Objectives: The SF-6D is a preference-based measure of health developed to generate utility values from the SF-36. The aim of this pilot 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 using SG. The sample size is appropriate for a pilot study, but smaller than the sample required for a full valuation study. Both interviewers and interviewees reported their understanding and effort levels in the SG tasks. Mean and individual level multivariate regression models were fitted to estimate preference weights for all SF-6D states. The models were compared with those estimated in the UK. Results: Interviewers reported few problems in completing SG tasks (0.8% with a lot of problems) and good respondent understanding (5.6% with little effort and concentration), and 25% of respondents reported the SG task was difficult. A total of 992 SG valuations were useable for econometric modeling. There was no significant change in the test–retest values from 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. Conclusion: This pilot confirmed that it was feasible and acceptable to generate preference values with the SG method for the Arabic SF-6D in a Lebanese population. However, further work is needed to extend this to a more representative population, and to explore why no utility values below zero were observed.

No abstract

This is a repository copy of Modelling a preference-based index for EQ-5D-3L and EQ-5D-3L + Sleep using a Bayesian framework.

No abstract

Background: The parameter uncertainty in the six-dimensional health state short form (SF-6D) value sets is commonly ignored. There are two sources of parameter uncertainty: uncertainty around the estimated regression coefficients and uncertainty around the model’s specification. This study explores these two sources of parameter uncertainty in the value sets using probabilistic sensitivity analysis (PSA) and a Bayesian approach. Methods: We used data from the original UK/SF-6D valuation study to evaluate the extent of parameter uncertainty in the value set. First, we re-estimated the Brazier model to replicate the published estimated coefficients. Second, we estimated standard errors around the predicted utility of each SF-6D state to assess the impact of parameter uncertainty on these estimated utilities. Third, we used Monte Carlo simulation technique to account for the uncertainty on these estimates. Finally, we used a Bayesian approach to quantifying parameter uncertainty in the value sets. The extent of parameter uncertainty in SF-6D value sets was assessed using data from the Hong Kong valuation study. Results: Including parameter uncertainty results in wider confidence/credible intervals and improved coverage probability using both approaches. Using PSA, the mean 95% confidence intervals widths for the mean utilities were 0.1394 (range: 0.0565–0.2239) and 0.0989 (0.0048–0.1252) with and without parameter uncertainty whilst, using the Bayesian approach, this was 0.1478 (0.053–0.1665). Upon evaluating the impact of parameter uncertainty on estimates of a population’s mean utility, the true standard error was underestimated by 79.1% (PSA) and 86.15% (Bayesian) when parameter uncertainty was ignored. Conclusions: Parameter uncertainty around the SF-6D value set has a large impact on the predicted utilities and estimated confidence intervals. This uncertainty should be accounted for when using SF-6D utilities in economic evaluations. Ignoring this additional information could impact misleadingly on policy decisions.