This volume presents novel concepts to help physicians and health care providers better understand the thought processes and approaches used in clinical decision-making and how we develop those skills as we transition from being a medical student to post-graduate trainee to independent practitioner. Approaches presented range from simple rules of thumb, pattern recognition, and heuristics, to more formulaic methods such as standard operating procedures, checklists, evidence-based medicine, mathematical modeling, and statistics. Ways to recognize and manage errors and how our decision-making can be improved, are also discussed. An Introduction to Medical Decision-Making presents several innovative techniques to allow the reader to use the principles presented and integrate the ethical, humanistic and social aspects of decision-making with the pragmatic and knowledge-based aspects of clinical medicine. It also highlights how our thinking processes, emotions, and biases affect decision-making. This invaluable resource will allow students and physicians to evaluate and critically discuss their decisions objectively to become more efficient and effective, and maximize the quality of care they provide.

Medical Decision Making provides clinicians with a powerful framework for helping patients make decisions that increase the likelihood that they will have the outcomes that are most consistent with their preferences. This new edition provides a thorough understanding of the key decision making infrastructure of clinical practice and explains the principles of medical decision making both for individual patients and the wider health care arena. It shows how to make the best clinical decisions based on the available evidence and how to use clinical guidelines and decision support systems in electronic medical records to shape practice guidelines and policies. Medical Decision Making is a valuable resource for all experienced and learning clinicians who wish to fully understand and apply decision modelling, enhance their practice and improve patient outcomes. “There is little doubt that in the future many clinical analyses will be based on the methods described in Medical Decision Making, and the book provides a basis for a critical appraisal of such policies.” - Jerome P. Kassirer M.D., Distinguished Professor, Tufts University School of Medicine, US and Visiting Professor, Stanford Medical School, US

The Encyclopedia of Medical Decision Making presents state-of-the-art research and ready-to-use facts sorting out findings on medical decision making and their applications.

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

Decision Making in Health Care, first published in 2000, is a comprehensive overview of the field of medical decision making.

For the past few years, the author, a renowned economist, has been applying the statistical tools of economics to decision making under uncertainty in the context of patient health status and response to treatment. He shows how statistical imprecision and identification problems affect empirical research in the patient-care sphere.

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.