Thomas Mayrhofer – författare

This textbook offers a comprehensive theory of medical decision making under uncertainty, combining informative test theory with the expected utility hypothesis. 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 result is determined by the decision maker. Finally, 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 become endogenous.

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.

This textbook offers a comprehensive analysis of medical decision-making under uncertainty by combining test information theory with expected utility theory. The authors show how the parameters of Bayes’ theorem can be combined with a value function of health states in order to arrive at informed test and treatment decisions in the face of diagnostic and therapeutic risks. Distinguishing between risk-neutral, risk-averse, and prudent decision-makers, they demonstrate the effects of risk preferences on medical decisions. Furthermore, they analyze individual and multiple tests as well as diagnostic models in which the decision-maker chooses the test outcome. The consequences of test and treatment decisions for the patient are encompassed by quality-adjusted life years (QALYs) and the standard economic model, which applies the willingness to pay for health approach. Lastly, non-expected utility models of choice under risk and uncertainty are presented. Although these models can explainsome of the test and treatment decisions observed, they are less suitable for normative analyses aimed at providing guidance on medical decision-making.

This third edition provides extensively revised versions of all chapters and reflects recent innovations in medical decision-making such as decision curve analysis. New chapters focus on the health economics of and revealed preferences in medical decisions. The book is intended for students of (health) economics and medicine as well as for medical decision-makers and physicians dealing with uncertainty in their test and treatment decisions.