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Comparing EQ-5D Valuation Studies

Author

Listed:
  • Feng Xie
  • Kathryn Gaebel
  • Kuhan Perampaladas
  • Brett Doble
  • Eleanor Pullenayegum

Abstract

Background . There has been a growing interest around the world in developing country-specific scoring algorithms for the EQ-5D. This study systematically reviews all existing EQ-5D valuation studies to highlight their strengths and limitations, explores heterogeneity in observed utilities using meta-regression, and proposes a methodological checklist for reporting EQ-5D valuation studies. Methods . We searched Medline, EMBASE, the National Health Service Economic Evaluation Database (NHS EED) via Wiley’s Cochrane Library, and Wiley’s Health Economic Evaluation Database from inception through November 2012, as well as bibliographies of key papers and the EuroQol Plenary Meeting Proceedings from 1991 to 2012 for English-language reports of EQ-5D valuation studies. Two reviewers independently screened the titles and abstracts for relevance. Three reviewers performed data extraction and compared the characteristics and scoring algorithms developed in the included valuation studies. Results . Of the 31 studies included in the review, 19 used the time trade-off (TTO) technique, 10 used the visual analogue scale (VAS) technique, and 2 used both TTO and VAS. Most studies included respondents from the general population selected by random or quota sampling and used face-to-face interviews or postal surveys. Studies valued between 7 and 198 total states, with 1–23 states valued per respondent. Different model specifications have been proposed for scoring. Some sample or demographic factors, including gender, education, percentage urban population, and national health care expenditure, were associated with differences in observed utilities for moderate or severe health states. Conclusions . EQ-5D valuation studies conducted to date have varied widely in their design and in the resulting scoring algorithms. Therefore, we propose the Checklist for Reporting Valuation Studies of the EQ-5D (CREATE) for those conducting valuation studies.

Suggested Citation

  • Feng Xie & Kathryn Gaebel & Kuhan Perampaladas & Brett Doble & Eleanor Pullenayegum, 2014. "Comparing EQ-5D Valuation Studies," Medical Decision Making, , vol. 34(1), pages 8-20, January.
    • Handle: RePEc:sae:medema:v:34:y:2014:i:1:p:8-20
    DOI: 10.1177/0272989X13480852
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    References listed on IDEAS

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    1. Nick Bansback & Aki Tsuchiya & John Brazier & Aslam Anis, 2012. "Canadian Valuation of EQ-5D Health States: Preliminary Value Set and Considerations for Future Valuation Studies," PLOS ONE, Public Library of Science, vol. 7(2), pages 1-11, February.
    2. Nancy J. Devlin & Paul Hansen & Paul Kind & Alan Williams, 2003. "Logical inconsistencies in survey respondents' health state valuations ‐ a methodological challenge for estimating social tariffs," Health Economics, John Wiley & Sons, Ltd., vol. 12(7), pages 529-544, July.
    3. L. M. Lamers & J. McDonnell & P. F. M. Stalmeier & P. F. M. Krabbe & J. J. V. Busschbach, 2006. "The Dutch tariff: results and arguments for an effective design for national EQ‐5D valuation studies," Health Economics, John Wiley & Sons, Ltd., vol. 15(10), pages 1121-1132, October.
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    Cited by:

    1. Anne Spencer & Ewan Tomeny & Ruben E. Mujica-Mota & Angela Robinson & Judith Covey & Jose Luis Pinto-Prades, 2019. "Do time trade-off values fully capture attitudes that are relevant to health-related choices?," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 20(4), pages 559-568, June.
    2. Schneider, Paul, 2019. "Social tariffs and democratic choice – do population-based health state values reflect the will of the people?," SocArXiv 2qvjb, Center for Open Science.
    3. Christian R. C. Kouakou & Thomas G. Poder, 2022. "Willingness to pay for a quality-adjusted life year: a systematic review with meta-regression," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 23(2), pages 277-299, March.
    4. Asrul Akmal Shafie & Annushiah Vasan Thakumar, 2020. "Multiplicative modelling of EQ-5D-3L TTO and VAS values," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 21(9), pages 1411-1420, December.
    5. M. F. Janssen & A. Szende & J. Cabases & J. M. Ramos-Goñi & G. Vilagut & H. H. König, 2019. "Population norms for the EQ-5D-3L: a cross-country analysis of population surveys for 20 countries," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 20(2), pages 205-216, March.
    6. Franz Ombler & Michael Albert & Paul Hansen, 2018. "How Significant Are “High†Correlations Between EQ-5D Value Sets?," Medical Decision Making, , vol. 38(6), pages 635-645, August.
    7. Franz Ombler & Michael Albert & Paul Hansen, 2017. "The true significance of ‘high’ correlations between EQ-5D value sets," Working Papers 1704, University of Otago, Department of Economics, revised Mar 2017.

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