This textbook offers a comprehensive analysis of medical decision making under uncertainty by combining Test Information Theory with Expected Utility Theory. The book shows how the parameters of Bayes' theorem can be combined with a value function of health states to arrive at informed test and treatment decisions. The authors distinguish between risk-neutral, risk-averse and prudent decision makers and demonstrate the effects of risk preferences on physicians' decisions. They analyze individual tests, multiple tests and endogenous tests where the test outcome is chosen by the decision maker.…mehr
This textbook offers a comprehensive analysis of medical decision making under uncertainty by combining Test Information Theory with Expected Utility Theory. The book shows how the parameters of Bayes' theorem can be combined with a value function of health states to arrive at informed test and treatment decisions. The authors distinguish between risk-neutral, risk-averse and prudent decision makers and demonstrate the effects of risk preferences on physicians' decisions. They analyze individual tests, multiple tests and endogenous tests where the test outcome is chosen by the decision maker. Moreover, the topic is examined in the context of health economics by introducing a trade-off between enjoying health and consuming other goods, so that the extent of treatment and thus the potential improvement in the patient's health becomes endogenous. Finally, non-expected utility models of choice under risk and uncertainty (i.e. ambiguity) are presented. While these models can explain observed test and treatment decisions, they are not suitable for normative analyses aimed at providing guidance on medical decision making.
Stefan Felder is a Full Professor of Health Economics at the Department of Business and Economics of the University of Basel, Switzerland. He studied economics and sociology, and received his Ph.D. and his venia docendi from the University of Bern, Switzerland. He worked and taught at the University of Western Ontario, Canada (1990/92), the University of Zurich, Switzerland (1992/1996), and the University of Fribourg, Switzerland (1993/95), before joining the Faculties of Medicine and Economics at the University of Magdeburg, Germany, in 1997. Between 2008 and 2011, he was Professor of Economics at the University of Duisburg-Essen, Germany, and from 2011 to 2015, Director of the German Health Economic Research Centre CINCH in Essen, Germany. He is currently the Executive Secretary of the European Health Economic Association and President-elect of the German Association of Health Economics. Thomas Mayrhofer is Professor of Economics at Stralsund University of Applied Sciences, Stralsund, Germany, and Instructor at Massachusetts General Hospital and Harvard Medical School of Harvard University, Boston, USA. He studied economics at the University of Magdeburg, Germany, and received his Ph.D. in economics at the University of Duisburg-Essen, Germany. Before becoming a professor in Stralsund, he worked at the German Health Economic Research Centre CINCH in Essen, Germany, and at Massachusetts General Hospital and Harvard Medical School of Harvard University, Boston, USA.
Inhaltsangabe
Introduction.- Basic Tools in Medical Decision Making.- Preferences, Expected Utility, Risk Aversion and Prudence.- Treatment Decisions Without Diagnostic Tests.- Treatment Decisions with Diagnostic Tests.- Treatment Decisions Under Comorbidity Risk.- Optimal Strategy for Multiple Diagnostic Tests.- The Optimal Cutoff Value of a Diagnostic Test.- A Test's Total Value of Information.- Valuing Health and Life.- Imperfect Agency and Non-expected Utility Models.
Introduction.- Basic Tools in Medical Decision Making.- Preferences, Expected Utility, Risk Aversion and Prudence.- Treatment Decisions Without Diagnostic Tests.- Treatment Decisions with Diagnostic Tests.- Treatment Decisions Under Comorbidity Risk.- Optimal Strategy for Multiple Diagnostic Tests.- The Optimal Cutoff Value of a Diagnostic Test.- A Test's Total Value of Information.- Valuing Health and Life.- Imperfect Agency and Non-expected Utility Models.
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