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The Handbook of Evaluation Methods for Health Informatics provides a complete compendium of methods for evaluation of IT-based systems and solutions within healthcare. Emphasis is entirely on assessment of the IT-system within its organizational environment. The author provides a coherent and complete assessment of methods addressing interactions with and effects of technology at the organizational, psychological, and social levels. It offers an explanation of the terminology and theoretical foundations underlying the methodological analysis presented here. The author carefully guides the reader through the process of identifying relevant methods corresponding to specific information needs and conditions for carrying out the evaluation study. The Handbook takes a critical view by focusing on assumptions for application, tacit built-in perspectives of the methods as well as their perils and pitfalls. Collects a number of evaluation methods of medical informatics Addresses metrics and measures Includes an extensive list of anotated references, case studies, and a list of useful Web sites
10.2 The Role and Contents of the URD in an Assessment Perspective -- 10.3 The Enterprise Model -- 10.4 The Normative Model -- 10.5 Assessment of the User Requirements Document -- 10.6 Discussion -- 11 Dynamic Aspects of the Assessment Methodology -- 11.1 Dynamic Aspects of IT-Development and Application -- 11.2 Adaptation of Frames of Reference for Assessment Activities -- 11.3 Feed-forward Loops -- 11.4 Support of Context Dependent Assessment -- 11.5 Conclusion -- 12 The Dynamic Assessment Methodology -- 12.1 Philosophy -- 12.2 Application Area -- 12.3 Operationalisation of the Methodology -- 12.4 Applicable Methods -- 12.5 Summary -- 13 Discussion -- 13.1 Discussion of Fulfilment of Objective for the 4th Goal -- 13.2 Conclusion of the Study -- References -- Appendix 1: Vocabulary -- Appendix 2: Abbreviations & Acronyms -- Appendix 3: KAVAS's & ISAR's Evaluation Methodology -- Appendix 4: Methodology for Assessment of Functionality -- Appendix 5: Experimental Observations: Functionality Assessment -- Appendix 6: Experimental Observations: LFA -- Appendix 7: Causal Analysis of Experimental Observations -- Appendix 8: Method for Elicitation of a Strategy -- Appendix 9: Selected References regarding Assessment Methods
As director of a training program in medical informatics, I have found that one of the most frequent inquiries from graduate students is, "Although I am happy with my research focus and the work I have done, how can I design and carry out a practical evaluation that proves the value of my contribution?" Informatics is a multifaceted, interdisciplinary field with research that ranges from theoretical developments to projects that are highly applied and intended for near-term use in clinical settings. The implications of "proving" a research claim accordingly vary greatly depending on the details of an individual student's goals and thesis state ment. Furthermore, the dissertation work leading up to an evaluation plan is often so time-consuming and arduous that attempting the "perfect" evaluation is fre quently seen as impractical or as diverting students from central programming or implementation issues that are their primary areas of interest. They often ask what compromises are possible so they can provide persuasive data in support of their claims without adding another two to three years to their graduate student life. Our students clearly needed help in dealing more effectively with such dilem mas, and it was therefore fortuitous when, in the autumn of 1991, we welcomed two superb visiting professors to our laboratories.
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Governments and clinical providers are investing billions of dollars in health information technologies. This book provides an easy-to-read reference outlining the basic concepts, theory, and methods required to perform a systematic evaluation of HIT.
Health Informatics (HI) focuses on the application of Information Technology (IT) to the field of medicine to improve individual and population healthcare delivery, education and research. This extensively updated fifth edition reflects the current knowledge in Health Informatics and provides learning objectives, key points, case studies and references.
The American Medical Informatics Association (AMIA) defines the term biomedical informatics (BMI) as: The interdisciplinary field that studies and pursues the effective uses of biomedical data, information, and knowledge for scientific inquiry, problem solving and decision making, motivated by efforts to improve human health. This book: Applied Interdisciplinary Theory in Health Informatics: A Knowledge Base for Practitioners, explores the theories that have been applied in health informatics and the differences they have made. The editors, all proponents of evidence-based health informatics, came together within the European Federation of Medical Informatics (EFMI) Working Group on Health IT Evaluation and the International Medical Informatics Association (IMIA) Working Group on Technology Assessment and Quality Development. The purpose of the book, which has a foreword by Charles Friedman, is to move forward the agenda of evidence-based health informatics by emphasizing theory-informed work aimed at enriching the understanding of this uniquely complex field. The book takes the AMIA definition as particularly helpful in its articulation of the three foundational domains of health informatics: health science, information science, and social science and their various overlaps, and this model has been used to structure the content of the book around the major subject areas. The book discusses some of the most important and commonly used theories relevant to health informatics, and constitutes a first iteration of a consolidated knowledge base that will advance the science of the field.
This User’s Guide is intended to support the design, implementation, analysis, interpretation, and quality evaluation of registries created to increase understanding of patient outcomes. For the purposes of this guide, a patient registry is an organized system that uses observational study methods to collect uniform data (clinical and other) to evaluate specified outcomes for a population defined by a particular disease, condition, or exposure, and that serves one or more predetermined scientific, clinical, or policy purposes. A registry database is a file (or files) derived from the registry. Although registries can serve many purposes, this guide focuses on registries created for one or more of the following purposes: to describe the natural history of disease, to determine clinical effectiveness or cost-effectiveness of health care products and services, to measure or monitor safety and harm, and/or to measure quality of care. Registries are classified according to how their populations are defined. For example, product registries include patients who have been exposed to biopharmaceutical products or medical devices. Health services registries consist of patients who have had a common procedure, clinical encounter, or hospitalization. Disease or condition registries are defined by patients having the same diagnosis, such as cystic fibrosis or heart failure. The User’s Guide was created by researchers affiliated with AHRQ’s Effective Health Care Program, particularly those who participated in AHRQ’s DEcIDE (Developing Evidence to Inform Decisions About Effectiveness) program. Chapters were subject to multiple internal and external independent reviews.
Focusing on a healthcare organization's ability to improve access, quality, and value of care to the patient, this volume provides an extensive and rich compilation of international research which discusses the use, adoption, design, and diffusion of information communication technologies (ICTs) in healthcare.
Clinical Research Computing: A Practitioner's Handbook deals with the nuts-and-bolts of providing informatics and computing support for clinical research. The subjects that the practitioner must be aware of are not only technological and scientific, but also organizational and managerial. Therefore, the author offers case studies based on real life experiences in order to prepare the readers for the challenges they may face during their experiences either supporting clinical research or supporting electronic record systems. Clinical research computing is the application of computational methods to the broad field of clinical research. With the advent of modern digital computing, and the powerful data collection, storage, and analysis that is possible with it, it becomes more relevant to understand the technical details in order to fully seize its opportunities. - Offers case studies, based on real-life examples where possible, to engage the readers with more complex examples - Provides studies backed by technical details, e.g., schema diagrams, code snippets or algorithms illustrating particular techniques, to give the readers confidence to employ the techniques described in their own settings - Offers didactic content organization and an increasing complexity through the chapters