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The Implications of Differing Methods of Utility Assessment for Patient-Specific Decision-Analytic Tools

I has become increasingly recognized that the comprehensive evaluation of medical tests and interventions should incorporate the measurement of health outcomes, and such assessments should include both length and quality of life. In economics, utility theory describes the relationships between discrete outcomes—such as varying amounts of goods—with the strength of one’s preferences or values for those goods, in the context of lessthan-certain probabilities of those outcomes. Previous authors have described how many aspects of decision making in health care and health care delivery are direct consequences of considering uncertain risks and benefits associated with those decisions. Thus, outcomes assessment using methods grounded in utility theory would appear to be an appropriate venue for assessing health-related quality of life, since much of decision making in health care involves consideration of potential risks and benefits and not certain ones. One difficulty with utility-based methods of healthrelated quality-of-life assessment has been the lack of a standardized measurement approach. Since there is no true gold standard for quality-of-life measures in general and health utility measures in particular, we are unable to test the criterion validity of utilities. The standard gamble (SG) is generally accepted to be the most valid form of assessing preferences and is based most closely on the axioms of utility theory. However, the valuation of health states based on the probabilities of health outcomes may be a difficult conceptual exercise for many in the general audience. Because most people would not previously have thought of health states in such contexts, this approach may be susceptible to departures from the logic assumptions necessary for utility assessment. In prior investigations of utilities for current health, various non–health-related individual characteristics have been shown to influence SG scores (as well as utility scores elicited by other methods). As such, utilities may only modestly reflect the value of the health state and may capture various other non–health-related factors. Some investigators have argued that the time tradeoff (TTO) approach is a preferable elicitation method in the context of health and illness because tradeoffs surrounding life expectancy may be easier to understand than probabilities. Studies comparing the 2 methods of utility elicitation have generally shown that most populations appear to assign higher aggregate SG values to health states than TTO values, with individual differences in results between the 2 methods being highly variable. Because of the conceptual and practical difficulties with direct utility assessment, a power function has been proposed that relates sample mean health rating scores with sample mean utilities: utility = 1 – (1 – rating), where x represents a constant. However, the nature of this relationship has been shown to be inconsistent between populations and across health states and highly susceptible to individual variation. Although such previous work has shown that the method of utility assessment influences values assigned to health states, less work has been performed to examine how differing methods of elicitation may explicitly affect diagnostic or treatment recommendations. In this issue of Medical Decision Making, Elkin and colleagues extend previous work on measurement issues surrounding health utilities. First, they compared values for 5 prostate cancer–related health states using 1) health rating scale scores (not true utilities), 2) utility estimates based on an exponential transformation of rating scale scores, and 3) directly derived TTO utilities. Not surprisingly, they found that different methods of deriving values resulted in different scores for those 5 health states, and scores did not correlate well when compared by rank ordering of those states. They then applied those results to a previously described prostate cancer decision analytic model. Depending on the method of deriving health utilities and the tumor grade, concordance between the 2 treatment recommendations—watchful waiting or radical prostatectomy—ranged from 79% to as low as 48%.