NURSING INFORMATICS and the Foundation of Knowledge

FOURTH EDITION

NURSING INFORMATICS and the Foundation of Knowledge

 

 

The Pedagogy Nursing Informatics and the Foundation of Knowledge, Fourth Edition drives comprehension through a variety of strategies geared toward meeting the learning needs of students, while also generating enthusiasm about the topic. This interactive approach addresses diverse learning styles, making this the ideal text to ensure mastery of key concepts. The pedagogical aids that appear in most chapters include the following:

Key Terms » Accessibility » Cognitive activity » Data » Data gatherer » Enumerative

approach » Expert systems

» Industrial Age » Information » Information Age » Information user » International

Classification of Nursing Practice

» Knowledge » Knowledge

builder » Knowledge user » Knowledge worker » Ontological

approach

» Reusability » Standardized Nurs-

ing Terminology » Technologist » Terminology » Ubiquity » Wisdom

1. Trace the evolution of nursing informatics from concept to specialty practice.

2. Relate nursing informatics metastructures, con- cepts, and tools to the knowledge work of nursing.

3. Explore the quest for consistent terminology in nursing and describe terminology approaches that

accurately capture and codify the contributions of nursing to health care.

4. Explore the concept of nurses as knowledge workers.

5. Explore how nurses can create and derive clinical knowledge from information systems.

Objectives

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Introduction Those who followed the actual events of Apollo 13, or who were enter- tained by the movie (Howard, 1995), watched the astronauts strive against all odds to bring their crippled spaceship back to Earth. The speed of their travel was incomprehensible to most viewers, and the task of bringing the spaceship back to Earth seemed nearly impossible. They were experienc- ing a crisis never imagined by the experts at NASA, and they made up their survival plan moment by moment. What brought them back to Earth safely? Surely, credit must be given to the technology and the spaceship’s ability to withstand the trauma it experienced. Most amazing, however, were the traditional nontechnological tools, skills, and supplies that were used in new and different ways to stabilize the spacecraft’s environment and keep the astronauts safe while traveling toward their uncertain future.

This sense of constancy in the midst of change serves to stabilize experi- ence in many different life events and contributes to the survival of crisis and change. This rhythmic process is also vital to the healthcare system’s stability and survival in the presence of the rapidly changing events of the Knowledge Age. No one can dispute the fact that the Knowledge Age is changing health care in ways that will not be fully recognized and under- stood for years. The change is paradigmatic, and every expert who ad- dresses this change reminds healthcare professionals of the need to go with the fl ow of rapid change or be left behind.

As with any paradigm shift, a new way of viewing the world brings with it some of the enduring values of the previous worldview. As health care continues its journey into digital communications, telehealth, and wearable technologies, it brings some familiar tools and skills recognized in the form of values, such as privacy, confi dentiality, autonomy, and nonma- lefi cence. Although these basic values remain unchanged, the standards for living out these values will take on new meaning as health professionals confront new and different moral dilemmas brought on by the adoption

Ethical applications of Informatics Dee McGonigle, Kathleen Mastrian, and Nedra Farcus

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ChapTEr 5

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Key Terms Found in a list at the beginning of each chapter, studying these terms will create an expanded vocabulary.

Objectives Providing a snapshot of the key information encountered in each chapter, the objectives serve as a checklist to help guide and focus study. Objectives can also be found within the text’s online resources.

Introductions Found at the beginning of each chapter, the introductions provide an overview highlighting the importance of the chapter’s topic. They also help keep students focused as they read.

Key Terms » Artificial

intelligence » Brain » Cognitive

informatics » Cognitive science » Computer science

» Connectionism » Decision making » Empiricism » Epistemology » Human Mental

Workload (MWL) » Intelligence

» Intuition » Knowledge » Logic » Memory » Mind » Neuroscience » Perception

» Problem solving » Psychology » Rationalism » Reasoning » Wisdom

1. Describe cognitive science. 2. Assess how the human mind processes and gener-

ates information and knowledge.

3. Explore cognitive informatics. 4. Examine artificial intelligence and its relationship

to cognitive science and computer science.

Objectives

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Summaries Summaries are included at the end of each chapter to provide a concise review of the material covered, highlighting the most important points and describing what the future holds.

uncertainty to the situational factors and personal beliefs that must be considered cre- ates a need for an ethical decision-making model to help one choose the best action.

Ethical Decision Making Ethical decision making refers to the process of making informed choices about ethical dilemmas based on a set of standards differentiating right from wrong. This type of decision making reflects an understanding of the principles and standards of ethical decision making, as well as the philosophic approaches to ethical decision making, and it requires a systematic framework for addressing the complex and often contro- versial moral questions.

As the high-speed era of digital communications evolves, the rights and the needs of individuals and groups will be of the utmost concern to all healthcare profession- als. The changing meaning of communication, for example, will bring with it new concerns among healthcare professionals about protecting patients’ rights of confi- dentiality, privacy, and autonomy. Systematic and flexible ethical decision-making abilities will be essential for all healthcare professionals.

Notably, the concept of nonmaleficence (“do no harm”) will be broadened to include those individuals and groups whom one may never see in person, but with whom one will enter into a professional relationship of trust and care. Mack (2000)

82 ChapTEr 5 Ethical Applications of Informatics

rESEarCh BrIEF

Using an online survey of 1,227 randomly selected respondents, Bodkin and Miaoulis (2007) sought to describe the characteristics of information seekers on e-health websites, the types of information they seek, and their perceptions of the quality and ethics of the websites. Of the respondents, 74% had sought health in- formation on the Web, with women accounting for 55.8% of the health informa- tion seekers. A total of 50% of the seekers were between 35 and 54 years of age. Nearly two thirds of the users began their searches using a general search engine rather than a health-specific site, unless they were seeking information related to symptoms or diseases. Top reasons for seeking information were related to dis- eases or symptoms of medical conditions, medication information, health news, health insurance, locating a doctor, and Medicare or Medicaid information. The level of education of information seekers was related to the ratings of website quality, in that more educated seekers found health information websites more understandable, but were more likely to perceive bias in the website information. The researchers also found that the ethical codes for e-health websites seem to be increasing consumers’ trust in the safety and quality of information found on the Web, but that most consumers are not comfortable purchasing health products or services online.

The full article appears in Bodkin, C., & Miaoulis, G. (2007). eHealth information quality and ethics issues: An exploratory study of consumer perceptions. International Journal of Pharmaceuti- cal and Healthcare Marketing, 1(1), 27–42. Retrieved from ABI/INFORM Global (Document ID: 1515583081).

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practices are sometimes more harmful than beneficial). A case in point is the long-standing practice of instilling endotracheal tubes with normal saline before suctioning (O’Neal, Grap, Thompson, & Dudley, 2001). Based on the evidence gathered through several studies, the potentially deleterious effects of this practice have become widely recognized. Conceivably, a meta-analysis approach to clinical studies will be expedited by convergence of large clinical data repositories across care settings, thereby making available to practitioners the collective contribu- tions of health professionals and longitudinal outcomes for individuals, families, and populations.

Nurses need to be engaged in the design of CIS tools that support access to and the generation of nursing knowledge. As we have emphasized, the adoption of clini- cal data standards is of particular importance to the future design of CIS tools. We are also beginning to see the development and use of expert systems that implement knowledge automatically without human intervention. For example, an insulin pump that senses the patient’s blood glucose level and administers insulin based on those data is a form of expert system. The expert system differs from decision support tools in that the decision support tools require the human to act on the information pro- vided, whereas the expert system intervenes automatically based on an algorithm that directs the intervention. Consider that as CISs are widely implemented, as standards for nursing documentation and reporting are adopted, and as healthcare IT solutions continue to evolve, the synthesis of findings from a variety of methods and world- views becomes much more feasible.

BOX 6-3 CaSE STuDy: CaSTINg TO ThE FuTurE

In the year 2025, nursing practice enabled by technology has created a profes- sional culture of reflection, critical inquiry, and interprofessional collaboration. Nurses use technology at the point of care in all clinical settings (e.g., primary care, acute care, community, and long-term care) to inform their clinical deci- sions and effect the best possible outcomes for their clients. Information is gath- ered and retrieved via human–technology biometric interfaces including voice, visual, sensory, gustatory, and auditory interfaces, which continuously monitor physiologic parameters for potentially harmful imbalances. Longitudinal records are maintained for all citizens from their initial prenatal assessment to death; all lifelong records are aggregated into the knowledge bases of expert systems. These systems provide the basis of the artificial intelligence being embedded in emerging technologies. Smart technologies and invisible computing are ubiqui- tous in all sectors where care is delivered. Clients and families are empowered to review and contribute actively to their record of health and wellness. Invasive diagnostic techniques are obsolete, nanotechnology therapeutics are the norm, and robotics supplement or replace much of the traditional work of all health professions. Nurses provide expertise to citizens to help them effectively manage their health and wellness life plans, and navigate access to appropriate informa- tion and services.

122 ChaPEr 6 History and Evolution of Nursing Informatics

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The Future The future landscape is yet to be fully understood, as technology continues to evolve with a rapidity and unfolding that is rich with promise and potential peril. Box 6-3 helps us to imagine what future practice might entail. It is anticipated that computing power will be capable of aggregating and transforming additional multidimensional data and information sources (e.g., historical, multisensory, experiential, and genetic sources) into CIS. With the availability of such rich repositories, further opportunities will open up to enhance the training of health professionals, advance the design and application of CDSs, deliver care that is informed by the most current evidence, and engage with individuals and families in ways yet unimagined.

The basic education of all health professions will evolve over the next decade to incorporate core informatics competencies. In general, the clinical care environments will be connected, and information will be integrated across disciplines to the benefit of care providers and citizens alike. The future of health care will be highly dependent on the use of CISs and CDSs to achieve the global aspiration of safer, quality care for all citizens.

The ideal is a nursing practice that has wholly integrated informatics and nursing education and that is driven by the use of information and knowledge from a myriad of sources, creating practitioners whose way of being is grounded in informatics. Nursing research is dynamic and an enterprise in which all nurses are engaged by virtue of their use of technologies to gather and analyze findings that inform specific clinical situations. In every practice setting, the contributions of nurses to health and well-being of citizens will be highly respected and parallel, if not exceed, the preemi- nence granted physicians.

Summary In this chapter, we have traced the development of informatics as a specialty, defined nursing informatics, and explored the DIKW paradigm central to informatics. We also explored the need for and the development of standardized terminologies to capture and codify the work of nursing and how informatics supports the knowledge work of nursing. This chapter advanced the view that every nurse’s practice will make contributions to new nursing knowledge in dynamically interactive CIS environ- ments. The core concepts associated with informatics will become embedded in the practice of every nurse, whether administrator, researcher, educator, or practitioner. Informatics will be prominent in the knowledge work of nurses, yet it will be a sub- tlety because of its eventual fulsome integration with clinical care processes. Clinical care will be substantially supported by the capacity and promise of technology today and tomorrow.

Most importantly, readers need to contemplate a future without being limited by the world of practice as it is known today. Information technology is not a panacea for all of the challenges found in health care, but it will provide the nursing profes- sion with an unprecedented capacity to generate and disseminate new knowledge at rapid speed. Realizing these possibilities necessitates that all nurses understand and leverage the informatician within and contribute to the future.

Summary 123

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This text is designed to include the necessary content to prepare nurses for prac- tice in the ever-changing and technology-laden healthcare environments. Informatics competence has been recognized as necessary in order to enhance clinical decision making and improve patient care for many years. This is evidenced by Goossen (2000), who reflected on the need for research in this area and believed that the focus of nursing informatics research should be on the structuring and processing of patient information and the ways that these endeavors inform nursing decision mak- ing in clinical practice. The increased use of technology to enhance nursing practice, nursing education, and nursing research will open new avenues for acquiring, pro- cessing, generating, and disseminating knowledge.

In the future, nursing research will make significant contributions to the devel- opment of nursing science. Technologies and translational research will abound, and clinical practices will continue to be evidence based, thereby improving patient outcomes and decreasing safety concerns. Schools of nursing will embrace nursing science as they strive to meet the needs of changing student populations and the increasing complexity of healthcare environments.

Summary Nursing science influences all areas of nursing practice. This chapter provided an overview of nursing science and considered how nursing science relates to typical nursing practice roles, nursing education, informatics, and nursing research. The Foundation of Knowledge model was introduced as the organizing conceptual framework for this text. Finally, the relationship of nursing science to nursing informatics was discussed. In subsequent chapters the reader will learn more about how nursing informatics supports nurses in their many and varied roles. In  an ideal world, nurses would embrace nursing science as knowledge users, knowledge managers, knowledge developers, knowledge engineers, and knowl- edge workers.

ThOUGhT-prOVOKING QUeSTIONS

1. Imagine you are in a social situation and someone asks you, “What does a nurse do?” Think about how you will capture and convey the richness that is nursing science in your answer.

2. Choose a clinical scenario from your recent experience and analyze it using the Foundation of Knowledge model. How did you acquire knowledge? How did you process knowledge? How did you generate knowledge? How did you dis- seminate knowledge? How did you use feedback, and what was the effect of the feedback on the foundation of your knowledge?

18 ChapTer 1 Nursing Science and the Foundation of Knowledge

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Research Briefs These summaries encourage students to access current research in the field.

Thought-Provoking Questions Students can work on these critical thinking assign­ ments individually or in a group. In addition, students can delve deeper into concepts by completing these exercises online.

Case Studies Case studies encourage active learning and promote critical think­ ing skills. Students can ask questions, analyze situations, and solve problems in a real­world context.

 

 

 

FOURTH EDITION

Dee McGonigle, PhD, RN, CNE, FAAN, ANEF Director, Virtual Learning Experiences (VLE) and Professor Graduate Program, Chamberlain College of Nursing Member, Informatics and Technology Expert Panel (ITEP) for the American Academy of Nursing

Kathleen Mastrian, PhD, RN Associate Professor and Program Coordinator for Nursing Pennsylvania State University, Shenango Sr. Managing Editor, Online Journal of Nursing Informatics (OJNI)

NURSING INFORMATICS and the Foundation of Knowledge

 

 

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Production Credits VP, Executive Publisher: David D. Cella Executive Editor: Amanda Martin Editorial Assistant: Christina Freitas Production Manager: Carolyn Rogers Pershouse Senior Marketing Manager: Jennifer Scherzay Product Fulfillment Manager: Wendy Kilborn Composition: S4Carlisle Publishing Services Cover and Text Design: Michael O’Donnell Rights & Media Specialist: Wes DeShano Media Development Editor: Shannon Sheehan Cover Image (Title Page, Part Opener, Chapter Opener): © fotomak/Shutterstock Printing and Binding: LSC Communications Cover Printing: LSC Communications

Library of Congress Cataloging-in-Publication Data Names: McGonigle, Dee, editor. | Mastrian, Kathleen Garver, editor. Title: Nursing informatics and the foundation of knowledge/[edited by] Dee McGonigle, Kathleen Mastrian. Description: Fourth edition. | Burlington, MA: Jones & Bartlett Learning, [2018] | Includes bibliographical references and index. Identifiers: LCCN 2016043838 | ISBN 9781284121247 (pbk.) Subjects: | MESH: Nursing Informatics | Knowledge Classification: LCC RT50.5 | NLM WY 26.5 | DDC 651.5/04261–dc23

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Special Acknowledgments

We want to express our sincere appreciation to the staff at Jones & Bartlett Learning, especially Amanda, Christina, and Carolyn, for their continued encouragement, assistance, and support during the writing process and publication of our book.

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Preface xvi Acknowledgments xix Contributors xxi

SECTION I: BUILDING BLOCKS OF NURSING INFORMATICS 1

1 Nursing Science and the Foundation of Knowledge 7 Dee McGonigle and Kathleen Mastrian Introduction 7 Quality and Safety Education for Nurses 16 Summary 18 References 19

2 Introduction to Information, Information Science, and Information Systems 21 Kathleen Mastrian and Dee McGonigle Introduction 21 Information 22 Information Science 25 Information Processing 26 Information Science and the Foundation of Knowledge 27 Introduction to Information Systems 28 Summary 32 References 33

3 Computer Science and the Foundation of Knowledge Model 35 Dee McGonigle, Kathleen Mastrian, and June Kaminski Introduction 35 The Computer as a Tool for Managing Information and Generating Knowledge 36 Components 38 What Is the Relationship of Computer Science to Knowledge? 53 How Does the Computer Support Collaboration and Information Exchange? 54 Cloud Computing 57 Looking to the Future 59 Summary 61 Working Wisdom 61 Application Scenario 62 References 62

Contents

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4 Introduction to Cognitive Science and Cognitive Informatics 65 Kathleen Mastrian and Dee McGonigle Introduction 65 Cognitive Science 65 Sources of Knowledge 68 Nature of Knowledge 69 How Knowledge and Wisdom Are Used in Decision Making 69 Cognitive Informatics 70 Cognitive Informatics and Nursing Practice 71 What Is AI? 72 Summary 73 References 74

5 Ethical Applications of Informatics 77 Dee McGonigle, Kathleen Mastrian, and Nedra Farcus Introduction 77 Ethics 78 Bioethics 79 Ethical Issues and Social Media 80 Ethical Dilemmas and Morals 81 Ethical Decision Making 82 Theoretical Approaches to Healthcare Ethics 83 Applying Ethics to Informatics 86 Case Analysis Demonstration 91 New Frontiers in Ethical Issues 95 Summary 96 References 97

SECTION II: PERSPECTIVES ON NURSING INFORMATICS 99

6 History and Evolution of Nursing Informatics 105 Kathleen Mastrian and Dee McGonigle Introduction 105 The Evolution of a Specialty 106 What Is Nursing Informatics? 108 The DIKW Paradigm 109 Capturing and Codifying the Work of Nursing 112 The Nurse as a Knowledge Worker 117 The Future 123 Summary 123 References 124

7 Nursing Informatics as a Specialty 127 Dee McGonigle, Kathleen Mastrian, Julie A. Kenney, and Ida Androwich Introduction 127 Nursing Contributions to Healthcare Informatics 127

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Scope and Standards 128 Nursing Informatics Roles 129 Specialty Education and Certification 131 Nursing Informatics Competencies 133 Rewards of NI Practice 138 NI Organizations and Journals 138 The Future of Nursing Informatics 139 Summary 141 References 142

8 Legislative Aspects of Nursing Informatics: HITECH and HIPAA 145 Kathleen M. Gialanella, Kathleen Mastrian, and Dee McGonigle Introduction 145 HIPAA Came First 145 Overview of the HITECH Act 148 How a National HIT Infrastructure Is Being Developed 153 How the HITECH Act Changed HIPAA 154 Implications for Nursing Practice 161 Future Regulations 165 Summary 165 References 166

SECTION III: NURSING INFORMATICS ADMINISTRATIVE APPLICATIONS: PRECARE AND CARE SUPPORT 169

9 Systems Development Life Cycle: Nursing Informatics and Organizational Decision Making 175 Dee McGonigle and Kathleen Mastrian Introduction 175 Waterfall Model 178 Rapid Prototyping or Rapid Application Development 180 Object-Oriented Systems Development 181 Dynamic System Development Method 181 Computer-Aided Software Engineering Tools 184 Open Source Software and Free/Open Source Software 184 Interoperability 185 Summary 186 References 187

10 Administrative Information Systems 189 Marianela Zytkowski, Susan Paschke, Kathleen Mastrian, and Dee McGonigle Introduction 189 Types of Healthcare Organization Information Systems 190 Communication Systems 190 Core Business Systems 191 Order Entry Systems 193 Patient Care Support Systems 194

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Interoperability 195 Aggregating Patient and Organizational Data 197 Department Collaboration and Exchange of Knowledge and Information 202 Summary 203 References 204

11 The Human–Technology Interface 207 Dee McGonigle, Kathleen Mastrian, and Judith A. Effken Introduction 207 The Human–Technology Interface 208 The Human–Technology Interface Problem 211 Improving the Human–Technology Interface 212 A Framework for Evaluation 221 Future of the Human–Technology Interface 221 Summary 223 References 224

12 Electronic Security 229 Lisa Reeves Bertin, Kathleen Mastrian, and Dee McGonigle Introduction 229 Securing Network Information 229 Authentication of Users 231 Threats to Security 232 Security Tools 237 Offsite Use of Portable Devices 238 Summary 241 References 242

13 Workflow and Beyond Meaningful Use 245 Dee McGonigle, Kathleen Mastrian, and Denise Hammel-Jones Introduction 245 Workflow Analysis Purpose 245 Workflow and Technology 249 Workflow Analysis and Informatics Practice 251 Informatics as a Change Agent 256 Measuring the Results 258 Future Directions 259 Summary 260 References 261

SECTION IV: NURSING INFORMATICS PRACTICE APPLICATIONS: CARE DELIVERY 263

14 The Electronic Health Record and Clinical Informatics 267 Emily B. Barey, Kathleen Mastrian, and Dee McGonigle Introduction 267 Setting the Stage 268

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Components of Electronic Health Records 269 Advantages of Electronic Health Records 274 Standardized Terminology and the EHR 278 Ownership of Electronic Health Records 280 Flexibility and Expandability 283 Accountable Care Organizations and the EHR 285 The Future 285 Summary 287 References 287

15 Informatics Tools to Promote Patient Safety and Quality Outcomes 293 Dee McGonigle and Kathleen Mastrian Introduction 293 What Is a Culture of Safety? 294 Strategies for Developing a Safety Culture 296 Informatics Technologies for Patient Safety 301 Role of the Nurse Informaticist 313 Summary 315 References 317

16 Patient Engagement and Connected Health 323 Kathleen Mastrian and Dee McGonigle Introduction 323 Consumer Demand for Information 324 Health Literacy and Health Initiatives 325 Healthcare Organization Approaches to Engagement 327 Promoting Health Literacy in School-Aged Children 329 Supporting Use of the Internet for Health Education 330 Future Directions for Engaging Patients 335 Summary 337 References 338

17 Using Informatics to Promote Community/Population Health 341 Dee McGonigle, Kathleen Mastrian, Margaret Ross Kraft, and Ida Androwich Introduction 341 Core Public Health Functions 343 Community Health Risk Assessment: Tools for Acquiring Knowledge 345 Processing Knowledge and Information to Support Epidemiology and Monitoring Disease Outbreaks 347 Applying Knowledge to Health Disaster Planning and Preparation 349 Informatics Tools to Support Communication and Dissemination 350 Using Feedback to Improve Responses and Promote Readiness 351 Summary 353 References 355

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18 Telenursing and Remote Access Telehealth 359 Original contribution by Audrey Kinsella, Kathleen Albright, Sheldon Prial, and Schuyler F. Hoss; revised by Kathleen Mastrian and Dee McGonigle Introduction 359 The Foundation of Knowledge Model and Home Telehealth 359 Nursing Aspects of Telehealth 361 History of Telehealth 362 Driving Forces for Telehealth 363 Telehealth Care 366 Telenursing 370 Telehealth Patient Populations 372 Tools of Home Telehealth 375 Home Telehealth Software 378 Home Telehealth Practice and Protocols 380 Legal, Ethical, and Regulatory Issues 381 The Patient’s Role in Telehealth 382 Telehealth Research 383 Evolving Telehealth Models 385 Parting Thoughts for the Future and a View Toward What the Future Holds 386 Summary 387 References 388

SECTION V: EDUCATION APPLICATIONS OF NURSING INFORMATICS 393

19 Nursing Informatics and Nursing Education 397 Heather E. McKinney, Sylvia DeSantis, Kathleen Mastrian, and Dee McGonigle Introduction: Nursing Education and the Foundation of Knowledge Model 397 Knowledge Acquisition and Sharing 398 Evolution of Learning Management Systems 398 Delivery Modalities 400 Technology Tools Supporting Education 405 Internet-Based Tools 413 Promoting Active and Collaborative Learning 420 Knowledge Dissemination and Sharing 423 Exploring Information Fair Use and Copyright Restrictions 426 The Future 427 Summary 428 References 429

20 Simulation, Game Mechanics, and Virtual Worlds in Nursing Education 433 Dee McGonigle, Kathleen Mastrian, Brett Bixler, and Nickolaus Miehl Introduction 433 Simulation in Nursing Informatics Education 434 Nursing Informatics Competencies in Nursing Education 436 A Case for Simulation in Nursing Informatics Education and Nursing Education 437

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Incorporating EHRs into the Learning Environment 441 Challenges and Opportunities 445 The Future of Simulation in Nursing Informatics Education 445 Game Mechanics and Virtual World Simulation for Nursing Education 446 Game Mechanics and Educational Games 448 Virtual Worlds in Education 450 Choosing Among Simulations, Educational Games, and Virtual Worlds 451 The Future of Simulations, Games, and Virtual Worlds in Nursing Education 452 Summary 453 References 454

SECTION VI: RESEARCH APPLICATIONS OF NURSING INFORMATICS 459

21 Nursing Research: Data Collection, Processing, and Analysis 463 Heather E. McKinney, Sylvia DeSantis, Kathleen Mastrian, and Dee McGonigle Introduction: Nursing Research and the Foundation of Knowledge Model 463 Knowledge Generation Through Nursing Research 464 Acquiring Previously Gained Knowledge Through Internet and Library Holdings 466 Fair Use of Information and Sharing 468 Informatics Tools for Collecting Data and Storage of Information 469 Tools for Processing Data and Data Analysis 471 The Future 473 Summary 473 References 474

22 Data Mining as a Research Tool 477 Dee McGonigle and Kathleen Mastrian Introduction: Big Data, Data Mining, and Knowledge Discovery 477 KDD and Research 481 Data Mining Concepts 482 Data Mining Techniques 483 Data Mining Models 486 Benefits of KDD 489 Data Mining and Electronic Health Records 490 Ethics of Data Mining 491 Summary 491 References 492

23 Translational Research: Generating Evidence for Practice 495 Jennifer Bredemeyer, Ida Androwich, Dee McGonigle, and Kathleen Mastrian Introduction 495 Clarification of Terms 495 History of Evidence-Based Practice 498 Evidence 498 Bridging the Gap Between Research and Practice 499 Barriers to and Facilitators of Evidence-Based Practice 500 The Role of Informatics 500

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Developing EBP Guidelines 503 Meta-Analysis and Generation of Knowledge 504 The Future 505 Summary 506 References 507

24 Bioinformatics, Biomedical Informatics, and Computational Biology 511 Dee McGonigle and Kathleen Mastrian Introduction 511 Bioinformatics, Biomedical Informatics, and Computational Biology Defined 511 Why Are Bioinformatics and Biomedical Informatics So Important? 514 What Does the Future Hold? 516 Summary 518 References 519

SECTION VII: IMAGINING THE FUTURE OF NURSING INFORMATICS 521

25 The Art of Caring in Technology-Laden Environments 525 Kathleen Mastrian and Dee McGonigle Introduction 525 Caring Theories 526 Presence 529 Strategies for Enhancing Caring Presence 530 Reflective Practice 533 Summary 534 References 535

26 Nursing Informatics and the Foundation of Knowledge 537 Dee McGonigle and Kathleen Mastrian Introduction 537 Foundation of Knowledge Revisited 537 The Nature of Knowledge 539 Knowledge Use in Practice 541 Characteristics of Knowledge Workers 544 Knowledge Management in Organizations 545 Managing Knowledge Across Disciplines 547 The Learning Healthcare System 548 Summary 550 References 551

Abbreviations 553 Glossary 556 Index 586

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Preface

The idea for this text originated with the development of nursing informatics (NI) classes, the publication of articles related to technology-based education, and the creation of the Online Journal of Nursing Infor- matics (OJNI), which Dee McGonigle cofounded with Renee Eggers. Like most nurse informaticists, we fell into the specialty; our love affair with technology and gadgets and our willingness to be the first to try new things helped to hook us into the specialty of informatics. The rapid evolution of technology and its transformation of the ways of nursing prompted us to try to capture the essence of NI in a text.

As we were developing the first edition, we realized that we could not possibly know all there is to know about informatics and the way in which it supports nursing practice, education, administration, and research. We also knew that our faculty roles constrained our opportunities for exposure to changes in this rapidly evolving field. Therefore, we developed a tentative outline and a working model of the theoretical framework for the text and invited participation from informatics experts and specialists around the world. We were pleased with the enthusiastic responses we received from some of those invited contributors and a few volunteers who heard about the text and asked to participate in their particular area of expertise.

In the second edition, we invited the original contributors to revise and update their chapters. Not everyone chose to participate in the second edition, so we revised several of the chapters using the original work as a springboard. The revisions to the text were guided by the contributors’ growing informatics expertise and the reviews provided by textbook adopters. In the revisions, we sought to do the following:

• Expand the audience focus to include nursing students from BS through DNP programs as well as nurses thrust into informatics roles in clinical agencies.

• Include, whenever possible, an attention-grabbing case scenario as an introduction or an illustrative case scenario demonstrating why the topic is important.

• Include important research findings related to the topic. Many chapters have research briefs pre- sented in text boxes to encourage the reader to access current research.

• Focus on cutting-edge innovations, meaningful use, and patient safety as appropriate to each topic. • Include a paragraph describing what the future holds for each topic.

New chapters that were added to the second edition included those focusing on technology and patient safety, system development life cycle, workflow analysis, gaming, simulation, and bioinformatics.

In the third edition, we reviewed and updated all of the chapters, reordered some chapters for better content flow, eliminated duplicated content, split the education and research content into two sections, integrated social media content, and added two new chapters: Data Mining as a Research Tool and The Art of Caring in Technology-Laden Environments.

In this fourth edition, we reviewed and updated all of the chapters based on technological advance- ments and changes to the healthcare arena, including reimbursement mechanisms for services. We have pared this edition down to 26 chapters from the previous edition’s 29; one chapter each was deleted from Sections II, V, and VII. Section I includes updates to the same five chapters on the building blocks of nurs- ing informatics, with extensive changes to Chapter 3, Computer Science and the Foundation of Knowledge Model. To improve flow, we combined content. In Section II, the previous four chapters were narrowed to three. New Chapters 6, History and Evolution of Nursing Informatics and 7, Nursing Informatics as

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a Specialty, were developed and appropriate material from previous Chapters 6, 7, and 8 were assimi- lated. This section ends with an updated Chapter 8, Legislative Aspects of Nursing Informatics: HITECH and HIPAA (formerly Chapter 9). Section III contains the same five chapters, although all were updated and Chapter 13, Workflow and Beyond Meaningful Use (formerly Chapter 14) now reflects the payment models and reimbursement issues that we are adjusting to after meaningful use has gone away. Section IV contains the same five chapters with updated content and some name changes to reflect the current status of informatics and healthcare. Chapter 15 was renamed to Informatics Tools to Promote Patient Safety and Quality Outcomes, and Chapter 16 has been changed to Patient Engagement and Connected Health. Section V went from three chapters to two chapters: Chapter 19 (formerly Chapter 20) was updated, while the new Chapter 20, Simulation, Game Mechanics, and Virtual Worlds in Nursing Education, had content from former Chapters 21 and 22 integrated during its development. Section VI was renamed to Research Applications of Nursing Informatics. It still has the same four chapters, which have been updated, but the first chapter in this section, 21, was renamed to reflect nursing research; its new name is Nursing Research: Data Collection, Processing, and Analysis. Section VII went from three chapters to two chapters. Because emerging technologies are discussed throughout the text, the chapter focusing specifically on that was removed. The two chapters that remain are Chapter 25, The Art of Caring in Technology-Laden Environ- ments, and the new Chapter 26, Nursing Informatics and Knowledge Management. In addition, the ancil- lary materials have been updated and enhanced to include competency-based self-assessments and mapping the content to the current NI standards.

We believe that this text provides a comprehensive elucidation of this exciting field. Its theoretical under- pinning is the Foundation of Knowledge model. This model is introduced in its entirety in the first chapter (Nursing Science and the Foundation of Knowledge), which discusses nursing science and its relationship to NI. We believe that humans are organic information systems that are constantly acquiring, processing, and generating information or knowledge in both their professional and personal lives. It is their high degree of knowledge that characterizes humans as extremely intelligent, organic machines. Individuals have the ability to manage knowledge—an ability that is learned and honed from birth. We make our way through life inter- acting with our environment and being inundated with information and knowledge. We experience our envi- ronment and learn by acquiring, processing, generating, and disseminating knowledge. As we interact in our environment, we acquire knowledge that we must process. This processing effort causes us to redefine and re- structure our knowledge base and generate new knowledge. We then share (disseminate) this new knowledge and receive feedback from others. The dissemination and feedback initiate this cycle of knowledge over again, as we acquire, process, generate, and disseminate the knowledge gained from sharing and re-exploring our own knowledge base. As others respond to our knowledge dissemination and we acquire new knowledge, we engage in rethinking and reflecting on our knowledge, processing, generating, and then disseminating anew.

The purpose of this text is to provide a set of practical and powerful tools to ensure that the reader gains an understanding of NI and moves from information through knowledge to wisdom. Defining the demands of nurses and providing tools to help them survive and succeed in the Knowledge Era remains a major challenge. Exposing nursing students and nurses to the principles and tools used in NI helps to prepare them to meet the challenge of practicing nursing in the Knowledge Era while striving to improve patient care at all levels.

The text provides a comprehensive framework that embraces knowledge so that readers can develop their knowledge repositories and the wisdom necessary to act on and apply that knowledge. The text is divided into seven sections.

• Section I, Building Blocks of Nursing Informatics, covers the building blocks of NI: nursing science, information science, computer science, cognitive science, and the ethical management of information.

• Section II, Perspectives on Nursing Informatics, provides readers with a look at various viewpoints on NI and NI practice as described by experts in the field.

Preface xvii

 

 

• Section III, Nursing Informatics Administrative Applications: Precare and Care Support, covers important functions of administrative applications of NI.

• Section IV, Nursing Informatics Practice Applications: Care Delivery, covers healthcare delivery applications including electronic health records (EHRs), clinical information systems, telehealth, patient safety, patient and community education, and care management.

• Section V, Education Applications of Nursing Informatics, presents subject matter on how informat- ics supports nursing education.

• Section VI, Research Applications of Nursing Informatics, covers informatics tools to support nursing research, including data mining and bioinformatics.

• Section VII, Imagining the Future of Nursing Informatics, focuses on the future of NI, emphasizes the need to preserve caring functions in technology-laden environments, and reviews the relationship of nursing informatics to organizational knowledge management.

The introduction to each section explains the relationship between the content of that section and the Foundation of Knowledge model. This text places the material within the context of knowledge acqui- sition, processing, generation, and dissemination. It serves both nursing students (BS to DNP/PhD) and professionals who need to understand, use, and evaluate NI knowledge. As nursing professors, our major responsibility is to prepare the practitioners and leaders in the field. Because NI permeates the entire scope of nursing (practice, administration, education, and research), nursing education curricula must include NI. Our primary objective is to develop the most comprehensive and user-friendly NI text on the market to prepare nurses for current and future practice challenges. In particular, this text provides a solid ground- work from which to integrate NI into practice, education, administration, and research.

Goals of this text are as follows:

• Impart core NI principles that should be familiar to every nurse and nursing student • Help the reader understand knowledge and how it is acquired, processed, generated, and

disseminated • Explore the changing role of NI professionals • Demonstrate the value of the NI discipline as an attractive field of specialization

Meeting these goals will help nurses and nursing students understand and use fundamental NI princi- ples so that they efficiently and effectively function as current and future nursing professionals to enhance the nursing profession and improve the quality of health care. The overall vision, framework, and peda- gogy of this text offer benefits to readers by highlighting established principles while drawing out new ones that continue to emerge as nursing and technology evolve.

xviii Preface

 

 

Acknowledgments

We are deeply grateful to the contributors who provided this text with a richness and diversity of content that we could not have captured alone. Joan Humphrey provided social media content integrated throughout the text. We especially wish to acknowledge the superior work of Alicia Mastrian, graphic designer of the Foundation of Knowledge model, which serves as the theoretical framework on which this text is anchored. We could never have completed this project without the dedicated and patient efforts of the Jones & Bartlett Learning staff, especially Amanda Martin, Emma Huggard, and Christina Freitas, all of whom fielded our questions and concerns in a very professional, respectful, and timely manner.

Dee acknowledges the undying love, support, patience, and continued encouragement of her best friend and husband, Craig, and her son, Craig, who has made her so very proud. She sincerely thanks her cousins Camille, Glenn, Mary Jane, and Sonny, and her dear friends for their support and encouragement, espe- cially Renee.

Kathy acknowledges the loving support of her family: husband Chip; children Ben and Alicia; sisters Carol and Sue; and parents Robert and Rosalie Garver. She dedicates her work on this edition to her dad, Robert, who died September 17, 2016. Kathy also acknowledges those friends who understand the impor- tance of validation, especially Katie, Lisa, Kathy, Maureen, Anne, Barbara, and Sally.

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This text provides an overview of nursing informatics from the perspective of diverse experts in the field, with a focus on nursing informatics and the Foundation of Knowledge model. We want our readers and students to focus on the relationship of knowledge to informatics and to embrace and maintain the caring functions of nursing—messages all too often lost in the romance with technology. We hope you enjoy the text!

Authors’ Note

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Contributors

Ida Androwich, PhD, RN, BC, FAAN Loyola University Chicago School of Nursing Maywood, IL

Emily Barey, MSN, RN Director of Nursing Informatics Epic Systems Corporation Madison, WI

Lisa Reeves Bertin, BS, EMBA Pennsylvania State University Sharon, PA

Brett Bixler, PhD Pennsylvania State University University Park, PA

Jennifer Bredemeyer, RN Loyola University Chicago School of Nursing Skokie, IL

Steven Brewer, PhD Assistant Professor, Administration of Justice Pennsylvania State University Sharon, PA

Sylvia M. DeSantis, MA Pennsylvania State University University Park, PA

Judith Effken, PhD, RN, FACMI University of Arizona College of Nursing Tucson, AZ

Nedra Farcus, MSN, RN Retired from Pennsylvania State University, Altoona Altoona, PA

Kathleen M. Gialanella, JD, RN, LLM Law Offices Westfield, NJ Associate Adjunct Professor Teachers College, Columbia University New York, NY Adjunct Professor Seton Hall University, College of Nursing &

School of Law South Orange & Newark, NJ

Denise Hammel-Jones, MSN, RN-BC, CLSSBB Greencastle Associates Consulting Malvern, PA

Nicholas Hardiker, PhD, RN Senior Research Fellow University of Salford School of Nursing & Midwifery Salford, UK

Glenn Johnson, MLS Pennsylvania State University University Park, PA

June Kaminski, MSN, RN Kwantlen University College Surrey, British Columbia, Canada

Julie Kenney, MSN, RNC-OB Clinical Analyst Advocate Health Care Oak Brook, IL

Margaret Ross Kraft, PhD, RN Loyola University Chicago School of Nursing Maywood, IL

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Wendy L. Mahan, PhD, CRC, LPC Pennsylvania State University University Park, PA

Heather McKinney, PhD Pennsylvania State University University Park, PA

Nickolaus Miehl, MSN, RN Oregon Health Sciences University Monmouth, OR

Lynn M. Nagle, PhD, RN Assistant Professor University of Toronto Toronto, Ontario, Canada

Ramona Nelson, PhD, RN-BC, FAAN, ANEF Professor Emerita, Slippery Rock University President, Ramona Nelson Consulting Pittsburgh, PA

Nancy Staggers, PhD, RN, FAAN Professor, Informatics University of Maryland Baltimore, MD

Jeff Swain Instructional Designer Pennsylvania State University University Park, PA

Denise D. Tyler, MSN/MBA, RN-BC Implementation Specialist Healthcare Provider, Consulting ACS, a Xerox Company Dearborn, MI

The Editors also acknowledge the work of the following first edition contributors (original contributions edited by McGonigle and Mastrian for second edition):

Kathleen Albright, BA, RN Strategic Account Manager at GE Healthcare Philadelphia, PA

Schuyler F. Hoss, BA Northwest Healthcare Management Vancouver, WA

Audrey Kinsella, MA, MS Information for Tomorrow Telehealth Planning Services Asheville, NC

Peter J. Murray, PhD, RN, FBCS Coachman’s Cottage Nocton, Lincoln, UK

Susan M. Paschke, MSN, RN The Cleveland Clinic Cleveland, OH

Sheldon Prial, RPH, BS Pharmacy Sheldon Prial Consultance Melbourne, FL

Jackie Ritzko Pennsylvania State University Hazelton, PA

Marianela Zytkowsi, MSN, RN The Cleveland Clinic Cleveland, OH

xxii Contributors

 

 

section i

Building Blocks of Nursing Informatics Chapter 1 Nursing Science and the Foundation of Knowledge

Chapter 2 Introduction to Information, Information Science, and Information Systems

Chapter 3 Computer Science and the Foundation of Knowledge Model

Chapter 4 Introduction to Cognitive Science and Cognitive Informatics

Chapter 5 Ethical Applications of Informatics

 

 

Nursing professionals are information-dependent knowledge workers. As health care continues to evolve in an increasingly competitive information marketplace, professionals—that is, the knowledge workers—must be well prepared to make significant contributions by harnessing appropriate and timely information. Nurs- ing informatics (NI), a product of the scientific synthesis of information in nursing, encompasses concepts from computer science, cognitive science, information science, and nursing science. NI continues to evolve as more and more professionals access, use, and develop the information, computer, and cognitive sciences necessary to advance nursing science for the betterment of patients and the profession. Regard- less of their future roles in the healthcare milieu, it is clear that nurses need to understand the ethical application of computer, information, and cognitive sciences to advance nursing science.

To implement NI, one must view it from the perspective of both the current healthcare delivery system and specific, individual organizational needs, while antici- pating and creating future applications in both the healthcare system and the nursing profession. Nursing professionals should be expected to discover opportunities to use NI, participate in the design of solutions, and be challenged to identify, develop, evaluate, modify, and enhance applications to improve patient care. This text is designed to provide the reader with the information and knowledge needed to meet this expectation.

Section I presents an overview of the building blocks of NI: nursing, information, computer, and cognitive sciences. Also included in this section is a chapter on ethical applications of healthcare informatics. This section lays the foundation for the remainder of the book.

The Nursing Science and the Foundation of Knowledge chapter describes nurs- ing science and introduces the Foundation of Knowledge model as the conceptual framework for the book. In this chapter, a clinical case scenario is used to illustrate the concepts central to nursing science. A definition of nursing science is also derived from the American Nurses Association’s definition of nursing. Nursing science is the ethical application of knowledge acquired through education, research, and practice to provide services and interventions to patients to maintain, enhance, or restore their health, and to acquire, process, generate, and disseminate nursing knowledge to advance the nursing profession. Information is a central concept and health care’s most valuable resource. Information science and systems, together with computers, are constantly changing the way healthcare organizations conduct their business. This will continue to evolve.

2 seCtIoN I Building Blocks of Nursing Informatics

 

 

To prepare for these innovations, the reader must understand fundamental infor- mation and computer concepts, covered in the Introduction to Information, Informa- tion Science, and Information Systems and Computer Science and the Foundation of Knowledge Model chapters, respectively. Information science deals with the in- terchange (or flow) and scaffolding (or structure) of information and involves the application of information tools for solutions to patient care and business problems in health care. To be able to use and synthesize information effectively, an individual must be able to obtain, perceive, process, synthesize, comprehend, convey, and man- age the information. Computer science deals with understanding the development, design, structure, and relationship of computer hardware and software. This science offers extremely valuable tools that, if used skillfully, can facilitate the acquisition and manipulation of data and information by nurses, who can then synthesize these resources into an ever-evolving knowledge and wisdom base. This not only facilitates professional development and the ability to apply evidence-based practice decisions within nursing care, but, if the results are disseminated and shared, can also advance the profession’s knowledge base. The development of knowledge tools, such as the automation of decision making and strides in artificial intelligence, has altered the understanding of knowledge and its representation. The ability to structure knowl- edge electronically facilitates the ability to share knowledge structures and enhance collective knowledge.

As discussed in the Introduction to Cognitive Science and Cognitive Informatics chapter, cognitive science deals with how the human mind functions. This science encompasses how people think, understand, remember, synthesize, and access stored information and knowledge. The nature of knowledge, including how it is developed, used, modified, and shared, provides the basis for continued learning and intellectual growth.

The Ethical Applications of Informatics chapter focuses on ethical issues associ- ated with managing private information with technology and provides a framework for analyzing ethical issues and supporting ethical decision making.

The material within this book is placed within the context of the Foundation of Knowledge model (shown in Figure I-1 and periodically throughout the book, but more fully introduced and explained in the Nursing Science and the Foundation of Knowledge chapter). The Foundation of Knowledge model is used throughout the text to illustrate how knowledge is used to meet the needs of healthcare delivery sys- tems, organizations, patients, and nurses. It is through interaction with these building blocks—the theories, architecture, and tools—that one acquires the bits and pieces of

seCtIoN I Building Blocks of Nursing Informatics 3

 

 

data necessary, processes these into information, and generates and disseminates the resulting knowledge. Through this dynamic exchange, which includes feedback, indi- viduals continue the interaction and use of these sciences to input or acquire, process, and output or disseminate generated knowledge. Humans experience their environ- ment and learn by acquiring, processing, generating, and disseminating knowledge. When they then share (disseminate) this new knowledge and receive feedback on the knowledge they have shared, the feedback initiates the cycle of knowledge all over again. As individuals acquire, process, generate, and disseminate knowledge, they are motivated to share, rethink, and explore their own knowledge base. This complex process is captured in the Foundation of Knowledge model. Throughout the chapters in the Building Blocks of Nursing Informatics section, readers are challenged to think about how the model can help them to understand the ways in which they acquire, process, generate, disseminate, and then receive and process feedback on their new knowledge of the building blocks of NI.

4 seCtIoN I Building Blocks of Nursing Informatics

 

 

Figure I-1 Foundation of Knowledge Model Designed by Alicia Mastrian

KA – Knowledge acquisition KD – Knowledge dissemination KG – Knowledge generation KP – Knowledge processing

Information

Information

Information Information

Data

Data

Bytes Bytes

Bytes

Bits

Bits Data

Bits

Bytes

Bytes Bytes Bits

Bits Data Information

Feedback

KA KP

KD

KG

Feedback

seCtIoN I Building Blocks of Nursing Informatics 5

 

 

Key terms » Borrowed theory » Building blocks » Clinical

databases » Clinical practice

guidelines » Conceptual

framework

» Data » Data mining » Evidence » Feedback » Foundation of

Knowledge model » Information » Knowledge

» Knowledge acquisition

» Knowledge dissemination

» Knowledge generation

» Knowledge processing

» Knowledge worker » Nursing

informatics » Nursing science » Nursing theory » Relational

database » Transparent wisdom

1. Define nursing science and its relationship to various nursing roles and nursing informatics.

2. Introduce the Foundation of Knowledge model as the organizing conceptual framework for the text.

3. Explain the relationships among knowledge acquisition, knowledge processing, knowledge generation, knowledge dissemination, and wisdom.

objectives

 

 

Introduction Nursing informatics has been traditionally defined as a specialty that integrates nursing science, computer science, and information science to manage and communicate data, information, knowledge, and wisdom in nursing practice. This chapter focuses on nursing science as one of the building blocks of nurs- ing informatics. As depicted in Figure 1-1, the  traditional definition of nursing

Nursing science and the Foundation of Knowledge Dee McGonigle and Kathleen Mastrian

Figure 1-1 Building Blocks of Nursing Informatics

Nursing Informatics

Nursing Science

Computer Science

Cognitive Science

Information Science

7

CHAPteR 1

 

 

informatics is extended to include cognitive science. The Foundation of Knowledge model is also introduced as the organizing conceptual framework of this text, and the model is tied to nursing science and the practice of nursing informatics. To lay the groundwork for this discussion, consider the following patient scenario:

Tom H. is a registered nurse who works in a very busy metropolitan hos- pital emergency room. He has just admitted a 79-year-old man whose wife brought him to the hospital because he is having trouble breathing. Tom immediately clips a pulse oximeter to the patient’s finger and performs a very quick assessment of the patient’s other vital signs. He discovers a rapid pulse rate and a decreased oxygen saturation level in addition to the rapid and labored breathing. Tom determines that the patient is not in immedi- ate danger and that he does not require intubation. Tom focuses his initial attention on easing the patient’s labored breathing by elevating the head of the bed and initiating oxygen treatment; he then hooks the patient up to a heart monitor. Tom continues to assess the patient’s breathing status as he performs a head-to-toe assessment of the patient that leads to the nursing diagnoses and additional interventions necessary to provide comprehensive care to this patient.

Consider Tom’s actions and how and why he intervened as he did. Tom relied on the immediate data and information that he acquired during his initial rapid assessment to deliver appropriate care to his patient. Tom also used tech- nology (a pulse oximeter and a heart monitor) to assist with and support the delivery of care. What is not immediately apparent, and some would argue is transparent (done without conscious thought), is the fact that during the rapid assessment, Tom reached into his knowledge base of previous learning and experiences to direct his care, so that he could act with transparent wisdom. He used both nursing theory and borrowed theory to inform his practice. Tom certainly used nursing process theory, and he may have also used one of several other nurs- ing theories, such as Rogers’s science of unitary human beings, Orem’s theory of self-care deficit, or Roy’s adaptation theory. In addition, Tom may have applied his knowledge from some of the basic sciences, such as anatomy, physiology, psy- chology, and chemistry, as he determined the patient’s immediate needs. Informa- tion from Maslow’s hierarchy of needs, Lazarus’s transaction model of stress and coping, and the health belief model may have also helped Tom practice profes- sional nursing. He gathered data, and then analyzed and interpreted those data to form a conclusion—the essence of science. Tom has illustrated the practical aspects of nursing science.

The American Nurses Association (2016) defines nursing in this way: “Nursing is the protection, promotion, and optimization of health and abilities, prevention of illness and injury, facilitation of healing, alleviation of suffering through the diagnosis and treatment of human response, and advocacy in the care of individu- als, families, groups, communities, and populations” (para. 1). Thus the focus of nursing is on human responses to actual or potential health problems and advo- cacy for various clients. These human responses are varied and may change over

8 CHAPteR 1 Nursing Science and the Foundation of Knowledge

 

 

time in a single case. Nurses must possess the technical skills to manage equip- ment and perform procedures, the interpersonal skills to interact appropriately with people, and the cognitive skills to observe, recognize, and collect data; ana- lyze and interpret data; and reach a reasonable conclusion that forms the basis of a decision. At the heart of all of these skills lies the management of data and information. This definition of nursing science focuses on the ethical application of knowledge acquired through education, research, and practice to provide ser- vices and interventions to patients to maintain, enhance, or restore their health and to acquire, process, generate, and disseminate nursing knowledge to advance the nursing profession.

Nursing is an information-intensive profession. The steps of using information, applying knowledge to a problem, and acting with wisdom form the basis of nursing practice science. Information is composed of data that were processed using knowledge. For information to be valuable, it must be accessible, accurate, timely, complete, cost-effective, flexible, reliable, relevant, simple, verifiable, and secure. Knowledge is the awareness and understanding of a set of information and ways that information can be made useful to support a specific task or arrive at a decision. In the case scenario, Tom used accessible, accurate, timely, relevant, and verifiable data and information. He compared that data and information to his knowledge base of previous experiences to determine which data and information were relevant to the current case. By applying his previous knowledge to data, he converted those data into information, and information into new knowledge—that is, an understanding of which nursing interventions were appropriate in this case. Thus information is data made functional through the application of knowledge.

Humans acquire data and information in bits and pieces and then transform the information into knowledge. The information-processing functions of the brain are frequently compared to those of a computer, and vice versa (see a dis- cussion of cognitive informatics for more information). Humans can be thought of as organic information systems that are constantly acquiring, processing, and generating information or knowledge in their professional and personal lives. They have an amazing ability to manage knowledge. This ability is learned and honed from birth as individuals make their way through life interacting with the environment and being inundated with data and information. Each person experi- ences the environment and learns by acquiring, processing, generating, and dis- seminating knowledge.

Tom, for example, acquired knowledge in his basic nursing education program and continues to build his foundation of knowledge by engaging in such activities as reading nursing research and theory articles, attending continuing education programs, consulting with expert colleagues, and using clinical databases and clinical practice guidelines. As he interacts in the environment, he acquires knowledge that must be processed. This processing effort causes him to redefine and restructure his knowledge base and generate new knowledge. Tom can then share (disseminate) this new knowledge with colleagues, and he may receive feedback on the knowledge that he shares. This dissemination and feedback builds the knowledge foundation anew

Introduction 9

 

 

as Tom acquires, processes, generates, and disseminates new knowledge as a result of his interactions. As others respond to his knowledge dissemination and he acquires yet more knowledge, he is engaged to rethink, reflect on, and re-explore his knowledge acquisition, leading to further processing, generating, and then disseminating knowledge. This ongoing process is captured in the Foundation of Knowledge model, which is used as an organizing framework for this text.

At its base, the model contains bits, bytes (a computer term used to quantify data), data, and information in a random representation. Growing out of the base are separate cones of light that expand as they reflect upward; these cones represent knowledge acquisition, knowledge generation, and knowledge dissemination. At the in- tersection of the cones and forming a new cone is knowledge processing. Encircling and cutting through the knowledge cones is feedback that acts on and may transform any or all aspects of knowledge represented by the cones. One should imagine the model as a dynamic figure in which the cones of light and the feedback rotate and interact rather than remain static. Knowledge acquisition, knowledge generation, knowledge dissemination, knowledge processing, and feedback are constantly evolving for nurse scientists. The transparent effect of the cones is deliberate and is intended to suggest that as knowledge grows and expands, its use becomes more transparent—a person uses this knowledge during practice without even being consciously aware of which aspect of knowledge is being used at any given moment.

Experienced nurses, thinking back to their novice years, may recall feeling like their head was filled with bits of data and information that did not form any type of cohesive whole. As the model depicts, the processing of knowledge begins a bit later (imagine a timeline applied vertically) with early experiences on the bottom and ex- pertise growing as the processing of knowledge ensues. Early on in nurses’ education, conscious attention is focused mainly on knowledge acquisition, and beginning nurses depend on their instructors and others to process, generate, and disseminate knowl- edge. As nurses become more comfortable with the science of nursing, they begin to take over some of the other Foundation of Knowledge functions. However, to keep up with the explosion of information in nursing and health care, they must continue to rely on the knowledge generation of nursing theorists and researchers and the dis- semination of their work. In this sense, nurses are committed to lifelong learning and the use of knowledge in the practice of nursing science.

The Foundation of Knowledge model (Figure 1-2) permeates this text, reflecting the understanding that knowledge is a powerful tool and that nurses focus on informa- tion as a key building block of knowledge. The application of the model is described to help the reader understand and appreciate the foundation of knowledge in nursing science and see how it applies to nursing informatics. All of the various nursing roles (practice, administration, education, research, and informatics) involve the science of nursing. Nurses are knowledge workers, working with information and generating information and knowledge as a product. They are knowledge acquirers, provid- ing convenient and efficient means of capturing and storing knowledge. They are knowledge users, meaning individuals or groups who benefit from valuable, viable knowledge. Nurses are knowledge engineers, designing, developing, implementing, and maintaining knowledge. They are knowledge managers, capturing and processing collective expertise and distributing it where it can create the largest benefit. Finally,

10 CHAPteR 1 Nursing Science and the Foundation of Knowledge

 

 

they are knowledge developers and generators, changing and evolving knowledge based on the tasks at hand and the information available.

In the case scenario, at first glance one might label Tom as a knowledge worker, a knowledge acquirer, and a knowledge user. However, stopping here might sell Tom short in his practice of nursing science. Although he acquired and used knowledge to help him achieve his work, he also processed the data and information he collected to develop a nursing diagnosis and a plan of care. The knowledge stores Tom used to develop and glean knowledge from valuable information are generative (having the ability to originate and produce or generate) in nature. For example, Tom may have learned something new about his patient’s culture from the patient or his wife that he will file away in the knowledge repository of his mind to be used in another similar situation. As he compares this new cultural information to what he already knows, he may gain insight into the effect of culture on a patient’s response to illness. In this sense, Tom is a knowledge generator. If he shares this newly acquired knowledge with another practitioner, and as he records his observations and his conclusions, he is then disseminating knowledge. Tom also uses feedback from the various technologies he has applied to monitor his patient’s status. In addition, he may rely on feedback from laboratory reports or even other practitioners to help him rethink, revise, and apply the knowledge about this patient that he is generating.

Figure 1-2 Foundation of Knowledge Model Designed by Alicia Mastrian

KA – Knowledge acquisition KD – Knowledge dissemination KG – Knowledge generation KP – Knowledge processing

Information

Information

Information Information

Data

Data

Bytes Bytes

Bytes

Bits

Bits Data

Bits

Bytes

Bytes Bytes Bits

Bits Data Information

Feedback

KA KP

KD

KG

Feedback

Introduction 11

 

 

To have ongoing value, knowledge must be viable. Knowledge viability refers to applications (most technology based) that offer easily accessible, accurate, and timely information obtained from a variety of resources and methods and presented in a manner so as to provide the necessary elements to generate new knowledge. In the case scenario, Tom may have felt the need to consult an electronic database or a clinical guidelines repository that he has downloaded on his tablet or smartphone, or that resides in the emergency room’s networked computer system, to assist him in the development of a comprehensive care plan for his patient. In this way, Tom uses tech- nology and evidence to support and inform his practice. It is also possible in this sce- nario that an alert might appear in the patient’s electronic health record or the clinical information system (CIS) reminding Tom to ask about influenza and pneumonia vac- cines. Clinical information technologies that support and inform nursing practice and nursing administration are an important part of nursing informatics.

This text provides a framework that embraces knowledge so that readers can develop the wisdom necessary to apply what they have learned. Wisdom is the applica- tion of knowledge to an appropriate situation. In the practice of nursing science, one expects actions to be directed by wisdom. Wisdom uses knowledge and experience to heighten common sense and insight to exercise sound judgment in practical mat- ters. It is developed through knowledge, experience, insight, and reflection. Wisdom is sometimes thought of as the highest form of common sense, resulting from accumu- lated knowledge or erudition (deep, thorough learning) or enlightenment (education that results in understanding and the dissemination of knowledge). It is the ability to apply valuable and viable knowledge, experience, understanding, and insight while being prudent and sensible. Knowledge and wisdom are not synonymous: Knowledge abounds with others’ thoughts and information, whereas wisdom is focused on one’s own mind and the synthesis of experience, insight, understanding, and knowledge. Wisdom has been called the foundation of the art of nursing.

Some nursing roles might be viewed as more focused on some aspects rather than other aspects of the foundation of knowledge. For example, some might argue that nurse educators are primarily knowledge disseminators and that nurse researchers are knowledge generators. Although the more frequent output of their efforts can certainly be viewed in this way, it is important to realize that nurses use all of the aspects of the Foundation of Knowledge model regardless of their area of practice. For nurse educators to be effective, they must be in the habit of constantly building and rebuilding their foundation of knowledge about nursing science. In addition, as they develop and implement curricular innovations, they must evaluate the effective- ness of those changes. In some cases, they use formal research techniques to achieve this goal and, therefore, generate knowledge about the best and most effective teach- ing strategies. Similarly, nurse researchers must acquire and process new knowledge as they design and conduct their research studies. All nurses have the opportunity to be involved in the formal dissemination of knowledge via their participation in pro- fessional conferences, either as presenters or as attendees. In addition, some nurses disseminate knowledge by formal publication of their ideas. In the cases of conference presentation and publication, nurses may receive feedback that stimulates rethinking about the knowledge they have generated and disseminated, in turn prompting them to acquire and process data and information anew.

12 CHAPteR 1 Nursing Science and the Foundation of Knowledge

 

 

All nurses, regardless of their practice arena, must use informatics and technology to inform and support that practice. The case scenario discussed Tom’s use of vari- ous monitoring devices that provide feedback on the physiologic status of the patient. It was also suggested that Tom might consult a clinical database or nursing practice guidelines residing on a tablet or smartphone, in the cloud (a virtual information storage system), or on a clinical agency network as he develops an appropriate plan of action for his nursing interventions. Perhaps the CIS in the agency supports the collection of data about patients in a relational database, providing an opportunity for data mining by nursing administrators or nurse researchers. In this way, administra- tors and researchers can glean information about best practices and determine which improvements are necessary to deliver the best and most effective nursing care (Swan, Lang, & McGinley, 2004).

The future of nursing science and nursing informatics is closely associated with nursing education and nursing research. Skiba (2007) suggested that techno-savvy and well-informed faculty who can demonstrate the appropriate use of technologies to enhance the delivery of nursing care are needed. Along those lines, Whitman-Price, Kennedy, and Godwin (2012) conducted research among senior nursing students to determine perceptions of personal phone use to access healthcare information dur- ing clinical. Their study indicated that ready access to electronic resources enhanced clinical decision making and confidence in patient care. Girard (2007) discussed cutting-edge operating room technologies, such as nanosurgery using nanorobots, smart fabrics that aid in patient assessment during surgery, biopharmacy techniques for the safe and effective delivery of anesthesia, and virtual reality training. She made an extremely provocative point about nursing education: “Educators will need to expand their knowledge and teach for the future and not the past. They must take heed that the old tried-and-true nursing education methods and curriculum that has lasted 100 years will have to change, and that change will be mandated for all areas of nursing” (p. 353). Bassendowski (2007) specifically addressed the potential for the generation of knowledge in educational endeavors as faculty apply new technologies to teaching and the focus shifts away from individual to group instruction that pro- motes sharing and processing of knowledge.

Several key national groups continue to promote the inclusion of informatics content in nursing education programs. These initiatives include the Vision Series by the National League for Nursing (NLN; 2015); recommendations in the Quality and Safety Education for Nurses (QSEN) learning modules (2014a); the Technology Informatics Guiding Education Reform (TIGER) Initiative (Healthcare Information and Management Systems Society, 2016); and Nursing Informatics Deep Dive by the American Association of Colleges of Nursing (AACN; 2016). These organizations focus on the need to integrate informatics competencies into nursing curricula to prepare future nurses for the tasks of managing data, information, and knowledge; alleviating errors and promoting safety; supporting decision making; and improving the quality of patient care. Nurse educators are challenged to prepare informatics- competent nurses who can practice safely in technology-laden settings.

The TIGER (2007) initiative identified steps toward a 10-year vision and stated a key purpose: “to create a vision for the future of nursing that bridges the quality chasm with information technology, enabling nurses to use informatics in practice

Introduction 13

 

 

and education to provide safer, higher-quality patient care” (p. 4). The pillars of the TIGER vision include the following:

• Management and Leadership: Revolutionary leadership that drives, empowers, and executes the transformation of health care.

• Education: Collaborative learning communities that maximize the possibilities of technology toward knowledge development and dissemination, driving rapid deployment and implementation of best practices.

• Communication and Collaboration: Standardized, person-centered, technology- enabled processes to facilitate teamwork and relationships across the continuum of care.

• Informatics Design: Evidence-based, interoperable intelligence systems that sup- port education and practice to foster quality care and safety.

• Information Technology: Smart, people-centered, affordable technologies that are universal, useable, useful, and standards based.

• Policy: Consistent, incentives-based initiatives (organizational and governmen- tal) that support advocacy and coalition-building, achieving and resourcing an ethical culture of safety.

• Culture: A respectful, open system that leverages technology and informatics across multiple disciplines in an environment where all stakeholders trust each other to work together toward the goal of high quality and safety (p. 4).

The Essentials of Baccalaureate Education for Professional Nursing Practice (AACN, 2008, pp. 18–19) includes the following technology-related outcomes for baccalaureate nursing graduates:

1. Demonstrate skills in using patient care technologies, information systems, and communication devices that support safe nursing practice.

2. Use telecommunication technologies to assist in effective communication in a variety of healthcare settings.

3. Apply safeguards and decision-making support tools embedded in patient care technologies and information systems to support a safe practice environment for both patients and healthcare workers.

4. Understand the use of CIS to document interventions related to achieving nurse-sensitive outcomes.

5. Use standardized terminology in a care environment that reflects nursing’s unique contribution to patient outcomes.

6. Evaluate data from all relevant sources, including technology, to inform the delivery of care.

7. Recognize the role of information technology in improving patient care out- comes and creating a safe care environment.

8. Uphold ethical standards related to data security, regulatory requirements, con- fidentiality, and clients’ right to privacy.

9. Apply patient care technologies as appropriate to address the needs of a diverse patient population.

10. Advocate for the use of new patient care technologies for safe, quality care.

14 CHAPteR 1 Nursing Science and the Foundation of Knowledge

 

 

11. Recognize that redesign of workflow and care processes should precede imple- mentation of care technology to facilitate nursing practice.

12. Participate in the evaluation of information systems in practice settings through policy and procedure development.

The report suggests the following sample content for achieving these student out- comes (AACN, 2008, pp. 19–20):

• Use of patient care technologies (e.g., monitors, pumps, computer-assisted devices)

• Use of technology and information systems for clinical decision making • Computer skills that may include basic software, spreadsheet, and healthcare

databases • Information management for patient safety • Regulatory requirements through electronic data-monitoring systems • Ethical and legal issues related to the use of information technology, including

copyright, privacy, and confidentiality issues • Retrieval information systems, including access, evaluation of data, and applica-

tion of relevant data to patient care • Online literature searches • Technological resources for evidence-based practice • Web-based learning and online literature searches for self and patient use • Technology and information systems safeguards (e.g., patient monitoring, equip-

ment, patient identification systems, drug alerts and IV systems, and bar coding) • Interstate practice regulations (e.g., licensure, telehealth) • Technology for virtual care delivery and monitoring • Principles related to nursing workload measurement and resources and informa-

tion systems • Information literacy • Electronic health record and physician order entry • Decision support tools • Role of the nurse informaticist in the context of health informatics and informa-

tion systems

The Informatics and Healthcare Technologies Essentials of Master’s Education in Nursing includes the following elements:

Essential V: Informatics and Healthcare Technologies Rationale Informatics and healthcare technologies encompass five broad areas:

• Use of patient care and other technologies to deliver and enhance care • Communication technologies to integrate and coordinate care • Data management to analyze and improve outcomes of care • Health information management for evidence-based care and health

education • Facilitation and use of electronic health records to improve patient care

(AACN, 2011, pp. 17–18)

Introduction 15

 

 

INFoRMAtICs

Knowledge skills Attitudes

Explain why information and technology skills are essential for safe patient care

Seek education about how information is managed in care settings before providing care

Apply technology and information management tools to support safe processes of care

Appreciate the necessity for all health professionals to seek lifelong, continuous learning of information technology skills

Identify essential information that must be available in a common database to support patient care

Contrast benefits and limitations of different communication technologies and their impact on safety and quality

Navigate the electronic health record

Document and plan patient care in an electronic health record

Employ communication technologies to coordinate care for patients

Value technologies that support clinical decision making, error prevention, and care coordination

Protect the confidentiality of protected health information in electronic health records

Describe examples of how technology and information management are related to the quality and safety of patient care

Recognize the time, effort, and skill required for computers, databases, and other technologies to become reliable and effective tools for patient care

Respond appropriately to clinical decision-making supports and alerts

Use information management tools to monitor outcomes of care processes

Use high quality electronic sources of healthcare information

Value nurses’ involvement in design, selection, implementation, and evaluation of information technologies to support patient care

Definition: Use information and technology to communicate, manage knowledge, mitigate error, and support decision making.

Reproduced from Cronenwett, L., Sherwood, G., Barnsteiner J., Disch, J., Johnson, J., Mitchell, P., . . . Warren, J. (2007). Quality and safety education for nurses. Nursing Outlook, 55(3), 122–131. Copyright 2007, with permission from Elsevier.

Quality and safety education for Nurses As nursing science evolves, it is critical that patient care improves. Sometimes, un- fortunately, patient care is less-than-adequate and is unsafe. Therefore, quality and safety have become paramount. The QSEN Institute project seeks to prepare future nurses who will have the knowledge, skills, and attitudes (KSAs) necessary to con- tinuously improve the quality and safety of the healthcare systems within which they work.

Prelicensure informatics KSAs include the following (QSEN Institute, 2014c):

16 CHAPteR 1 Nursing Science and the Foundation of Knowledge

 

 

Graduate-level informatics KSAs include the following (QSEN Institute, 2014b):

INFoRMAtICs

Knowledge skills Attitudes

Contrast benefits and limitations of common information technology strategies used in the delivery of patient care

Evaluate the strengths and weaknesses of information systems used in patient care

Participate in the selection, design, implementation, and evaluation of information systems

Communicate the integral role of information technology in nurses’ work

Model behaviors that support implementation and appropriate use of electronic health records

Assist team members to adopt information technology by piloting and evaluating proposed technologies

Value the use of information and communication technologies in patient care

Formulate essential information that must be available in a common database to support patient care in the practice specialty

Evaluate benefits and limitations of different communication technologies and their impact on safety and quality

Promote access to patient care information for all professionals who provide care to patients

Serve as a resource for how to document nursing care at basic and advanced levels

Develop safeguards for protected health information

Champion communication technologies that support clinical decision making, error prevention, care coordination, and protection of patient privacy

Appreciate the need for consensus and collaboration in developing systems to manage information for patient care

Value the confidentiality and security of all patient records

Describe and critique taxonomic and terminology systems used in national efforts to enhance interoperability of information systems and knowledge management systems

Access and evaluate high quality electronic sources of healthcare information

Participate in the design of clinical decision-making supports and alerts

Search, retrieve, and manage data to make decisions using information and knowledge management systems

Anticipate unintended consequences of new technology

Value the importance of standardized terminologies in conducting searches for patient information

Appreciate the contribution of technological alert systems

Appreciate the time, effort, and skill required for computers, databases, and other technologies to become reliable and effective tools for patient care

Definition: Use information and technology to communicate, manage knowledge, mitigate error, and support decision making.

Reproduced from Cronenwett, L., Sherwood, G., Pohl, J., Barnsteiner J., Moore, D., Sullivan, D., . . . Warren, J. (2009). Quality and safety education for nurses. Nursing Outlook, 57(6), 338–348. Copyright 2009, with permission from Elsevier.

Quality and Safety Education for Nurses 17

 

 

This text is designed to include the necessary content to prepare nurses for prac- tice in the ever-changing and technology-laden healthcare environments. Informatics competence has been recognized as necessary in order to enhance clinical decision making and improve patient care for many years. This is evidenced by Goossen (2000), who reflected on the need for research in this area and believed that the focus of nursing informatics research should be on the structuring and processing of patient information and the ways that these endeavors inform nursing decision mak- ing in clinical practice. The increased use of technology to enhance nursing practice, nursing education, and nursing research will open new avenues for acquiring, pro- cessing, generating, and disseminating knowledge.

In the future, nursing research will make significant contributions to the devel- opment of nursing science. Technologies and translational research will abound, and clinical practices will continue to be evidence based, thereby improving patient outcomes and decreasing safety concerns. Schools of nursing will embrace nursing science as they strive to meet the needs of changing student populations and the increasing complexity of healthcare environments.

summary Nursing science influences all areas of nursing practice. This chapter provided an overview of nursing science and considered how nursing science relates to typical nursing practice roles, nursing education, informatics, and nursing research. The Foundation of Knowledge model was introduced as the organizing conceptual framework for this text. Finally, the relationship of nursing science to nursing informatics was discussed. In subsequent chapters the reader will learn more about how nursing informatics supports nurses in their many and varied roles. In  an ideal world, nurses would embrace nursing science as knowledge users, knowledge managers, knowledge developers, knowledge engineers, and knowl- edge workers.

tHoUGHt-PRoVoKING QUestIoNs

1. Imagine you are in a social situation and someone asks you, “What does a nurse do?” Think about how you will capture and convey the richness that is nursing science in your answer.

2. Choose a clinical scenario from your recent experience and analyze it using the Foundation of Knowledge model. How did you acquire knowledge? How did you process knowledge? How did you generate knowledge? How did you dis- seminate knowledge? How did you use feedback, and what was the effect of the feedback on the foundation of your knowledge?

18 CHAPteR 1 Nursing Science and the Foundation of Knowledge

 

 

References American Association of Colleges of Nursing (AACN). (2008, October 20). The essentials of

baccalaureate education for professional nursing practice. Retrieved from http://www.aacn .nche.edu/education-resources/BaccEssentials08.pdf

American Association of Colleges of Nursing (AACN). (2011, March 21). The essentials of master’s education in nursing. Retrieved from http://www.aacn.nche.edu/ education -resources/MastersEssentials11.pdf

American Association of Colleges of Nursing (AACN). (2016). Background and overview: Nursing informatics Deep Dive. Retrieved from http://www.aacn.nche.edu/qsen-informatics /background-overview

American Nurses Association. (2016). What is nursing? Retrieved from http://www.nursingworld .org/EspeciallyForYou/What-is-Nursing

Bassendowski, S. (2007). NursingQuest: Supporting an analysis of nursing issues. Journal of Nursing Education, 46(2), 92–95. Retrieved from Education Module database [document ID: 1210832211].

Cronenwett, L., Sherwood, G., Barnsteiner J., Disch, J., Johnson, J., Mitchell, P., . . . Warren, J. (2007). Quality and safety education for nurses. Nursing Outlook, 55(3), 122–131.

Girard, N. (2007). Science fiction comes to the OR. Association of Operating Room Nurses. AORN Journal, 86(3), 351–353. Retrieved from Health Module database [document ID: 1333149261].

Goossen, W. (2000). Nursing informatics research. Nurse Researcher, 8(2), 42. Retrieved from ProQuest Nursing & Allied Health Source database [document ID: 67258628].

Healthcare Information and Management Systems Society. (2016). The TIGER initiative. Retrieved from http://www.himss.org/professional-development/tiger-initiative

National League for Nursing (NLN). (2015). A vision for the changing faculty role: Preparing students for the technological world of health care. Retrieved from https://www.nln.org /docs/default-source/about/nln-vision-series-(position-statements)/a-vision-for-the-changing -faculty-role-preparing-students-for-the-technological-world-of-health-care.pdf?sfvrsn=0

Quality and Safety Information for Nurses (QSEN) Institute. (2014a). Courses: Learning modules. Retrieved from http://www.qsen.org/courses/learning-modules

QSEN Institute. (2014b). Graduate KSAs. Retrieved from http://www.qsen.org/competencies /graduate-ksas

QSEN Institute. (2014c). Pre-licensure KSAs. Retrieved from http://www.qsen.org/competencies /pre-licensure-ksas

Skiba, D. (2007). Faculty 2.0: Flipping the novice to expert continuum. Nursing Education Perspectives, 28(6), 342–344. Retrieved from ProQuest Nursing & Allied Health Source database [document ID: 1401240241].

Swan, B., Lang, N., & McGinley, A. (2004). Access to quality health care: Links between evidence, nursing language, and informatics. Nursing Economic$, 22(6), 325–332. Retrieved from Health Module database [document ID: 768191851].

Technology Informatics Guiding Education Reform. (2007). Evidence and informatics transforming nursing: 3-year action steps toward a 10-year vision. Retrieved from http:// www.aacn.nche.edu/education-resources/TIGER.pdf

Whitman-Price, R., Kennedy, L., & Godwin, C. (2012). Use of personal phones by senior nursing students to access health care information during clinical education: Staff nurses’ and students’ perceptions. Journal of Nursing Education, 51(11), 642–646.

References 19

 

 

Key Terms » Acquisition » Alert » Analysis » Chief information

officers » Chief technical

officers » Chief technology

officers » Cloud computing » Cognitive science » Communication

science » Computer-based

information systems » Computer science » Consolidated

Health Informatics » Data

» Dissemination » Document » Electronic health

records » Federal Health

Information Exchange

» Feedback » Health information

exchange » Health Level Seven » Indiana Health

Information Exchange

» Information » Information

science » Information

systems

» Information technology

» Input » Interfaces » Internet2 » Internet of

Things (IoT) » Knowledge » Knowledge worker » Library science » Massachusetts

Health Data Consortium

» National Health Information Infrastructure

» National Health Information Network

» New England Health EDI Network

» Next-Generation Internet

» Outcome » Output » Processing » Rapid

Syndromic Validation Project

» Report » Social sciences » Stakeholders » Summaries » Synthesis » Telecommunications

1. Reflect on the progression from data to informa- tion to knowledge.

2. Describe the term information. 3. Assess how information is acquired. 4. Explore the characteristics of quality information. 5. Describe an information system. 6. Explore data acquisition or input and processing

or retrieval, analysis, and synthesis of data.

7. Assess output or reports, documents, summaries, alerts, and outcomes.

8. Describe information dissemination and feedback. 9. Define information science.

10. Assess how information is processed. 11. Explore how knowledge is generated in informa-

tion science.

Objectives

 

 

Introduction This chapter explores information, information systems (ISs), and infor­ mation science as one of the building blocks of informatics. (Refer to Figure 2-1.) The key word here, of course, is information. Information and information processing are central to the work of health care. A healthcare professional is known as a knowledge worker because he or she deals with and processes information on a daily basis to make it meaningful and inform his or her practice.

Healthcare information is complex, and many concerns and issues arise with healthcare information, such as ownership, access, disclosure, exchange, security, privacy, disposal, and dissemination. The widespread implementation of electronic health records (EHRs) has promoted collabora­ tion among public­ and private­sector stakeholders on a wide­ranging va­ riety of healthcare information solutions. Some of these initiatives include Health Level Seven (HL7), the eGov initiative by Consolidated Health Informat- ics (CHI), the National Health Information Infrastructure (NHII), the National Health Information Network (NHIN), Next-Generation Internet (NGI), Internet2, and iHealth record. There are also health information exchange (HIE) systems, such as Connecting for Health, the eHealth initiative, the Federal Health Information Exchange (FHIE), the Indiana Health Information Exchange (IHIE), the Massachusetts Health Data Consortium (MHDC), the New England Health EDI Network (NEHEN), the State of New Mexico Rapid Syndromic Validation Project (RSVP), the Southeast Michigan e­Prescribing Initiative, and the Tennessee Volunteer eHealth Initiative (Goldstein, Groen, Ponkshe, & Wine, 2007). Many of these were sparked by the HITECH Act of 2011, which set the 2014 deadline for implementing EHRs and provided the impetus for HIE initiatives.

It is quite evident from the previous brief listing that there is a need to remedy healthcare information technology (IT) concerns, challenges, and issues faced today. One of the main issues deals with how healthcare infor­ mation is managed to make it meaningful. It is important to understand

Introduction to Information, Information Science, and Information Systems Kathleen Mastrian and Dee McGonigle

21

CHAPTER 2

 

 

how people obtain, manipulate, use, share, and dispose of information. This chapter deals with the information piece of this complex puzzle.

Information Suppose someone states the number 99.5. What does that mean? It could be a radio station or a score on a test. Now suppose someone says that Ms. Howsunny’s tem­ perature is 99.5°F—what does that convey? It is then known that 99.5 is a person’s temperature. The data (99.5) were processed to the information that 99.5° is a spe­ cific person’s temperature. Data are raw facts. Information is processed data that has meaning. Healthcare professionals constantly process data and information to pro­ vide the best possible care for their patients.

Many types of data exist, such as alphabetic, numeric, audio, image, and video data. Alphabetic data refer to letters, numeric data refer to numbers, and alphanumeric data combine both letters and numbers. This includes all text and the numeric outputs of digital monitors. Some of the alphanumeric data encountered by healthcare profes­ sionals are in the form of patients’ names, identification numbers, or medical record numbers. Audio data refer to sounds, noises, or tones—for example, monitor alerts or alarms, taped or recorded messages, and other sounds. Image data include graphics and pictures, such as graphic monitor displays or recorded electrocardiograms, radio­ graphs, magnetic resonance imaging (MRI) outputs, and computed tomography (CT) scans. Video data refer to animations, moving pictures, or moving graphics. Using

22 CHAPTER 2 Introduction to Information, Information Science, and Information Systems

Figure 2-1 Building Blocks of Nursing Informatics

Nursing Informatics

Nursing Science

Computer Science

Cognitive Science

Information Science

 

 

these data, one may review the ultrasound of a pregnant patient, examine a patient’s echocardiogram, watch an animated video for professional development, or learn how to operate a new technology tool, such as a pump or monitoring system. The data we gather, such as heart and lung sounds or X­rays, help us produce information. For ex­ ample, if a patient’s X­rays show a fracture, it is interpreted into information such as spiral, compound, or hairline. This information is then processed into knowledge and a treatment plan is formulated based on the healthcare professional’s wisdom.

The integrity and quality of the data, rather than the form, are what matter. Integrity refers to whole, complete, correct, and consistent data (Figure 2-2). Data integrity can be compromised through human error; viruses, worms, or other computer bugs; hard­ ware failures or crashes; transmission errors; or hackers entering the system. Figure 2-3 illustrates some ways that data can be compromised. Information technologies help to decrease these errors by putting into place safeguards, such as backing up files on a routine basis, error detection for transmissions, and user interfaces that help people enter the data correctly. High­quality data are relevant and accurately represent their cor­ responding concepts. Data are dirty when a database contains errors, such as duplicate, incomplete, or outdated records. One author (D.M.) found 50 cases of tongue cancer in a database she examined for data quality. When the records were tracked down and analyzed, and the dirty data were removed, only one case of tongue cancer remained. In this situation, the data for the same person had been entered erroneously 49 times. The major problem was with the patient’s identification number and name: The num­ ber was changed or his name was misspelled repeatedly. If researchers had just taken the number of cases in that defined population as 50, they would have concluded that tongue cancer was an epidemic, resulting in flawed information that is not meaningful. As this example demonstrates, it is imperative that data be clean if the goal is quality information. The data that are processed into information must be of high quality and integrity to create meaning to inform assessments and decision making.

To be valuable and meaningful, information must be of good quality. Its value relates directly to how the information informs decision making. Characteristics of valuable, quality information include accessibility, security, timeliness, accuracy, rel­ evancy, completeness, flexibility, reliability, objectivity, utility, transparency, verifiabil­ ity, and reproducibility.

Information 23

Figure 2-2 Data Integrity

Data integrity

C on

si st

en t

Co rre

ctC om

ple te

Wh ole Quality data

 

 

Accessibility is a must; the right user must be able to obtain the right information at the right time and in the right format to meet his or her needs. Getting meaningful information to the right user at the right time is as vital as generating the information in the first place. The right user refers to an authorized user who has the right to obtain the data and information he or she is seeking. Security is a major challenge because unauthorized users must be blocked while the authorized user is provided with open, easy access (see the Electronic Security chapter).

Timely information means that the information is available when it is needed for the right purpose and at the right time. Knowing who won the lottery last week does not help one to know if the person won it today. Accurate information means that there are no errors in the data and information. Relevant information is a subjective descriptor, in that the user must have information that is relevant or applicable to his or her needs. If a healthcare provider is trying to decide whether a patient needs insulin and only the patient’s CT scan information is available, this information is not relevant for that cur­ rent need. However, if one needed information about the CT scan, the information is relevant.

Complete information contains all of the necessary essential data. If the healthcare provider needs to contact the only relative listed for the patient and his or her contact information is listed but the approval for that person to be a contact is missing, this information is considered incomplete. Flexible information means that the informa­ tion can be used for a variety of purposes. Information concerning the inventory of

24 CHAPTER 2 Introduction to Information, Information Science, and Information Systems

Figure 2-3 Threats to Data Integrity

• Connectivity issues • Data corruption • Lost data

• Hardware failures • Software crashes

• Viruses • Worms • Spam • Ransomware

• Incorrect data entry • Spelling errors

Human Error Malware

Transmission ErrorsMachine Error

 

 

supplies on a nursing unit, for example, can be used by nurses who need to know if an item is available for use for a patient. The nurse manager accesses this information to help decide which supplies need to be ordered, to determine which items are used most frequently, and to do an economic assessment of any waste.

Reliable information comes from reliable or clean data gathered from authorita­ tive and credible sources. Objective information is as close to the truth as one can get; it is not subjective or biased, but rather is factual and impartial. If someone states something, it must be determined whether that person is reliable and whether what he or she is stating is objective or tainted by his or her own perspective.

Utility refers to the ability to provide the right information at the right time to the right person for the right purpose. Transparency allows users to apply their intellect to accomplish their tasks while the tools housing the information disappear into the background. Verifiable information means that one can check to verify or prove that the information is correct. Reproducibility refers to the ability to produce the same information again.

Information is acquired either by actively looking for it or by having it conveyed by the environment. All of the senses (vision, hearing, touch, smell, and taste) are used to gather input from the surrounding world, and as technologies mature, more and more input will be obtained through the senses. Currently, people receive infor­ mation from computers (output) through vision, hearing, or touch (input); and the response (output) to the computer (input) is the interface with technology. Gesture recognition is increasing, and interfaces that incorporate it will change the way people become informed. Many people access the Internet on a daily basis seeking information or imparting information. Individuals are constantly becoming informed, discovering, or learning; becoming reinformed, rediscovering, or relearning; and purging what has been acquired. The information acquired through these processes is added to the personal knowledge base. Knowledge is the awareness and understanding of a set of information and ways that information can be made useful to support a specific task or arrive at a decision. This knowledge building is an ongoing process engaged in while a person is conscious and going about his or her normal daily activities.

Information Science Information science has evolved over the last 50 or so years as a field of scientific inquiry and professional practice. It can be thought of as the science of informa­ tion, studying the application and usage of information and knowledge in organi­ zations and the interface or interaction between people, organizations, and ISs. This extensive, interdisciplinary science integrates features from cognitive  science, communication science, computer science, library science, and the social sciences. Information science is primarily concerned with the input, processing, output, and feedback of data and information through technology integration with a focus on comprehending the perspective of the stakeholders involved and then applying IT as needed. It is systemically based, dealing with the big picture rather than individual pieces of technology.

Information Science 25

 

 

Information science can also be related to determinism. Specifically, it is a response to technologic determinism—the belief that technology develops by its own laws, that it realizes its own potential, limited only by the material resources available, and must therefore be regarded as an autonomous system controlling and ultimately permeating all other subsystems of society (Web Dictionary of Cybernetics and Systems, 2007, para. 1).

This approach sets the tone for the study of information as it applies to itself, the people, the technology, and the varied sciences that are contextually related depending on the needs of the setting or organization; what is important is the interface between the stakeholders and their systems, and the ways they generate, use, and locate information. According to Cornell University (2010), “Informa­ tion Science brings together faculty, students and researchers who share an interest in combining computer science with the social sciences of how people and society interact with information” (para. 1). Information science is an interdisciplinary, people­oriented field that explores and enhances the interchange of information to transform society, communication science, computer science, cognitive science, library science, and the social sciences. Society is dominated by the need for information, and knowledge and information science focus on systems and individ­ ual users by fostering user­centered approaches that enhance society’s information capabilities, effectively and efficiently linking people, information, and technology. This impacts the configuration and mix of organizations and influences the nature of work—namely, how knowledge workers interact with and produce meaningful information and knowledge.

Information Processing Information science enables the processing of information. This processing links people and technology. Humans are organic ISs, constantly acquiring, process­ ing, and generating information or knowledge in their professional and personal lives. This high degree of knowledge, in fact, characterizes humans as extremely intelligent organic machines. The premise of this text revolves around this concept, and the text is organized on the basis of the Foundation of Knowledge model: knowledge acquisition, knowledge processing, knowledge generation, and knowl­ edge dissemination.

Information is data that are processed using knowledge. For information to be valu­ able or meaningful, it must be accessible, accurate, timely, complete, cost­effective, flexible, reliable, relevant, simple, verifiable, and secure. Knowledge is the awareness and understanding of an information set and ways that information can be made useful to support a specific task or arrive at a decision. As an example, if an architect were going to design a building, part of the knowledge necessary for developing a new building is understanding how the building will be used, what size of building is needed compared to the available building space, and how many people will have or need access to this building. Therefore, the work of choosing or rejecting facts based on their significance or relevance to a particular task, such as designing a build­ ing, is also based on a type of knowledge used in the process of converting data into information. Information can then be considered data made functional through the

26 CHAPTER 2 Introduction to Information, Information Science, and Information Systems

 

 

application of knowledge. The knowledge used to develop and glean knowledge from valuable information is generative (having the ability to originate and produce or generate) in nature. Knowledge must also be viable. Knowledge viability refers to ap­ plications that offer easily accessible, accurate, and timely information obtained from a variety of resources and methods and presented in a manner so as to provide the necessary elements to generate knowledge.

Information science and computational tools are extremely important in enabling the processing of data, information, and knowledge in health care. In this environ­ ment, the hardware, software, networking, algorithms, and human organic ISs work together to create meaningful information and generate knowledge. The links between information processing and scientific discovery are paramount. However, without the ability to generate practical results that can be disseminated, the process­ ing of data, information, and knowledge is for naught. It is the ability of machines (inorganic ISs) to support and facilitate the functioning of people (human organic ISs) that refines, enhances, and evolves nursing practice by generating knowledge. This knowledge represents five rights: the right information, accessible by the right people in the right settings, applied the right way at the right time.

An important and ongoing process is the struggle to integrate new knowledge and old knowledge so as to enhance wisdom. Wisdom is the ability to act appropriately; it assumes actions directed by one’s own wisdom. Wisdom uses knowledge and experi­ ence to heighten common sense, and uses insight to exercise sound judgment in prac­ tical matters. It is developed through knowledge, experience, insight, and reflection. Wisdom is sometimes thought of as the highest form of common sense, resulting from accumulated knowledge or erudition (deep, thorough learning) or enlightenment (education that results in understanding and the dissemination of knowledge). It is the ability to apply valuable and viable knowledge, experience, understanding, and insight while being prudent and sensible. Knowledge and wisdom are not synony­ mous, because knowledge abounds with others’ thoughts and information, whereas wisdom is focused on one’s own mind and the synthesis of one’s own experience, insight, understanding, and knowledge.

If clinicians are inundated with data without the ability to process it, the situation results in too much data and too little wisdom. Consequently, it is crucial that clini­ cians have viable ISs at their fingertips to facilitate the acquisition, sharing, and use of knowledge while maturing wisdom; this process leads to empowerment.

Information Science and the Foundation of Knowledge Information science is a multidisciplinary science that encompasses aspects of com­ puter science, cognitive science, social science, communication science, and library science to deal with obtaining, gathering, organizing, manipulating, managing, stor­ ing, retrieving, recapturing, disposing of, distributing, and broadcasting information. Information science studies everything that deals with information and can be defined as the study of ISs. This science originated as a subdiscipline of computer science, as practitioners sought to understand and rationalize the management of technology

Information Science and the Foundation of Knowledge 27

 

 

within organizations. It has since matured into a major field of management and is now an important area of research in management studies. Moreover, information science has expanded its scope to examine the human–computer interaction, interfac­ ing, and interaction of people, ISs, and corporations. It is taught at all major universi­ ties and business schools worldwide.

Modern­day organizations have become intensely aware of the fact that informa­ tion and knowledge are potent resources that must be cultivated and honed to meet their needs. Thus information science or the study of ISs—that is, the application and usage of knowledge—focuses on why and how technology can be put to best use to serve the information flow within an organization.

Information science impacts information interfaces, influencing how people inter­ act with information and subsequently develop and use knowledge. The information a person acquires is added to his or her knowledge base. Knowledge is the awareness and understanding of an information set and ways that information can be made use­ ful to support a specific task or arrive at a decision.

Healthcare organizations are affected by and rely on the evolution of information science to enhance the recording and processing of routine and intimate information while facilitating human­to­human and human­to­systems communications, delivery of healthcare products, dissemination of information, and enhancement of the organiza­ tion’s business transactions. Unfortunately, the benefits and enhancements of informa­ tion science technologies have also brought to light new risks, such as glitches and loss of information and hackers who can steal identities and information. Solid leadership, guidance, and vision are vital to the maintenance of cost­effective business performance and cutting­edge, safe information technologies for the organization. This field studies all facets of the building and use of information. The emergence of information science and its impact on information have also influenced how people acquire and use knowledge.

Information science has already had a tremendous impact on society and will undoubtedly expand its sphere of influence further as it continues to evolve and inno­ vate human activities at all levels. What visionaries only dreamed of is now possible and part of reality. The future has yet to fully unfold in this important arena.

Introduction to Information Systems Consider the following scenario: You have just been hired by a large healthcare facil­ ity. You enter the personnel office and are told that you must learn a new language to work on the unit where you have been assigned. This language is used just on this unit. If you had been assigned to a different unit, you would have to learn another language that is specific to that unit, and so on. Because of the differences in various units’ languages, interdepartmental sharing and information exchange (known as interoperability) are severely hindered.

This scenario might seem far­fetched, but it is actually how workers once operated in health care—in silos. There was a system for the laboratory, one for finance, one for clinical departments, and so on. As healthcare organizations have come to appreciate the importance of communication, tracking, and research, however, they have devel­ oped integrated information systems that can handle the needs of the entire organization.

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Information and IT have become major resources for all types of organizations, and health care is no exception (see Box 2-1). Information technologies help to shape a healthcare organization, in conjunction with personnel, money, materials, and equipment. Many healthcare facilities have hired chief information officers (CIOs) or chief technical officers (CTOs), also known as chief technology officers. The CIO is in­ volved with the IT infrastructure, and this role is sometimes expanded to include the position of chief knowledge officer. The CTO is focused on organizationally based scientific and technical issues and is responsible for technological research and devel­ opment as part of the organization’s products and services. The CTO and CIO must be visionary leaders for the organization, because so much of the business of health care relies on solid infrastructures that generate potent and timely information and

BOX 2-1 EXAMPLES OF INFORMATION SYSTEMS

Information System How It Is Used

Clinical Information System (CIS) Comprehensive and integrative system that manages the administrative, financial, and clinical aspects of a clinical facility; a CIS should help to link financial and clinical outcomes. An example is the EHR.

Decision Support System (DSS) Organizes and analyzes information to help decision makers formulate decisions when they are unsure of their decision’s possible outcomes. After gathering relevant and useful information, develops “what if” models to analyze the options or choices and alternatives.

Executive Support System Collects, organizes, analyzes, and summarizes vital information to help executives or senior management with strategic decision making. Provides a quick view of all strategic business activities.

Geographic Information System (GIS) Collects, manipulates, analyzes, and generates information related to geographic locations or the surface of the earth; provides output in the form of virtual models, maps, or lists.

Management Information Systems (MIS) Provides summaries of internal sources of information, such as information from the transaction processing system, and develops a series of routine reports for decision making.

Office Systems Facilitates communication and enhances the productivity of users needing to process data and information.

Transaction Processing System (TPS) Processes and records routine business transactions, such as billing systems that create and send invoices to customers, and payroll systems that generate employees’ pay stubs and wage checks and calculate tax payments.

Hospital Information System (HIS) Manages the administrative, financial, and clinical aspects of a hospital enterprise. It should help to link financial and clinical outcomes.

Introduction to Information Systems 29

 

 

knowledge. The CTO and CIO are sometimes interchangeable positions, but in some organizations the CTO reports to the CIO. These positions will become critical roles as companies continue to shift from being product oriented to knowledge oriented, and as they begin emphasizing the production process itself rather than the product. In health care, ISs must be able to handle the volume of data and information neces­ sary to generate the needed information and knowledge for best practices, because the goal is to provide the highest quality of patient care.

Information Systems ISs can be manually based, but for the purposes of this text, the term refers to computer-based information systems (CBISs). According to Jessup and Valacich (2008), CBISs “are combinations of hardware, software and telecommunications networks that people build and use to collect, create, and distribute useful data, typically in organizational settings” (p. 10). Along the same lines, ISs are also defined as “a col­ lection of interconnected elements that gather, process, store and distribute data and information while providing a feedback structure to meet an objective” (Stair & Reynolds, 2016, p. 4). ISs are designed for specific purposes within organizations. They are only as functional as the decision­making capabilities, problem­solving skills, and programming potency built in and the quality of the data and information input into them. The capability of the IS to disseminate, provide feedback, and adjust the data and information based on these dynamic processes is what sets them apart. The IS should be a user­friendly entity that provides the right information at the right time and in the right place.

An IS acquires data or inputs; processes data through the retrieval, analysis, or synthesis of those data; disseminates or outputs information in the form of reports, documents, summaries, alerts, prompts, or outcomes; and provides for responses or feedback. Input or data acquisition is the activity of collecting and acquiring raw data. Input devices include combinations of hardware, software, and telecommunications, including keyboards, light pens, touch screens, mice or other pointing devices, automatic scanners, and machines that can read magnetic ink characters or lettering. To watch a pay­per­view movie, for example, the viewer must first input the chosen movie, verify the purchase, and have a payment method approved by the vendor. The IS must acquire this information before the viewer can receive the movie.

Processing—the retrieval, analysis, or synthesis of data—refers to the alteration and transformation of the data into helpful or useful information and outputs. The processing of data can range from storing it for future use; to comparing the data, making calculations, or applying formulas; to taking selective actions. Processing devices consist of combinations of hardware, software, and telecommunications and include processing chips where the central processing unit (CPU) and main memory are housed. Some of these chips are quite ingenious. According to Schupak (2005), the bunny chip could save the pharmaceutical industry money while sparing “millions of furry creatures, with a chip that mimics a living organism” (para. 1). The HµREL Corporation has developed environments or biologic ISs that reside on chips and actually mimic the functioning of the human body. Researchers can use these environ­ ments to test for both the harmful and beneficial effects of drugs, including those that

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are considered experimental and that could be harmful if used in human and animal testing. Such chips also allow researchers to monitor a drug’s toxicity in the liver and other organs.

One patented HµREL microfluidic “biochip” comprises an arrangement of sepa­ rate but fluidically interconnected “organ” or “tissue” compartments. Each com­ partment contains a culture of living cells drawn from, or engineered to mimic the primary functions of, the respective organ or tissue of a living animal. Microfluidic channels permit a culture medium that serves as a “blood surrogate” to recirculate just as in a living system, driven by a microfluidic pump. The geometry and fluidics of the device are fashioned to simulate the values of certain related physiologic parameters found in the living creature. Drug candidates or other substrates of interest are added to the culture medium and allowed to recirculate through the device. The effects of drug compounds and their metabolites on the cells within each respective organ compartment are then detected by measuring or monitoring key physiologic events. The cell types used may be derived from either standard cell culture lines or primary tissues (HµREL Corporation, 2010, para. 2–3). As new technologies such as the HµREL chips continue to evolve, more and more robust ISs that can handle a variety of biological and clinical applications will be seen.

Returning to the movie rental example, the IS must verify the data entered by the viewer and then process the request by following the steps necessary to provide ac­ cess to the movie that was ordered. This processing must be instantaneous in today’s world, where everyone wants everything now. After the data are processed, they are stored. In this case, the rental must also be processed so the vendor receives payment for the movie, whether electronically, via a credit card or checking account with­ drawal, or by generating a bill for payment.

Output or dissemination produces helpful or useful information that can be in the form of reports, documents, summaries, alerts, or outcomes. A report is designed to inform and is generally tailored to the context of a given situation or user or user group. Reports may include charts, figures, tables, graphics, pictures, hyperlinks, ref­ erences, or other documentation necessary to meet the needs of the user. A document represents information that can be printed, saved, emailed, or otherwise shared, or displayed. Summaries are condensed versions of the original information designed to highlight the major points. An alert is comprised of warnings, feedback, or additional information necessary to assist the user in interacting with the system. An outcome is the expected result of input and processing. Output devices are combinations of hardware, software, and telecommunications and include sound and speech synthesis outputs, printers, and monitors.

Continuing with the movie rental example, the IS must be able to provide the con­ sumer with the movie ordered when it is wanted and somehow notify the purchaser that he or she has, indeed, purchased the movie and is granted access. The IS must also be able to generate payment either electronically or by generating a bill, while storing the transactional record for future use.

Feedback or responses are reactions to the inputting, processing, and outputs. In ISs, feedback refers to information from the system that is used to make modifica­ tions in the input, processing actions, or outputs. In the movie rental example, what if the consumer accidentally entered the same movie order three times, but really

Introduction to Information Systems 31

 

 

wanted to order the movie only once? The IS would determine that more than one movie order is out of range for the same movie order at the same time and provide feedback. Such feedback is used to verify and correct the input. If undetected, the viewer’s error would result in an erroneous bill and decreased customer satisfaction while creating more work for the vendor, which would have to engage in additional transactions with the customer to resolve this problem. The Nursing Informatics Practice Applications: Care Delivery section of this text provides detailed descriptions of clinical ISs that operate on these same principles to support healthcare delivery.

Summary Information systems deal with the development, use, and management of an organi­ zation’s IT infrastructure. An IS acquires data or inputs; processes data through the retrieval, analysis, or synthesis of those data; disseminates or outputs in the form of reports, documents, summaries, alerts, or outcomes; and provides for responses or feedback. Quality decision­making and problem­solving skills are vital to the develop­ ment of effective, valuable ISs. Today’s organizations now recognize that their most precious asset is their information, as represented by their employees, experience, competence or know­how, and innovative or novel approaches, all of which are de­ pendent on a robust information network that encompasses the information technol­ ogy infrastructure.

In an ideal world, all ISs would be fluid in their ability to adapt to any and all users’ needs. They would be Internet oriented and global, where resources are avail­ able to everyone. Think of cloud computing—it is just the beginning point from which ISs will expand and grow in their ability to provide meaningful information to their users. As technologies advance, so will the skills and capabilities to compre­ hend and realize what ISs can become. As wearable tracking technologies and other health­related mobile applications expand, more robust and timely health data will be generated, and this data will need to be processed into meaningful information. “Practitioners and medical researchers can look forward to technologies that enable them to apply data analysis to develop new insights into finding cures for difficult diseases. Healthcare CIOs and other IT leaders can expect to be called upon to man­ age all the new data and devices that will be transforming healthcare as we know it” (Schindler, 2015, para. 2). Devices with sensors communicating with each other is known as the Internet of Things (IoT) and the future possibilities for health care are tremendous. “The IoT raises the bar—enabling connection and communication from anywhere to anywhere—and allows analytics to replace the human decision­maker” (Glasser, 2015, para. 3). Essentially, the sensor­collected data are transmitted to another technology, triggering an action or an alert that prompts feedback for an action. For example, “imagine a miniaturized, implanted device or skin patch that monitors a diabetic’s blood sugar, movement, skin temperature and more, and informs an insulin pump to adjust the dosage” (para. 8).

It is important to continue to develop and refine functional, robust, visionary ISs that meet the current meaningful information needs while evolving systems that are even better prepared to handle future information and knowledge needs of the health­ care industry.

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References Cornell University. (2010). Information science. Retrieved from http://www.infosci.cornell.edu Goldstein, D., Groen, P., Ponkshe, S., & Wine, M. (2007). Medical informatics 20/20. Sudbury,

MA: Jones and Bartlett. Glasser, J. (2015). How the Internet of Things will affect health care. Hospitals and Health

Networks. Retrieved from http://www.hhnmag.com/articles/3438­how­the­internet­of ­things­will­affect­health­care

HµREL Corporation. (2010). Human­relevant: HµREL. Technology overview. Retrieved from http://www.hurelcorp.com/overview.php

Jessup, L., & Valacich, J. (2008). Information systems today (3rd ed.). Upper Saddle River, NJ: Pearson Prentice Hall.

Schindler, E. (2015). Healthcare IT: Hot Trends for 2016, Part 1. InformationWeek. Retrieved from http://www.informationweek.com/healthcare/leadership/healthcare­it­hot­trends­for ­2016­part­1/d/d­id/1323722

Schupak, A. (2005). Technology: The bunny chip. Forbes. Retrieved from http://www.forbes .com/forbes/2005/0815/053.html

Stair, R., & Reynolds, G. (2016). Principles of information systems (12th ed.). Boston, MA: Cengage Learning.

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