OP95 Examining The Feasibility And Acceptability Of Valuing The Lebanese Version Of The SF-6D Using Standard Gamble

Abstract

Introduction

The SF-6D is a preference-based measure of health, derived from the SF-36 for economic evaluation. No value set exists for the SF-6D in Lebanon and other Arabic speaking countries in the Middle East. The aim of this study was to examine the feasibility and acceptability of using the standard gamble (SG) technique to generate preference-based values for the Arabic version of SF-6D in a Lebanese population.

Methods

The SF-6D was translated into Arabic using forward and backward translations. Forty-nine states defined by the SF-6D were selected using an orthogonal design and grouped into seven sets. A gender-occupation stratified sample of 126 Lebanese adults from the American University of Beirut were recruited to value seven states and the pits (worst) SF-6D health states using SG. Mean and individual level multivariate regression models were fitted to estimate preference weights for all SF-6D states. The quality of data and the predictive power of the models were compared with results from the United Kingdom (UK).

Results

All respondents completed the interviews with 25 percent reporting that the SG task was difficult and 21 percent felt some degree of irritation or boredom. A total of 992 (98% out of 1,008 observations) SG valuations were useable for econometric modeling. There was no significant change in the test–retest values of 21 subjects. The mean absolute errors in the mean and individual level models were 0.036 and 0.050, respectively, both of which were lower than the UK results. The random effects model adequately predicts the SG values, with the worst state having a value of 0.322 compared to 0.271 in the UK.

Conclusions

This study confirmed that it was feasible and acceptable to generate preference values with the SG method for the Arabic SF-6D in a Lebanese population. This would be the first step towards developing SF-6D value set for Lebanon to be used in economic evaluation studies and to support resources allocation decisions.