Health utility bias: a systematic review and meta-analytic evaluation.
BACKGROUND
A common assertion is that rating scale (RS) values are lower than both standard gamble (SG) and time tradeoff (TTO) values. However, differences among these methods may be due to method specific bias. Although SG and TTOs suffer systematic bias, RS responses are known to depend on the range and frequency of other health states being evaluated. Over many diverse studies this effect is predicted to diminish. Thus, a systematic review and data synthesis of RS-TTO and RS-SG difference scores may better reveal persistent dissimilarities.


OBJECTIVE
The purpose of this study was to establish through systematic review and meta-analysis the net effect of biases that endure over many studies of utilities.


METHODS
A total of 2206 RS and TTO and 1318 RS and SG respondents in 27 studies of utilities participated. MEDLINE was searched for data from 1976 to 2004, complemented by a hand search of full-length articles and conference abstracts for 9 journals known to publish utility studies, as well as review of results and additional recommendations by 5 outside experts in the field. Two investigators abstracted the articles. We contacted the investigators of the original if required information was not available.


RESULTS
No significant effect for RS and TTO difference scores was observed: effect size (95% confidence interval [CI]) = 0.04 (-0.02, 0.09). In contrast, RS scores were significantly lower than SG scores: effect size (95% CI ) =-0.23 (-0.28, -0.19). Correcting SG scores for 3 known biases (loss aversion, framing, and probability weighting) eliminated differences between RS and SG scores: effect size (95% CI ) = 0.01 (-0.03, 0.05). Systematic bias in the RS method may exist but be heretofore unknown. Bias correction formulas were applied to mean not individual utilities.


CONCLUSIONS
The results of this study do not support the common view that RS values are lower than TTO values, may suggest that TTO biases largely cancel, and support the validity of formulas for correcting SG bias.
Doctor
Jason N
JN
Department of Pharmaceutical Economics and Policy, School of Pharmacy, University of Southern California, Los Angeles, CA, USA. jdoctor@u.washington.edu
Bleichrodt
Han
H
Lin
H Jill
HJ
D015982:Bias; D006304:Health Status; D006305:Health Status Indicators; D006801:Humans; D011788:Quality of Life