HEALTH ECONOMICS Health Econ. 17: 31–40 (2008) Published online 4 April 2007 in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/hec.1235 THE CONSTRUCTION OF STANDARD GAMBLE UTILITIES SYLVIE M. C. VAN OSCH and ANNE M. STIGGELBOUT* Department of Medical Decision Making, Leiden University Medical Center, The Netherlands SUMMARY Health effects for cost-effectiveness analysis are best measured in life years, with quality of life in each life year expressed in terms of utilities. The standard gamble (SG) has been the gold standard for utility measurement. However, the biases of probability weighting, loss aversion, and scale compatibility have an inconclusive effect on SG utilities. We determined their effect on SG utilities using qualitative data to assess the reference point and the focus of attention. While thinking aloud, 45 healthy respondents provided SG utilities for six rheumatoid arthritis health states. Reference points, goals, and focuses of attention were coded. To assess the effect of scale compatibility, correlations were assessed between focus of attention and mean utility. The certain outcome served most frequently as reference point, the SG was perceived as a mixed gamble. Goals were mostly mentioned with respect to this outcome. Scale compatibility led to a significant upward bias in utilities; attention lay relatively more on the low outcome and this was positively correlated with mean utility. SG utilities should be corrected for loss aversion and probability weighting with the mixed correction formula proposed by prospect theory. Scale compatibility will likely still bias SG utilities, calling for research on a correction. Copyright # 2007 John Wiley & Sons, Ltd. Received 20 June 2005; Accepted 25 January 2007 KEY WORDS: health-utility measurement; reference point; standard gamble; time trade-off INTRODUCTION In cost-effectiveness analyses, additional costs associated with a health-care intervention are compared to additional effectiveness (health effects). It is commonly acknowledged that health effects are best measured in terms of life years and that quality of life in each life year is best expressed in terms of utilities as a weighting factor, yielding quality-adjusted life years (QALYs) (Drummond et al., 1990; Sox et al., 1988; van den Hout et al., 2002). Based on normative expected-utility arguments, the standard gamble (SG) method has often been considered the gold standard for utility measurement because, unlike other elicitation methods, it incorporates risk. The SG generally requires a respondent to compare the certainty of being in the health state to be valued for the remaining life expectancy (LE), with a gamble that offers a chance of optimal health for the remaining LE but also entails a risk of immediate death. In the generally used probability equivalent of the SG, the respondent is asked to indicate at what probabilities of the gamble he or she would be indifferent to the choice between the health state and the gamble. There is much empirical evidence demonstrating that expected utility is not descriptively valid, the three main reasons for this being probability weighting, loss aversion and scale compatibility (Bleichrodt, 2002; Delquie, 1993; Hershey and Schoemaker, 1985; Tversky and Kahneman, 1992). These biases generally lead to SG utilities that are too high. The use of biased utilities leads to biased resource allocation decisions and, therefore, the joint effect of these biases should be minimized in the *Correspondence to: Department of Medical Decision Making, Leiden University Medical Center, J10-S, P.O. Box 9600, 2300 RC Leiden, The Netherlands. E-mail: a.m.stiggelbout@lumc.nl Copyright # 2007 John Wiley & Sons, Ltd.