IDEAS home Printed from https://ideas.repec.org/a/spr/eujhec/v19y2018i4d10.1007_s10198-017-0902-x.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10198-017-0902-x
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10198-017-0902-x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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 & 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. 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.
    3. 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).
    4. 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).
    5. 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).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Tsuchiya, Aki & Brazier, John & Roberts, Jennifer, 2006. "Comparison of valuation methods used to generate the EQ-5D and the SF-6D value sets," Journal of Health Economics, Elsevier, vol. 25(2), pages 334-346, March.
    2. D. Stratmann‐Schoene & T. Kuehn & R. Kreienberg & R. Leidl, 2006. "A preference‐based index for the SF‐12," Health Economics, John Wiley & Sons, Ltd., vol. 15(6), pages 553-564, June.
    3. Stavros Petrou & Christine Hockley, 2005. "An investigation into the empirical validity of the EQ‐5D and SF‐6D based on hypothetical preferences in a general population," Health Economics, John Wiley & Sons, Ltd., vol. 14(11), pages 1169-1189, November.
    4. Garry R. Barton & Tracey H. Sach & Anthony J. Avery & Claire Jenkinson & Michael Doherty & David K. Whynes & Kenneth R. Muir, 2008. "A comparison of the performance of the EQ‐5D and SF‐6D for individuals aged ≥ 45 years," Health Economics, John Wiley & Sons, Ltd., vol. 17(7), pages 815-832, July.
    5. Janelle Seymour & Paul McNamee & Anthony Scott & Michela Tinelli, 2010. "Shedding new light onto the ceiling and floor? A quantile regression approach to compare EQ‐5D and SF‐6D responses," Health Economics, John Wiley & Sons, Ltd., vol. 19(6), pages 683-696, June.
    6. Yaling Yang & John Brazier & Louise Longworth, 2015. "EQ-5D in skin conditions: an assessment of validity and responsiveness," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 16(9), pages 927-939, December.
    7. İlkay Unay-Gailhard & Mark A. Brennen, 2022. "How digital communications contribute to shaping the career paths of youth: a review study focused on farming as a career option," Agriculture and Human Values, Springer;The Agriculture, Food, & Human Values Society (AFHVS), vol. 39(4), pages 1491-1508, December.
    8. Mahin Ghafari & Vali Baigi & Zahra Cheraghi & Amin Doosti-Irani, 2016. "The Prevalence of Asymptomatic Bacteriuria in Iranian Pregnant Women: A Systematic Review and Meta-Analysis," PLOS ONE, Public Library of Science, vol. 11(6), pages 1-10, June.
    9. Elizabeth T Cafiero-Fonseca & Andrew Stawasz & Sydney T Johnson & Reiko Sato & David E Bloom, 2017. "The full benefits of adult pneumococcal vaccination: A systematic review," PLOS ONE, Public Library of Science, vol. 12(10), pages 1-23, October.
    10. Santos Urbina & Sofía Villatoro & Jesús Salinas, 2021. "Self-Regulated Learning and Technology-Enhanced Learning Environments in Higher Education: A Scoping Review," Sustainability, MDPI, vol. 13(13), pages 1-12, June.
    11. Oded Berger-Tal & Alison L Greggor & Biljana Macura & Carrie Ann Adams & Arden Blumenthal & Amos Bouskila & Ulrika Candolin & Carolina Doran & Esteban Fernández-Juricic & Kiyoko M Gotanda & Catherine , 2019. "Systematic reviews and maps as tools for applying behavioral ecology to management and policy," Behavioral Ecology, International Society for Behavioral Ecology, vol. 30(1), pages 1-8.
    12. Nadine Desrochers & Adèle Paul‐Hus & Jen Pecoskie, 2017. "Five decades of gratitude: A meta‐synthesis of acknowledgments research," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 68(12), pages 2821-2833, December.
    13. Alene Sze Jing Yong & Yi Heng Lim & Mark Wing Loong Cheong & Ednin Hamzah & Siew Li Teoh, 2022. "Willingness-to-pay for cancer treatment and outcome: a systematic review," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 23(6), pages 1037-1057, August.
    14. Xue-Ying Xu & Hong Kong & Rui-Xiang Song & Yu-Han Zhai & Xiao-Fei Wu & Wen-Si Ai & Hong-Bo Liu, 2014. "The Effectiveness of Noninvasive Biomarkers to Predict Hepatitis B-Related Significant Fibrosis and Cirrhosis: A Systematic Review and Meta-Analysis of Diagnostic Test Accuracy," PLOS ONE, Public Library of Science, vol. 9(6), pages 1-16, June.
    15. Vicente Miñana-Signes & Manuel Monfort-Pañego & Javier Valiente, 2021. "Teaching Back Health in the School Setting: A Systematic Review of Randomized Controlled Trials," IJERPH, MDPI, vol. 18(3), pages 1-18, January.
    16. Agnieszka A. Tubis & Katarzyna Grzybowska, 2022. "In Search of Industry 4.0 and Logistics 4.0 in Small-Medium Enterprises—A State of the Art Review," Energies, MDPI, vol. 15(22), pages 1-26, November.
    17. Obsa Urgessa Ayana & Jima Degaga, 2022. "Effects of rural electrification on household welfare: a meta-regression analysis," International Review of Economics, Springer;Happiness Economics and Interpersonal Relations (HEIRS), vol. 69(2), pages 209-261, June.
    18. Caloffi, Annalisa & Colovic, Ana & Rizzoli, Valentina & Rossi, Federica, 2023. "Innovation intermediaries' types and functions: A computational analysis of the literature," Technological Forecasting and Social Change, Elsevier, vol. 189(C).
    19. García-Poole, Chloe & Byrne, Sonia & Rodrigo, María José, 2019. "How do communities intervene with adolescents at psychosocial risk? A systematic review of positive development programs," Children and Youth Services Review, Elsevier, vol. 99(C), pages 194-209.
    20. Jie Zhao & Ji Chen & Damien Beillouin & Hans Lambers & Yadong Yang & Pete Smith & Zhaohai Zeng & Jørgen E. Olesen & Huadong Zang, 2022. "Global systematic review with meta-analysis reveals yield advantage of legume-based rotations and its drivers," Nature Communications, Nature, vol. 13(1), pages 1-9, December.

    More about this item

    Keywords

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

    JEL classification:

    • I - Health, Education, and Welfare

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:eujhec:v:19:y:2018:i:4:d:10.1007_s10198-017-0902-x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.