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How does cost matter in health‐care discrete‐choice experiments?

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  • F. Reed Johnson
  • Ateesha F. Mohamed
  • Semra Özdemir
  • Deborah A. Marshall
  • Kathryn A. Phillips

Abstract

Willingness‐to‐pay (WTP) estimates derived from discrete‐choice experiments (DCEs) generally assume that the marginal utility of income is constant. This assumption is consistent with theoretical expectations when costs are a small fraction of total income. We analyze the results of five DCEs that allow direct tests of this assumption. Tests indicate that marginal utility often violates theoretical expectations. We suggest that this result is an artifact of a cognitive heuristic that recodes cost levels from a numerical scale to qualitative categories. Instead of evaluating nominal costs in the context of a budget constraint, subjects may recode costs into categories such as ‘low’, ‘medium’, and ‘high’ and choose as if the differences between categories were equal. This simplifies the choice task, but undermines the validity of WTP estimates as welfare measures. Recoding may be a common heuristic in health‐care applications when insurance coverage distorts subjects' perception of the nominal costs presented in the DCE instrument. Recoding may also distort estimates of marginal rates of substitution for other attributes with numeric levels. Incorporating ‘cheap talk’ or graphic representation of attribute levels may encourage subjects to be more attentive to absolute attribute levels. Copyright © 2010 John Wiley & Sons, Ltd.

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  • F. Reed Johnson & Ateesha F. Mohamed & Semra Özdemir & Deborah A. Marshall & Kathryn A. Phillips, 2011. "How does cost matter in health‐care discrete‐choice experiments?," Health Economics, John Wiley & Sons, Ltd., vol. 20(3), pages 323-330, March.
    • Handle: RePEc:wly:hlthec:v:20:y:2011:i:3:p:323-330
    DOI: 10.1002/hec.1591
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    References listed on IDEAS

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    Cited by:

    1. Axel Mühlbacher & Peter Zweifel & Anika Kaczynski & F. Johnson, 2015. "Experimental measurement of preferences in health care using best-worst scaling (BWS): theoretical and statistical issues," Health Economics Review, Springer, vol. 6(1), pages 1-12, December.
    2. Regier, Dean A. & Watson, Verity & Burnett, Heather & Ungar, Wendy J., 2014. "Task complexity and response certainty in discrete choice experiments: An application to drug treatments for juvenile idiopathic arthritis," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 50(C), pages 40-49.
    3. Milad Haghani & Michiel C. J. Bliemer & John M. Rose & Harmen Oppewal & Emily Lancsar, 2021. "Hypothetical bias in stated choice experiments: Part I. Integrative synthesis of empirical evidence and conceptualisation of external validity," Papers 2102.02940, arXiv.org.
    4. Haghani, Milad & Bliemer, Michiel C.J. & Rose, John M. & Oppewal, Harmen & Lancsar, Emily, 2021. "Hypothetical bias in stated choice experiments: Part II. Conceptualisation of external validity, sources and explanations of bias and effectiveness of mitigation methods," Journal of choice modelling, Elsevier, vol. 41(C).
    5. Caplan, Arthur J. & Akhundjanov, Sherzod B. & Toll, Kristopher, 2021. "Measuring heterogeneous preferences for residential amenities," Regional Science and Urban Economics, Elsevier, vol. 87(C).
    6. Axel Mühlbacher & Anika Kaczynski & Peter Zweifel & F. Johnson, 2015. "Experimental measurement of preferences in health and healthcare using best-worst scaling: an overview," Health Economics Review, Springer, vol. 6(1), pages 1-14, December.
    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. Axel C. Mühlbacher & Peter Zweifel & Anika Kaczynski & F. Reed Johnson, 2016. "Experimental measurement of preferences in health care using best-worst scaling (BWS): theoretical and statistical issues," Health Economics Review, Springer, vol. 6(1), pages 1-12, December.
    9. Yi Qian & Jorge Arellano & A. Brett Hauber & Ateesha F. Mohamed & Juan Marcos Gonzalez & Guy Hechmati & Francesca Gatta & Stacey Harrelson & Cynthia Campbell-Baird, 2016. "Patient, Caregiver, and Nurse Preferences for Treatments for Bone Metastases from Solid Tumors," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 9(4), pages 323-333, August.
    10. Genie, Mesfin G. & Ryan, Mandy & Krucien, Nicolas, 2021. "To pay or not to pay? Cost information processing in the valuation of publicly funded healthcare," Social Science & Medicine, Elsevier, vol. 276(C).
    11. Michael Clark & Domino Determann & Stavros Petrou & Domenico Moro & Esther Bekker-Grob, 2014. "Discrete Choice Experiments in Health Economics: A Review of the Literature," PharmacoEconomics, Springer, vol. 32(9), pages 883-902, September.
    12. Scott D. Grosse & Jamison Pike & Rieza Soelaeman & J. Mick Tilford, 2019. "Quantifying Family Spillover Effects in Economic Evaluations: Measurement and Valuation of Informal Care Time," PharmacoEconomics, Springer, vol. 37(4), pages 461-473, April.
    13. Axel C. Mühlbacher & Anika Kaczynski & Peter Zweifel & F. Reed Johnson, 2016. "Experimental measurement of preferences in health and healthcare using best-worst scaling: an overview," Health Economics Review, Springer, vol. 6(1), pages 1-14, December.
    14. John Buckell & David A Hensher & Stephane Hess, 2021. "Kicking the habit is hard: A hybrid choice model investigation into the role of addiction in smoking behavior," Health Economics, John Wiley & Sons, Ltd., vol. 30(1), pages 3-19, January.
    15. Phillips Kathryn A. & Sakowski Julie Ann & Liang Su-Ying & Ponce Ninez A., 2013. "Economic Perspectives on Personalized Health Care and Prevention," Forum for Health Economics & Policy, De Gruyter, vol. 16(2), pages 57-86, June.
    16. 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.

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