Value Health 2013 Jul;16(5):814-822, 01-07-2013

Italian population-based values of EQ-5D health states

Scalone L, Cortesi PA, Ciampichini R, Belisari A, D'Angiolella LS, Cesana G, Mantovani LG

Abstract

OBJECTIVE: To estimate a value set for the calculation of Italian-specific quality-adjusted life years (QALYs), based on preferences elicited on EuroQol five-dimensional (EQ-5D) questionnaire health states using the time trade-off technique. METHODS: The revised standard Measurement and Valuation of Health protocol was followed. Twenty-five health states, divided into three groups and given to 450 subjects, were selected to obtain 300 observations per state. Subjects aged 18 to 75 years were recruited to be representative of the Italian general adult population for age, sex, and geographical distribution. To improve efficiency, face-to-face interviews were conducted by using the Computer Assisted Personal Interviewing approach. Several random effects regression models were tested to predict the full set of EQ-5D questionnaire health states. Model selection was based on logical consistency of the estimates, sign and magnitude of the regression coefficients, goodness of fit, and parsimony. RESULTS: The model that satisfied the criteria of logical consistency and was more efficient includes 10 main effect dummy variables for the EQ-5D questionnaire domain levels and the D1 interaction term, which accounts for the number of dimensions at levels 2 or 3 beyond the first. This model has an R(2) of 0.389 and a mean absolute error of 0.03, which are comparable to or better than those of models used in other countries. The utility estimates after state 11111 range from 0.92 (21111) to -0.38 (33333). Italian utility estimates are higher than those estimated in the United Kingdom and Spain and used so far to assess QALYs and conduct cost-utility evaluations in Italy. CONCLUSIONS: A specific value set is now available to calculate QALYs for the conduction of health economic studies targeted at the Italian health care system


Keywords:
Adolescent;Adult;Age Factors;Aged;Attitude to Health;Cost-Benefit Analysis;Female;Health Status;Humans;Italy;Male;Middle Aged;Psychometrics;Quality of Life;Quality-Adjusted Life Years;Sex Factors;Socioeconomic Factors;Time Factors;Young Adult;EQ-5D;EQ5D