Valuing EQ-5D-5L health states ‘in context’ using a discrete choice experiment
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In health state valuation studies, health states are typically presented as a series of sentences, each describing a health dimension and severity ‘level’. Differences in the severity levels can be subtle, and confusion about which is ‘worse’ can lead to logically inconsistent valuation data. A solution could be to mimic the way patients self-report health, where the ordinal structure of levels is clear. We develop and test the feasibility of presenting EQ-5D-5L health states in the ‘context’ of the entire EQ-5D-5L descriptive system.
An online two-arm discrete choice experiment was conducted in the UK (n = 993). Respondents were randomly allocated to a control (standard presentation) or ‘context’ arm. Each respondent completed 16 paired comparison tasks and feedback questions about the tasks. Differences across arms were assessed using regression analyses.
Presenting health states ‘in context’ can significantly reduce the selection of logically dominated health states, particularly for labels ‘severe’ and ‘extreme’ (χ2 = 46.02, p < 0.001). Preferences differ significantly between arms (likelihood ratio statistic = 42.00, p < 0.05). Comparing conditional logit modeling results, coefficients are ordered as expected for both arms, but the magnitude of decrements between levels is larger for the context arm.
Health state presentation is a key consideration in the design of valuation studies. Presenting health states ‘in context’ affects valuation data and reduces logical inconsistencies. Our results could have implications for other valuation tasks such as time trade-off, and for the valuation of other preference-based measures.
KeywordsEQ-5D Health states Valuation methods Discrete choice experiment Stated preferences
This study was funded by the EuroQol Research Foundation. However, the views expressed do not necessarily reflect the views of the EuroQol Research Foundation. We would like to thank Richard Norman for his constructive comments on an earlier version of this paper, and are grateful for feedback obtained from participants at the EuroQol Scientific Plenary Meeting and the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) congress, where earlier versions of the paper were presented. We would also like to thank Rob White from EpiGenesys for survey development, and Andreea Sisman, Oana Baraitarus and colleagues at Survey Sampling International (SSI) for the recruitment of respondents.
Compliance with ethical standards
Conflict of interest
Koonal Shah, Yan Feng, Brendan Mulhern, and Nancy Devlin are members of the EuroQol Group. There are no other relationships or potential conflicts of interest to declare.
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