This is a unique, in-depth discussion of the uses and conduct of cost-effectiveness analyses (CEA) as decision-making aids in the health and medical fields. The product of over two years of deiberation by a multi-disciplinary Public Health Service appointed panel that included economists, ethicists, psychometricians, and clinicians, it explores cost-effectiveness in the context of societal decision-making for resource allocation purposes. It proposes that analysts include a "reference-case" analysis in all CEA's designed to inform resource allocation and puts forth the most expicit set of guidelines (together with their rationale) ever outlined of the conduct of CEAs. Important theoretical and practical issues encountered in measuring costs and effectiveness, valuing outcomes, discounting, and dealing with uncertainty are examined in separate chapters. These discussions are complemented by additional chapters on framing and reporting of CEAs that aim to clarify the purpose of the analysis and the effective communication of its findings. Primarily intended for analysts in medicine and public health who wish to improve practice and comparability of CEAs, this book will also be of interest to decision-makers in government, managed care, and industry who wish to consider the roles and limitations of CEA and become familiar with criteria for evaluating these studies.

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.