailoring

Intervention for

Patient Safety) on

high-risk units at

BWH and at MMC

was to establish

efficacy and a

foundation for

adoption and spread.

Pilot Study Sampling Technique:

Convenient sampling at

two large medical

centers

Eligible Participants:

At Brigham and

women’s Hospital

(BWH)

31 patients answered

the pre-survey

33 the post survey

Intervention Protocol:

Conceptual model used

was The Institute of

Healthcare

Improvement’s (IHI)

Framework for Spread

(FFS). The four phases

of FFS include:

Communication:

The expert team

presented evidence on

Dependent variable:

Fall rate and Fall with

injury rates

Adherence to

Protocol, Fall

Rates/Injury Rates

Compliance to fall

TIPS protocol was

monitored via weekly

spot checks on each

unit

Patient surveys

At BWH; Boston

Changing levels of

progress – from baseline

to post Fall TIPS with

scores – were shown by

results of the Mann

Whitney U test; as well

as capability of patients

in recognizing their fall

risk (pre mean 3.7;

IMPLEMENTATION OF A FALL PREVENTION TOOLKIT 33

At Montefiore Medical

Center (MMC)

32 answered the pre

survey

30 patients answered

the post survey

Group Homogeneity:

The majority at BWH

were patients in the pre

and post survey were

female (60%), age 55

years, or older (53%)

and Caucasian (66%).

The majority of patients

in MMC were females

(68%) age 55 years and

older (53%) black or

African American

(53%) and

Hispanic/Latino (32%)

Power Analysis: No

power analysis was

reported which

increased the risk of

making a Type II error.

Fall TIPS to leadership

and quality and nursing

grand rounds to gain

support and

communicate value of

the Fall TIPS.

Planning and set up

Targeting relevant

population: patients on

units with fall rates

above the mean and

above the benchmark

for the institution.

Spread within the

target population

Secured support of unit

level clinical

leadership, unit-based

practice council, and

staff members

Unit champions and

stakeholders identified

and given education

and training for

associated practice

change.

Training sessions were

for all staff.

Continued monitoring

and feedback

Implementing auditing

to evaluate and provide

feedback on practice

adherence and patient

outcomes

Falls TIPS was

complete with patient

name, proper date, risk

factor and prevention

plan.

Patient fall and fall

related injury rates was

obtained through

hospital quality

department and

monthly report was

provided to clinical

champions.

Patient Surveys

Baseline data collected

regarding what patients

knew about their

personal risk of falling

and their fall prevention

plan. Survey employed

the five-point Likert

response format on the

following:

1. Do I recognize my

fall risks?

2. Am I aware of my

fall prevention plan?

Patient survey results

for pre- and post-

implementation of Fall

TIPS were compared

post-mean 4.5,

p=0.031), and

conception knowledge

of fall prevention (pre

mean 3.7: post 4.4,

p=0.264).

At MMC (Bronx, New

York)

The Mann Whitney U

test results showed

progress from baseline

to post Fall TIPS with

scores; for patients’

perceived ability to

recognize fall risk (pre-

mean 4.0; post 4.6.,

p=0.023) and

knowledge of how to

prevent a fall (pre-mean

3.6; post 4,7. p=0.001).

Protocol

Adherence/Fall

rates/Injury rates

At BWH, mean

adherence was 82% to

fall TIPS protocol.

The mean fall rate was

reduced from 3.28 per

1000 patient-days to

2.80 per 1,000 patient-

days

The mean fall-

associated injury rate

dropped from 1.00 per

1000 patient-days to

0.54 per 1,000 patient-

days

At MMC, according to

the audit the mean

IMPLEMENTATION OF A FALL PREVENTION TOOLKIT 34

adherence rate to fall

TIPS protocol was

91%. The mean fall rate

saw a slight increase

from 3.04 to 3.10 per

1,000 patient -days

The mean falls-

associated injury rate

dropped from 0.47 per

1,000 patient-days to

0.31 per 1,000 patient-

days

Fowler, S. B., Reising, S. E. (2021). A Replication Study of Fall TIPS (Tailoring Interventions for Patient Safety): A Patient-

Centered Fall Prevention Toolkit. MEDSURG Nursing, 30(1), 28–34. http://eds.a.ebscohost.com.proxy-

hs.researchport.umd.edu/eds/pdfviewer/pdfviewer?vid=3&sid=5c483b22-5891-41c9-8096-3e9def02a892%40sessionmgr4007

Level III

Purpose/

Hypothesis

Design Sample Intervention Outcomes Results

“The primary purpose

of this research was to

replicate a published

study to determine the

suitability of a patient-

centered fall

prevention tool and its

impact on patient

knowledge of fall risk

factors and prevention

interventions, overall

fall rates, and falls

with injury. A

secondary objective

was to evaluate ease of

use of the patient-

centered fall

prevention tool and

the need for

modifications”

Qualitative Study

pre and post intervention

design

Sampling Technique

Four Convenient

samples of 30 patients

each period.

Eligible Participants

Inpatients on a medical

telemetry unit.

Inclusion:

Patients who are alert

and oriented and

speaking English or

Spanish.

Excluded: Patients who

were not alert and

oriented and did not

speak English or

Spanish.

Sample size:

Pre-intervention (N-30)

at 1 month

Intervention:

Intervention in the

study included patients

interviewed pre-

implementation at 1

month and during

implementation at 3,

and 6-months regarding

knowledge of their fall

risk and fall prevention

plan

Intervention Fidelity

Alert and oriented

patients selected by

investigator with

consent for the study

Patients were asked two

Likert-style statements

pre and during

implementation bout

Dependent variables:

The two main

outcomes included

Patients’ knowledge on

Fall risk factors and fall

prevention plan.

Overall fall rates and

Fall with injury rates

Measurement tool

(reliability) time,

procedure:

Patients’ knowledge on

fall risk factors and fall

prevention plan was

measured by the study

team members by

asking 2 questions, (a)

An independent t-test

was employed to

compare pre and post

scores of patient

knowledge of falls risk

and fall prevention

The mean scores of

statements

(a) identify falls risks

increased from 4.13 to

4.6 at 1 month; It

remained unaffected in

month 3 and 6 months

(4.57 and 4.47,

individually

The mean for question

(b) how to prevent a fall

increased from 3.97 to

4.67 at 1 month and

remained unchanged at

IMPLEMENTATION OF A FALL PREVENTION TOOLKIT 35

During the intervention

(N-120) at 3 months

and 6 months.

Group Homogeneity

None noted

Power Analysis: No

power analysis was

reported which

increased the risk of

making a Type II error.

the knowledge of fall

risk and fall factors and

prevention plan which

include, (a) I am able to

identify my risk for

falling, (b) I know what

I need to do to prevent

from falling

Nurses updated the

laminated Fall TIPS

poster at the bedside,

patients were assessed

for fall risks using the

MFS, individualized

teaching to patient and

family was done using

the Fall TIPS

prevention tool

Investigators checked

compliance to

documentation on the

poster three time a

week for patient name,

date, risk factor and

prevention plan.

Can you identify the

risk for falls.

(b) Are you aware of

what needs to be done

to prevent a fall?

The 5-point Likert scale

was used as a response

format (1=strongly

disagree and,

5=strongly.

Overall, compliance of

nurses to fall TIPS

protocol was measured

by Fall TIPS audit tool

bi-weekly on the 5 data

points patients

name/bed umber,

current date and time,

verbalization of fall risk

factor and fall

prevention plan.

Fall rates and injury

rates were acquired

from the hospital for

the pre and post

intervention period.

3 and 6 months (4.53

and 4.7, individually

The patient’s

knowledge about falls

at 1, 3 and 6 months

compared to pre-

implementation

(p=0.001-0.05)

The overall fall rate

pre-intervention

reduced from 3.3% to

1.9% post intervention.

Staff adherence to the

Laminated Fall TIPS

was 85%.

Leung, W. Y., Adelman, J., Bates, D. W., Businger, A., Dykes, J. S., Ergai, A., Hurley, A., Katsulis, Z., Khorasani, S., Scanlan,

M., Schenkel, L., Rai, A., & Dykes, P. C. (2017). Validating Fall Prevention Icons to Support Patient-Centered Education. Journal

of Patient Safety. 1-10. doi: 10.1097/PTS.0000000000000354

Level IV

Purpose/

Hypothesis

Design Sample Intervention Outcomes Results

“The objective of this

project was to refine

fall risk and

prevention icons for a

patient-centric bedside

toolkit to promote

patient and nurse

Mixed method

descriptive and

qualitative study, which

involved psychometric

evaluation with pre- and

post-test

Sampling Technique:

Convenient sampling

Accepted participants:

88 patients and 60

nurses from 2 academic

medical centers.

Intervention Protocol:

Patients n=88 and

nurses n=60 from 2

academic medical

centers contributed in 4

iterations of testing to

upgrade 6 fall risk and

Dependent Variable:

Fall risk and prevention

icons for a toolkit at

patient bedside.

Measure:

Content validity-

visualization of Icon

Results:

Content validity index

scores enhanced after

modification of icons.

Icons that depicted

several concepts

IMPLEMENTATION OF A FALL PREVENTION TOOLKIT 36

engagement in

accurately assessing

fall risks and

developing a tailored

fall prevention plan”.

Eligible participants

Included 88 patients

who were physically

and cognitively able to

participate.

Nurses n=60 from

oncology and medical

surgical units at BWH

and MMC.

Group Homogeneity:

Demographic

characteristic of

patient’s and nurses

was presented in Table

1, which represents

descriptive statistics.

Power Analysis: No

power analysis was

reported which

increased the risk of

making a Type II error.

10 fall prevention

icons.

The methodological

approach of

determination and

quantification of

content validity was

used.

In individual interviews

participants graded

their satisfaction with

the degree to which

icons signified the

concept on a 4-point

Likert scale, aiding

computation of a

Content Validity Index

(CVI)

Comments and

suggestions were

provided by

participants for

improvement.

Treatment Fidelity:

Successive phases of

iterative icon evaluation

and refinement were

carried out until all

stakeholders agreed on

icon’s validity

After reviewing CVI

scores and feedback,

the research team

discussed with the

illustrator to modify the

ions

refinement process and

outcomes:

In the first iteration

each of the preliminary

6 fall risk and 10 fall

prevention icons was

revised by 16 patients.

The mean CV rating

from 1.7 to 3.8 and both

negative remarks about

the picture for the

research team to

address and made

suggestion

All 16 items were

improved.

Second iteration:

12 patients and 30

nurses rated the 16

improved icons and

second group of 30

patients and 30 nurses

rated those icons that

had been further

improved.

Third iteration:

A slash through the

CVI cell demonstrated

that the improved icons

were regarded

acceptable.

Fourth iteration:

Was vital for 2 risk

icons established on

low CVI rating from

the patients.

The final round

involved testing “forget

to call” and “unsteady

required further

iteration for acceptance.

All 16 concepts were

preserved and were

perfected on the basis

of nurses and patient

response.

Using icons to describe

an accurate and easy to

interpret fall risk

assessment and

intervention plan for

care team members

which includes patient

and family was led to

enhanced adherence

with that plan and

decreased falls.

IMPLEMENTATION OF A FALL PREVENTION TOOLKIT 37

gait” with 30 extra

patients and 30 extra

nurses.

IMPLEMENTATION OF A FALL PREVENTION TOOLKIT 38

Appendix B.

Fall TIPS Readiness Implementation Checklist

IMPLEMENTATION OF A FALL PREVENTION TOOLKIT 39

Appendix C

The Project Timeline for Fall TIPS Implementation

Strategies and Tactics Dates Individuals or groups

affected

Educational Strategies

Pre-test on fall prevention 9/2/20- 9/10/20 Nurses

Formal education on Fall TIPS 9/11//20-9/18/20 Champions, Nurses,

CNA’s, and

Stakeholders

Train the Trainer 9/20/20 – 12/04/20 Unit Champions

Post-test on fall prevention 10/25/20 – 11/06/20 Nurses

Develop educational material 9/2/20-9/10/20 Unit Staff

Data Strategies

Complete audits and individual

feedback

09/27/20 – 12/05/20 Nurses

Provide data report on unit bulletin

board

Weekly Nurses, CNA’s

Identify barriers and facilitator Weekly Nurses, CNA’s,

Champions

Discourse strategies

One-to-one discussion Weekly Nurses and CNA’s

Remind unit staff on coming events 09/27/21-12/05/20 Nurses and CNA’s

E-Mails 9/11/20-12/04/20 Nurses and CNA’s

Rewards 10/25/20-12/05/20 Nurses and CNA’s

Accountability

Obtain formal Commitments 9/13/20-9/18/20 Champions

Provide Supervision 9/27/20-12/05/20 Nurses and CNA’s

Collaboration and communication

Meetings 09/22/20-12/04/20 Champions, Nurses,

CNA’s, and

Stakeholders

IMPLEMENTATION OF A FALL PREVENTION TOOLKIT 40

Appendix D

Written Commitment from champions

Adoption and spread of the innovation – Fall TIPS

Education of patients and family on their fall risks and fall prevention plan

1. Nurse champion

a. Fall TIPS is completed and updated daily with the patient’s name, correct date,

risk factors, and individualized fall prevention plan.

b. Complete audits – FALL TIPS Quality Audit Tool and give individual and group

feedback.

c. Give awareness of the daily falls in the unit.

d. Remind unit staff of upcoming events – Fall Prevention Knowledge Pre-test,

education and training on Fall Prevention and Fall TIPS Toolkit, Fall Prevention

Knowledge Post-test

e. Train the trainer

f. Identify barriers and facilitators

g. One-to-one discussion

h. Peer-to-peer feedback

2. Certified Nursing Assistant

a. Fall TIPS in place, with markers and erasers.

b. Patients have the correct mobility aids in the room such as walkers or cane.

c. Bed alarms and chair alarms are working and kept on.

d. Check the universal precautions are in place – Fall sign on, Yellow socks, yellow

bands.

e. Clearing the clutter in patients’ room.

f. Check Laminated Fall TIPS toolkit is available on admission.

3. Physical and Occupational therapist

Communication to the care team on the mobility related concerns:

a. Appropriate device needed for ambulation.

b. The amount of assistance needed for Activities of Daily Living (ADL).

c. Communicating to health team about the patient’s strength and balance.

d. Educate patients on falls prevention.

4. Housekeepers –

a. Cleaning and disinfecting the Laminated Paper Fall TIPS at bedside upon

discharge.

b. Keeping a clean Fall TIPS ready for use.

c. Clearing clutter and spills as soon as possible.

I agree to serve as a champion, to assist with the training, answer questions, and provide

feedback to the healthcare team on 6 North unit

Name: ____________________________

Signature: ____________________________

Date: ____________________________

IMPLEMENTATION OF A FALL PREVENTION TOOLKIT 41

Appendix E

Lesson plan for Fall TIPS Education Session

Learning Objectives Content Outline Method of Instruction Time Spent Method of Evaluation

Stakeholders, champions,

Nurses and CNA’s at the

medical surgical unit will

be knowledgeable on the

evidence base for

engaging patient in the

fall prevention protocol.

• Problem of patient falls

• Fall TIPS Findings:
Two-year mixed method study and

Randomized control trial (RCT)

Qualitative results summary

• Fall prevention lessons learned

• The Fall TIPS toolkit

• Bed poster

• Patient engagement

• PowerPoint
presentation

10 minutes Discussion of why

patient engagement is

vital in fall prevention

Nurses will be informed

on the information and

illustrations of how to

perform a fall risk

assessment utilizing the

Morse Fall Scale (MFS)

and the fall TIPS protocol

• Evidence-based fall prevention
strategies

• Universal Fall Precautions

• Three step fall prevention process

• Conducting fall risk assessment
(MFS)

• Completing tailored fall prevention
care plan

• Consistently implementing the plan

• PowerPoint
presentation

• Discussion

• Demonstration

10 minutes Discussion and

demonstrate of the

accurate use of Morse

Fall Scale

Nurses with an interactive

case study, will be able to

complete the three-step

fall prevention process

using the Fall TIPS

• Accurately performing an MFS
assessment

• Interactive case study – completing a
3-step fall prevention process by

utilizing Fall TIPS toolkit.

• PowerPoint
presentation

• Return
Demonstration

10 minutes Return demonstration

of MFS and the use of

Fall TIPS toolkit

IMPLEMENTATION OF A FALL PREVENTION TOOLKIT 42

Appendix F

FPTK 11-item Answer Key

Item’s raw correct score for conversion to 1 or 0 T F

1. Bedside nurses know their patients and are better than a standardized
screening scale at identifying patients likely to fall.

F

2. The 3-step fall prevention process is comprised of 1) screening for fall
risks, 2) developing a tailored fall prevention plan, 3) completing fall

prevention documentation.

F

3. A 75-year-old male with history of recent falls and osteoporosis is
admitted for severe abdominal pain. He is at increased risk for injury

if he falls due to his age.

F

4. A common reason why hospitalized patients fall is that their fall
prevention plan is not followed.

T

5. Falls can be prevented in patients who are susceptible to falling
because of physiological problems by providing a safe environment;

e.g., clear path to bathroom, room free of clutter, good footwear.

F

6. Patient engagement in fall prevention means that the nurse completes
the fall risk assessment and prevention plan, and then teaches the

patient about their personal fall risk factors and prevention plan.

F

7. All hospitals are different; therefore, they should develop their own
fall risk assessment forms.

F

8. A fall risk screening scale identifies those patients who are likely to
fall because they have one or more physiological problems.

T

9. When nurses communicate with patients about their increased risk for
injury if they fall, this improves the likelihood that patients will follow

their personalized fall prevention plan.

T

10. Patients at low risk for falls do not require a fall prevention plan.

F

11. Bed and chair alarms should be activated for all patients who screen
positive for being at a high risk of falling.

F

IMPLEMENTATION OF A FALL PREVENTION TOOLKIT 43

Appendix G

Fall TIPS Copyright Permission

May 25, 2020

Usha Khandagale

DNP Candidate

University of Maryland

Adventist HealthCare White Oak Medical Center

11890 Healing Way, Silver Spring, MD 20904

www.AdventistWhiteOak.com

Dear Ms. Khandagale:

This letter serves as permission for your use of the Fall TIPS Toolkit in your quality

improvement project on fall prevention on a medical surgical unit as a course requirement for

the Doctor of Nursing Practice. You have permission to use the Fall TIPS (Tailoring

Interventions for Preventions for Patient Safety) toolkit in the form of a laminated poster that

staff complete and post it at the bedside. You will not make any changes to the Fall TIPS

Toolkit (except for adding your institutional logo if desired) without a written permission.

Sincerely,

Patricia C Dykes PhD, MA, RN, FAAN, FACMI

Program Director Research

Center for Patient Safety, Research and Practice

Brigham & Women’s Hospital

Associate Professor

Harvard Medical School

[email protected]

IMPLEMENTATION OF A FALL PREVENTION TOOLKIT 44

Appendix H

Laminated Fall TIPS Poster in English

IMPLEMENTATION OF A FALL PREVENTION TOOLKIT 45

Appendix I

Fall TIPS Quality Audit Instructions

1) Is the patient’s Fall TIPS report hanging at the bedside? Instructions: Record “Yes” if
there is a Fall TIPS poster hanging at the bedside and it is for the correct patient. Record

“No” if there is no Fall TIPS poster hanging at the bedside or if it is for the incorrect

patient (i.e., wrong patient name).

2) Can the patient/family verbalize the patient’s fall risk factors?
Instructions: Record “Yes” if the patient/family can verbalize any of the fall risk factors

that are displayed on the Fall TIPS poster. Record “No” if the patient/family cannot

verbalize any of the fall risk factors that are displayed on the Fall TIPS poster.

Record “N/A” if the patient is nonverbal or not alert and oriented, and no family is

present.

3) Can the patient/family verbalize the patient’s personalized fall prevention plan?
Instructions: Record “Yes” if the patient/family can verbalize any of the fall prevention

interventions that are displayed on the Fall TIPS poster. Record “No” if the

patient/family cannot verbalize any of the fall prevention interventions that are displayed

on the Fall TIPS poster.

Record “N/A” if the patient is nonverbal or not alert and oriented, and no family is

present.

4) If you answered “No” to any question, did you provide peer-to-peer feedback?

Instructions: Record “Yes” if you followed up with the nurse whose patient you audited.

Record “No” if you did not follow up with the nurse whose patient you audited. Record

“Other” if you would like to share why you did not provide peer-to-peer feedback. **We

have found that the peer-to-peer feedback piece is especially important for

implementation. By following up with the nurse, you can identify if there is a gap in

knowledge or another barrier to Fall TIPS completion that we can address.

IMPLEMENTATION OF A FALL PREVENTION TOOLKIT 46

Appendix J

Fall TIPS Quality Audit Tool

Original Investigation | Public Health

Evaluation of a Patient-Centered Fall-Prevention Tool Kit
to Reduce Falls and Injuries
A Nonrandomized Controlled Trial
Patricia C. Dykes, PhD, RN; Zoe Burns, MPH; Jason Adelman, MD; James Benneyan, PhD; Michael Bogaisky, MD; Eileen Carter, PhD, RN; Awatef Ergai, PhD;
Mary Ellen Lindros, EdD, RN; Stuart R. Lipsitz, ScD; Maureen Scanlan, MSN, RN; Shimon Shaykevich, MS; David Westfall Bates, MD, MSc

Abstract

IMPORTANCE Falls represent a leading cause of preventable injury in hospitals and a frequently
reported serious adverse event. Hospitalization is associated with an increased risk for falls and
serious injuries including hip fractures, subdural hematomas, or even death. Multifactorial strategies
have been shown to reduce falls in acute care hospitals, but evidence for fall-related injury
prevention in hospitals is lacking.

OBJECTIVE To assess whether a fall-prevention tool kit that engages patients and families in the fall-
prevention process throughout hospitalization is associated with reduced falls and injurious falls.

DESIGN, SETTING, AND PARTICIPANTS This nonrandomized controlled trial using stepped wedge
design was conducted between November 1, 2015, and October 31, 2018, in 14 medical units within
3 academic medical centers in Boston and New York City. All adult inpatients hospitalized in
participating units were included in the analysis.

INTERVENTIONS A nurse-led fall-prevention tool kit linking evidence-based preventive
interventions to patient-specific fall risk factors and designed to integrate continuous patient and
family engagement in the fall-prevention process.

MAIN OUTCOMES AND MEASURES The primary outcome was the rate of patient falls per 1000
patient-days in targeted units during the study period. The secondary outcome was the rate of falls
with injury per 1000 patient-days.

RESULTS During the interrupted time series, 37 231 patients were evaluated, including 17 948
before the intervention (mean [SD] age, 60.56 [18.30] years; 9723 [54.17%] women) and 19 283
after the intervention (mean [SD] age, 60.92 [18.10] years; 10 325 [53.54%] women). There was an
overall adjusted 15% reduction in falls after implementation of the fall-prevention tool kit compared
with before implementation (2.92 vs 2.49 falls per 1000 patient-days [95% CI, 2.06-3.00 falls per
1000 patient-days]; adjusted rate ratio 0.85; 95% CI, 0.75-0.96; P = .01) and an adjusted 34%
reduction in injurious falls (0.73 vs 0.48 injurious falls per 1000 patient-days [95% CI, 0.34-0.70
injurious falls per 1000 patient-days]; adjusted rate ratio, 0.66; 95% CI, 0.53-0.88; P = .003).

CONCLUSIONS AND RELEVANCE In this nonrandomized controlled trial, implementation of a fall-
prevention tool kit was associated with a significant reduction in falls and related injuries. A patient–
care team partnership appears to be beneficial for prevention of falls and fall-related injuries.

TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT02969343

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Key Points
Question Is a fall-prevention tool kit
that engages patients and families

associated with a reduction in falls?

Findings In this nonrandomized
controlled trial including 37 231 patients

from 14 medical units within 3 academic

medical centers, an interrupted time

series found that implementation of a

fall-prevention tool kit was associated

with a statistically significant 15%

reduction in overall inpatient falls and a

34% reduction in injurious falls.

Meaning The findings suggest that
tools to support patient engagement

throughout hospitalization in the fall-

prevention process may be associated

with a reduction in falls and fall-related

injuries.

+ Supplemental content
Author affiliations and article information are
listed at the end of this article.

Open Access. This is an open access article distributed under the terms of the CC-BY License.

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Introduction

Falls represent a leading cause of preventable injury.1 Hospitalized patients are at an increased risk for
falls, which may result in serious injuries, such as hip fractures, subdural hematomas, or even
death.2,3 Injurious falls are associated with increased hospital stays of 6 to 12 days,4 and the costs of
serious episodes of injury range from $19 376 to $32 215 (2019 USD).5 Patient falls and related injuries
are considered nursing-sensitive indicators because fall prevention depends on the quantity and
quality of nursing care.6-8 Most falls in hospitals are preventable,9 and resultant injuries are not
reimbursed by the Centers for Medicare & Medicaid Services.10 Multifactorial strategies can reduce
rates of falls in hospitals, although the evidence for reducing fall-related injuries is inconclusive owing
to the limited number of clinical trials that have assessed this outcome.11 To our knowledge, no prior
multisite evaluation in acute care hospitals has shown a significant reduction in injurious falls.

A previous study12 theorized that fall prevention in hospitals was a 3-step process: (1) assessing
fall risk, (2) developing a personalized prevention plan, and (3) executing the plan consistently. Our
team developed the Fall Tailoring Interventions for Patient Safety (TIPS) tool kit, a nurse-led,
evidence-based fall-prevention intervention that uses bedside tools to communicate patient-specific
risk factors for falls and a tailored prevention plan. The tool kit provides care team members with the
information they need to routinely engage in the fall-prevention process.12 In a randomized clinical
trial within a single health care system, Fall TIPS reduced patient falls by 25%, but there was no
difference noted in fall-related injuries.13 A follow-up case-control study suggested that falls within
the intervention units were largely attributable to patients’ nonadherence to their fall-prevention
plan14 and that further strategies are needed for engaging patients in the 3-step fall-prevention
process during hospitalization.

In collaboration with Northeastern University’s Healthcare Systems Engineering Institute, we
conducted observational and qualitative research with hospitalized inpatients, family members, and
health care professional to make the Fall TIPS tool kit more patient-centered and to address barriers
to engaging patients and families in the 3-step fall-prevention process.15,16 The project was divided
into the 5 following iterative phases using the Reach, Effectiveness, Adoption, Implementation, and
Maintenance (RE-AIM) framework17 (Figure 1): (1) problem analysis using workflow observations and
individual and group interviews18; (2) design using knowledge gained in phase 1 to plan a patient-
centered Fall TIPS tool kit with multiple modalities18,19; (3) development using participatory design,

Figure 1. Five-Phase Intervention Development and Evaluation

e-Bedside
display

1. Problem analysis: learn about the needs and preferences
of patients and providers and other social-technical factors
that relate to fall prevention

4. Implementation: conduct a pilot test of fall TIPS and
compare for effectiveness in engaging patients and
families in the 3-step fall prevention process15,20

Laminated
paper poster

2. Design and 3. Development: implement content, display,
and workflow integration strategies most likely to address
requirements and overcome barriers18,19

EHR toolkit
Iterative

Patient activation survey and
efficacy analysis 21 mo before
and after intervention

6-mo Pilot test on patient care
units and compliance audits

Participatory design, icon
validation with patients and
families, usability testing,
rapid prototyping, and piloting
prototype refinement

Focus groups, interviews,
and workflow observations

5. Evaluation: evaluate the toolkit’s efficacy on patient
activation,21 falls, and injurious falls

Unit staff and patients were engaged in developing,
refining, implementing, and pilot testing a patient-
centered Fall Tailoring Interventions for Patient Safety
(TIPS) tool kit with high-tech and low-tech modalities.
EHR indicates electronic health record.

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rapid prototyping, computer modeling, and simulation methods to construct the patient-centered
Fall TIPS tool kit18,19; (4) implementation and pilot testing of the tool kit in patient care units19,20; and
(5) evaluation of the association of the tool kit with patient activation.21 The end result was a tool kit
that included high-tech and low-tech Fall TIPS modalities, can be used by nursing staff and integrated
into various hospital workflows, and supports patient activation and engagement in the 3-step fall-
prevention process.20,21 Modalities included (1) a laminated paper poster,19 (2) a tool kit integrated
with the electronic health record (EHR),13 and (3) an electronic bedside screen (e-bedside) display.20

From September 2014 to September 2015, unit staff were involved in developing, refining, and
piloting the intervention, testing its association with patient activation in the fall-prevention plan
(phases 1-5 above and Figure 1) and selecting the modality they would implement. At the end of this
period, the laminated paper poster and the refined EHR-integrated tool kit modalities were
complete. The e-bedside display design was complete, but this modality required additional EHR
integration and was not available for implementation until October 1, 2016. Nine units chose to
implement the laminated paper poster, 2 chose the EHR-integrated tool kit, and 3 chose the
e-bedside display modality. The goal of the trial was to assess whether a fall-prevention tool kit that
engages patients and families in the fall-prevention process throughout hospitalization is associated
with reduced falls and injurious falls.

Methods

Overall Design
This nonrandomized controlled trial (NCT02969343) used a stepped-wedge design (Figure 2). The
trial protocol is given in Supplement 1. Owing to active staff engagement in the problem analysis, design,
development, pilot implementation, and evaluation phases (Figure 1), data from these phases were
not included in the analysis. Each unit served as its own control. Randomization of unit start dates was
not done for practical reasons, including constraints in unit operations owing to pending go-live dates
of new EHR systems at all 3 hospitals and other concurrent projects. The research team assigned start
dates to each unit based on the Fall TIPS modality selected, and these constraints (ie, EHR modalities)
were tied to EHR go-live dates. Regardless of start date, each unit contributed 21 weeks of
preintervention data and was followed up for 21 weeks after a 2-month implementation and wash-in

Figure 2. Nonrandomized Stepped-Wedge Design for Fall Tailoring Interventions for Patient Safety (TIPS) Implementation by Modality

Site 2/1 unita

Site 1/2 unitsc

Site 1/2 unitsc

Site 1/3 unitsc

Site 1/2 unitsc

Site 1/3 unitsd

Site 3/1 unita

Preintervention period (21 mo)

Dec 2012-Sep 2014

Dec 2012-Sep 2014

Dec 2012-Sep 2014

Dec 2012-Sep 2014

Dec 2012-Sep 2014

Dec 2012-Sep 2014

Dec 2012-Sep 2014 Sep 2014-Nov 2015

Sep 2014-Jan 2016

Sep 2014-Feb 2016

Sep 2014-Apr 2016

Sep 2014-Jun 2016

Sep 2014-Dec 2016

Sep 2014-Jan 2017

Postintervention period (21 mo)

Intervention development/refinement/piloting period

Nov 2015-Aug 2017

Jan 2016-Oct 2017

Feb 2016-Nov 2017

Apr 2016-Jan 2018

Jun 2016-Mar 2018

Dec 2016-Sep 2018

Jan 2017-Oct 2018

b

b

b

b

b

b

b

Problem analysis, design, development, pilot implementation, and evaluation periods
were inserted into the interrupted time-series analysis to account for potential
confounders associated with developing the intervention. Start dates were assigned to
each unit based on the selected Fall TIPS modality and unit-based constraints. Regardless
of start date, each unit contributed 21 weeks of preintervention data and was followed
up for 21 weeks after a 2-month implementation and wash-in period.

a Electronic health record.
b Two-month implementation and wash-in period.
c Laminated paper poster.
d Electronic bedside display.

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period (Figure 2). The study was approved by the Partners HealthCare Human Subjects Committee
of Brigham and Women’s Hospital, the Human Research Protection Office of Columbia University, and
the Montefiore Einstein Office of Clinical Trials. Owing to the quality-improvement nature of the
intervention, a waiver of informed consent was granted by the institutional review boards of Brigham
and Women’s Hospital, New York–Presbyterian, and Montefiore Medical Center. The study followed
the Transparent Reporting of Evaluations With Nonrandomized Designs (TREND) reporting guideline.22

Unit Selection and Participants
An interrupted time-series evaluation of the patient-centered Fall TIPS tool kit was conducted among
37 231 patients in 14 adult medical units in 3 academic medical centers: site 1 (Boston,
Massachusetts), site 2 (Bronx, New York), and site 3 (New York, New York) between November 1,
2015, and October 31, 2018. The purpose was to evaluate the tool kit’s effectiveness and compare the
rates of falls and falls with injury from a 21-month preintervention period and a 21-month
postintervention period (Figure 2). Site 1 agreed to implement Fall TIPS in all 12 medical units. Sites 2
and 3 each agreed to implement Fall TIPS in 1 acute care medical unit with rates of falls and injuries
that were above average for their institutions.

Study Design and Intervention
In collaboration with unit leadership, the study team assigned the month when the intervention
would go live between September 2015 and November 2016 based on the modality selected and
associated constraints (Figure 2). Previous testing revealed that all modalities were effective in
facilitating patient engagement in the 3-step fall-prevention process.20 An 11-by-17-inch laminated
Fall TIPS poster was displayed at the bedside and used color-coded clinical decision support to link
the Morse Fall Scale9 risk factors to evidence-based interventions. Nurses completed the poster with
a dry-erase marker at admission and during each shift with the patient and family (if available) and
posted it at the bedside. Using the Fall TIPS EHR-integrated tool kit, nurses identified patient-specific
risk factors using the Morse Fall Scale,9 and clinical decision support automatically linked each risk
factor with the appropriate preventive interventions. Nurses could further tailor prevention plans
based on their knowledge of the patient. Once completed, posters (8.5 × 11 in) detailing the risk
factors and fall-prevention plan were generated and printed from the EHR system, hung at the
bedside (sites 2 and 3), or automatically displayed on the bedside computer screensaver (e-bedside
display, site 1) and reviewed with the patient and family at admission and during each shift.

Methods for stakeholder engagement and implementation in study units are described
elsewhere.19 In brief, study staff engaged leadership at institutional and care-unit levels through
presentations on the evidence supporting Fall TIPS. We used a peer-champion model of existing unit-
based nursing staff for education and training.19 Nurse champions who completed competency
training were involved in continuous engagement of staff nurses, monitoring of fidelity, and
reinforcement, with the intention of successful integration of the intervention into practice.19 Study
staff visited study units to provide training during the go-live week.19 Unit-based nurse champions
measured adherence to the protocol with patient engagement audits consisting of 3 questions: (1) Is
the Fall TIPS poster updated with the correct patient information? (2) Can the patient/family express
their fall risk factors? and (3) Can the patient/family express their fall-prevention plan? Based on
continuous feedback from unit champions, barriers to adoption and spread were addressed.19 After
the go-live date, nurse champions completed 5 random audits per month and provided peer
feedback to the nurses caring for the audited patients.

Outcomes
The primary outcome measure was the overall rate of patient falls per 1000 patient-days during the
study period. The overall rate of falls with injury per 1000 patient-days was the secondary outcome.
Data on falls and resulting injury levels are routinely recorded in an event reporting system at all
participating hospitals and were used in the analysis.

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Statistical Analysis
The association between the intervention and the rate of patient falls and falls with injury per 1000
patient-days on the unit was analyzed using Poisson regression (for rates) estimated with
overdispersion via generalized estimating equations to account for clustering within a unit using an
exchangeable correlation for patients within the same unit. In the Poisson regression models, we fit
segmented lines for the 2 periods (before and after intervention) to test for the statistical significance
of observed changes in the fall rates in the interrupted time series associated with the intervention.
In the Poisson regression model for rates with clustering by unit, we adjusted for the following
patient-level characteristics: sex (as classified in the EHR), race/ethnicity, insurance (public or
private), age at admission, and binary Charlson Comorbidity Index score (0-1 or �2). For the Poisson
regression parameters to be interpreted as log rate ratios, unit length of stay was used as an offset
term with Poisson modeling.

In a secondary analysis to assess whether the changes before vs after intervention differed by
age group (younger than 65 years vs 65 years or older), we fit the adjusted Poisson regression model
for rates with an interaction between age group and period. In another secondary analysis to assess
whether the changes from before the intervention to after the intervention differed by site, we fit the
adjusted Poisson regression model for rates with an interaction between site and period.

Patient characteristics in the 2 periods are presented as means for continuous variables and
proportions for categorical variables. Balance in patient characteristics in the 2 periods was assessed
using standardized differences. All analyses used the intention-to-treat principle. Statistical
significance was set at P < .05 using a 2-sided test. We used SAS statistical software, version 9.4 (SAS
Institute), for the analyses.23,24

Results

The study included 37 231 patients and 277 655 patient-days; 17 948 patients were included in the
preintervention period and 19 283 in the postintervention period (Table). Patients in both periods
were similar regarding age, sex, race/ethnicity, primary insurance type, hospital and unit length of
stay, and Charlson Comorbidity Index score at admission. A total of 9723 (54.17%) patients during the

Table. Patient Characteristics and Standardized Differences Before and After Implementation of the Fall TIPS
Tool Kit Intervention

Characteristics
Before the
intervention, No.

After the
intervention, No.

Standardized
difference (%)a

Patient-days, No. 135 163 142 492 NA

Patients, No. 17 948 19 283 NA

Hospital length of stay, mean (SD) 7.53 (9.04) 7.39 (10.03) 1.47

Unit length of stay, mean (SD) 5.86 (6.07) 5.88 (7.45) –0.29

Age, mean (SD) 60.56 (18.30) 60.92 (18.10) –1.98

Women, No. (%) 9723 (54.17) 10 325 (53.54) 1.26

Race/ethnicity, No. (%)

White 9760 (62.57) 10 521 (60.17) 4.93

Otherb 5843 (37.46) 6971 (39.87) –4.93

Missing 2349 1797 NA

Primary insurance, No. (%)

Public 12 455 (70.84) 12 754 (70.14) 1.53

Private 5126 (29.16) 5429 (29.86) –1.53

Missing 285 1797 NA

Total Charlson Comorbidity Index score
at admission, No. (%)

0-1 8039 (44.79) 7953 (41.25) 7.15

≥2 9909 (55.21) 11 328 (58.75) –7.15

Missing 0 2 NA

Abbreviatons: NA, not applicable; TIPS, Tailoring
Interventions for Patient Safety.
a Standardized differences with absolute values of less

than 10% reflect well-balanced covariates
across periods.23

b Other included Black, Asian, and Native American.

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preintervention period and 10 325 (53.54%) during the postintervention period were women, and
9760 (62.57%) patients during the preintervention and 10 521 (60.17%) during the postintervention
period were White. The mean (SD) age of patients was 60.56 (18.30) years in the preintervention
period and 60.92 (18.10) years in the postintervention period. The mean (SD) hospital length of stay
was 7.53 (9.04) days in the preintervention period and 7.39 (10.03) days in the postintervention
period. All standardized differences comparing demographics across periods were less than 10%
(Table), suggesting that the demographics were well balanced over periods.23,24 Nevertheless, to
protect against possible confounding, we adjusted for all demographics in the interrupted time-
series analyses. There were no statistically significant trends from month to month within the
preintervention or postintervention periods in relation to falls or falls with injury. Therefore, we
compared adjusted rates across the preintervention and postintervention periods. After Fall TIPS
implementation, site 1 had a mean compliance rate of 86% on the 3-question audit, and sites 2 and 3
had mean compliance rates greater than 95%. This translated into a clinically significant patient-
centered Fall TIPS intervention in all study units.20

In the adjusted analysis, the overall fall rate in study units decreased from 2.92 falls per 1000
patient-days (95% CI, 2.53-3.36 falls per 1000 patient-days) before implementation to 2.49 falls per
1000 patient-days (95% CI, 2.06-3.0 falls per 1000 patient-days) in the postintervention period.
After adjustment for demographics in the Poisson regression model, study units using the patient-
centered Fall TIPS tool kit achieved a 15% reduction in patient falls in the postintervention period
(adjusted rate ratio [RR], 0.85; 95% CI, 0.75-0.96; P = .01). In the subanalysis by age, the decrease in
falls was largest for patients younger than 65 years; units achieved an 18% reduction in patient falls
in this age group in the postintervention period (adjusted RR, 0.82; 95% CI, 0.70-0.97; P = .02) vs a
10% reduction for patients age 65 and older (adjusted RR, 0.90; 95% CI, 0.74-1.09; P = .28), with
the latter difference not being statistically significant.

In the adjusted analysis, the overall injurious fall rate in study units decreased from 0.73
injurious falls per 1000 patient-days (95% CI, 0.59-0.92 falls per 1000 patient-days) before
implementation to 0.48 injurious falls per 1000 patient-days (95% CI, 0.34-0.70 falls per 1000
patient-days) in the postintervention period. After adjustment for demographics in the Poisson
regression model, study units achieved a 34% reduction in overall falls with injury in the
postintervention period (adjusted RR, 0.66; 95% CI, 0.53-0.88; P = .003). The rate ratios for falls
and injurious falls before and after the intervention are shown in Figure 3. In the subanalysis by age,
the decrease in injurious falls was largest for patients aged 65 years or older, among whom units
achieved a 48% reduction in the postintervention period (adjusted RR, 0.52; 95% CI, 0.34-0.82;
P = .004) vs a 19% reduction for patients younger than 65 (adjusted RR, 0.81; 95% CI, 0.54-1.19;
P = .28), with the latter difference not being statistically significant.

Figure 3. Adjusted Rate Ratios of Falls and Injurious Falls by Site Before vs After Fall Tailoring Interventions for Patient Safety (TIPS) Intervention

P value
Favors

fall TIPS
Favors
usual care

0.5 21
Adjusted rate ratio (95% CI)

Adjusted rate
ratio (95% CI)

FallsA

.01Overall 0.85 (0.75-0.96)

.16Site 1 0.88 (0.74-1.05)

.13Site 2 0.81 (0.62-1.06)

.21Site 3 0.83 (0.63-1.11)

P value
Favors

fall TIPS
Favors
usual care

Adjusted rate
ratio (95% CI)

Injurious fallsB

.01Overall 0.66 (0.49-0.89)

.01Site 1 0.58 (0.38-0.89)

.25Site 2 0.69 (0.36-1.31)

.96Site 3 0.97 (0.44-2.18)

310.2
Adjusted rate ratio (95% CI)

The adjusted rate ratios were obtained from a Poisson regression model with
overdispersion and clustering by unit, adjusted for the following patient-level
characteristics: sex, race/ethnicity, insurance (public vs private), age at admission, and

binary Charlson comorbidity score (0-1; �2). Unit length-of-stay was used as an offset
term with Poisson modeling so rates could be interpreted as events per patient length
of stay.

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Discussion

We evaluated a nurse-led intervention focused on engaging patients and families with the care team
at 3 institutions and found that the intervention was associated with overall reduced rates of falls
and fall-related injuries. Previous quality improvement studies25-27 have shown a reduction in injuries
but not in acute-care units in multiple geographic locations. This study suggests that hospital-based
fall-prevention interventions are associated with reduced rates of falls when they routinely engage
patients and families in the fall-prevention plan.

These findings build on research supporting patient engagement in safety initiatives, which has
been associated with improved quality, safety, patient experience, and empowerment.28,29 Patients
are prepared to carry out specific and actionable interventions recommended by health care
professionals when they are engaged in the process.30,31 As shown in previous work,20,21 both high-
tech and low-tech tools can facilitate patient engagement in the fall-prevention plan. Patient
engagement in the 3-step fall-prevention process results in a partnership between the patient and
care team and strengthens the Fall TIPS tool kit13 intervention.

In the subanalysis, we found that the intervention was associated with reduced falls in younger
patients and with reduced fall-related injuries in older patients. These results differ from another
evaluation,13 in which the tool kit was associated with reduced falls in older patients and there was no
difference in the injurious fall rate. Interviews with younger patients revealed that they did not
believe that they were at risk for falls in the hospital, especially those who were independent at
home.32 We refined the tool kit to improve patient engagement in the 3-step fall-prevention process.
Our rationale was that if patients were included in risk assessment and the development of their
prevention plan, they would be more likely to believe that they are at risk for falls in the hospital and
perhaps more likely to follow their prevention plan. The findings suggest that engaging patients in
the fall-prevention process is important because this simple practice was associated with fewer falls
among younger patients and substantially fewer fall-related injuries among older patients—those at
greatest risk of injury.

Strengths and Limitations
This study has strengths. Inclusion of 3 academic medical centers with many patients and different
patient populations enhanced the generalizability of the Fall TIPS tool kit. Engagement of leadership
at both the institutional and care-unit levels was important for the integration of the intervention
into practice. Fidelity was high owing to unit champions and staff nurse engagement through
continuous monitoring and peer feedback. Unit-based nurse champions had a key role in discovering
and addressing barriers to use of the tool kit, which proved to be vital to the success and
sustainability of the intervention.

This study also has limitations. There are challenges to conducting pragmatic studies that engage
stakeholders in intervention development in complex clinical settings. Despite evidence that participa-
tory design and development with end users strengthen interventions, they also make quantifying the
association between the intervention and a reduction in falls more difficult.33 Methods in the early
phases of this project included extensive clinician and patient involvement in developing, refining, and
pilot testing the patient-centered Fall TIPS tool kit (Figure 1). Iteratively changing processes could have
impacted practice and outcomes. To account for this, we evaluated the intervention using an inter-
rupted time series design and removed the problem analysis, design, development, and pilot imple-
mentation phases that began before the first prototypes of the Fall TIPS tool kit were developed and
extended until the Fall TIPS tool kit modalities’ design was complete. We included a wash-in period 2
months after going live in each study unit. This was the time it took nurses on clinical units to fully inte-
grate the tool kit and consistently submit compliance audits.

We assessed the effectiveness of the patient-centered Fall TIPS tool kit within existing
institutional infrastructures and workflows. One limitation is that support from hospital leadership
and unit champions, communication channels, timing of implementation, and nurse and patient

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adherence to the protocol were variables that could not be fully controlled. We had originally planned
to randomize the go-live dates for site 2 (Supplement 1), but the decision to implement a new EHR
at each site after the start of the study and the decision to allow clinicians to select the Fall TIPS
modality that best fit unit workflow limited the ability to randomize. Although the study design did
not allow for perfect comparability, it revealed valuable information about the generalizability of the
tool kit and its effectiveness in diverse, real-world acute care environments for a relatively long
duration (21 months). Although the multisite evaluation is a strength of the study, limiting the
evaluation to a single unit at sites 2 and 3 is a limitation. A larger evaluation is needed to fully evaluate
generalizability. We acknowledge that there are overlapping 95% CIs in the secondary analyses by
site and age. However, examining the overlap between 95% CIs is a conservative approach to testing
whether 2 groups are significantly different (compared with the P value for testing for differences in
2 groups). Others have shown that if the two 95% CIs overlap, it does not mean that the 2 groups are
not significantly different.34,35

Conclusions

In this nonrandomized controlled trial, implementation of a nurse-led, patient-centered fall-
prevention tool kit was associated with reduced rates of falls and injurious falls. The fall-prevention
tool kit helped link patient-specific risk factors to interventions most likely to prevent a fall.20 Various
modalities of the tool kit allow for integration into existing clinical workflows in diverse hospital
settings. This tool kit appears to addresses the gap among nursing assessment of fall risk, tailored fall-
prevention interventions, and engagement of patients throughout the fall-prevention process.13,36

ARTICLE INFORMATION
Accepted for Publication: September 18, 2020.

Published: November 17, 2020. doi:10.1001/jamanetworkopen.2020.25889

Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2020 Dykes PC
et al. JAMA Network Open.

Corresponding Author: Patricia C. Dykes, PhD, RN, Center for Patient Safety, Research and Practice, Division of
General and Internal Medicine and Primary Care, Brigham and Women’s Hospital, 1620 Tremont St, 3rd Floor,
Boston, MA 02120 ([email protected]).

Author Affiliations: Center for Patient Safety, Research and Practice, Division of General and Internal Medicine
and Primary Care, Brigham and Women’s Hospital, Boston, Massachusetts (Dykes, Burns, Lipsitz, Shaykevich,
Bates); Harvard Medical School, Harvard University, Boston, Massachusetts (Dykes, Lipsitz, Bates); School of
Nursing, Columbia University, New York, New York (Adelman, Carter); Columbia University Irving Medical
Center/New York–Presbyterian, New York, New York (Adelman, Carter); Institute of Healthcare Systems
Engineering, Boston, Massachusetts (Benneyan); Montefiore Medical Center Hospitals, Bronx, New York
(Bogaisky, Lindros, Scanlan); Kennesaw State University, Kennesaw, Georgia (Ergai).

Author Contributions: Drs Dykes and Lipsitz had full access to all of the data in the study and take responsibility
for the integrity of the data and the accuracy of the data analysis.

Concept and design: Dykes, Adelman, Ergai, Lindros, Lipsitz, Bates.

Acquisition, analysis, or interpretation of data: Dykes, Burns, Adelman, Benneyan, Bogaisky, Carter, Lipsitz,
Scanlan, Shaykevich, Bates.

Drafting of the manuscript: Dykes, Burns, Ergai, Lipsitz.

Critical revision of the manuscript for important intellectual content: Dykes, Burns, Adelman, Benneyan, Bogaisky,
Carter, Lindros, Lipsitz, Scanlan, Shaykevich, Bates.

Statistical analysis: Lipsitz, Shaykevich.

Obtained funding: Dykes, Carter.

Administrative, technical, or material support: Dykes, Burns, Adelman, Benneyan, Bogaisky, Scanlan.

Supervision: Dykes, Burns, Adelman, Lipsitz.

JAMA Network Open | Public Health Evaluation of a Patient-Centered Fall-Prevention Tool Kit

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Conflict of Interest Disclosures: Drs Dykes, Adelman, Benneyan, and Carter reported receiving grants from the
Agency for Healthcare Research and Quality (AHRQ) during the conduct of the study. Dr Bates reported receiving
grants from AHRQ during the conduct of the study and grants and personal fees from EarlySense; personal fees
from the Center for Digital Innovation–Negev; equity from Valera Health, CLEW, and MDClone; personal fees and
equity from AESOP; and grants from IBM Watson outside the submitted work. No other disclosures were reported.

Funding/Support: This study was funded by grant #P30HS023535 from the Agency for Healthcare Research
and Quality.

Role of the Funder/Sponsor: The AHRQ had no role in the design and conduct of the study; collection,
management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and
decision to submit the manuscript for publication.

Additional Contributions: We acknowledge the contributions of our collaborators at Northeastern University’s
Healthcare Systems Engineering Institute and the unit champions at sites 1, 2, and 3 for their role in implementing
and sustaining the Fall TIPS tool kit. Paul Bain, PhD, MLIS, at Countway Library of Medicine (an alliance of the
Harvard Medical School and Boston Medical Library) assisted with the literature review. None of the contributors
received financial compensation.

Data Sharing Statement: See Supplement 2.

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SUPPLEMENT 1.
Trial Protocol

SUPPLEMENT 2.
Data Sharing Statement

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healthcare

Article

Development and Effect of a Fall Prevention Program Based on
King’s Theory of Goal Attainment in Long-Term Care Hospitals:
An Experimental Study

Bom-Mi Park

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Citation: Park, B.-M. Development

and Effect of a Fall Prevention

Program Based on King’s Theory of

Goal Attainment in Long-Term Care

Hospitals: An Experimental Study.

Healthcare 2021, 9, 715. https://

doi.org/10.3390/healthcare9060715

Academic Editor: Nandu Goswami

Received: 14 April 2021

Accepted: 7 June 2021

Published: 10 June 2021

Publisher’s Note: MDPI stays neutral

with regard to jurisdictional claims in

published maps and institutional affil-

iations.

Copyright: © 2021 by the author.

Licensee MDPI, Basel, Switzerland.

This article is an open access article

distributed under the terms and

conditions of the Creative Commons

Attribution (CC BY) license (https://

creativecommons.org/licenses/by/

4.0/).

Department of Nursing, Konkuk University Glocal Campus, Chungju-si 27478, Korea; [email protected];
Tel.: +82-43-840-3960

Abstract: A fall prevention program based on King’s goal attainment theory was developed to verify
its effect on those in long-term care hospitals. The experiment was conducted at K Long-Term Care
Hospital in S city for eight weeks. The study employed 57 elderly patients and 58 nurses. The
program comprised an individual training conducted in a ward and hospital room for 20–30 min and
a group training held in a conference room for 60 min. Significance levels were analyzed at p < 0.05
via frequency analysis, descriptive statistics, independent sample t-test, χ2-test, Mann–Whitney’s U
test, Wilcoxon code rank test, and Cronbach’s α, and the clinical trial number was KCT0005908. In
the patient intervention group, fall prevention behavior and knowledge increased, and the fear of
falling decreased. Fall prevention behavior and knowledge increased in the nurse intervention group.
Patient and nurse interaction satisfaction also increased. In contrast, the number of falls and nurses’
burden did not decrease. The fall prevention program was verified via the interaction of personal,
interpersonal, and social systems. Thus, the patient’s fear of falling was reduced. Moreover, the
program was effective for the fall knowledge, interaction satisfaction, and fall prevention behavior of
both the patient and nurse.

Keywords: accidental falls; aged; goal; long-term care; patients

1. Introduction

In Korea, the elderly population aged 65 and above is expected to rapidly increase
from 14.9% in 2019 to 20.3% in 2025 and 46.5% in 2067. Moreover, the number of elderly
households aged 65 and above would increase 2.8-fold from 3,998,000 households (20.4%)
in 2017 to 11,058,000 (49.9%) in 2047 [1,2]. The average annual medical expense per person
(>65 years old) is 4,910,000 won, which is about three times higher than the annual average
medical expenses of 1,680,000 won, per applied population in 2019 [3].

Falls are a frequent problem observed in elderly patients in long-term care hospi-
tals [4,5]. They can cause psychological (e.g., fear of falling, anxiety, pain, and depression)
and physical problems [4]. Severe cases may lead to death [6]. Falls are a serious prob-
lem; they are the largest hospital accident category [7]. The World Health Organization
(WHO) reported that 646,000 people die each year from falls worldwide, and falls are most
commonly observed in the elderly over age 65 [8]. Falling experience in the elderly is a
serious sequela that lowers physical function, induces loss of daily life independence, and
limits physical, psychological, and social activities, ultimately lowering life quality [9].
Further, fear of falling may reduce daily activities and weaken muscles, leading to an
increased risk of falling [10]. Accordingly, the WHO reported that fall prevention programs
based on environmental factors of hospitals are effective for hospitalized patients with a
high risk of or previous experiences of falling [11]. Thus, various measures to standardize
nursing practices to prevent falls [12], improve work processes, and reduce environmental
restrictions [13] are necessary.

Healthcare 2021, 9, 715. https://doi.org/10.3390/healthcare9060715 https://www.mdpi.com/journal/healthcare

Healthcare 2021, 9, 715 2 of 21

Intrinsic factors such as weak lower extremities, falling experience, lack of gain/balance,
and visual field defects and extrinsic factors such as insufficient lighting high beds and
chairs. Inadequate assistive devices and improperly fitted shoes are highly corrected with
patient falls [14]. In particular, elderly patients who are admitted to long-term care hospi-
tals have difficulties in moving due to diseases that decrease cognitive function, such as
dementia or stroke [15]. Therefore, nurses are responsible for assessing fall risk factors for
elderly patients with high risk of falls and providing fall prevention care accordingly [16].

Nurses have the greatest effect on reducing the number of falls among patients [17]
since they directly interact with patients the most [14]. Nursing goals are achieved via
patient–nurse interactions; thus, effective interaction is an important tool for patient treat-
ment [18] and an essential condition for nurses to establish a therapeutic relationship with
patients [19]. Therefore, nurses must interact with patients and induce fall prevention
behaviors through repetitive fall prevention education programs, considering individual
circumstances, diseases, and medication status [9].

King’s goal attainment theory defines a process of interaction where patients and
nurses acknowledge each other, set goals, and agree on how to achieve them in fulfilling ex-
changes between patients and nurses [20]. The theory pivots on respect for patients. It is a
patient–nurse relationship that values information exchange, goal setting, and patient treat-
ment; thus, it requires a positive correlation between trust and patient satisfaction [20,21].
Moreover, it must include interactions that describe patient–nurse values and needs [20,21].
The theory posits a high probability of achieving goals when patients and nurses interact
and set goals together [20]. Such interactions allow patients to assume responsibility for
and actively participate in the proposed treatment for positive changes. Thus, the goal
attainment theory is a health strategy in nursing patients [22].

Recent studies on fall prevention programs include fall education [23,24], exercise
and pain control [25], and motivation and group discussions [26]. Goal attainment theory
has effectively reduced the number of falls in elderly patients at a high risk of falling [27].
However, 31% of falls and 47% of falls with injuries occur among patients [28]. Moreover,
those who overestimate and are not aware of their functional capacities have a high risk
of falling [29,30]. Studies have also shown that 12.3% of patients overestimate and forget
their functional levels [31]. In contrast, elderly patients at high risk of falling are more
aware of and cautious about the risk of falls [32]. Thus, a fall prevention program based on
King’s goal attainment theory where patients better understand their conditions [33] and
set behavior modification goals [34] via interactions with nurses is essential.

Many studies aim to prevent falls. However, only a few incorporate fall theory and
demonstrations, medication education, environmental management, motivation, and indi-
vidual repetitive education tailored to the personal circumstances of the elderly. Therefore,
this study developed a fall prevention program where patients and nurses set goals together
and actively participate. These observations provide the basis for an effective nursing inter-
vention program. Specifically, the study evaluates the program’s effects on (1) the fear of
falling, fall knowledge, fall prevention behavior, and the number of falls among the patient
groups; (2) the burden of falling, fall knowledge, and fall prevention behavior among nurse
groups; and (3) the interaction satisfaction between patients and nurses.

The conceptual framework was established based on King’s goal attainment theory
from a review of the relevant literature. First, perception is an individual’s experience
and image of reality, and an individual’s perception and judgment translate to actions
and responses. Second, current obstacles and problems, the setting of mutual goals, and
seeking and agreeing on how to achieve these goals are assessed via interactions. Third,
interactions through personal, interpersonal, and social systems lead to the achievement of
goals [35,36].

Patients and nurses acted via the perception and judgment processes. Actions in-
clude nurses’ suggestions for patients to participate in the program and patients’ positive
reactions to participation. Response refers to their agreeing to participate in the program.

Healthcare 2021, 9, 715 3 of 21

In the interaction system, disturbances or problematic factors during the program are
identified by assessing factors related to falls, interest in fall prevention, and relationships
with the surrounding environment. Mutual goal setting is performed by patients and nurses
who explore the situation together and share information. Exploration and agreement on
how to achieve goals comprise a discussion of the program methods. Individual education,
group education, individual counseling, and individual activities were performed to
achieve the goals.

Transaction refers to the interaction between patients and nurses through personal,
interpersonal, and social systems to achieve the goal of reducing the total number of falls
by reducing the fear of falling among patients and the burden of falling on the nurses while
increasing fall knowledge, interaction satisfaction, and fall prevention behaviors.

In this study, it is expected that a fall prevention program based on King’s goal achieve-
ment theory would reduce patients’ number of falls and fear of falling, and increase fall
knowledge, fall prevention behavior, and interaction satisfaction. In addition, it is ex-
pected that nurses’ burden of falling would be reduced, and fall knowledge, fall prevention
behaviors and interaction satisfaction would be increased.

2. Methods
2.1. Fall Prevention Program Based on King’s Goal Achievement Theory
2.1.1. Fall Prevention Program Contents

This study employed a goal attainment theory-based intervention program, developed
via a review of the literature on fall-related intervention programs for patients and nurses.
Figure 1 illustrates the relationship between the concepts of this study. The program was
offered once a week for eight weeks (comprising individual education, group education
for nurses only, and emotional support) to establish a mutual goal between the researchers
and both patients and nurses, respectively. Furthermore, the program comprised various
contents such as fall prevention education and demonstration, medication education,
environmental management, motivation, and repetitive individual education. The assessed
outcome variables included fear of falling, the burden of falling, fall knowledge, interaction
satisfaction, fall prevention behavior, and the number of patient falls (Table 1).

Healthcare 2021, 9, x 4 of 25

Figure 1. Conceptual framework of a fall prevention program on King’s goal attainment theory.

Figure 1. Conceptual framework of a fall prevention program on King’s goal attainment theory.

Healthcare 2021, 9, 715 4 of 21

Table 1. Basic principles and implementation schedule of the program based on King’s goal attainment theory.

King’s
Conceptual

System
King’s

Concept
Configuration

Element
Main Strategy Goal Intervention Content

Intervention Methods

Individual
Education

Group
Education

Individual
Counseling

Individual
Activities

Personal
system

Perception

Fear of falling

Problem
assessment

Knowledge and
information provision

Decreased fear
of falling among

patients

(1) Assessment of
problems related to falling among patients

(2) Understanding the fear of falling
• •

Burden of falling

Problem
assessment

Knowledge and
information provision

Reduced
burden of falling

among nurses

(1) Assessment of
problems related to falling regarding nurses

(2) Understanding the burden of falling
• •

Growth and
development Fall knowledge

Knowledge and
information provision

Improved fall
knowledge

(1) Understanding fall knowledge using guidelines and prints • •

Interpersonal
system

Communication

Interaction
satisfaction

Goal setting and
motivation

Knowledge and
information provision

Increased fall
prevention
behavior
through

communication

Increased
interaction
satisfaction

(1) Mutual goal setting to reduce the number of falls
(2) Assessment of

disturbance factors for fall prevention
(3) Education on fall prevention guidelines and demonstrations

(4) Feedback on
understanding after

education
(5) Mutual assessment of fall prevention checklist

(6) Fall prevention
education using the 5A method by the assigned nurse

7) Medication
education

• • •

Interaction

Social
System

Education
system

Fall
prevention
behavior

Improved
function and behavior

Improved fall
prevention
behavior

(1) Fall prevention
education for patients and nurses

(2) Fall prevention
education with

therapists and a nurse in charge of patient safety

• •

Social
support

Motivation and emotional
support

Enhanced
motivation

through
improved

social support

(1) Consultation and support for difficulties and concerns related to
falls among patients

(2) Consultation and support for difficulties and concerns related to
falls regarding nurses

(3) Supporting
continued participation for fall prevention

Group Intervention Method
Program Schedule (Weeks)

1 2 3 4 5 6 7 8

Intervention group

Individual education • • • • • • • •
Group education •

Individual counseling • • • • • • • •
Individual activities • •

Healthcare 2021, 9, 715 5 of 21

The personal system comprises the recognition of the importance of fall prevention,
personal growth, and development during the program. In this system, problems related
to falls among patients were assessed, and knowledge and information were provided
via individual education and counseling to reduce the fear of falling. Thus, to reduce the
burden of falling on nurses, problems related to falls among nurses were assessed, and
related knowledge and information were provided through individual education and
counseling. Moreover, knowledge and information were provided to patients and nurses
to improve their fall knowledge, and guidelines and handouts on fall prevention were
provided to improve fall knowledge cognition.

The interpersonal system was characterized as nurses and patients setting goals to-
gether and improving satisfaction with interaction via communication. Mutual goals were
set, and motivation was provided to improve interaction satisfaction among patients and
nurses and assess barriers to fall prevention. Further, related knowledge and information
were provided. Education and demonstrations of fall prevention guidelines were provided,
after which participants were required to reiterate their understanding. Patients and nurses
evaluated the fall prevention checklist, as education on fall prevention and medication
was provided.

Social systems are defined by repetitive fall education systems for patients and nurses
and improvement of fall prevention behaviors via social support from researchers and
nurses. Fall prevention education was provided to patients and nurses to improve their
abilities and behaviors. Physiotherapists and nurses in charge of patient safety provided
fall prevention education. Counseling and support on challenges and concerns about falls
were provided to patients, and continuous participation was encouraged for fall prevention
to motivate and provide emotional support to nurses to induce fall prevention behaviors.

Fall prevention guidelines and checklists were created by selecting necessary items
from the Fall Prevention Guideline by the US Health Care Improvement Organization [37],
certification survey standard collection of long-term care hospitals by the Korea Institute
for Healthcare Accreditation [38], and safety assurance activities of the 1st Comprehen-
sive Patient Safety Plan proposed by the Ministry of Health and Welfare [39] to suit the
characteristics of long-term care hospitals. The items were then reviewed and verified by a
member of the certification evaluation survey of long-term care hospitals, a rehabilitation
medicine specialist, and two physiotherapists. The fall prevention program was reviewed
and verified by a nursing college professor, an individual in charge of patient safety, and
six head nurses.

A. Individual education

The patients were vacant from the hospital room for 30–120 min in the morning and
afternoon for rehabilitation treatment. Therefore, each patient’s schedule was checked
with the patient or caregiver to organize individual patient schedules before the study.
Individual training was provided in the hospital room for 20–30 min before and after the
rehabilitation treatment.

Individual education was provided once a week for eight weeks. Six (two) sessions
were conducted by the researcher (nurse in charge). Individual education to nurses was
provided by the researcher once a week for seven weeks. The nurses worked in three
shifts. Thus, their schedule was organized for eight weeks by checking the researcher’s
shift schedule. For nurses with day, evening, and night shifts, the researcher provided
education after the shift, before the shift or in the evening, and in the morning after shift,
respectively, for 20–30 min.

Individual education for nurses was provided seven times. The goal was to provide
individual education to ten patients and ten nurses every day. However, in cases where
the patients and nurses were not available due to schedule conflicts, individual education
was provided on weekends (Table 1).

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B. Group education

Group education was provided only to nurses in the evening of the second week
for one session of 60 min in a conference room of the hospital, where demonstrations
were provided. The session was provided by a nurse in charge of patient safety and two
rehabilitation therapists. After the education and demonstrations for fall prevention by
therapists, two nurses teamed up to practice. Chairs and braces were prepared in advance
such that 19 nurses could practice immediately after training. Individual feedback was
provided to each nurse team by a rehabilitation therapist. For six nurses with evening
shifts and five nurses who could not participate, the researcher was permitted to film the
demonstrations by the rehabilitation therapists to provide individual education. In the
wards, videos were shown individually to the nurses, and they practiced with chairs and
braces in pairs with the researcher.

C. Individual counseling

In the first week of individual counseling, fall-related problems were checked by
nurses, and sessions were held weekly during individual education. Challenges and
concerns about fall behaviors were mostly consulted and, in weeks 5 and 6, the interaction
importance was emphasized for encouragement and support.

D. Individual activities

In weeks 5 and 6, individual activities were conducted for assigned patient–nurse
interactions. Such interactions without the researcher are vital for fall prevention behaviors
beyond the 8-week period. Thus, the nurses who received individual education from the
researcher provided the same education to the assigned patients.

In week 5, the nurses were asked to practice the 5A (Ask-Advise-Assess-Assist-
Arrange) method of the Clinical Guidelines for Smoking Cessation, published by the
US Public Health Service [40], on the assigned patients via effective communication. First,
the nurses “asked” the patients questions regarding falls. Second, the nurses provided
clear information and brief and personalized “advice” on the risk factors of falls. Third,
personal relevance to the risk and prevention of all patients was “assessed.” Fourth, confi-
dence in planning for change, acquiring behavioral skills, and success in preventing falls
was provided whenever “assistance” was needed. Finally, the fall prevention behavior of
patients was supported and encouraged in the “arrange” stage.

In week 6, the efficacy and side effects of medications were explained by the nurses to
the assigned patients; they were educated on their importance and danger. Further, the
nurses provided fall prevention education and demonstrations to assigned patients, in
which patients directed their questions to the nurses. A grape sticker was provided if no
fall was observed every week, and after eight weeks, a gift (a towel set) was provided to
the patients who acquired a grape sticker for all eight weeks (Table 1).

2.1.2. Weekly Themes and Goals of the Fall Prevention Program

The theme of the first week was “reducing fear and burden of falling,” and the goal
was “identifying fall problems and setting goals.” The patients and nurses shared their fear
and burden of falling based on direct and indirect experiences, and they sympathized with
the necessity of preventing falls and setting mutual goals.

The theme of weeks 2 to 4 was “improvement of fall knowledge,” and the goals were
“understanding and practicing fall prevention education” and “solving problems after
individualized fall prevention education.” Education on fall prevention guidelines and
checklists was conducted individually and in groups.

The theme of weeks 5 and 6 was “interaction,” with a goal of “promoting fall preven-
tion through interaction.” The nurses provided individual education on fall prevention,
efficacy, and side effects of medications via the 5As based on the education they received
from the researcher. The patients were educated to be aware of hypertension, diabetes,
dysuria, and anti-psychotics, which are high-risk factors for falls.

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The theme of weeks 7 and 8 was “improvement of fall prevention behavior,” with
the goal of “improved execution through individualized fall education.” The researchers
held a discussion with patients and nurses and compared well-executed fall prevention
behaviors to those otherwise to improve the practice of fall prevention behaviors.

2.2. Verification of the Effects of the Fall Prevention Program Based on King’s Goal
Attainment Theory
2.2.1. Design

The non-equivalent control group (pre- and post-test study) was conducted at K long-
term care hospital, located in S city, for eight weeks from 12 July 2019 to 5 September 2019.
The study comprised 57 elderly patients (27 and 30 in the intervention and control groups,
respectively) and 58 nurses (28 and 30 in the intervention and control groups, respectively).

In the control group, the conventional fall prevention program (patient fall prevention
education after hospitalization, periodic evaluation of patient falls, quarterly multidisci-
plinary team meetings on fall, fall prevention announcements before bedtime, notification
announcements in cases of falls, fall prevention rounds, posting status on fall accidents,
and improvement plans) were provided.

2.2.2. Participants and Sampling Method

In this study, patients and nurses were recruited from elderly long-term care hospitals
in Seoul, South Korea, with more than 300 beds. The study was explained to the participants,
and those who wished to participate in the program after the explanation were selected.
Thus, to prevent the diffusion of treatments in the control and intervention groups, the
floor separation intervention study by Krauss et al. [41] was used as a reference.

The second (fourth) and third (fifth) floors were grouped together, and a nurse ran-
domly allocated the floors to intervention and control groups in blinded settings. Within
the hospital, patients are restricted from moving without caregivers or family members,
who can only move to the first floor, patient floors, and rehabilitation treatment floor with
an access card. Thus, a slight possibility of treatment diffusion existed. As the patients
underwent 1:1 rehabilitation treatment with a therapist, conversations between patients
were challenging. The nurses also conducted their shifts in the corresponding ward with
little interaction between different floors.

The minimum sample size was calculated using the G*power 3.1(Kiel University, Kiel,
Germany.) [42]. It was based on the effect size of (d) = 1.20, following a similar study by
Jung and Kim [43], where the goal attainment theory was applied. With a significance
level (α) = 0.05, power (1-β) = 0.80, and effect size (d) = 0.08, the minimum sample size
for both groups was 21 and, given possible withdrawals, 30, which is 1.4 times greater
than the required size selected for each group. Three patients who were unwilling or could
not answer the questionnaire due to poor health were excluded; thus, 27 and 30 patients
were included in the intervention and control groups, respectively. Two nurses on night
shifts could not continue their part in the study and, thus, were excluded. Therefore, 28
and 30 nurses were included in the intervention and control groups, respectively. Figure 2
presents a flowchart of the study.

Patient selection criteria included the following: (a) those who understood the purpose
of the study and agreed to participate, (b) those whose legal guardian consented to the study,
and (c) those who communicated with nurses and complete the survey questionnaires.
Those expected to be discharged during the intervention period were excluded. The
selection criteria for nurses were those who understood the purpose of this study and
agreed to participate.

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Healthcare 2021, 9, x 10 of 25

Figure 2. Flow chart of the study.

Figure 2. Flow chart of the study.

Data collections was conducted by 2 researchers and the collection was conducted at
the start of the intervention and 8 weeks after the intervention.

2.2.3. Research Tools
Patients

Fear of falling. To measure the fear of falling, a tool developed by Tinetti et al. [44],
adapted by Jang [45], and modified by Kim [46] was used. The tool consists of 10 items,

Healthcare 2021, 9, 715 9 of 21

and the total score ranges from 10 to 100 points. A higher score indicated a greater fear
of falling. In this study, the mean value was calculated by dividing the total score by the
number of items for unity by the other item scores.

Fall knowledge. A tool developed by Kim [47] and modified by Kim [48] was used to
measure fall knowledge. The total score ranged from 0 to 15, with higher scores indicating
greater fall knowledge.

Interaction satisfaction. A tool developed by Lim and Kwon [49] and modified by
Kim [50] was used to measure interaction satisfaction. It comprised nine items, evaluated
on a 5-point Likert scale; a higher score indicated greater interaction satisfaction.

Fall prevention behavior. A tool developed by Kim [48] for hospitalized elderly pa-
tients was used to assess fall prevention behaviors. The tool comprised 10 questions,
evaluated on a 5-point Likert scale, with a higher score indicating a higher level of fall
prevention behaviors.

Nurses

Burden of falling. A tool developed by Kim and Kim [51] was used to measure the
burden of falling. This tool comprised 16 items, evaluated on a 4-point Likert scale, with a
higher score indicating a greater burden of falling.

Fall knowledge. A tool developed by Kim [47] and modified and complemented by
Kim and Seo [52] was used to measure fall knowledge. It comprised 16 items, and the total
score ranged from 0 to 16 points. A higher point indicated greater fall knowledge.

Interaction satisfaction. A tool developed by Lim and Kwon [49] and modified and
complemented by Kim [50] was used to measure interaction satisfaction. It comprised
nine items, evaluated on a 5-point Likert scale, with a higher score indicating greater
interaction satisfaction.

Fall prevention behavior. Kim [48] developed a tool for hospitalized elderly patients,
modified and complemented by Kim and Seo [52], for nurses in hospitals for the elderly
to assess fall prevention behaviors. The tool comprised 13 items, evaluated on a 5-point
Likert scale, with a higher score indicating a higher level of fall prevention behaviors.

2.2.4. Data Analysis

The data were analyzed using SPSS 25.0. Frequency analysis on categorical variables
assessed the general and disease-related characteristics of patients and general characteris-
tics of nurses. Descriptive statistics were employed for continuous variables. Independent
sample t-tests and χ2 tests were performed to verify the differences between the general
and disease-related characteristics of patients and the general characteristics of nurses.
Skewness and kurtosis determined whether the data satisfied the normality assumption,
and a non-parametric statistical analysis was performed when skewness and kurtosis
were less than two and absolute values of seven, respectively. The Mann–Whitney test
was conducted to gauge the differences in the number of falls between the groups, and
Wilcoxon’s signed-rank test was performed to gauge the difference in the pre- and post-test
number of falls. Cronbach’s α assessed the tools’ reliability, and the statistical significance
level was p < 0.05. An independent sample t-test assessed pre-test homogeneity, post-test
differences, and differences in the amount of change between the groups for fear of falling,
fall knowledge, interaction satisfaction, and fall prevention behavior of patients, as well as
the burden of falling, fall knowledge, interaction satisfaction, and fall prevention behavior
of nurses. A paired t-test assessed whether post-test changes in the outcome variables
regarding patients and nurses were significant relative to pre-test values.

2.2.5. Ethical Considerations

This study was conducted for eight weeks after approval from the Institutional Review
Board, Korea University (KUIRB-2019-0159-01) in Seoul, South Korea. The author received
the clinical trial number (KCT0005908) from the Clinical Research Information Service in
Seoul, South Korea. Prior to the start of the program, the objectives and procedures of the

Healthcare 2021, 9, 715 10 of 21

study were explained to the participants, and both oral and written consent were obtained.
Small compensation was provided to the study participants. Consent was obtained from
patients, legal guardians, and nurses in both control and intervention groups, and written
consent included information on the purpose, necessity, expected effects, participation
period, study procedure, and emergency response methods for vulnerable participants.
Moreover, the consent noted that the collected data would not be used for purposes
other than the study, and the participants would be coded in numbers for confidentiality.
Moreover, the participants were informed that the study could be withdrawn at any time.
In the control group, information regarding the fall prevention program was provided after
the study was completed, and a fall prevention program was offered to those participants
who wished to participate. All tools in this study were used after obtaining approval from
the original authors.

3. Results
3.1. General and Disease-Related Characteristics
3.1.1. Patients

There were 27 and 30 patients in the control and intervention groups, respectively.
Among the general and disease-related characteristics of patients, there was a significant
difference only in the informative past education programs. However, the number of
patients with education experience was too small, and there were no significant differences
between the groups for other variables (Table 2).

3.1.2. Nurses

There were 28 and 30 nurses in the intervention and control groups, respectively.
There were no significant differences between the groups, except for the age and falling
experience of the assigned patients (Table 2).

3.2. Pre-Test Homogeneity Test for Study Variables
3.2.1. Patients

The number of falls, fall prevention behavior, interaction satisfaction, fall knowledge,
and fear of falling did not significantly differ between the two groups of patients (Table 2).

3.2.2. Nurses

Fall prevention behavior, interaction satisfaction, fall knowledge, and burden of falling
were not significantly different between the two groups of nurses (Table 2).

3.3. Effects of the Fall Prevention Program
3.3.1. Patients’ Number of Falls, Fall Prevention Behavior, Fall Knowledge, and Fear
of Falling

The number of falls decreased from three to two after the intervention. In the control
group, the number of falls increased from three to five; however, the number of falls was
not significantly lower in the intervention group than in the control group (Z = −0.98,
p = 0.326).

The mean fall prevention behavior increased from 2.38 to 3.83 after the intervention in
the intervention group. The control group saw a 2.60 to 2.38 decrease. Thus, fall prevention
behavior in the intervention group significantly increased relative to that in the control
group (t = −11.66, p < 0.001). Fall knowledge increased from 6.89% to 13.41% after the
intervention. The control group saw a slight increase from 8.13 to 8.27. Thus, fall knowledge
in the intervention group significantly increased relative to that in the control group
(t = −6.57, p < 0.001).

Fear of falling decreased from 6.34 to 1.91 after the intervention. In the control group,
the fear of falling decreased from 6.34 to 5.91. Thus, the reduction was significant in the
intervention group relative to the control group (t = 5.58, p < 0.001) (Table 3).

Healthcare 2021, 9, 715 11 of 21

Table 2. Pre-test homogeneity test of general and disease-related characteristics between patients and nurses in the control and intervention groups.

Variable Classification
Patient Intervention

Group (n = 27)
Mean ± SD or

Number (%) or Cases

Patient Control
Group (n = 30)
Mean ± SD or

Number (%) or Cases
Total χ2/Z/t p

Age 78.78 ± 9.50 78.77 ± 10.58 78.77 ± 9.99 0.00 0.997
Number of days in the hospital 583.52 ± 444.28 376.60 ± 349.08 474.61 ± 406.95 1.97 0.054

Sex
Female 18 (66.7) 19 (63.3) 37 (64.9)

0.07 0.792Male 9 (33.3) 11 (36.7) 20 (35.1)

Educational level

Elementary school 6 (22.2) 8 (26.7) 14 (24.6)

0.62 0.961
Middle school 5 (18.5) 4 (13.3) 9 (15.8)
High school 5 (18.5) 5 (16.7) 10 (17.5)

Professional school 1 (3.7) 2 (6.7) 3 (5.3)
College and above 10 (37.0) 11 (36.7) 21 (36.8)

Fall experience in the past year
Yes 5 (18.5%) 8 (26.7%) 13 (22.8%)

0.66 0.513No 22 (81.5%) 22 (73.3%) 44 (71.2%)

Experience of fall prevention
education in the past year

Yes 5 (18.5) 6 (20.0) 11 (19.3) 0.02 0.887
No 22 (81.5) 24 (80.0) 46 (80.7)

How informative was the
education session

Very helpful 0 (0.0) 5 (83.3) 5 (45.5)
7.77 0.026Helpful 4 (80.0) 1 (16.7) 5 (45.5)

Not helpful 1 (20.0) 0 (0.0) 1(9.1)

Diagnosis

Cerebrovascular disease 22 (81.5) 26 (86.7) 48 (84.2) 0.29 0.592
Parkinson’s disease 3 (11.1) 3 (10.0) 6 (10.5) 0.02 0.891

Dementia 15 (55.6) 23 (76.7) 38 (66.7) 2.85 0.091
Femur fracture 0 (0.0) 1 (3.3) 1 (1.8) 0.92 0.339

Others 3 (11.1) 0 (0.0) 3 (5.3) 3.52 0.061

Comorbidity

Hypertension 22 (81.5) 23 (76.7) 45 (78.9) 0.20 0.656
Diabetes 5 (18.5) 6 (20.0) 11 (19.3) 0.02 0.887

Cerebrovascular disease 24 (88.9) 27 (90.0) 51 (89.5) 0.02 0.891
Parkinson’s disease 4 (14.8) 4 (13.3) 8 (14.0) 0.02 0.872

Hemiparalysis 22 (81.5) 24 (80.0) 46 (80.7) 0.02 0.887
Paraplegia 3 (11.1) 0 (0.0) 3 (5.3) 3.52 0.061

Anti-psychotic medication
Yes 9 (33.3) 14 (46.7) 23 (40.4)

1.05 0.306No 18 (66.7) 16 (53.3) 34 (59.6)

MMSE 24.44 ± 4.10 23.97 ± 3.84 24.19 ± 3.93 0.46 0.651
MFS 50.19 ± 23.88 56.33 ± 21.49 53.42 ± 22.66 1.02 0.331

Healthcare 2021, 9, 715 12 of 21

Table 2. Cont.

Variable Classification
Nurse Intervention

Group (n = 28)
Mean ± SD or Number (%)

Nurse Control
Group (n = 30)

Mean ± SD or Number (%)
Total χ2/t p

Age 42.25 ± 7.53 35.97 ± 9.83 39.00 ± 9.28 2.72 0.008
Sex Female 28 (100.0) 27 (90.0) 55 (94.8) 2.95 0.086

Male 0 (0.0) 3 (10.0) 3 (5.2)

Educational level Professional school 11 (39.3) 9 (30.0) 20 (34.5) 0.55 0.457

College 17 (60.7) 21 (70.0) 38 (65.5)

Working experience 11.80 ± 8.07 8.01 ± 6.22 9.84 ± 7.36 2.01 0.052
Fall experience of assigned

patients in the past year
Yes 18 (64.3) 26 (86.7) 44 (75.9) 3.96 0.047

No 10 (35.7) 4 (13.3) 14 (24.1)

Fall prevention education in
the past year

Yes 28 (100.0) 29 (96.7) 57 (98.3) 0.95 0.330

No 0 (0.0) 1 (3.3) 1 (1.7)

How informative was the
education session Very helpful 11 (39.3) 5 (17.2) 16 (28.1) 4.25 0.119

Helpful 15 (53.6) 23 (79.3) 38 (66.7)

Not helpful 2 (7.1) 1 (3.4) 3 (5.3)

Nursing performance for
fall prevention

Strongly agree 7 (25.0) 3 (10.0) 10 (17.2) 3.12 0.374

Agree 19 (67.9) 24 (80.0) 43 (74.1)

Disagree 2 (7.1) 2 (6.7) 4 (6.9)

Strongly disagree 0 (0.0) 1 (3.3) 1 (1.7)

Necessity of fall
prevention education

Strongly agree 12 (42.9) 12 (40.0) 24 (41.4) 0.05 0.825

Agree 16 (57.1) 18 (60.0) 34 (58.6)

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Table 3. Pre–post-difference test of the main study variables between patients and nurses in the control and intervention groups.

Variable Time

Patient Intervention Group
(n = 27)

Patient Control Group
(n = 30) Z/t p

N (%) or Cases N (%) or Cases

Number of falls

Pre-test 3 3 −0.14 0.892
Post-test 2 5 −1.22 0.222

Pre-post difference −1 2 −0.98 0.326
Z(p) −0.71 (0.480) −0.38 (0.705)

Fall prevention behavior

Pre-test 2.38 ± 0.42 2.60 ± 0.60 1.57 0.121
Post-test 3.83 ± 0.22 2.38 ± 0.55 −13.25 <0.001

Pre-post difference 1.44 ± 0.49 −0.22 ± 0.58 −11.66 <0.001
t(p) −15.26 (<0.001) 2.12 (0.043)

Fall knowledge

Pre-test 6.89 ± 3.19 8.13 ± 3.41 1.42 0.162
Post-test 13.41 ± 1.72 8.27 ± 4.39 −5.93 <0.001

Pre-post difference 6.52 ± 3.57 0.13 ± 3.79 −6.57 <0.001
t(p) −9.50 (<0.001) −0.20 (0.847)

Fear of falling

Pre-test 6.34 ± 1.87 6.34 ± 2.17 −0.01 0.994
Post-test 1.91 ± 1.23 5.91 ± 2.95 6.79 <0.001

Pre-post difference −4.43 ± 2.27 −0.43 ± 3.04 5.58 <0.001
t(p) 10.15 (<0.001) 0.78 (0.444)

Interaction satisfaction

Pre-test 3.35 ± 0.54 3.43 ± 0.49 0.59 0.558
Post-test 4.87 ± 0.42 3.32 ± 0.61 −11.33 <0.001

Pre-post difference 1.52 ± 0.69 −0.11 ± 0.82 −8.06 <0.001
t(p) −11.39 (<0.001) 0.74 (0.465)

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Table 3. Cont.

Variable Time

Nurse Intervention Group
(n = 28)

Nurse Control Group
(n = 30) t p

Mean ± SD Mean ± SD

Fall prevention behavior

Pre-test 3.96 ± 0.48 3.78 ± 0.74 −1.12 0.269
Post-test 4.69 ± 0.35 3.76 ± 0.71 −6.40 <0.001

Pre-post difference 0.73 ± 0.68 −0.02 ± 0.88 −3.60 <0.001
t(p) −5.67 (<0.001) 0.11 (0.912)

Fall knowledge

Pre-test 13.50 ± 2.43 13.43 ± 2.11 −0.11 0.911
Post-test 15.79 ± 0.63 14.00 ± 1.64 −5.54 <0.001

Pre-post difference 2.29 ± 2.46 0.57 ± 2.43 −2.67 0.010
t(p) −4.91 (<0.001) −1.28 (0.212)

Burden of falling

Pre-test 2.76 ± 0.26 2.69 ± 0.26 −0.92 0.362
Post-test 2.70 ± 0.51 2.84 ± 0.48 1.03 0.306

Pre-post difference −0.05 ± 0.49 0.14 ± 0.43 1.65 0.105
t(p) 0.58 (0.565) −1.85 (0.074)

Interaction satisfaction

Pre-test 3.37 ± 0.70 3.19 ± 0.54 −1.10 0.278
Post-test 4.28 ± 0.67 3.22 ± 0.67 −6.45 <0.001

Pre-post difference 0.92 ± 0.84 0.04 ± 0.77 −4.16 <0.001
t(p) −5.78 (<0.001) −0.26 (0.795)

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3.3.2. Nurses’ Fall Prevention Behavior, Fall Knowledge, and Burden of Falling

Fall prevention behavior increased from a mean of 3.96 to 4.69 after the intervention.
In the control group, it decreased from 3.78 to 3.76, and the fall prevention behavior of the
intervention group significantly increased relative to that in the control group (t = −3.60,
p < 0.001).

Fall knowledge increased from a mean of 13.50 to 15.79 after the intervention. It
also increased from 13.43 to 14.00 in the control group. Thus, fall knowledge significantly
increased in the intervention group relative to that in the control group (t = −2.67, p < 0.010).
The burden of falling decreased from 2.76 to 2.70 after the intervention. In the control
group, it increased from 2.69 to 2.84. Thus, the burden of falling did not significantly
decrease in the intervention group relative to that in the control group (t = 1.65, p = 0.105)
(Table 3).

3.3.3. Interaction Satisfaction among Patients and Nurses

Interaction satisfaction in the intervention group of patients increased from 3.35 to 4.87
after the program. In the control group, it decreased from 3.43 to 3.32. Thus, the interaction
satisfaction in the intervention group significantly increased relative to that in the control
group (t = −8.06, p < 0.001) (Table 3).

In the intervention group of nurses, interaction satisfaction increased from 3.37 to 4.28
after the program. In the control group, it increased from 3.19 to 3.22. Thus, interaction
satisfaction significantly increased in the intervention group relative to that in the control
group (t = −4.16, p < 0.001) (Table 3).

4. Discussion
4.1. Fall Prevention Program Based on King’s Goal Achievement Theory

In this study, a fall prevention program based on King’s goal attainment theory was
provided to elderly patients and nurses in a long-term care hospital to decrease the fear of
falling, reduce the burden of falling of nurses, and increase fall knowledge and interaction
satisfaction of both patients and nurses, ultimately increasing fall prevention behavior and
reducing the number of falls. The program is significant in the following ways.

First, this study developed and applied a fall prevention program based on King’s goal
attainment theory, in which patients and nurses participated together. Patient participation
is regarded as an international standard for the healthcare system and the legal rights
of patients. Thus, patients should participate in decisions related to health management
planning, effects, and evaluations. In particular, patient-centered health care must be
planned per the opinions, needs, and preferences of patients to allow them to maintain
control over their health [53]. However, studies have shown that patients believe nurses are
solely responsible for preventing falls and that their role in preventing falls is passive [54].
Therefore, patient-centered nursing [55] and interaction via communication are effective
for treatment [56]. Both patient– and nurse–researcher and patient–nurse interactions
were included in the fall prevention program based on King’s goal attainment theory to
promote patient participation. Thus, fall prevention behavior, interaction satisfaction, and
fall knowledge increased, while fear of falling among patients was reduced.

Second, a fall prevention program was developed and applied using guidelines and
prints made of visual data of hospital conditions familiar to the patients. An effective fall
prevention program requires environmental, educational, nursing process, and fall pre-
vention interventions [57] per individual circumstances via effective communication [58].
Therefore, guidelines and prints containing visual data of familiar hospital conditions
based on King’s goal attainment theory were used to provide systematic fall prevention
education tailored to each patient. Additionally, this study included various meaningful
contents, such as an environment-related fall prevention checklist, demonstrations, and
practical education by rehabilitation therapists.

Healthcare 2021, 9, 715 16 of 21

4.2. Effects of the Fall Prevention Program

Fear of falling was reduced, and fall knowledge, interaction satisfaction, and fall
prevention behavior increased regarding both patients and nurses. The results on the
effects of the fall prevention program are discussed as follows.

Most studies have reported on knowledge [52], fall prevention behavior [24], and
the number of falls [27]. However, no studies have examined the perception of falls and
interactions. Moreover, fall prevention programs that included individual education tai-
lored to each subject, demonstration, and repetitive education were challenging to find.
Therefore, this study reduced the negative perception of falls by analyzing the fear of
falling among patients and the burden of falling among nurses after the fall prevention
program. Furthermore, interactions between patients and nurses were included to show
that nurses are not solely responsible for falls and that fall prevention behaviors are more
effective when both patients and nurses exercise such behavior.

In this study, nurses better understood the risk of falling and answered patient ques-
tions related to falls. Such an interaction allowed patients and nurses to continue fall
prevention behaviors even beyond the study. Rehabilitation therapists and nurses in charge
of patient safety participated in providing demonstrations and opportunities to practice
necessary clinical skills. Further, education and demonstrations, exchange of opinions,
counseling and support, and environmental management were included in the program
via personal, interpersonal, and social systems, leading to a significant increase in fall
prevention behavior.

Tzeng and Yin [59] suggested that understanding patient-centered care and patient
involvement in fall prevention programs is necessary to prevent falls. In this study, patients
and nurses set mutual goals together; the demands and needs of patients were reflected in
the program. A grape sticker was provided to the patients every week when falls did not
occur to induce confidence. The nurses were asked to encourage the patients to increase
the effects of the program further.

A checklist, fall risk assessment tool, fall environment assessment tool, fall preven-
tion patient education and re-education, fall report form, and hourly rounding have been
suggested as effective for fall prevention [28]. In our study, a checklist, fall risk assess-
ment, environmental assessment, repetitive individual education, fall reports, and periodic
rounding were included in the program to promote fall prevention behaviors further.

In this study, the number of falls in the intervention group decreased from three to two
(p = 0.480). In the control group, it increased from three to five (p = 0.705). Intuitively, the
number of falls would decrease as the fall prevention behavior of patients improves. How-
ever, the number of falls was insufficient to observe a statistically significant difference, and
the eight-week intervention period was insufficient relative to the 6-month fall intervention
study that reported an effective decrease in the number of falls (p < 0.004) [60–62] and falls
with injury (p < 0.01) [63]. Therefore, more participants should be selected in future studies,
and the effects should be observed over a longer period of at least six months.

Further, fear of falling was lower in the patient intervention group than in the control
group (p < 0.001). Expectedly, mutual goal setting and communication help assess objective
and subjective risk factors of falling, thus leading to a decreased fear of falling. In particular,
patient behavior characteristics were evaluated, and patients were encouraged to continue
fall prevention activities to be actively involved in managing their health [64]. This study
observed that patients were afraid of falling when traveling to bathrooms. Lim et al. [54]
also reported that the number of falls was highest in bathrooms. During the intervention
period of this study, two cases of falls were observed in the bathroom of the same patient.

Regarding the fear of falling, McMahon, Talley, and Wyman [65] reported that au-
tonomy and independence of patient behavior are necessary. Therefore, in this study,
patients were sufficiently educated on the risk of falling, and lighting was increased in
surrounding environments to prevent as much falling as possible. Further, patients wore
gait belts and were accompanied by a caregiver, and repetitive education was provided
using an emergency bell for the toilet. Thus, cases of participants collapsing to the floor

Healthcare 2021, 9, 715 17 of 21

were observed. Given the likelihood of falls, opinions were exchanged between patients
and staff to prevent continuous falls.

This study also aimed to lower the burden of falling among nurses; however, the
effects were not significant (p = 0.105). This finding may have been due to nurses’ increased
responsibility for patients’ fall accidents and the increased burden of work [66]. In most
medical negligence claims, nurses are often responsible. Thus, falls are an important
problem for nurses [67]. Long-term care hospital patients are elderly and suffer from
complex chronic diseases [68]; confusion, gait problems, Alzheimer’s, loss of directional
senses, and failure to comply with safety guidelines are frequently observed risk factors [59].
Therefore, continuous education and evaluation, activities suitable for nursing manpower
structures, and systematic management are required [69].

Particularly, it is necessary to develop educational programs to help nurses overcome
the effects of falls, prevent falls, and improve patient safety [70]. The Patient Safety Act,
effective since July 2016, states that medical staff are required to voluntarily report patient
safety incidents to avoid the omission of reporting due to fear or guilt of punishment and
that adverse actions cannot be taken against the one who reported, given the aim of the
report [71]. Thus, the hospital environment that considers falls as the full responsibility
of nurses should be reviewed; emotional and educational support must be provided to
reduce the burden of falling among nurses. Moreover, an improved legal system should be
established to avoid imposing excessive responsibility on nurses.

In this study, pictures of high-risk hospital situations were incorporated into brochures
and prints for individual education on fall knowledge. As most of the patients answered
that they were not aware of their medications, medication description sheets with photos
and explanations were printed and explained by assigned nurses. Moreover, explanations
were repeated by the researchers to ensure comprehension. Lim et al. [54] reported that
fall prevention programs provided to all patients during patient waiting time at hospitals
are not effective. In our study, fall prevention education was provided to every patient
at the time of hospitalization; however, only a few patients were aware of such educa-
tion. Therefore, this finding suggests that additional fall prevention education is required
for patients.

Personal attention and effort are important for elderly patients. However, personal ef-
fort alone cannot prevent falls due to old age, disease status, and medication difficulties [4].
Thus, the education program must be modified regularly per changing fall knowledge and
tasks (p = 0.001) [72]. Further, the appropriate methods, quantity, and education intensity
must be provided per the knowledge level of elderly patients (p < 0.001) [9], and efforts
such as systematic education and evaluation are required [73].

Altogether, as elderly and vulnerable patients are mostly in long-term care hospitals,
a fall prevention program suitable for long-term care hospitals is needed. Therefore,
in this study, fall knowledge, diseases, and medications for each elderly patient were
identified. Repetitive education was individually provided and fall prevention behaviors
were improved through the interaction between patients and nurses, who were aware of
the health status and lifestyle of patients. Hence, the fall prevention program based on
King’s goal attainment theory is relevant in that it significantly reduces the fear of falling
among patients and improves fall knowledge, interaction satisfaction, and fall prevention
behavior of patients and nurses through transactions, including systems and interactions
between patients and nurses. This study provides a basis for developing a systematic fall
prevention system and positively contributing to fall prevention in practice.

4.3. Limitations

First, the study design and sampling methods were not randomly assigned. The
separation of floors between wards was performed in a non-equivalent control pre- and
post-test study. Moreover, this study was conducted at a single hospital in Seoul, and
the results cannot be generalized to patients and nurses in all long-term care hospitals.
Therefore, future studies should employ a fall prevention program using a cluster or subject

Healthcare 2021, 9, 715 18 of 21

randomization method for several long-term care hospitals. Second, only short-term effects
immediately before the intervention and eight weeks of the intervention period were
assessed. The participants were not followed up, and long-term continuous effects of the
program could not be assessed. Thus, it is necessary to assess the continuous effects of the
intervention in future studies. Third, there was no significant difference in terms of prior
homogeneity between groups, and since the data did not follow normality and proceeded
to non-parametric statistics, the corresponding variable was not adjusted. However, if
sufficient samples are collected and various characteristic variables are corrected, more
clear effect verification will be possible in future studies. Fourth, fear of falling decreased,
and fall knowledge, interaction satisfaction, and fall prevention behavior improved among
patients in this study; however, the number of falls and burden of falling on nurses did not
significantly change. Therefore, further studies are needed to reduce the number of falls
and the burden of falling among nurses.

5. Conclusions

In this study, a fall prevention program was developed based on King’s goal attain-
ment theory, and the effects of the developed program were assessed. The fall prevention
program employed transactions of personal systems (fear of falling, burden of falling, and
fall knowledge), interpersonal system (interaction satisfaction), and social system (fall pre-
vention behavior). Thus, fear of falling was reduced among patients, and fall knowledge,
interaction satisfaction, and fall prevention behavior of patients were improved. Although
the burden of falling among nurses was not reduced statistically, fall knowledge, interaction
satisfaction, and fall prevention behavior of nurses were improved. Therefore, based on
the positive effects identified in this study, it is thought that the fall prevention program
based on the goal attainment theory will be applied to clinical studies and research to help
prevent falls.

Funding: This research received no external funding.

Institutional Review Board Statement: This study was conducted in accordance with the guidelines
of the Declaration of Helsinki and approved by the Institutional Review Board of Korea University
(approval number: KUIRB-2019-0159-01; date of approval: 27 June 2019) in Seoul, South Korea.

Informed Consent Statement: Prior to the start of the program, the objectives and procedures of the
study were explained to the participants, and oral and written consent were obtained.

Data Availability Statement: All data generated or analyzed during this study are included in this
published article.

Acknowledgments: The author would like to thank all participants of this study for their contribution.

Conflicts of Interest: The author declares no conflict of interest. The funder had no role in the design
of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or
in the decision to publish the results.

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  • Introduction
  • Methods
    • Fall Prevention Program Based on King’s Goal Achievement Theory
      • Fall Prevention Program Contents
      • Weekly Themes and Goals of the Fall Prevention Program
    • Verification of the Effects of the Fall Prevention Program Based on King’s Goal Attainment Theory
      • Design
      • Participants and Sampling Method
      • Research Tools
      • Data Analysis
      • Ethical Considerations
  • Results
    • General and Disease-Related Characteristics
      • Patients
      • Nurses
    • Pre-Test Homogeneity Test for Study Variables
      • Patients
      • Nurses
    • Effects of the Fall Prevention Program
      • Patients’ Number of Falls, Fall Prevention Behavior, Fall Knowledge, and Fear of Falling
      • Nurses’ Fall Prevention Behavior, Fall Knowledge, and Burden of Falling
      • Interaction Satisfaction among Patients and Nurses
  • Discussion
    • Fall Prevention Program Based on King’s Goal Achievement Theory
    • Effects of the Fall Prevention Program
    • Limitations
  • Conclusions
  • References

RESEARCH ARTICLE

Acceptability of the 6-PACK falls prevention

program: A pre-implementation study in

hospitals participating in a cluster randomized

controlled trial

Anna L. Barker
1☯*, Renata T. Morello1☯, Darshini R. Ayton1☯, Keith D. Hill2‡, Caroline

A. Brand
1‡

, Patricia M. Livingston
3‡

, Mari Botti
4‡

1 Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine,

Monash University, Melbourne, Victoria, Australia, 2 School of Physiotherapy and Exercise Science, Curtin

University, Bentley, Western Australia, Australia, 3 Epworth/Deakin Centre for Clinical Nursing Research,

Deakin University, Richmond, Victoria, Australia, 4 School of Nursing and Midwifery, Deakin University,

Burwood, Victoria, Australia

☯ These authors contributed equally to this work.
‡ These authors also contributed equally to this work.

* [email protected]

Abstract

There is limited evidence to support the effectiveness of falls prevention interventions in the

acute hospital setting. The 6-PACK falls prevention program includes a fall-risk tool; ‘falls alert’

signs; supervision of patients in the bathroom; ensuring patients’ walking aids are within

reach; toileting regimes; low-low beds; and bed/chair alarms. This study explored the accept-

ability of the 6-PACK program from the perspective of nurses and senior staff prior to its imple-

mentation in a randomised controlled trial. A mixed-methods approach was applied involving

24 acute wards from six Australian hospitals. Participants were nurses working on participating

wards and senior hospital staff including: Nurse Unit Managers; senior physicians; Directors of

Nursing; and senior personnel involved in quality and safety or falls prevention. Information on

program acceptability (suitability, practicality and benefits) was obtained by surveys, focus

groups and interviews. Survey data were analysed descriptively, and focus group and inter-

view data thematically. The survey response rate was 60%. Twelve focus groups (n = 96

nurses) and 24 interviews with senior staff were conducted. Falls were identified as a priority

patient safety issue and nurses as key players in falls prevention. The 6-PACK program was

perceived to offer practical benefits compared to current practice. Nurses agreed fall-risk

tools, low-low beds and alert signs were useful for preventing falls (>70%). Views were mixed
regarding positioning patients’ walking aid within reach. Practical issues raised included

access to equipment; and risk of staff injury with low-low bed use. Bathroom supervision was

seen to be beneficial, however not always practical. Views on the program appropriateness

and benefits were consistent across nurses and senior staff. Staff perceived the 6-PACK pro-

gram as suitable, practical and beneficial, and were open to adopting the program. Some prac-

tical concerns were raised highlighting issues to be addressed by the implementation plan.

PLOS ONE | DOI:10.1371/journal.pone.0172005 February 15, 2017 1 / 15

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a1111111111

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OPEN ACCESS

Citation: Barker AL, Morello RT, Ayton DR, Hill KD,

Brand CA, Livingston PM, et al. (2017)

Acceptability of the 6-PACK falls prevention

program: A pre-implementation study in hospitals

participating in a cluster randomized controlled

trial. PLoS ONE 12(2): e0172005. doi:10.1371/

journal.pone.0172005

Editor: Angel M. Foster, University of Ottawa,

CANADA

Received: May 26, 2016

Accepted: January 30, 2017

Published: February 15, 2017

Copyright: © 2017 Barker et al. This is an open
access article distributed under the terms of the

Creative Commons Attribution License, which

permits unrestricted use, distribution, and

reproduction in any medium, provided the original

author and source are credited.

Data Availability Statement: All relevant data are

within the paper and its Supporting Information. If

enquire about more data (e.g. interview transcripts)

they can email the corresponding author.

Funding: This work was supported by a grant from

the National Health and Medical Research Council

(NHMRC), Australia (APP1007627). AB’s salary

was funded by a Fellowship from the NHMRC

(APP1067236). RM’s salary was supported by a

scholarship from the NHMRC (APP1055604).

Introduction

Despite implementation of several activities designed to reduce fall injuries, they remain com-

mon in hospitals [1–3]. There is limited high quality evidence to support the effectiveness of

prevention interventions in the acute setting [4]. The 6-PACK is a nurse-led falls prevention

program designed for acute wards [5]. It includes a fall-risk tool [6] and individualised selec-

tion of a ‘falls alert’ sign; bathroom supervision; ensuring patients’ walking aids are within

reach; a toileting regime; a low-low bed; and a bed/chair alarm. The program involves nurses

assessing their patients’ falls risk each shift and applying a ‘falls alert’ sign and one or more of

the remaining 6-PACK interventions to high risk patients. A single-centre study suggests the

program is feasible to implement and may reduce fall injuries [7]. A randomised controlled

trial (RCT) was conducted to provide robust estimates of effect and generalisability [8]. Prior

to the RCT, assessment of the program acceptability was considered important to inform

development of a plan to optimise implementation effectiveness [9–11].

Acceptability studies facilitate implementation tailored to local needs and context. There

are several components of acceptability including suitability, practicality and benefits. Suitabil-
ity, relates to underlying demand [10] or matching of the program to opportunity (underlying
problem) [12]. It can be referred to as ‘appropriateness’ of a program and explores the pro-

gram’s alignment to needs of patients and likelihood of being used. Practicality, relates to the
extent to which the program can be implemented efficiently within existing resources [10].

Benefits, relate to the program’s potential to achieve intended outcomes—for example, reduce
fall-related injuries, and relative advantages above existing care models such as reducing work

load for hospital staff. It is also referred to as the ‘potential effectiveness’ [10].

Three prior studies have sought to explore the acceptability of hospital falls prevention pro-

grams [11, 13, 14]. The first used a survey to obtain information on barriers and enablers to

implementation of a falls prevention guideline from 1,467 nurses in five Singaporean hospitals.

High levels of acceptability were reported. However, 25% of nurses reported delivery of the

guideline as too time consuming, and 20% that it had limited flexibility with respect to clinical

judgement and tailoring for individual patients [11]. The second involved a survey of health

care professionals, patients and their relatives (N = 200) at a U.K. general hospital. High levels

of acceptability were reported for observation beds, identification bracelets, bed/chair alarms,

bed rails and ‘at risk’ labels by the bed [13]. The last study in one sub-acute ward used a survey

(N = 12) and focus group (N = 9) of nurses and reported high acceptability of an electronic

sensor bed/chair alarm system for patients with cognitive impairment from the perspective of

nurses [14]. While the above mentioned studies provide insights, the small sample sizes and

single centre designs highlight further studies are required.

This study aimed to explore the acceptability of the 6-PACK program from the perspective

of nurses and senior staff prior to implementation of the program as part of a RCT [5]. Specific

study objectives were to assess perceived suitability, practicality, and benefits of the program

components (fall-risk tool, interventions and integrated care plan) and protocol (nurses to

review and update the tool and required interventions each shift). This information would

inform development of an implementation plan.

Materials and methods

Design

A multi-centre mixed methods pre-implementation study done in accordance with COREQ

guidelines (S1 Appendix). This study was part of the 6-PACK project that incorporated a

three-year research plan: 1) Studies of current falls prevention practice and moderators (pre-

Acceptability of the 6-PACK falls prevention program for hospitals

PLOS ONE | DOI:10.1371/journal.pone.0172005 February 15, 2017 2 / 15

Competing interests: The authors have declared

that no competing interests exist.

implementation) [15]; 2) A cluster RCT testing 6-PACK effectiveness (S2 Appendix), includ-

ing economic [16] and program evaluations (implementation); and 3) a longitudinal assess-

ment of sustainability of practice change and outcomes (maintenance).

Participants and setting

Nurses and senior staff from 24 acute wards (16 medical; 8 surgical) recruited to participate in

the RCT were the study participants. Ward recruitment procedures are described in detail else-

where (S3 Appendix). Nurses were eligible to participate in the survey and/or focus group if

they had worked on wards for �7.5 hours per week two months prior to survey administra-

tion. Staff who did not meet this criteria were excluded as they might have limited knowledge

of ward prevention practices and falls. Interviews were conducted with 24 senior staff nomi-

nated by the hospital Director of Nursing (DON) and invited by letter from the research team.

These included Nurse Unit Managers (NUMs); senior physicians; DONs; and senior personnel

involved in quality and safety or falls prevention.

Nurse survey

A 43-item survey was developed by the research team that included 15 acceptability items

(Table 1). The survey was piloted at the hospital that developed and implemented the 6-PACK

program to test dissemination approach and comprehension [7]. The length of the survey was

the main issue raised by pilot participants, however, it was deemed difficult to further reduce

items without losing important content. Formal construct validity of the survey was not under-

taken. Survey scores were not intended to be summed or analysed with parametric statistics.

Participants rated their agreement to items on a 5-point Likert scale (strongly disagree to

strongly agree). The survey was administered to all eligible nurses over two-weeks at each hos-

pital. The researchers described the study purpose, privacy issues and instructions for comple-

tion. Completed surveys were placed into a sealed box that was collected by the researcher at

the end of the dissemination period.

Focus groups and key informant interviews

Two focus groups and four interviews were scheduled at each hospital. Focus group and inter-

view question guides were developed by researchers experienced in the development, imple-

mentation and evaluation of hospital based patient safety programs and informed by relevant

literature [15]. Questions related to beliefs about falls; current falls prevention practice;

6-PACK program components; best practice guidelines and key recommendations; and falls

reporting practices, and were mapped to the Theoretical Domain Framework (TDF). The TDF

includes 12 domains: knowledge; skills; social/professional role and identity; beliefs about

capabilities; beliefs about consequences; motivation and goals; memory, attention and decision

making processes; environmental context and resources; social influences; emotion; behavioral

regulation and nature of the behaviors [17]. Question guides differed slightly between focus

groups and interviews. For example, focus groups were with nurses and therefore questions

focused on their experiences with falls and preventing falls. Interviews with senior staff

included questions that were more operational in nature for example the expected outcomes

from the 6-PACK program and how these will be measured. Sessions were led by AB, were 1hr

in duration and explored the perceived acceptability of the 6-PACK program (Table 1). Dis-

cussions were recorded and transcribed, and transcripts were made available to participants

for verification.

Acceptability of the 6-PACK falls prevention program for hospitals

PLOS ONE | DOI:10.1371/journal.pone.0172005 February 15, 2017 3 / 15

Data analysis

Descriptive statistics were calculated for survey responses using Stata MP v13. Interview and

focus group data were analysed by three independent researchers using thematic analysis

[18]. Discrepancies were resolved by discussion and consultation with the investigator team

as required. All interviews and focus groups were transcribed verbatim and uploaded into

Nvivo 11 for data management and analysis. DA coded and recoded transcripts as actions,

processes and themes emerged to test applicability and consistency in relation to acceptabil-

ity of the 6-PACK program. Three rounds of coding were conducted: open, axial and the-

matic. Deductive theory-driven codes were used to identify overarching acceptability themes

based on the survey, FG and interview questions [18]. AB and MB checked the coding frame-

work for the open and axial coding to ensure that coding was consistent. They were also

involved in developing the conceptual links and testing for the thematic codes. Quantitative

and qualitative data were analysed separately with triangulation at the interpretation stage

where findings from each component were considered to determine convergence or diver-

gence [19].

Table 1. Mapping of survey, focus group and interview questions to the acceptability domains.

Survey Focus group Interview Questions/Statements

Suitability—Underlying demand or matching of the program to opportunity and to the care needs of patients.

✓ ✓ How does falls prevention compare with other patient safety priorities at your hospital?

✓ Falls are not a problem on my ward so falls prevention programs are not required.

✓ Falls prevention is not a priority on this ward.

✓ ✓ Are falls or fall injuries an issue on your ward/in your hospital?

✓ ✓ What do you see as your role in falls prevention?

✓ Falls prevention is primarily the responsibility of the physiotherapist.

✓ It is not my responsibility to stop patients from falling.

✓ It is my responsibility as the patient’s treating nurse to assess their falls risk each shift.

✓ It is my responsibility, to update my patient’s falls risk status if a fall and/or change in condition occurs.

✓ ✓ Are you familiar with the six interventions included in the 6-PACK program?

✓ ✓ Would 6-PACK be appropriate for your ward and patients?

✓ How does the 6-PACK program fit into existing/planned quality and safety programs/other ward/hospital activities?

Practicality—Relates to the extent to which the program can be implemented within existing resources and care models.

✓ I don’t have time to complete a falls risk assessment on all my patients.

✓ Falls risk assessment is a waste of time.

✓ Falls risk assessment tools are a useful way of identifying patients at risk of falling.

✓ A “Falls risk” sign above the bed is a useful way to communicate to staff which patients are at risk of falling.

✓ Low-low beds are an effective way to prevent injuries in patients at risk of falling out of bed.

Benefits—Potential to achieve intended outcomes and relative advantage above existing care models.

✓ It is my responsibility to implement prevention strategies for patients I identify as high risk

✓ The current falls prevention program is effective at reducing falls on my ward.

✓ Falls risk assessment tools are a useful way of identifying patients at risk of falling.

✓ ✓ What do you think the benefits would be of implementing the 6-PACK program on your ward/in your hospital?

✓ What outcomes are you seeking from the 6-PACK program and how will you measure these?

✓ ✓ What strategies do you feel are most important for preventing falls?

✓ What effect, if any, do you feel the 6-PACK project will have on your hospital?

✓ Falls risk assessment tools are better than my own judgment for identifying patients most at risk of falling.

doi:10.1371/journal.pone.0172005.t001

Acceptability of the 6-PACK falls prevention program for hospitals

PLOS ONE | DOI:10.1371/journal.pone.0172005 February 15, 2017 4 / 15

Ethics

This study was approved by Monash University Human Research Ethics Committee–CF11/

0229–2011000072 and relevant hospital ethics committees. Participants were given verbal

information about the study and asked to sign consent forms if they were interested in

participating.

Results

Participants

A total of 702 surveys were distributed with 420 returned (60%). Respondents were mostly reg-

istered nurses (74%); and medical ward staff (75%) (Table 2). Fig 1 presents the survey results.

Twelve focus groups with 96 nurses and 24 interviews with senior staff (SS) were conducted

(Table 2).

Key concepts were identified across the surveys, focus groups and interview responses and

mapped to acceptability domains as outlined in Table 3. These were explored in a more in-

depth manner below.

Matching of program to opportunity

The 6-PACK program was perceived to be suitable with high levels of demand for a new falls

prevention approach. Survey data indicated falls remained a problem—84% of nurses disagreed

Table 2. Survey, focus group and interview participants.

Hospital 1 Hospital 2 Hospital 3 Hospital 4 Hospital 5^ Hospital 6^ Total

Surveys

Ward, n (%)

Medical 42 (54.5) 34 (65.4) 87 (77.7) 41 (61.2) 42 (100.0) 70 (100.0) 316 (75.2)

Surgical 35 (45.5) 18 (34.6) 25 (22.3) 26 (38.8) 0 (0.0) 0 (0.0) 104 (24.8)

Qualification, n (%)

RN 68 (88.3) 24 (46.2) 91 (81.3) 39 (58.2) 31 (73.8) 59 (84.3) 312 (74.3)

LPN 3 (3.9) 2 (3.8) 18 (16.1) 4 (6.0) 10 (23.8) 8 (11.4) 45 (10.7)

UAP 1 (1.3) 18 (34.6) 0 (0.0) 18 (26.9) 0 (0.0) 0 (0.0) 37 (8.8)

Not recorded 5 (6.5) 8 (15.4) 3 (2.7) 6 (9.0) 1 (2.4) 3 (4.3) 26 (6.2)

Focus groups

Group 1 8 8 11 5 10 8 50

Group 2 4 9 8 12 9 4 46

Total 12 17 19 17 19 12 96

Interviews

Director of Nursing 1 1 1 1 1 1 6

Nurse Unit Manager 1 1 1 2 1 1 7

Clinical risk coordinator 1 0 0 0 0 0 1

Quality and safety manager 0 0 0 0 1 0 1

Nurse educator 1 1 2 3 0 2 9

Total 4 3 4 6 3 4 24

RN = Registered Nurse; LPN = Licensed practical nurse; UAP = Unlicensed assistive personnel

^No surgical wards at these hospitals participated in the study

doi:10.1371/journal.pone.0172005.t002

Acceptability of the 6-PACK falls prevention program for hospitals

PLOS ONE | DOI:10.1371/journal.pone.0172005 February 15, 2017 5 / 15

with the statement ‘Falls are not a problem on my ward so falls prevention programs are not
required’. Staff believed that falls remained their “leading incident”. Current falls prevention
activities were perceived to have limited effectiveness.

Two patients have died. . .falls are such an important issue for our patients
(SS1, Hospital (H)4).

I think there’s a lot more we can do in terms of falls prevention
(Nurse, H4)

Staff highlighted current falls prevention practice was inconsistent and that the 6-PACK

program could address this.

We don’t always implement things in a structured manner. It [6-PACK program] gives us a
really structured way of implementing

(SS1, H5).

Fig 1. Survey of nurses’ perceived acceptability of key components of the 6-PACK program.

doi:10.1371/journal.pone.0172005.g001

Acceptability of the 6-PACK falls prevention program for hospitals

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Integrated care plan with daily nurse review

The program was considered suitable. Nurses agreed it was their responsibility to assess

patients’ fall risk status each shift (86%) and to implement interventions for high risk patients

(90%). Inclusion of the fall-risk tool and interventions on the care plan was perceived to be a

practical, suitable and a beneficial improvement on current practice as it promoted more fre-

quent review of patients’ risk status.

[The care plan is] really good. . .If I didn’t know that patient and I came to care for them, I
would know straightaway I had to check their falls risk. You are more alert to making sure
strategies are in place. Nurses will like it

(SS2, H5)

The 6-PACK care plan was identified as practical to use in the busy ward environment.

Nurses felt check boxes would save time “because it only takes 10 seconds” and were easy to use.
Some concerns were raised whether the review and updating of the care plan would occur

consistently.

Table 3. Concepts identified mapped to acceptability domains.

Suitability

• Falls are the number 1 patient safety problem.

• Nurses are key players in falls prevention.

• There is opportunity to improve current falls prevention practice.

• Risk factors included on 6-PACK fall-risk tool match perceived local risk factors.

• Alert signs, low-low beds and bathroom supervision were considered matched to local falls problem.

Practicality

• An integrated care plan is useful and could be used with minimal training.

• 6-PACK falls risk tool is easy to complete.

• Time restraints may limit the risk tool and required interventions from being updated regularly.

• 6-PACK equipment need to be easy to identify, access and well maintained.

• Completing the risk tool on patients recently admitted can be difficult.

• Bed/chair alarms can be annoying.

• There may be privacy issues with using alert signs and bathroom supervision.

• Bathroom supervision creates a challenge to safely manage other high falls risk patients justify

unattended.

• Bathroom supervision and toileting regimes take time to implement.

Benefits (and perceived harms)

• An integrated care plan promotes frequent review of patients’ risk status and required interventions.

• The 6-PACK will bring consistency to falls prevention practice and should reduce falls and fall injuries.

• Use of a shorter risk tool and fewer interventions will save time.

• The 6-PACK risk tool provides a useful way to identify patients at risk of falling.

• ‘Falls alert’ signs increase awareness of patient falls risk amongst staff.

• Low-low beds reduce injuries from falls.

• Bathroom supervision prevents bathroom falls.

• Toileting regimes may exacerbate continence issues.

• Positioning patients’ walking aids in reach may increase falls.

• Staff and patients may incur injuries with low-low bed use.

• Bed/chair alarms may not be effective if used in isolation.

doi:10.1371/journal.pone.0172005.t003

Acceptability of the 6-PACK falls prevention program for hospitals

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Fall-risk tool

Nurses believed fall-risk tools were useful for identifying patients at risk of falling (73%).

Nurse and senior staff felt the 6-PACK tool was suitable and more practical than current tools.

It was recognised as being shorter and simpler, with appropriate risk factors and use of a two

rather than three-level risk status (i.e. high or low v. low, medium or high).

[Our tool is] four pages long. It is not meaningful to staff because they just see it as cumber-
some.

(SS1, H5)

[The current tool] doesn’t identify very well people at risk of falling.
(Nurse, H1)

Practical barriers to completion of the tool for patients recently admitted were identified.

If the patient has just been transferred I have to observe them before I can complete the tool
properly. If there’s no family around, you go through all the files, it takes more than 10 minutes
to do properly.

(Nurse, H5)

Despite acknowledging completing fall-risk tools take time, 80% of nurses disagreed that

they were a waste of time.

Alert signs

Nurses reported signs were already used to some extent on wards highlighting suitability.

Nurses reported signs were useful at communicating patients’ falls risk status to the care team

(73%) and had the potential to decrease falls.

I find signs effective. . .the moment I enter the room and I see it I’ll be aware that the patient is
high falls risk, I’ll keep an eye on them.

(Nurse, H5)

They were considered particularly beneficial when attending patients not known by staff.

A practical barrier to sign use was ease of access.

We do have signs . . . they are just not in the room and not accessible.
(Nurse, H4)

Bathroom supervision

Supervising patients in the bathroom was considered suitable and beneficial based on knowl-

edge that many falls occur in the bathroom amongst unsupervised patients. Currently, it was

used variably.

I think presence in the bathroom is really important. It’s something that can get missed. You
find patients left in the bathroom that you know shouldn’t have been.

(SS1, H3)

Acceptability of the 6-PACK falls prevention program for hospitals

PLOS ONE | DOI:10.1371/journal.pone.0172005 February 15, 2017 8 / 15

Practical barriers to bathroom supervision were identified. Firstly, bathroom supervision of

one patient meant that other patients are left unattended.

If you’re in the bathroom with someone and another patient buzzed, you get a phone call or
page it’s really challenging to stay in the bathroom.

(Nurse, H1)

The second barrier identified was privacy. Some nurses believed bathroom supervision was

uncomfortable for patients and nurses.

You want to just say, ‘I’m just out here and I’ll check in’, and then you hear crash, bang. You
try to give them that little bit of dignity that they’ve got left to go to the toilet in peace.

(Nurse, H1)

The third barrier identified was limited time.

Sometimes we don’t have time to supervise them on the toilet. . .we’ve got a lot of things to do.
(Nurse, H1)

The use of ‘partner’ nursing was identified as a strategy to promote bathroom supervision.

Working with a partner, you know you’ve got each other’s patients if something comes up that
you can’t attend.

(Nurse, H1)

Patients’ walking aids within reach

There were mixed beliefs regarding the benefits of positioning patients’ walking aid within

reach. Some acknowledged if a patient is going to get up it is best to “give them something to
hold on to” whilst others felt it was “dangerous having the walking aid near the patient” as
“patients can trip on it”. Concerns were also raised about the suitability and benefits of this
intervention for people with cognitive impairment.

If they’ve got dementia they’re just as likely to fall over with the walking aid as without.
(Nurse, H3)

Toileting regimes

Nurses and senior staff expressed contrasting views regarding toileting regimes. Senior staff

believed they were useful while nurses reported other interventions such as the use of bed pans

to be more practical, allowing them to continue to supervise other patients.

We encourage all our falls risk patients are second-hourly toileted.
(SS2, Hospital 3)

If I took them [to the toilet] every two hours I’m going to make their bladder worse.
(Nurse, H5)

Acceptability of the 6-PACK falls prevention program for hospitals

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Sometimes we just have to use a bedpan, so at least we don’t have to take them to the toilet
and stay with them.

(Nurse, H2)

There were different opinions as to whether toileting regimes are easier to implement dur-

ing the day or at night.

At night, when you’ve got 8–10 patients. . .you can’t toilet someone on a schedule when you’ve
got that many to worry about.

(Nurse, H4)

[Toileting schedules are] easy to do on night duty because you have your regular rounds, but
during the day I find it disruptive and virtually impossible.

(Nurse, H1)

Low-low beds

Nurses agreed low-low beds were an effective intervention to minimise injuries in patients that

fall getting out of bed (80%). Staff highlighted “even if patients were to fall, the height reduces
the impact and injuries”.

Practical barriers to the use of low-low beds were identified including accessibility.

We know these patients are fallers but we’ve only got so many beds. . .So it’s always a battle,
which I think is a bit of a barrier. How do I get a bed? How do I hire one?

(SS3, H3)

Concerns were also raised regarding their potential to increase staff and patient injury.

I’ve seen a nurse trip over [the low-low bed] and hit her head on the bedside table.
(Nurse, H3)

Low-low beds are helpful but are hard for staff. Once the patient is on the floor it’s hard to lift
them back to bed.

(Nurse, H6)

They rolled out and hit their head against the bedside locker.
(Nurse, H1)

Issues regarding the identification, ease of use and practicality of the beds were also raised.

They are not marked. You don’t know which ones are the low-low beds.
(Nurse, H3)

You can’t use them for transport. You can’t put folders or air mattresses on them.
(Nurse, H1)

Bed/chair alarm

Nurses had mixed beliefs about the benefits of alarms. Some believed they were only useful if

used in conjunction with other interventions.

Acceptability of the 6-PACK falls prevention program for hospitals

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You’ve got to use alarms in conjunction with the patient being close to the nurses’ station. It’s
no good having them right up the other end where you hear the alarm and by the time you’ve
got there the patient’s fallen over.

(SS4, H3)

Practical barriers to alarm use included a perception they were annoying and therefore

ignored, that they increase workload and are often broken.

After a while I’d just get sick of it and just ignore it.
(SS1, H6)

I think they’re good however can be temperamental. . .they’re not long-lasting.
(SS1, H5)

They don’t help your workload because every five minutes they go off and you have to respond
even if you’re busy elsewhere.

(Nurse, H6)

Overall impressions

Staff identified the 6-PACK program promoted more “standardised”, “streamlined” and “con-
sistent” use of interventions than was undertaken in current practice. Staff believed the pro-
gram offered potential to reduce falls and injuries highlighting potential effectiveness.

You’d have to see some reduction in falls and falls related injuries after implementing the
6-PACK.

(Nurse, H1)

Discussion

Nurses have a key role in falls prevention. This study extends prior studies [11, 13, 14] by seek-

ing information not only from nurses but also senior staff providing a detailed understanding

of falls prevention practice in acute hospitals. This is the first multi-centre, mixed methods

study of the acceptability of many commonly used falls prevention interventions. Staff per-

ceived the 6-PACK program is suitable and for the most part practical and beneficial. Some

practicality concerns were raised highlighting targets to be addressed by the implementation

plan.

Staff highlighted need for a new falls prevention approach. Falls are perceived as prevalent

and deleterious, and existing prevention practices have numerous limitations. The 6-PACK

was perceived to offer advantages over existing practice. Staff believed it was practical—a

short, simple risk tool, integrated care plan, and focus on only a few interventions—and was

appropriate for the needs of their patients—risk factors on the tool were considered relevant

and the interventions were considered useful in local context. Others have also identified a

need for simple programs with nurses reporting ‘too many must do’s are daunting’ [20] and
that integration into exiting work practices facilitates practice change [21]. Staff agreed with

the program focus on nurses and identified falls as a nursing sensitive outcome, consistent

with prior literature [22]. The program was considered easy to integrate into existing care and

able to be used with minimal training.

Acceptability of the 6-PACK falls prevention program for hospitals

PLOS ONE | DOI:10.1371/journal.pone.0172005 February 15, 2017 11 / 15

Staff perceived many benefits to both themselves and patients with implementation of the

6-PACK program. Benefits included more frequent review of patients’ risk status, a more con-

sistent falls prevention approach across staff and reduced time spent on documentation. Signs

were considered an effective means of communicating falls risk amongst staff that would

increase use of interventions, consistent with U.K. studies [13]. Low-low beds were believed to

be effective for reducing injuries from bed falls, and bathroom supervision an effective way to

prevent bathroom falls.

The perceived suitability and benefits of the 6-PACK program suggests a high likelihood

of the program being used by nurses and use supported by senior staff. A perceived lack of

time, access to equipment, and patient privacy issues may compromise the use of the pro-

gram. Time constraints and access to equipment have been identified by prior falls preven-

tion studies as factors limiting uptake [11, 20]. The implementation plan must ensure there

is appropriate access to signs, low-low beds and alarms. This includes adequate provision of

equipment to meet patient demand, storage of equipment in patient rooms, and clear label-

ling so it is easily identifiable. Access to equipment was identified in a large study of U.S hos-

pitals as a factor reducing opportunity to provide safe care [23]. Staff time, workload and

resource constraints are the most commonly reported barriers to implementing nursing

practice guidelines [21]. Education sessions should address privacy issues with bathroom

supervision. Use of dignity gowns and avoiding direct eye contact while patients are voiding

could be promoted.

Consistent with others [13, 14], we identified that nurses perceived bed/chair alarms as a

useful way to prevent patient falls. However, nurses raised alarms were often not in working

order, are less effective when used in isolation or when too many are used at once. This high-

lights the need for regular maintenance audits, education that promotes the use of alarms in

combination with other interventions and guidelines about prioritising use to only 1–3

patients on a ward at a time.

Some staff also identified risks associated with the use of the 6-PACK. ‘Partner’ nursing

was identified as a strategy to mitigate the risk of leaving patients unattended when providing

bathroom supervision. While there is evidence that increased levels of nursing (higher nurse-

patient ratios) are associated with fewer falls [24, 25], there is an absence of evidence regarding

associations between ‘partner’ nursing and falls. A Canadian study reported nurses were con-

cerned about the fall hazard created by keeping walking aids within reach especially when

bedside space is limited [20]. Education should include recommendations on ensuring the

bedside area is clear of clutter to minimise patient injury. Education should also recommend

the patient’s bed is raised to an appropriate height during transfers and care activities.

In this study, perspectives from both nurses and senior staff provided a detailed under-

standing of falls prevention in acute hospitals, contributing to knowledge of how to enhance

implementation fidelity of programs. Focus groups and interviews provided more comprehen-

sive information on beliefs about effectively preventing falls, compared to survey only methods

[11]. This study was conducted as part of the 6-PACK RCT [8] which introduced bias as par-

ticipants were recruited from hospitals that had volunteered to participate in the RCT.

The 6-PACK program is nurse-led and therefore our focus was to seek the perspectives of

nurses. Doctors, pharmacists and allied health professionals are also important falls prevention

stakeholders and may have different perspectives. Further research to explore this is war-

ranted. Patient and family perspectives would also be important to consider. Additional publi-

cations present the findings of the other pre-implementation studies conducted as part of the

6-PACK project [8] including a profile of safety climate, review of current falls prevention

practice, in-hospital fall epidemiology, and investigation of implementation barriers and

enablers.

Acceptability of the 6-PACK falls prevention program for hospitals

PLOS ONE | DOI:10.1371/journal.pone.0172005 February 15, 2017 12 / 15

Conclusions

While the 6-PACK program remained fixed in the RCT, implementation was tailored to local

context to optimise implementation and effects. This study confirmed the acceptability of the

6-PACK program to nurses who are the program end-users and senior staff who are executive

sponsors. Staff believed the program to be a suitable, practical and beneficial way to assist them

to reduce falls. Information obtained from this study was incorporated with that from other

pre-implementation studies to develop the implementation RCT plan.

Supporting information

S1 Appendix. COREQ checklist.

(DOCX)

S2 Appendix. 6-PACK programme to decrease fall injuries in acute hospitals: Cluster ran-

domised controlled trial (published article).

(PDF)

S3 Appendix. Development of an implementation plan for the 6-PACK falls prevention

programme as part of a randomised controlled trial: Protocol for a series of preimplemen-

tation studies (published article).

(PDF)

Acknowledgments

We acknowledge Jeannette Kamar and the Injury Prevention Unit, The Northern Hospital,

Northern Health, Melbourne, Australia who developed the 6-PACK Program. The study could

not have been completed without the collaboration and support from the participating hospi-

tals, site clinical leaders and nursing staff.

We also acknowledge the inputs of Jason Talevski and Sheral Rifat who provided editorial

assistance.

Author Contributions

Conceptualization: AB CB KH PL MB.

Data curation: DA AB RM MB.

Formal analysis: DA AB.

Funding acquisition: AB CB KH PL MB.

Investigation: AB RM CB DA KH PL MB.

Methodology: AB CB KH PL MB.

Project administration: RM AB DA.

Resources: DA AB RM.

Software: DA AB.

Supervision: AB RM MB.

Validation: DA AB RM MB.

Visualization: DA AB RM.

Acceptability of the 6-PACK falls prevention program for hospitals

PLOS ONE | DOI:10.1371/journal.pone.0172005 February 15, 2017 13 / 15

Writing – original draft: DA AB RM CB.

Writing – review & editing: AB RM CB DA KH PL MB.

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