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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.
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