Decision Making In Medicine

This popular reference facilitates diagnostic and therapeutic decision making for a wide range of common and often complex problems faced in outpatient and inpatient medicine. Comprehensive algorithmic decision trees guide you through more than 245 disorders organized by sign, symptom, problem, or laboratory abnormality. The brief text accompanying each algorithm explains the key steps of the decision making process, giving you the clear, clinical guidelines you need to successfully manage even your toughest cases. An algorithmic format makes it easy to apply the practical, decision-making approaches used by seasoned clinicians in daily practice. Comprehensive coverage of general and internal medicine helps you successfully diagnose and manage a full range of diseases and disorders related to women's health, emergency medicine, urology, behavioral medicine, pharmacology, and much more. A Table of Contents arranged by organ system helps you to quickly and easily zero in on the information you need. More than a dozen new topics focus on the key diseases and disorders encountered in daily practice. Fully updated decision trees guide you through the latest diagnostic and management guidelines.

A guide for everyone involved in medical decision making to plot a clear course through complex and conflicting benefits and risks.

DECISION MAKING IN MEDICINE offers an algorithmic approach to the diagnosis and treatment of common disorders and diseases. By providing nearly 250 clinical decision making algorithms, this practical reference helps you arrive at the proper diagnosis and also leads you to the appropriate therapy or course of action. Brief text appears on the page facing each algorithm to provide additional explanations or details about key decision points on the algorithm. Topics are organized by sign, symptom, problem, or laboratory abnormality. The consistent format and decision tree approach of DECISION MAKING IN MEDICINE is certain to enhance your clinical efficiency.

This book clearly demonstrates how to best make medicaldecisions while incorporating clinical practice guidelines anddecision support systems for electronic medical record systems. New to this edition is how medical decision making ideas arebeing incorporated into clinical decision support systems inelectronic medical records and also how they are being used toshape practice guidelines and policies.

On average, a physician will interrupt a patient describing her symptoms within eighteen seconds. In that short time, many doctors decide on the likely diagnosis and best treatment. Often, decisions made this way are correct, but at crucial moments they can also be wrong—with catastrophic consequences. In this myth-shattering book, Jerome Groopman pinpoints the forces and thought processes behind the decisions doctors make. Groopman explores why doctors err and shows when and how they can—with our help—avoid snap judgments, embrace uncertainty, communicate effectively, and deploy other skills that can profoundly impact our health. This book is the first to describe in detail the warning signs of erroneous medical thinking and reveal how new technologies may actually hinder accurate diagnoses. How Doctors Think offers direct, intelligent questions patients can ask their doctors to help them get back on track. Groopman draws on a wealth of research, extensive interviews with some of the country’s best doctors, and his own experiences as a doctor and as a patient. He has learned many of the lessons in this book the hard way, from his own mistakes and from errors his doctors made in treating his own debilitating medical problems. How Doctors Think reveals a profound new view of twenty-first-century medical practice, giving doctors and patients the vital information they need to make better judgments together.

This analysis of the law's approach to healthcare decision-making critiques its liberal foundations in respect of three categories of people: adults with capacity, adults without capacity and adults who are subject to mental health legislation. Focusing primarily on the law in England and Wales, the analysis also draws on the law in the United States, legal positions in Australia, Canada, Ireland, New Zealand and Scotland and on the human rights protections provided by the ECHR and the Convention on the Rights of Persons with Disabilities. Having identified the limitations of a legal view of autonomy as primarily a principle of non-interference, Mary Donnelly questions the effectiveness of capacity as a gatekeeper for the right of autonomy and advocates both an increased role for human rights in developing the conceptual basis for the law and the grounding of future legal developments in a close empirical interrogation of the law in practice.

Never before have the powerful techniques of decision analysis had more importance for patient and doctor. This book translates the major principles of medical decision making into clinically relevant and easy-to-understand terms. Filled with examples drawn from patient care and familiar games of chance, Making Medical Decisions teaches the reader how to feel confident about giving the best advice in the face of the inherent uncertainties of real-world medicine.

Medical decision making has evolved in recent years, as more complex problems are being faced and addressed based on increasingly large amounts of data. In parallel, advances in computing power have led to a host of new and powerful statistical tools to support decision making. Simulation-based Bayesian methods are especially promising, as they provide a unified framework for data collection, inference, and decision making. In addition, these methods are simple to implement and can help to address the most pressing practical and ethical concerns arising in medical decision making. * Provides an overview of the necessary methodological background, including Bayesian inference, Monte Carlo simulation, and utility theory. * Driven by three real applications, presented as extensively detailed case studies. * Case studies include simplified versions of the analysis, to approach complex modelling in stages. * Features coverage of meta-analysis, decision analysis, and comprehensive decision modeling. * Accessible to readers with only a basic statistical knowledge. Primarily aimed at students and practitioners of biostatistics, the book will also appeal to those working in statistics, medical informatics, evidence-based medicine, health economics, health service research and health policy.