Valuing Wellbeing alongside Health with the Discrete Choice Experiment Method

Currently, there is no valuation study generating value set for EQ-HWB on the QALY scale with Discrete choice experiment (DCE) method. This study tested the feasibility of valuing the long health and wellbeing measure using the DCE method.
The DCE with duration (DCE-TTO) design and DCE with a triplet dead state (DCE-Death) design were tested, with varied attribute order for the DCE-TTO to explore the order effect. A generator design approach applied for the choice set selection after simulation. 4056 UK and Australian general public completed the DCE survey. Demographic factors, overall QoL, health state preference, decision strategy and feedback were collected. Analysis using homogeneity and heterogeneity logit model, as well as constrained utility function, was conducted. The DCE-TTO data was anchored by calculating the marginal substitution rate to duration and the DCE-Death anchored by relative distance to latent dead state value.
All of the designs collected high-quality responses, where the proportion of negative feedback, strategic bias and inconsistency for the repeated question remained lower than 5%. The data analysis proved the feasibility of both DCE designs to generate QALY-scale value set. With the conditional logit regression result, this study found a varied order effect in UK and Australia. The DCE-Death had a larger proportion of health states defined as worse-than-death in both countries. A regression with constrained utility function generated value set with no insignificance and non-monotonicity, but utility distribution was systematically different from the individual effect models.
This study justified the feasibility of DCE in health and wellbeing preference valuation with empirical evidence. However, the design effect, model appropriateness and preference heterogeneity should be explored more in the future.