ESTIMATING THE TIME TRADE-OFF VALUES OF THE EQ-5D-5L HEALTH STATES IN URBAN CHINA

OBJECTIVES: The EQ-5D-5L is a new health-state classification system consisting of five dimensions (mobility, self-care, usual activities, pain/discomfort, and anxiety/depression), with each dimension described into five problem levels (no, slight, moderate, severe, and extreme). This study aimed to estimate the time trade-off (TTO) values of the 3,125 EQ-5D-5L health states to urban residents in China.  METHODS: The values for 86 selected EQ-5D-5L health states were elicited using the ‘composite’ TTO technique from a general population sample (n=1,250) drawn from 5 Chinese cities. In computer-assisted personal interviews, participants each valued a randomly selected block of health states (n=10). Various function forms were constructed to specify the possible relationship between TTO values and health-state characteristics and estimated using linear regression models. The function form exhibiting the best fit of the data and the least prediction biases was identified to estimate the values of all EQ-5D-5L health states.  RESULTS: The Hausman test suggested that random effects estimator was more efficient than fixed effects estimator for all function forms. The best model comprised a constant and twenty-one dummy variables indicating the presence or absence of specific problems or patterns of problems in a given EQ-5D-5L health state, including nineteen for all individual health problems except for slight anxiety/depression, one for severe or extreme problems in any functional dimensions, and one for the 5 mildest EQ-5D-5L health states. According to the final model, the mean absolute error of the predicted values for the 86 health states was 0.032 and the range of all the predicted values was -0.339 to 0.893.  CONCLUSIONS: Values of EQ-5D-5L health states can be estimated using time trade-off values of a small portion of the health states. The EQ-5D-5L preference values estimated in this study may be used as quality-of-life weights in cost-utility analysis of health technologies and programs in China.