Hybrid anchoring method demonstrated better performance in predicting observed cTTO values, whereas DCE_TTO model showed greater deviations and a tendency to underestimate health state values. Hybrid anchoring method also appeared as the most appropriate and reliable approach for anchoring ordinal utility data to the full health-dead scale.

Dans ce rapport, nous comparons empiriquement sept techniques d’élicitation pour évaluer les utilités associées aux états de santé décrits par le Short-Form 6-Dimension version 2 (SF-6Dv2) et où le pari ordinaire (standard gamble – SG) est considérée comme l’approche de référence. Ce faisant, cela nous permet d’estimer un ensemble de valeurs d’utilité pour le SF-6Dv2 à utiliser au Québec et d’introduire une nouvelle approche basée sur le choix dichotomique multiple borné (multiple bounded discrete choice, MBDC). D…

Background: An updated version of the Short-Form 6-Dimension (SF-6D) Classification System has been developed. This new version (SF-6Dv2) with improved consistency and dimension descriptors is now requiring the development of new utility value sets. The aim of this study was to estimate an SF-6Dv2 value set from a general population in Quebec, Canada. Methods: A discrete choice experiment with time trade-off (DCETTO) was conducted using two designs: binary choice sets (Design 1) and best-worst choice sets (Design …

A heteroskedastic hybrid model using data from SG, cTTO, and DCE was identified as the most effective approach for generating the SF-6Dv2 value set and is expected to provide key input for healthcare decision-making.

Based on empirical evidence, it can be inferred that the MBDC method is not only feasible but also holds the potential to generate meaningful and well-informed preference data from respondents. This approach can be used to derive a value set for preference-based instrument.