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Using Conjoint Analysis and Choice Experiments to Estimate QALY Values

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  • Terry Flynn

Abstract

There is increasing interest in using ranking tasks, discrete choice experiments and best-worst scaling studies to estimate QALY values for use in cost-utility analysis. The research frontier in choice modelling is moving rapidly, with a number of issues being explored across several disciplines. These issues include the estimation of discount factors, proper modelling of the variance scale factor and the estimation of individual-level utility functions. Some of these issues are particularly acute when discrete choice tasks are used to facilitate extra-welfarist analyses that rely on populationbased values. There are also potential problems in implementing such tasks that have received little interest in the non-health discrete choice literature because they are specific to the QALY framework. This article details these issues and offers recommendations on the conduct of 21st century QALY valuation exercises that propose to use any tasks that rely on discrete choices. Copyright Springer International Publishing AG 2010

Suggested Citation

  • Terry Flynn, 2010. "Using Conjoint Analysis and Choice Experiments to Estimate QALY Values," PharmacoEconomics, Springer, vol. 28(9), pages 711-722, September.
  • Handle: RePEc:spr:pharme:v:28:y:2010:i:9:p:711-722
    DOI: 10.2165/11535660-000000000-00000
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    Cited by:

    1. Yoo, Hong Il & Doiron, Denise, 2013. "The use of alternative preference elicitation methods in complex discrete choice experiments," Journal of Health Economics, Elsevier, vol. 32(6), pages 1166-1179.
    2. Marcel F. Jonker & Arthur E. Attema & Bas Donkers & Elly A. Stolk & Matthijs M. Versteegh, 2017. "Are Health State Valuations from the General Public Biased? A Test of Health State Reference Dependency Using Self‐assessed Health and an Efficient Discrete Choice Experiment," Health Economics, John Wiley & Sons, Ltd., vol. 26(12), pages 1534-1547, December.
    3. Edward J. D. Webb & John O’Dwyer & David Meads & Paul Kind & Penny Wright, 2020. "Transforming discrete choice experiment latent scale values for EQ-5D-3L using the visual analogue scale," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 21(5), pages 787-800, July.
    4. Potoglou, Dimitris & Burge, Peter & Flynn, Terry & Netten, Ann & Malley, Juliette & Forder, Julien & Brazier, John E., 2011. "Best-worst scaling vs. discrete choice experiments: An empirical comparison using social care data," Social Science & Medicine, Elsevier, vol. 72(10), pages 1717-1727, May.
    5. Bansback, Nick & Hole, Arne Risa & Mulhern, Brendan & Tsuchiya, Aki, 2014. "Testing a discrete choice experiment including duration to value health states for large descriptive systems: Addressing design and sampling issues," Social Science & Medicine, Elsevier, vol. 114(C), pages 38-48.
    6. Julie Ratcliffe & Terry Flynn & Frances Terlich & Katherine Stevens & John Brazier & Michael Sawyer, 2012. "Developing Adolescent-Specific Health State Values for Economic Evaluation," PharmacoEconomics, Springer, vol. 30(8), pages 713-727, August.
    7. Zhang, Jing & Reed Johnson, F. & Mohamed, Ateesha F. & Hauber, A. Brett, 2015. "Too many attributes: A test of the validity of combining discrete-choice and best–worst scaling data," Journal of choice modelling, Elsevier, vol. 15(C), pages 1-13.
    8. Lisa Prosser & Scott Grosse & Eve Wittenberg, 2012. "Health Utility Elicitation," PharmacoEconomics, Springer, vol. 30(2), pages 83-86, February.
    9. Osman, Ahmed M.Y. & Wu, Jing & He, Xiaoning & Chen, Gang, 2021. "Eliciting SF-6Dv2 health state utilities using an anchored best-worst scaling technique," Social Science & Medicine, Elsevier, vol. 279(C).
    10. Balbontin, C. & Ortúzar, J. de D. & Swait, J.D., 2015. "A joint best–worst scaling and stated choice model considering observed and unobserved heterogeneity: An application to residential location choice," Journal of choice modelling, Elsevier, vol. 16(C), pages 1-14.
    11. Adele Diederich & Joffre Swait & Norman Wirsik, 2012. "Citizen Participation in Patient Prioritization Policy Decisions: An Empirical and Experimental Study on Patients' Characteristics," PLOS ONE, Public Library of Science, vol. 7(5), pages 1-10, May.
    12. Huynh, Elisabeth & Coast, Joanna & Rose, John & Kinghorn, Philip & Flynn, Terry, 2017. "Values for the ICECAP-Supportive Care Measure (ICECAP-SCM) for use in economic evaluation at end of life," Social Science & Medicine, Elsevier, vol. 189(C), pages 114-128.
    13. N. Flynn, Terry & J. Peters, Tim & Coast, Joanna, 2013. "Quantifying response shift or adaptation effects in quality of life by synthesising best-worst scaling and discrete choice data," Journal of choice modelling, Elsevier, vol. 6(C), pages 34-43.
    14. Cooper, Bethany & Crase, Lin & Rose, John M., 2018. "Cost-reflective pricing: empirical insights into irrigators’ preferences for water tariffs," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 62(2), April.

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