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A Framework for Estimating Health State Utility Values within a Discrete Choice Experiment

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  • Angela Robinson
  • Anne Spencer
  • Peter Moffatt

Abstract

Background. There has been recent interest in using the discrete choice experiment (DCE) method to derive health state utilities for use in quality-adjusted life year (QALY) calculations, but challenges remain. Objectives. We set out to develop a risk-based DCE approach to derive utility values for health states that allowed 1) utility values to be anchored directly to normal health and death and 2) worse than dead health states to be assessed in the same manner as better than dead states. Furthermore, we set out to estimate alternative models of risky choice within a DCE model. Method. A survey was designed that incorporated a risk-based DCE and a “modified†standard gamble (SG). Health state utility values were elicited for 3 EQ-5D health states assuming “standard†expected utility (EU) preferences. The DCE model was then generalized to allow for rank-dependent expected utility (RDU) preferences, thereby allowing for probability weighting. A convenience sample of 60 students was recruited and data collected in small groups. Results. Under the assumption of “standard†EU preferences, the utility values derived within the DCE corresponded fairly closely to the mean results from the modified SG. Under the assumption of RDU preferences, the utility values estimated are somewhat lower than under the assumption of standard EU, suggesting that the latter may be biased upward. Conclusion. Applying the correct model of risky choice is important whether a modified SG or a risk-based DCE is deployed. It is, however, possible to estimate a probability weighting function within a DCE and estimate “unbiased†utility values directly, which is not possible within a modified SG. We conclude by setting out the relative strengths and weaknesses of the 2 approaches in this context.

Suggested Citation

  • Angela Robinson & Anne Spencer & Peter Moffatt, 2015. "A Framework for Estimating Health State Utility Values within a Discrete Choice Experiment," Medical Decision Making, , vol. 35(3), pages 341-350, April.
  • Handle: RePEc:sae:medema:v:35:y:2015:i:3:p:341-350
    DOI: 10.1177/0272989X14554715
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    Cited by:

    1. Spencer, Anne & Rivero-Arias, Oliver & Wong, Ruth & Tsuchiya, Aki & Bleichrodt, Han & Edwards, Rhiannon Tudor & Norman, Richard & Lloyd, Andrew & Clarke, Philip, 2022. "The QALY at 50: One story many voices," Social Science & Medicine, Elsevier, vol. 296(C).
    2. José Luis Pinto‐Prades & José Antonio Robles‐Zurita & Fernando‐Ignacio Sánchez‐Martínez & José María Abellán‐Perpiñán & Jorge Martínez‐Pérez, 2017. "Improving scope sensitivity in contingent valuation: Joint and separate evaluation of health states," Health Economics, John Wiley & Sons, Ltd., vol. 26(12), pages 304-318, December.
    3. Mina Bahrampour & Joshua Byrnes & Richard Norman & Paul A. Scuffham & Martin Downes, 2020. "Discrete choice experiments to generate utility values for multi-attribute utility instruments: a systematic review of methods," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 21(7), pages 983-992, September.
    4. Feng Xie & Eleanor Pullenayegum & A. Simon Pickard & Juan Manuel Ramos Goñi & Min‐woo Jo & Ataru Igarashi, 2017. "Transforming Latent Utilities to Health Utilities: East Does Not Meet West," Health Economics, John Wiley & Sons, Ltd., vol. 26(12), pages 1524-1533, December.

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