QL2: LOGICAL CONSISTENCY AND THE VALUATION OF HEALTH: AN ANALYSIS OF US SURVEY DATA

Abstract

OBJECTIVES: It is widely held that values of the general public should be used in the evaluation of health care. Surveys designed to record such values involve the participation of individuals with different health experiences and with different socioeconomic backgrounds. The technical performance of these participants is likely to vary as a function of these factors, for example the logical consistency of responses is often associated with socioeconomic status. This paper examines the relationship between logical consistency and respondent health using US survey data designed to capture values for states defined by the EQ-5D classification. METHODS: A standardised questionnaire was used to elicit valuations for EQ-5D health states in a postal survey conducted by Johnson et al (1998, Pharmacoeconomics) in Arizona in which US respondents (N = 905) rated eight states along a visual analog scale from best to worst imaginable health. A logical ordering is defined for 23 unique pairs of states in that one state dominates the other over all 5 dimension of the EQ-5D. A logical inconsistency was noted when a respondent assigned a lower value to the “better” state in such a pair. Censored regression models were used to assess the relationship between consistency and respondent health. We tested the robustness of these findings using survey data from Wisconsin, which applied the same questionnaire (N = 222). RESULTS: From the best imaginable state, each 20-point decrement in respondent's self-rated health status yielded significantly greater inconsistency in their valuation of EQ-5D health states controlling for age and sex. Inclusion of education and income reduced this effect slightly, yet it remained statistically significant. CONCLUSIONS: Respondents in poor health demonstrate greater difficult in valuing health states in a logically consistent manner. Censoring survey data to remove inconsistent respondents may violate the principle of using representative population values in evaluating cost-effectiveness of health care.