Developing a preference-based measure for weight-specific health-related quality of life in adolescence: the WAItE UK valuation study protocol

Valuing selected WAItE health states using the Time Trade-Off methodology: findings from an online interviewer-assisted remote survey

PURPOSE

The Weight-Specific Adolescent Instrument for Economic Evaluation (WAItE) is a physical weight-specific patient reported outcome measure for use in adolescence. The purpose of this study was to use the Time Trade-Off (TTO) methodology, administered using an online interviewer-assisted remote survey, to obtain utility values for several health states from the WAItE descriptive system from a sample of the UK adult general population.

METHODS

The adult sample was gathered using a market research company and a sample of local residents. All participants completed the same interviewer-assisted remote survey, which included rating WAItE states of varying impairment using the TTO.

RESULTS

42 adults completed the survey. Utility values were gathered for four health states, ranging from low impairment to the most severe health from the WAItE descriptive system (the Pits state). Consistent orderings of the WAItE health states were observed; the health state with the lowest level of impairment was valued highest and the Pits state was valued lowest. Several respondents (n = 7, 17%) considered the Pits state to be worse than death; however, the mean value of this health state was 0.23.

CONCLUSIONS

The utility value of the Pits state relative to death generated from this study will be used to anchor latent values for WAItE health states generated from a Discrete Choice Experiment onto the 0 = death, 1 = full health Quality Adjusted Life Year (QALY) scale as part of a valuation study for the WAItE in the UK population. This study also provides further evidence that interviewer-assisted digital studies are feasible for collecting TTO data.

Analytical Considerations When Anchoring Discrete Choice Experiment Values Using Composite Time Trade-Off Data: The Case of EQ-5D-Y-3L

Discrete choice experiments (DCEs) are becoming increasingly used to elicit preferences for children's health states. However, DCE data need to be anchored to produce value sets, and composite time trade-off (cTTO) data are typically used in the context of EQ-5D-Y-3L valuation. The objective of this paper is to compare different anchoring methods, summarise the characteristics of the value sets they produce, and outline key considerations for analysts. Three anchoring methods were compared using data from published studies: (1) rescaling using the mean value for the worst health state; (2) linear mapping; and (3) hybrid modelling. The worst state rescaling value set had the largest range. The worst state rescaling and linear mapping value sets preserved the relative importance of the dimensions from the DCE, whereas the hybrid model value set did not. Overall, the predicted values from the hybrid model value set were more closely aligned with the cTTO values. These findings are relatively generalisable. Deciding upon which anchoring approach to use is challenging, as there are numerous considerations. Where cTTO data are collected for more than one health state, anchoring on the worst health state will arguably be suboptimal. However, the final choice of approach may require value judgements to be made. Researchers should seek input from relevant stakeholders when commencing valuation studies to help guide decisions and should clearly set out their rationale for their preferred anchoring approach in study outputs.