A critical re-evaluation of the regression model specification in the US D1 EQ-5D value function

Population Health Metrics

Research

Liv A Augestad¹  Fredrik A Dahl¹  Kim Rand-Hendriksen² 

[1] Health Services Research Centre, Akershus University Hospital, Lørenskog, Norway;Health Services Research Centre, Akershus University Hospital, Lørenskog, Norway;Institute of Psychology, University of Oslo, Oslo, Norway;

关键词: EQ-5D;    tariff;    regression model;    misspecification;   

DOI  :  10.1186/1478-7954-10-2

 received in 2011-06-20, accepted in 2012-01-13,  发布年份 2012

来源: Springer

【 摘 要 】

BackgroundThe EQ-5D is a generic health-related quality of life instrument (five dimensions with three levels, 243 health states), used extensively in cost-utility/cost-effectiveness analyses. EQ-5D health states are assigned values on a scale anchored in perfect health (1) and death (0).The dominant procedure for defining values for EQ-5D health states involves regression modeling. These regression models have typically included a constant term, interpreted as the utility loss associated with any movement away from perfect health. The authors of the United States EQ-5D valuation study replaced this constant with a variable, D1, which corresponds to the number of impaired dimensions beyond the first. The aim of this study was to illustrate how the use of the D1 variable in place of a constant is problematic.MethodsWe compared the original D1 regression model with a mathematically equivalent model with a constant term. Comparisons included implications for the magnitude and statistical significance of the coefficients, multicollinearity (variance inflation factors, or VIFs), number of calculation steps needed to determine tariff values, and consequences for tariff interpretation.ResultsUsing the D1 variable in place of a constant shifted all dummy variable coefficients away from zero by the value of the constant, greatly increased the multicollinearity of the model (maximum VIF of 113.2 vs. 21.2), and increased the mean number of calculation steps required to determine health state values.DiscussionUsing the D1 variable in place of a constant constitutes an unnecessary complication of the model, obscures the fact that at least two of the main effect dummy variables are statistically nonsignificant, and complicates and biases interpretation of the tariff algorithm.

【 授权许可】

CC BY   
© Rand-Hendriksen et al; licensee BioMed Central Ltd. 2012