Is Expected Utility Theory Normative for Medical Decision Making?

Abstract

Expected utility theory is felt by its proponents to be a normative theory of decision making under uncertainty. The theory starts with some simple axioms that are held to be rules that any rational person would follow. It can be shown that if one adheres to these axioms, a numerical quantity, generally referred to as utility, can be assigned to each possible outcome, with the preferred course of action being that which has the highest expected utility. One of these axioms, the independence principle, is controversial, and is frequently violated in experimental situations. Proponents of the theory hold that these violations are irrational. The independence principle is simply an axiom dictating consistency among preferences, in that it dictates that a rational agent should hold a specified preference given another stated preference. When applied to preferences between lotteries, the independence principle can be demonstrated to be a rule that is followed only when preferences are formed in a particular way. The logic of expected utility theory is that this demonstration proves that preferences should be formed in this way. An alternative interpretation is that this demonstrates that the independence principle is not a valid general rule of consistency, but in particular, is a rule that must be followed if one is to consistently apply the decision rule "choose the lottery that has the highest expected utility." This decision rule must be justified on its own terms as a valid rule of rationality by demonstration that violation would lead to decisions that conflict with the decision maker's goals. This rule does not appear to be suitable for medical decisions because often these are one-time decisions in which expectation, a long-run property of a random variable, would not seem to be applicable. This is particularly true for those decisions involving a non-trivial risk of death.

Finding Useful Questions: On Bayesian Diagnosticity, Probability, Impact, and Information Gain.

“…Because "the complexity of any real decision problem defies complete explicit description" (Savage, 1954, p. 107), the probability models below reflect simplified experimental tasks. For instance, although Baron, Beattie, and Hershey (1988) studied a simple case of medical diagnosis, extension of that analysis to actual medical decision making is not straightforward (Cohen, 1996;Baron, 1996). Nor is it straightforward to predict how subjects will interpret an experimental task (McKenzie, Wixted, & Noelle, 2004 (Table 4) in a pair of questions.…”

The comparability and reliability of five health-state valuation methods

“…The value (utility) of the stationary state is defined as the probability p at the indifference situation. SG is regarded as a valid operationalisation of the von Neuman-Morgenstern utility gamble (Neumann von and Morgenstern, 1953;Cohen, 1996).…”

DAHP Expected Utility Based Evaluation Model for Management Performance on Interior Environmental Decoration – An Example in Taiwan

“…By the combination of Delphi method, Analytical hierarchy process (AHP), and Utility theory, the development of the DAHP Expected Utility Function in this study presents high objectivity. Cohen indicated that the axioms need not be descriptive to be normative, and they need not be attractive to all decision makers for expected utility theory to be useful for some (Cohen, 1996). Housing Market Search Behavior and Expected Utility Theory: Measuring Preferences for Housing (Smith and Clark, 1982) is a case to establish the decision-making analysis model with Expected Utility Theory for housing issues.…”