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Population norms for the EQ-5D-3L: a cross-country analysis of population surveys for 20 countries

Author

Listed:
  • M. F. Janssen

    (Erasmus MC
    EuroQol Group)

  • A. Szende

    (Covance)

  • J. Cabases

    (Public University of Navarra)

  • J. M. Ramos-Goñi

    (EuroQol Group)

  • G. Vilagut

    (IMIM (Institut Hospital del Mar d′Investigacions Mèdiques)
    CIBER Epidemiología y Salud Pública (CIBERESP))

  • H. H. König

    (University Medical Center Hamburg-Eppendorf)

Abstract

This study provides EQ-5D population norms for 20 countries (N = 163,838), which can be used to compare profiles for patients with specific conditions with data for the average person in the general population in a similar age and/or gender group. Descriptive EQ-5D data are provided for the total population, by gender and by seven age groups. Provided index values are based on European VAS for all countries, based on TTO for 11 countries and based on VAS for 10 countries. Important differences exist in EQ-5D reported health status across countries after standardizing for population structure. Self-reported health according to all five dimensions and EQ VAS generally decreased with increasing age and was lower for females. Mean self-rated EQ VAS scores varied from 70.4 to 83.3 in the total population by country. The prior living standards (GDP per capita) in the countries studied are correlated most with the EQ VAS scores (0.58), while unemployment appeared to be significantly correlated in people over the age of 45 only. A country’s expenditure on health care correlated moderately with higher ratings on the EQ VAS (0.55). EQ-5D norms can be used as reference data to assess the burden of disease of patients with specific conditions. Such information, in turn, can inform policy-making and assist in setting priorities in health care.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:eujhec:v:20:y:2019:i:2:d:10.1007_s10198-018-0955-5
    DOI: 10.1007/s10198-018-0955-5
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    References listed on IDEAS

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    Cited by:

    1. Mathieu F. Janssen & A. Simon Pickard & James W. Shaw, 2021. "General population normative data for the EQ-5D-3L in the five largest European economies," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 22(9), pages 1467-1475, December.
    2. 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).
    3. Takaaki Ikeda & Ataru Igarashi & Satomi Odani & Masayasu Murakami & Takahiro Tabuchi, 2022. "Health-Related Quality of Life during COVID-19 Pandemic: Assessing Impacts of Job Loss and Financial Support Programs in Japan," Applied Research in Quality of Life, Springer;International Society for Quality-of-Life Studies, vol. 17(2), pages 541-557, April.

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    JEL classification:

    • I10 - Health, Education, and Welfare - - Health - - - General
    • I30 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General
    • J11 - Labor and Demographic Economics - - Demographic Economics - - - Demographic Trends, Macroeconomic Effects, and Forecasts
    • H51 - Public Economics - - National Government Expenditures and Related Policies - - - Government Expenditures and Health

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