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A Comparison of EQ-5D Index Scores Derived from the US and UK Population-Based Scoring Functions

Centre for Health Services Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, medln{at}nus.edu.sg

Jeffrey A. Johnson, PhD

Institute of Health Economics & University of Alberta, Edmonton, Alberta, Canada

James W. Shaw, PhD, PharmD, MPH

Department of Pharmacy Administration and Center for Pharmacoeconomics, College of Pharmacy, University of Illinois at Chicago, Illinois

Stephen Joel Coons, PhD

College of Pharmacy and College of Public Health, University of Arizona, Tucson, Arizona

The authors recently introduced a new preference-based scoring function for the EQ-5D (D1 model) based on time tradeoff valuations from the general adult US population. In this study, they compared the EQ-5D index scores derived from the US (D1) algorithm to the more familiar UK (N3) algorithm. They compared preference-based EQ-5D index scores for all possible EQ-5D health states and differences in EQ-5D index scores between pairs of EQ-5D health states predicted by the D1 and N3 models. The responsiveness of D1- and N3-predicted EQ-5D index scores was assessed using simulated transitions between EQ-5D health states. The mean (SD) EQ-5D index scores for all 243 health states predicted by the D1 and N3 models were 0.37 (0.23) and 0.14 (0.31), respectively. The mean (SD) absolute difference in EQ-5D index scores for all 29,403 pairs of health states was 0.25 (0.19) and 0.35 (0.27), according to the D1 and N3 models, respectively. The D1 and N3 models were consistent in predicting gains/losses for 27,592 (94%) transitions between EQ-5D health state pairs; Cohen effect size, calculated using these 27,592 consistent transitions, was 1.58 and 1.59 for the D1 and N3 models, respectively. Based on these simulation results, it appears that the D1 model would lead to smaller gains in quality-adjusted life years than the N3 model; however, their responsiveness appears to be similar. Empirical studies are needed to examine whether these 2 EQ-5D scoring functions would lead to different conclusions in cost-utility analyses.

Key Words: EQ-5D • health state preferences • health state values • valuation • cost-utility analysis

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