IDEAS home Printed from https://ideas.repec.org/a/sae/medema/v37y2017i3p252-261.html
   My bibliography  Save this article

Handling Regional Variation in Health State Preferences within a Country

Author

Listed:
  • Eleanor M. Pullenayegum
  • Kelly M. Sunderland
  • Jeffrey A. Johnson
  • Feng Xie

Abstract

Background . Health state preferences vary among countries, and country-specific value sets are important in health care reimbursement decisions. When decisions are made at the regional level, regional variation in health state preferences may be important. We propose that shrinkage analysis and Bland-Altman plots can be a helpful way to investigate regional variation. Methods . The presence of regional variation can be investigated by introducing interactions between regions and the regression coefficients in the scoring algorithm. When variation is present, regional scoring algorithms can be derived through shrinkage analysis. The impact of using regional algorithms in place of the national algorithm can be investigated using simulation and illustrated using Bland-Altman plots. We applied this methodological approach to the Canadian EQ-5D-5L valuation study, which used time-tradeoff (TTO) tasks to elicit health state preferences from 1073 participants from 4 regions (Alberta, British Columbia, Ontario, and Quebec). Results . There were statistically significant interactions between the fixed effects of the scoring algorithm and region. On computing regional scoring algorithms and applying them to the EQ-5D-5L health states reported by our population, the mean utility using the Canada-wide scoring algorithm was 0.87 (standard error, 0.0013), compared to 0.85 (0.0013) on using the algorithm for Alberta, 0.80 (0.0013) on using the algorithm for British Columbia, 0.91 (0.0013) for Ontario, and 0.89 (0.0014) for Quebec. Conclusions . When health care falls under regional jurisdiction, shrinkage estimators can be used to generate regional scoring algorithms for the EQ-5D-5L and Bland-Altman plots used to assess the importance of regional variation in health state preferences. Our results suggest that mean health state preferences vary among Canada’s regions and make a sizable impact on estimates of population mean utility.

Suggested Citation

  • Eleanor M. Pullenayegum & Kelly M. Sunderland & Jeffrey A. Johnson & Feng Xie, 2017. "Handling Regional Variation in Health State Preferences within a Country," Medical Decision Making, , vol. 37(3), pages 252-261, April.
    • Handle: RePEc:sae:medema:v:37:y:2017:i:3:p:252-261
    DOI: 10.1177/0272989X16651885
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0272989X16651885
    Download Restriction: no
    File URL: https://libkey.io/10.1177/0272989X16651885?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
    ---><---

    References listed on IDEAS

    as
    1. Andrew R. Willan & Eleanor M. Pinto & Bernie J. O'Brien & Padma Kaul & Ron Goeree & Larry Lynd & Paul W. Armstrong, 2005. "Country specific cost comparisons from multinational clinical trials using empirical Bayesian shrinkage estimation: the Canadian ASSENT‐3 economic analysis," Health Economics, John Wiley & Sons, Ltd., vol. 14(4), pages 327-338, April.
    Full references (including those not matched with items on IDEAS)

    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. Richard Grieve & John Cairns & Simon G. Thompson, 2010. "Improving costing methods in multicentre economic evaluation: the use of multiple imputation for unit costs," Health Economics, John Wiley & Sons, Ltd., vol. 19(8), pages 939-954, August.
    2. Kelvin K. W. Chan & Feng Xie & Andrew R. Willan & Eleanor M. Pullenayegum, 2018. "Conducting EQ-5D Valuation Studies in Resource-Constrained Countries: The Potential Use of Shrinkage Estimators to Reduce Sample Size," Medical Decision Making, , vol. 38(1), pages 26-33, January.
    3. Christian E. H. Boehler & Joanne Lord, 2016. "Mind the Gap! A Multilevel Analysis of Factors Related to Variation in Published Cost-Effectiveness Estimates within and between Countries," Medical Decision Making, , vol. 36(1), pages 31-47, January.
    4. Andrew R. Willan & Matthew E. Kowgier, 2008. "Cost‐effectiveness analysis of a multinational RCT with a binary measure of effectiveness and an interacting covariate," Health Economics, John Wiley & Sons, Ltd., vol. 17(7), pages 777-791, July.
    5. Andrea Manca & Paul C. Lambert & Mark Sculpher & Nigel Rice, 2007. "Cost-Effectiveness Analysis Using Data from Multinational Trials: The Use of Bivariate Hierarchical Modeling," Medical Decision Making, , vol. 27(4), pages 471-490, July.
    6. Mark J. Sculpher & Karl Claxton & Mike Drummond & Chris McCabe, 2006. "Whither trial‐based economic evaluation for health care decision making?," Health Economics, John Wiley & Sons, Ltd., vol. 15(7), pages 677-687, July.
    7. Felix Achana & Daniel Gallacher & Raymond Oppong & Sungwook Kim & Stavros Petrou & James Mason & Michael Crowther, 2021. "Multivariate Generalized Linear Mixed-Effects Models for the Analysis of Clinical Trial–Based Cost-Effectiveness Data," Medical Decision Making, , vol. 41(6), pages 667-684, August.
    8. Andrew R. Willan & Simon Eckermann, 2012. "Accounting For Between‐Study Variation In Incremental Net Benefit In Value Of Information Methodology," Health Economics, John Wiley & Sons, Ltd., vol. 21(10), pages 1183-1195, October.

    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:sae:medema:v:37:y:2017:i:3:p:252-261. 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: SAGE Publications (email available below). General contact details of provider: .

    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.