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COVID-19 and EQ-5D-5L health state valuation

Author

Listed:
  • Edward J. D. Webb

    (Academic Unit of Health Economics, Leeds Institute of Health Sciences, University of Leeds)

  • Paul Kind

    (Institute of Epidemiology and Health, University College London, UK and Academic Unit of Health Economics, Leeds Institute of Health Sciences, University of Leeds)

  • David Meads

    (Academic Unit of Health Economics, Leeds Institute of Health Sciences, University of Leeds)

  • Adam Martin

    (Academic Unit of Health Economics, Leeds Institute of Health Sciences, University of Leeds)

Abstract

Background We investigate whether and how general population health state values were influenced by the initial stages of the COVID-19 pandemic. Changes could have important implications, as general population values are used in health resource allocation. Data In Spring 2020, participants in a UK general population survey rated 2 EQ-5D-5L states, 11111 and 55555, as well as dead, using a visual analogue scale (VAS) from 100 = best imaginable health to 0 = worst imaginable health. Participants answered questions about their pandemic experiences, including COVID-19’s effect on their health and quality of life, and their subjective risk/worry about infection. Analysis VAS ratings for 55555 were transformed to the full health = 1, dead = 0 scale. Tobit models were used to analyse VAS responses, as well as multinomial propensity score matching (MNPS) to create samples balanced according to participant characteristics. Results Of 3021 respondents, 2599 were used for analysis. There were statistically significant, but complex associations between experiences of COVID-19 and VAS ratings. For example, in the MNPS analysis, greater subjective risk of infection implied higher VAS ratings for dead, yet worry about infection implied lower ratings. In the Tobit analysis, people whose health was affected by COVID-19 rated 55555 higher, whether the effect on health was positive or negative. Conclusion The results complement previous findings that the onset of the COVID-19 pandemic may have impacted EQ-5D-5L health state valuation, and different aspects of the pandemic had different effects.

Suggested Citation

  • Edward J. D. Webb & Paul Kind & David Meads & Adam Martin, 2024. "COVID-19 and EQ-5D-5L health state valuation," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 25(1), pages 117-145, February.
  • Handle: RePEc:spr:eujhec:v:25:y:2024:i:1:d:10.1007_s10198-023-01569-8
    DOI: 10.1007/s10198-023-01569-8
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    References listed on IDEAS

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    1. Edward J. D. Webb & Paul Kind & David Meads & Adam Martin, 2021. "Does a health crisis change how we value health?," Health Economics, John Wiley & Sons, Ltd., vol. 30(10), pages 2547-2560, September.
    2. Arthur Eumann Mesas & Iván Cavero-Redondo & Celia Álvarez-Bueno & Marcos Aparecido Sarriá Cabrera & Selma Maffei de Andrade & Irene Sequí-Dominguez & Vicente Martínez-Vizcaíno, 2020. "Predictors of in-hospital COVID-19 mortality: A comprehensive systematic review and meta-analysis exploring differences by age, sex and health conditions," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-23, November.
    3. David Daeho Kim & Peter J. Neumann, 2020. "Analyzing the Cost Effectiveness of Policy Responses for COVID-19: The Importance of Capturing Social Consequences," Medical Decision Making, , vol. 40(3), pages 251-253, April.
    4. Claudia R. Schneider & Sarah Dryhurst & John Kerr & Alexandra L. J. Freeman & Gabriel Recchia & David Spiegelhalter & Sander van der Linden, 2021. "COVID-19 risk perception: a longitudinal analysis of its predictors and associations with health protective behaviours in the United Kingdom," Journal of Risk Research, Taylor & Francis Journals, vol. 24(3-4), pages 294-313, April.
    5. Jennifer Beam Dowd & Liliana Andriano & David M. Brazel & Valentina Rotondi & Per Block & Xuejie Ding & Yan Liu & Melinda C. Mills, 2020. "Demographic science aids in understanding the spread and fatality rates of COVID-19," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 117(18), pages 9696-9698, May.
    6. 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.
    7. Mark Oppe & Kim Rand-Hendriksen & Koonal Shah & Juan M. Ramos‐Goñi & Nan Luo, 2016. "EuroQol Protocols for Time Trade-Off Valuation of Health Outcomes," PharmacoEconomics, Springer, vol. 34(10), pages 993-1004, October.
    8. Beatriz González López-Valcárcel & Laura Vallejo-Torres, 2021. "The costs of COVID-19 and the cost-effectiveness of testing," Applied Economic Analysis, Emerald Group Publishing Limited, vol. 29(85), pages 77-89, February.
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    More about this item

    Keywords

    COVID-19; EQ-5D-5L; Valuation; Visual analogue scale; Health shock;
    All these keywords.

    JEL classification:

    • D7 - Microeconomics - - Analysis of Collective Decision-Making
    • I10 - Health, Education, and Welfare - - Health - - - General
    • I30 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General

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