Running Head: QUANTITATIVE RESEARCH CRITIQUE 1
QUANTITATIVE RESEARCH CRITIQUE 2
Quantitative Research Critique
Background of Study
Mehrolhasani et al. (2017) indicate that nurses get an average of about 30% of any hospital’s wage-bill. This is because they are a major part of the human resource. Considering that the human resources are allocated between 50 and 80% of the entire expenditure per financial year, it is apparent that the financial resources the nurses end-up getting is substantial. Without nurses, a hospital would find it hard to achieve its objectives.
According to Mehrolhasani et al. (2017), the success of nursing depends on how efficient these important stakeholders are. For instance, some of the clients who visit the emergency rooms are in dire conditions; and delays and/or mistakes would mean that their fate would worsen. The authors also indicate that over 28% of the clients who are seen at the emergency department end-up being hospitalized based on the seriousness of their cases. It follows that there is the need to improve on communication, bed planning, the ‘discharge by noon’ programs, the internal staffing pool, incentives, and also special assignments for patient transition units.
Considering that nursing is such a critical mission, Mehrolhasani et al. (2017) conducted the study with the intention to understand how their numbers and services could be optimized, particularly at the Emergency Department (or ED). The stated main objective is to assess the impact that optimal allocation of the members of staff has on the efficiency of service provision. The researchers used the Linear Programming Model which seeks to arrive at the optimal outcome with respect to planning and management of resources.
Even though the study does not list the research questions explicitly, it is evident that the researchers hoped to answer the following:
i. What potential gaps exist in facilitating quality improvement at the ED?
ii. How can the creative power of the ED be harnessed to optimize service delivery?
iii. How does the number of nurses at the ED help improve efficiency?
iv. Does the use of the linear programming (LP) technique help mitigate discrepancies at the ED?
Quality improvement in this case refers to the continuous and systematic actions which ultimately lead to the perfection of the care related services availed to the targeted group.
Method of Study
The study was conducted through the use of the Linear Programming (LP) model. A census was used to determine the study population, and this included every nurse in the ED as well as the clients visiting them. For the nurses, n=84 and n=3342 for the patients. Hospital information systems as well as the human resource database were utilized in obtaining these statistics. The optimum count of nurses in every shift was determined using the LP model (Mehrolhasani et al., 2017).
Literature review came in handy in determining the research gaps, and the researchers did also seek the relevant expert advice. The execution of the LP model was via the WinQSB software, and the WinQSB software was selected since it is one of the accurate and yet simplest to use in regards to solving problems of this nature. It is designed to facilitate the ease of data entry, and has several solution methods to pick from. Once every parameter has been analyzed, a comprehensible output is generated (Mehrolhasani et al., 2017).
The conceptual framework is not clear; but based on the objectives that the researchers had, the independent variables most likely included the potential gaps, creative power, the number of nurses, and the influence that the use of LP has. The researchers hoped to understand how each of these as well as how they together influence the optimization of service delivery. This is a resource-based view since it is about ascertaining the managerial framework which could be utilized to determine how strategic resources can be allocated and exploited towards gaining and maintaining the competitive advantage.
Results of Study
Prior to the implementation of the model, the researchers determined the numbers of nurses working in the night shift, morning shift, and the evening shift as 34, 26, and 24 respectively. Those who worked at the facility upon the running of the model numbered 62. This included 28 for the night shift, and 17 each for both morning and evening shifts. The number still reduced further following the completion of the sensitivity analysis (Mehrolhasani et al., 2017).
The argument is that whenever the current shifts at a hospital are changed and the nurses are allowed to commence working in various shifts, then their numbers can as well be lowered since there are reduced constraints. In essence, the hospitals suffer the cost of maintaining nurses whose presence is only needed until 11pm yet they register as working until 8 am. If the nurses started working in the middle of their current shifts, then the resolution of the LP model means that their presence and hence numbers can be optimized as much as possible (Mehrolhasani et al., 2017).
For this to happen, nonetheless, hospitals are required to avail complete and accurate pieces of data in order to ensure that assumptions are created in accordance to the kind of demands the hospital is having. Since the demand tends to fluctuate, there ought to be flexibility in determining the right number to be engaged. One thing that came-out when using the model is that it is inflexible and it can ruin groups’ decision making efforts; and this is due to its single-objective nature. Other ideal programming methods may need to be sought.
The researchers appreciated that conflicting values, ambiguity, and other ethical issues do emerge while making decisions. This causes the lack of clarity in regards to composing and maintaining standards. The, therefore, sought to ensure that they have developed the moral principles which ought to be followed in regards to completing studies of this nature. The idea is to make it possible to respect the rights and welfare of the groups, individuals, and the community in general. The researchers were keen on averting any source of harm as a result of their experimental intervention.
Participants were safeguarded from any form of exploitation. The risk-benefits ratio was established for the subjects, and incase the risks were deemed to be significant, the researchers were willing to abandon the exercise. Above all, they did maintain respect, privacy, dignity, and nondisclosure promises to their fullest; and there was also fairness in the kind of treatment that the study subjects received. Finally, written consents were sought every time the need arose. In most of these cases, such consent was formally sought from the departmental offices.
Mehrolhasani et al. (2017) is about the optimization of the emergency department’s nursing at an educational hospital. The essence of the study is to understand the role that the human resources play at health facilities. This is revealed, analyzed, and discussed by taking a sample of trained and specialized nurses who are, indeed, the nucleus of every health system. Incidentally, those working at the emergency department are tasked with ensuring life and survival of their clients and hence a quantitative study of their success rate is important. The researchers managed to estimate that the number of nurses who used the LP was lesser than those who were permanently stationed at the ED. The discrepancy can be reduced if there is the scientific apprehension of the issues which influence the optimal allocation of nurses in flexible organizations.
Mehrolhasani, M.H., Mouseli, A., Vali, L., & Mastaneh, Z. (2017, Feb.). Quantitative optimization of emergency department’s nurses of an educational hospital: A case study. Electronic Physician, 9(2), 3803-3809. DOI: http://dx.doi.org/10.19082/3803