Estimating an EQ-5D-5L Value Set for China

• Published in: Value in health Vol. 20; no. 4; pp. 662 - 669
• Main Authors: Luo, Nan, PhD, Liu, Gordon, PhD, Li, Minghui, MSc, Guan, Haijing, MSc, Jin, Xuejing, MSc, Rand-Hendriksen, Kim, PhD
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01-04-2017; Elsevier Science Ltd; Blackwell Publishers
• Subjects: Activities of Daily Living; Additives; Adolescent; Adult; China; Cost analysis; Cross-Sectional Studies; cross-validation; EQ-5D-5L; Errors; Female; Health services utilization; Health Status; Health Status Indicators; Humans; Internal Medicine; Interviews as Topic; Linear Models; Male; Medical technology; Mental Health; Middle Aged; modeling; Nonlinear Dynamics; Pain Measurement; Preferences; Psychometrics; Quality of Life; Questionnaires; Regression analysis; Reproducibility of Results; Scaling; Self Care; Surveys and Questionnaires; time trade-off; Urban areas; Urban Health; Validity; Values; Young Adult; China; cross-validation; EQ-5D-5L; modeling; time trade-off
• ISSN: 1098-3015; 1524-4733
• DOI: 10.1016/j.jval.2016.11.016

Abstract Objectives To estimate a five-level EuroQol five-dimensional questionnaire (EQ-5D-5L) value set for China using the health preferences of residents living in the urban areas of the country. Methods The values of a subset of the EQ-5D-5L–defined health states (n = 86) were elicited using the time trade-off (TTO) technique from a sample of urban residents (n = 1271) recruited from five Chinese cities. In computer-assisted personal interviews, participants each completed 10 TTO tasks. Two additive and two multiplicative regression models were evaluated for their performance in describing the relationship between TTO values and health state characteristics using a cross-validation approach. Final values were generated using the best-performed model and a rescaling method. Results The 8- and 9-parameter multiplicative models unanimously outperformed the 20-parameter additive model using a random or fixed intercept in predicting values for out-of-sample health states in the cross-validation analysis and their coefficients were estimated with lower standard errors. The prediction accuracies of the two multiplicative models measured by the mean absolute error and the intraclass correlation coefficient were very similar, thus favoring the more parsimonious model. Conclusions The 8-parameter multiplicative model performed the best in the study and therefore was used to generate the EQ-5D-5L value set for China. We recommend using rescaled values whereby 1 represents the value of instrument-defined full health in economic evaluation of health technologies in China whenever the EQ-5D-5L data are available.