Medical Decision Making

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Focusing on medical decision-making under uncertainty, this textbook integrates test information theory with expected utility theory. It explores how Bayes' theorem parameters and health state value functions inform test and treatment choices amidst diagnostic risks. By distinguishing between different risk preferences—risk-neutral, risk-averse, and prudent—the authors illustrate their impact on decisions. The analysis includes individual and multiple tests, diagnostic models, and evaluates outcomes using quality-adjusted life years (QALYs). Additionally, it discusses non-expected utility models, highlighting their limitations for normative guidance in medical choices.