The Impact of Different DCE-Based Approaches When Anchoring Utility Scores
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Discrete choice experiments (DCEs) have been proposed as a method to estimate utility weights for health states within utility instruments. However, the most appropriate method to anchor the utility values on the full health to dead quality-adjusted life year (QALY) scale remains uncertain. We test four approaches to anchoring in which dead is valued at zero and full health at one.
We use data from two DCEs valuing EQ-5D-3L and EQ-5D-5L health states, which presented pairs of health profiles with an associated duration, and a dead option. The approaches to anchoring the results on the required scale were (1) using only preferences between non-dead health profiles; (2) including the dead data, treating it as a health profile with zero duration; (3) explicitly modelling both duration and dead; and (4) using the preferences regarding the dead health state as an external anchor subsequent to the estimation of approach 1.
All approaches lead to differences in the scale of utility decrements, but not the ranking of EQ-5D health states. The models differ in their ability to predict preferences around dead health states, and the characteristics of the value sets in terms of their range and the proportion of states valued as worse than dead.
Appropriate anchoring of DCEs with or without complementary time trade-off (TTO) data remains unresolved, and the method chosen will impact on health resource allocation decision making employing the value sets.
KeywordsUtility Function Discrete Choice Experiment Health Profile Full Health Zero Condition
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Conflict of interest
The authors (Norman, Mulhern, and Viney) declare no conflict of interests. Data collection was funded by a National Health and Medical Research Council Project Grant (403303).
Norman conceived and undertook the analysis, and was primarily responsible for drafting the manuscript. Mulhern helped to develop the approaches to anchoring explored in the analysis, and commented on and amended the draft manuscript. Viney was responsible for the design and collection of the underpinning data, and commented on and amended the draft manuscript.
- 8.McFadden D. Conditional logit analysis of qualitative choice behaviour. In: Zarembka P, editor. Frontiers in econometrics. New York: New York Academic Press; 1974. p. 105–42.Google Scholar
- 12.Ramos-Goñi JM, Rivero-Arias O, Errea M, Stolk EA, Herdman M, Cabases JM. Dealing with the health state ‘dead’ when using discrete choice experiments to obtain values for EQ-5D-5L heath states. Eur J Health Econ HEPAC Health Econ Prev Care. 2013;14(Suppl 1):S33–42. doi: 10.1007/s10198-013-0511-2.CrossRefGoogle Scholar
- 14.Mulhern B, Bansback N, Brazier J, Buckingham K, Cairns J, Devlin N et al. Preparatory study for the revaluation of the EQ-5D tariff: methodology report. Health Technol Assess. 2014;18(12):vii–xxvi, 1–191. doi: 10.3310/hta18120.
- 17.Street DJ, Burgess L. The construction of optimal stated choice experiments: theory and methods. Wiley series in probability and statistics. New Jersey: Wiley; 2007.Google Scholar