Common scale valuations across different preference-based measures: estimation using rank data.

ABSTRACT: Background: Di¤erent preference-based measures (PBMs) used to estimate Quality Adjusted Life Years (QALYs) provide di¤erent utility values for the same patient. Dif- ferences are expected since values have been obtained using di¤erent samples, valuation techniques and descriptive systems. Previous studies have estimated the relationship be- tween pairs of PBMs using patient self-reported data. However, there is a need for an approach capable of generating values directly on a common scale for a range of PBMs using the same sample of general population respondents and valuation technique but keeping the advantages of the di¤erent descriptive systems. Methods: General public survey data (n=501) where respondents ranked health states described using subsets of six PBMs were analysed. We develop a new model based on the mixed logit to overcome two key limitations of the standard rank ordered logit model, namely, the unrealistic choice pattern (Independence of Irrelevant Alternatives) and the independence of repeated observations. Results: There are substantial di¤erences in the estimated parameters between the two models (mean di¤erence 0.07) leading to di¤erent orderings across the measures. Estimated values for the best states described by di¤erent PBMs are substantially and signi�cantly di¤erent using the standard model, unlike our approach which yields more consistent results. Limitations: Data come from a exploratory study that is relatively small both in sample size and coverage of health states. Conclusions: This study develops a new, �exible econometric model speci�cally designed to re�ect appropriately the features of rank data. Results support the view that the standard model is not appropriate in this setting and will yield very di¤erent and apparently inconsistent results. PBMs can be compared using a common scale by implementation of this new approach.