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What is the evidence for the performance of generic preference-based measures? A systematic overview of reviews

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  • Aureliano Paolo Finch

    (University of Sheffield)

  • John Edward Brazier

    (University of Sheffield)

  • Clara Mukuria

    (University of Sheffield)

Abstract

Objective To assess the evidence on the validity and responsiveness of five commonly used preference-based instruments, the EQ-5D, SF-6D, HUI3, 15D and AQoL, by undertaking a review of reviews. Methods Four databases were investigated using a strategy refined through a highly sensitive filter for systematic reviews. References were screened and a search for grey literature was performed. Identified citations were scrutinized against pre-defined eligibility criteria and data were extracted using a customized extraction template. Evidence on known group validity, convergent validity and responsiveness was extracted and reviewed by narrative synthesis. Quality of the included reviews was assessed using a modified version of the AMSTAR checklist. Results Thirty reviews were included, sixteen of which were of excellent or good quality. The body of evidence, covering more than 180 studies, was heavily skewed towards EQ-5D, with significantly fewer studies investigating HUI3 and SF-6D, and very few the 15D and AQoL. There was also lack of head-to-head comparisons between GPBMs and the tests reported by the reviews were often weak. Where there was evidence, EQ-5D, SF-6D, HUI3, 15D and AQoL seemed generally valid and responsive instruments, although not for all conditions. Evidence was not consistently reported across reviews. Conclusions Although generally valid, EQ-5D, SF-6D and HUI3 suffer from some problems and perform inconsistently in some populations. The lack of head-to-head comparisons and the poor reporting impedes the comparative assessment of the performance of GPBMs. This highlights the need for large comparative studies designed to test instruments’ performance.

Suggested Citation

  • Aureliano Paolo Finch & John Edward Brazier & Clara Mukuria, 2018. "What is the evidence for the performance of generic preference-based measures? A systematic overview of reviews," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 19(4), pages 557-570, May.
  • Handle: RePEc:spr:eujhec:v:19:y:2018:i:4:d:10.1007_s10198-017-0902-x
    DOI: 10.1007/s10198-017-0902-x
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    References listed on IDEAS

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    1. Sanghera, Sabina & Frew, Emma & Kai, Joe & Gupta, Janesh & Elizabeth Roberts, Tracy, 2013. "An assessment of economic measures used in menorrhagia: A systematic review," Social Science & Medicine, Elsevier, vol. 98(C), pages 149-153.
    2. John Brazier & Jennifer Roberts & Aki Tsuchiya & Jan Busschbach, 2004. "A comparison of the EQ‐5D and SF‐6D across seven patient groups," Health Economics, John Wiley & Sons, Ltd., vol. 13(9), pages 873-884, September.
    3. A. Pickard & Caitlyn Wilke & Hsiang-Wen Lin & Andrew Lloyd, 2007. "Health Utilities Using the EQ-5D in Studies of Cancer," PharmacoEconomics, Springer, vol. 25(5), pages 365-384, May.
    4. John Brazier & Mark Deverill, 1999. "A checklist for judging preference‐based measures of health related quality of life: Learning from psychometrics," Health Economics, John Wiley & Sons, Ltd., vol. 8(1), pages 41-51, February.
    5. David Moher & Alessandro Liberati & Jennifer Tetzlaff & Douglas G Altman & The PRISMA Group, 2009. "Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement," PLOS Medicine, Public Library of Science, vol. 6(7), pages 1-6, July.
    6. Ayse Kuspinar & Nancy Mayo, 2014. "A Review of the Psychometric Properties of Generic Utility Measures in Multiple Sclerosis," PharmacoEconomics, Springer, vol. 32(8), pages 759-773, August.
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    Cited by:

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    2. Kamilla Koszorú & Krisztina Hajdu & Valentin Brodszky & Alex Bató & L. Hunor Gergely & Anikó Kovács & Zsuzsanna Beretzky & Miklós Sárdy & Andrea Szegedi & Fanni Rencz, 2023. "Comparing the psychometric properties of the EQ-5D-3L and EQ-5D-5L descriptive systems and utilities in atopic dermatitis," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 24(1), pages 139-152, February.
    3. Koonal K. Shah & Bryan Bennett & Andrew Lenny & Louise Longworth & John E. Brazier & Mark Oppe & A. Simon Pickard & James W. Shaw, 2021. "Adapting preference-based utility measures to capture the impact of cancer treatment-related symptoms," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 22(8), pages 1301-1309, November.
    4. Finch, Aureliano Paolo & Meregaglia, Michela & Ciani, Oriana & Roudijk, Bram & Jommi, Claudio, 2022. "An EQ-5D-5L value set for Italy using videoconferencing interviews and feasibility of a new mode of administration," Social Science & Medicine, Elsevier, vol. 292(C).
    5. Finch, Aureliano Paolo & Mulhern, Brendan, 2022. "Where do measures of health, social care and wellbeing fit within a wider measurement framework? Implications for the measurement of quality of life and the identification of bolt-ons," Social Science & Medicine, Elsevier, vol. 313(C).
    6. Pickles, Kristen & Lancsar, Emily & Seymour, Janelle & Parkin, David & Donaldson, Cam & Carter, Stacy M., 2019. "Accounts from developers of generic health state utility instruments explain why they produce different QALYs: A qualitative study," Social Science & Medicine, Elsevier, vol. 240(C).

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    More about this item

    Keywords

    Preference based measures; Psychometric properties; Quality of life; Review;
    All these keywords.

    JEL classification:

    • I - Health, Education, and Welfare

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