An EQ-5D-5L Value Set for Belgium

Objective This study aimed to establish a Belgian EQ-5D-5L value set based on the preferences of the adult Belgian general population. Methods The most recent EuroQol Valuation Technology (EQ-VT 2.1) protocol for EQ-5D-5L valuation studies was followed. Computer-assisted personal interviews were carried out in a representative sample of the adult Belgian population. Potential respondents were randomly selected from the National Register using a multistage, stratified, cluster sampling with unequal probability design. Each respondent valued 10 or 11 health states using composite time trade-off (cTTO) and 14 health states in seven paired choice tasks using a discrete choice experiment (DCE). Different model specifications were explored and assessed based on logical consistency, goodness of fit, predictive accuracy and theoretical considerations. Results A total of 892 respondents were included in the analyses. The sample was representative of the Belgian adult population in terms of age, sex, region of residence, educational attainment, labour market status, self-assessed health status and health-related quality of life (HRQoL). The preferred model specification was a hybrid (DCE and cTTO data combined) multiplicative eight-coefficient model with intercept random effects and correction for heteroskedasticity. Values range from - 0.532 to 1. Loss of HRQoL is highest in the dimension pain/discomfort, closely followed by anxiety/depression. Conclusions This study developed a Belgian EQ-5D-5L value set, based on the preferences of the Belgian adult general population. It provides opportunities for future clinical and economic evaluations in healthcare, for the measurement of patient-reported outcomes and for population health assessments.

Automated summary

This study aimed to establish a Belgian EQ-5D-5L value set based on the preferences of the adult Belgian general population. The preferred model specification was a hybrid multiplicative eight-coefficient model with intercept random effects and correction for heteroskedasticity. The study provides opportunities for future clinical and economic evaluations, measurement of patient-reported outcomes, and population health assessments.