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One Method, Many Methodological Choices: A Structured Review of Discrete-Choice Experiments for Health State Valuation

Author

Listed:
  • Brendan Mulhern

    (University of Technology)

  • Richard Norman

    (Curtin University)

  • Deborah J. Street

    (University of Technology)

  • Rosalie Viney

    (University of Technology)

Abstract

Background Discrete-choice experiments (DCEs) are used in the development of preference-based measure (PBM) value sets. There is considerable variation in the methodological approaches used to elicit preferences. Objective Our objective was to carry out a structured review of DCE methods used for health state valuation. Methods PubMed was searched until 31 May 2018 for published literature using DCEs for health state valuation. Search terms to describe DCEs, the process of valuation and preference-based instruments were developed. English language papers with any study population were included if they used DCEs to develop or directly inform the production of value sets for generic or condition-specific PBMs. Assessment of paper quality was guided by the recently developed Checklist for Reporting Valuation Studies. Data were extracted under six categories: general study information, choice task and study design, type of designed experiment, modelling and analysis methods, results and discussion. Results The literature search identified 1132 published papers, and 63 papers were included in the review. Paper quality was generally high. The study design and choice task formats varied considerably, and a wide range of modelling methods were employed to estimate value sets. Conclusions This review of DCE methods used for developing value sets suggests some recurring limitations, areas of consensus and areas where further research is required. Methodological diversity means that the values should be seen as experimental, and users should understand the features of the value sets produced before applying them in decision making.

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  • Brendan Mulhern & Richard Norman & Deborah J. Street & Rosalie Viney, 2019. "One Method, Many Methodological Choices: A Structured Review of Discrete-Choice Experiments for Health State Valuation," PharmacoEconomics, Springer, vol. 37(1), pages 29-43, January.
  • Handle: RePEc:spr:pharme:v:37:y:2019:i:1:d:10.1007_s40273-018-0714-6
    DOI: 10.1007/s40273-018-0714-6
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    References listed on IDEAS

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    1. Yuanyuan Gu & Richard Norman & Rosalie Viney, 2014. "Estimating Health State Utility Values From Discrete Choice Experiments—A Qaly Space Model Approach," Health Economics, John Wiley & Sons, Ltd., vol. 23(9), pages 1098-1114, September.
    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. Julie Ratcliffe & John Brazier & Aki Tsuchiya & Tara Symonds & Martin Brown, 2009. "Using DCE and ranking data to estimate cardinal values for health states for deriving a preference‐based single index from the sexual quality of life questionnaire," Health Economics, John Wiley & Sons, Ltd., vol. 18(11), pages 1261-1276, November.
    4. Richard Norman & Paula Cronin & Rosalie Viney, 2013. "A Pilot Discrete Choice Experiment to Explore Preferences for EQ-5D-5L Health States," Applied Health Economics and Health Policy, Springer, vol. 11(3), pages 287-298, June.
    5. Yan Feng & Nancy J. Devlin & Koonal K. Shah & Brendan Mulhern & Ben van Hout, 2018. "New methods for modelling EQ‐5D‐5L value sets: An application to English data," Health Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 23-38, January.
    6. Juan Ramos-Goñi & Oliver Rivero-Arias & María Errea & Elly Stolk & Michael Herdman & Juan Cabasés, 2013. "Dealing with the health state ‘dead’ when using discrete choice experiments to obtain values for EQ-5D-5L heath states," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 14(1), pages 33-42, July.
    7. Rosalie Viney & Richard Norman & John Brazier & Paula Cronin & Madeleine T. King & Julie Ratcliffe & Deborah Street, 2014. "An Australian Discrete Choice Experiment To Value Eq‐5d Health States," Health Economics, John Wiley & Sons, Ltd., vol. 23(6), pages 729-742, June.
    8. Renske J. Hoefman & Job Exel & Werner B. F. Brouwer, 2017. "Measuring Care-Related Quality of Life of Caregivers for Use in Economic Evaluations: CarerQol Tariffs for Australia, Germany, Sweden, UK, and US," PharmacoEconomics, Springer, vol. 35(4), pages 469-478, April.
    9. Brazier, John & Roberts, Jennifer & Deverill, Mark, 2002. "The estimation of a preference-based measure of health from the SF-36," Journal of Health Economics, Elsevier, vol. 21(2), pages 271-292, March.
    10. 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.
    11. 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.
    12. Nicolas Krucien & Verity Watson & Mandy Ryan, 2017. "Is Best–Worst Scaling Suitable for Health State Valuation? A Comparison with Discrete Choice Experiments," Health Economics, John Wiley & Sons, Ltd., vol. 26(12), pages 1-16, December.
    13. Hensher,David A. & Rose,John M. & Greene,William H., 2015. "Applied Choice Analysis," Cambridge Books, Cambridge University Press, number 9781107465923, November.
    14. Walters, SJ & Brazier, JE, 2002. "Sample sizes for the SF-6D preference based measure of health from the SF-36: a practical guide," MPRA Paper 29742, University Library of Munich, Germany.
    15. Amanda Cole & Koonal Shah & Brendan Mulhern & Yan Feng & Nancy Devlin, 2018. "Valuing EQ-5D-5L health states ‘in context’ using a discrete choice experiment," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 19(4), pages 595-605, May.
    16. Yan Feng & Arne Risa Hole & Milad Karimi & Aki Tsuchiya & Ben van Hout, 2018. "An exploration of the non‐iterative time trade‐off method to value health states," Health Economics, John Wiley & Sons, Ltd., vol. 27(8), pages 1247-1263, August.
    17. Zafar Hakim & Dev S. Pathak, 1999. "Modelling the EuroQol data: a comparison of discrete choice conjoint and conditional preference modelling," Health Economics, John Wiley & Sons, Ltd., vol. 8(2), pages 103-116, March.
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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. Richard Norman & Rebecca Mercieca‐Bebber & Donna Rowen & John E. Brazier & David Cella & A. Simon Pickard & Deborah J. Street & Rosalie Viney & Dennis Revicki & Madeleine T. King & On behalf of the Eu, 2019. "U.K. utility weights for the EORTC QLU‐C10D," Health Economics, John Wiley & Sons, Ltd., vol. 28(12), pages 1385-1401, December.
    3. Marcel F. Jonker & Richard Norman, 2022. "Not all respondents use a multiplicative utility function in choice experiments for health state valuations, which should be reflected in the elicitation format (or statistical analysis)," Health Economics, John Wiley & Sons, Ltd., vol. 31(2), pages 431-439, February.
    4. Ruvini M. Hettiarachchi & Peter Arrow & Sameera Senanayake & Hannah Carter & David Brain & Richard Norman & Utsana Tonmukayawul & Lisa Jamieson & Sanjeewa Kularatna, 2023. "Developing an Australian utility value set for the Early Childhood Oral Health Impact Scale-4D (ECOHIS-4D) using a discrete choice experiment," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 24(8), pages 1285-1296, November.
    5. 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.
    6. McDonald, Rebecca & Mullett, Timothy L. & Tsuchiya, Aki, 2020. "Understanding the composite dimensions of the EQ-5D: An experimental approach," Social Science & Medicine, Elsevier, vol. 265(C).
    7. Elliott, Jack & Tsuchiya, Aki, 2022. "Do they just know more, or do they also have different preferences? An exploratory analysis of the effects of self-reporting serious health problems on health state valuation," Social Science & Medicine, Elsevier, vol. 315(C).

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