Decision making in health care involves consideration of a complex set of diagnostic, therapeutic and prognostic uncertainties. Medical therapies have side effects, surgical interventions may lead to complications, and diagnostic tests can produce misleading results. Furthermore, patient values and service costs must be considered. Decisions in clinical and health policy require careful weighing of risks and benefits and are commonly a trade-off of competing objectives: maximizing quality of life vs maximizing life expectancy vs minimizing the resources required. This text takes a proactive, systematic and rational approach to medical decision making. It covers decision trees, Bayesian revision, receiver operating characteristic curves, and cost-effectiveness analysis; as well as advanced topics such as Markov models, microsimulation, probabilistic sensitivity analysis and value of information analysis. It provides an essential resource for trainees and researchers involved in medical decision modelling, evidence-based medicine, clinical epidemiology, comparative effectiveness, public health, health economics, and health technology assessment.

Learning Clinical Reasoning uses a case-based approach to teach students the basics of clinical reasoning. The first section explains the chief components of the clinical reasoning process, such as generating and refining diagnostic hypotheses, using and interpreting diagnostic tests, assembling a working diagnosis, therapeutic decision making, and examining and applying evidence, and also includes a discussion of cognitive errors. The second section contains 69 cases in which clinicians "think out loud" about diagnostic and therapeutic dilemmas, and the authors critique these clinicians' reasoning. This edition has thirty new cases from the New England Journal of Medicine and other sources and expanded discussions of evidence-based medicine, clinical practice guidelines, and cognitive errors. A companion Website includes fully searchable text, references, and a "Pattern Recognition" section similar to Images in Clinical Medicine in NEJM.