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Getting the right diagnosis is a key aspect of health care - it provides an explanation of a patient's health problem and informs subsequent health care decisions. The diagnostic process is a complex, collaborative activity that involves clinical reasoning and information gathering to determine a patient's health problem. According to Improving Diagnosis in Health Care, diagnostic errors-inaccurate or delayed diagnoses-persist throughout all settings of care and continue to harm an unacceptable number of patients. It is likely that most people will experience at least one diagnostic error in their lifetime, sometimes with devastating consequences. Diagnostic errors may cause harm to patients by preventing or delaying appropriate treatment, providing unnecessary or harmful treatment, or resulting in psychological or financial repercussions. The committee concluded that improving the diagnostic process is not only possible, but also represents a moral, professional, and public health imperative. Improving Diagnosis in Health Care, a continuation of the landmark Institute of Medicine reports To Err Is Human (2000) and Crossing the Quality Chasm (2001), finds that diagnosis-and, in particular, the occurrence of diagnostic errorsâ€"has been largely unappreciated in efforts to improve the quality and safety of health care. Without a dedicated focus on improving diagnosis, diagnostic errors will likely worsen as the delivery of health care and the diagnostic process continue to increase in complexity. Just as the diagnostic process is a collaborative activity, improving diagnosis will require collaboration and a widespread commitment to change among health care professionals, health care organizations, patients and their families, researchers, and policy makers. The recommendations of Improving Diagnosis in Health Care contribute to the growing momentum for change in this crucial area of health care quality and safety.
Mental illness is many things at once: It is a natural phenomenon that is also shaped by society and culture. It is biological but also behavioral and social. Mental illness is a problem of both the brain and the mind, and this ambiguity presents a challenge for those who seek to accurately classify psychiatric disorders. The leading resource we have for doing so is the American Psychiatric Association’s Diagnostic and Statistical Manual, but no edition of the manual has provided a decisive solution, and all have created controversy. In The Diagnostic System, the sociologist Jason Schnittker looks at the multiple actors involved in crafting the DSM and the many interests that the manual hopes to serve. Is the DSM the best tool for defining mental illness? Can we insure against a misleading approach? Schnittker shows that the classification of psychiatric disorders is best understood within the context of a system that involves diverse parties with differing interests. The public wants a better understanding of personal suffering. Mental-health professionals seek reliable and treatable diagnostic categories. Scientists want definitions that correspond as closely as possible to nature. And all parties seek definitive insight into what they regard as the right target. Yet even the best classification system cannot satisfy all of these interests simultaneously. Progress toward an ideal is difficult, and revisions to diagnostic criteria often serve the interests of one group at the expense of another. Schnittker urges us to become comfortable with the socially constructed nature of categorization and accept that a perfect taxonomy of mental-health disorders will remain elusive. Decision making based on evolving though fluid understandings is not a weakness but an adaptive strength of the mental-health profession, even if it is not a solid foundation for scientific discovery or a reassuring framework for patients.
This handbook describes the diagnostic process clearly and logically, aiding medical students and others who wish to improve their diagnostic performance and to learn more about the diagnostic process.
The definitive evidence-based introduction to patient history-taking NOW IN FULL COLOR For medical students and other health professions students, an accurate differential diagnosis starts with The Patient History. The ideal companion to major textbooks on the physical examination, this trusted guide is widely acclaimed for its skill-building, and evidence based approach to the medical history. Now in full color, The Patient History defines best practices for the patient interview, explaining how to effectively elicit information from the patient in order to generate an accurate differential diagnosis. The second edition features all-new chapters, case scenarios, and a wealth of diagnostic algorithms. Introductory chapters articulate the fundamental principles of medical interviewing. The book employs a rigorous evidenced-based approach, reviewing and highlighting relevant citations from the literature throughout each chapter. Features NEW! Case scenarios introduce each chapter and place history-taking principles in clinical context NEW! Self-assessment multiple choice Q&A conclude each chapter—an ideal review for students seeking to assess their retention of chapter material NEW! Full-color presentation Essential chapter on red eye, pruritus, and hair loss Symptom-based chapters covering 59 common symptoms and clinical presentations Diagnostic approach section after each chapter featuring color algorithms and several multiple-choice questions Hundreds of practical, high-yield questions to guide the history, ranging from basic queries to those appropriate for more experienced clinicians
This open access book comprehensively covers the fundamentals of clinical data science, focusing on data collection, modelling and clinical applications. Topics covered in the first section on data collection include: data sources, data at scale (big data), data stewardship (FAIR data) and related privacy concerns. Aspects of predictive modelling using techniques such as classification, regression or clustering, and prediction model validation will be covered in the second section. The third section covers aspects of (mobile) clinical decision support systems, operational excellence and value-based healthcare. Fundamentals of Clinical Data Science is an essential resource for healthcare professionals and IT consultants intending to develop and refine their skills in personalized medicine, using solutions based on large datasets from electronic health records or telemonitoring programmes. The book’s promise is “no math, no code”and will explain the topics in a style that is optimized for a healthcare audience.
A quick guide to appropriately selecting and interpreting laboratory tests, Small Animal Clinical Diagnosis by Laboratory Methods, 5th Edition helps you utilize your in-house lab or your specialty reference lab to efficiently make accurate diagnoses without running a plethora of unnecessary and low-yield tests. It provides answers to commonly asked questions relating to laboratory tests, and solutions to frequently encountered problems in small animal diagnosis. For easy reference, information is provided by clinical presentation and abnormalities, and includes hundreds of tables, boxes, key points, and algorithms. This edition, now in full color, is updated with the latest advances in laboratory testing methods and diagnostic problem solving. Written by noted educators Dr. Michael Willard and Dr. Harold Tvedten, this book may be used as an on-the-spot guide to specific problems or conditions as well as a reference for more detailed research on difficult cases. - Concise discussions address laboratory approaches to various disorders, possible conclusions from various test results, artifacts and errors in diagnoses, and interpretations leading to various diagnoses. - Hundreds of tables, boxes, algorithms, and key points offer at-a-glance information including cautions, common pitfalls, and helpful "pearls," and lead to proper differential and clinical diagnostic decision making. - Note boxes identify key considerations in correlating clinical signs with test data for accurate diagnoses, highlight safety precautions, and offer helpful tips for sample preparation and interpretation. - Chapters on laboratory diagnostic toxicology and therapeutic drug monitoring help in handling potentially fatal poisonings and other special situations. - Expert editors and contributors provide clinical knowledge and successful diagnostic problem-solving solutions. - A practical appendix lists referral laboratories that may be contacted for certain diseases, and reference values with the normal or expected range for coagulation, hematology, and more. - Updated coverage integrates the newest advances in testing methods and diagnostic problem solving. - Full-color photos and schematic drawings are placed adjacent to related text, and accurately depict diagnostic features on microscopic slide preparations as well as test procedures and techniques.
Risk and Reasoning in Clinical Diagnosis is an accessible and readable look at the medical diagnostic process. Based on 30 years experience as a primary care clnician, the author presents insights and concepts developed in cognitive psychology that bear on the diagnostic process, reviews what recent evidence tells us about diagnosis, and suggests specific, practical steps aimed at improving diagnosis in medical training and practice.
Written by nationally and internationally recognised experts on the design, evaluation and application of such systems, this book examines the impact of practitioner and patient use of computer-based diagnostic tools. It serves simultaneously as a resource book on diagnostic systems for informatics specialists; a textbook for teachers or students in health or medical informatics training programs; and as a comprehensive introduction for clinicians, with or without expertise in the applications of computers in medicine, who are interested in learning about current developments in computer-based diagnostic systems. Designed for a broad range of clinicians in need of decision support.
Technology assessment can lead to the rapid application of essential diagnostic technologies and prevent the wide diffusion of marginally useful methods. In both of these ways, it can increase quality of care and decrease the cost of health care. This comprehensive monograph carefully explores methods of and barriers to diagnostic technology assessment and describes both the rationale and the guidelines for meaningful evaluation. While proposing a multi-institutional approach, it emphasizes some of the problems involved and defines a mechanism for improving the evaluation and use of medical technology and essential resources needed to enhance patient care.
v. 1. Research findings -- v. 2. Concepts and methodology -- v. 3. Implementation issues -- v. 4. Programs, tools and products.