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A Systematic Review of Methods Used for Confounding Adjustment in Observational Economic Evaluations in Cardiology Conducted between 2013 and 2017

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  • Jason R. Guertin

    (Department of Social and Preventive Medicine, Université Laval, Quebec City, Canada
    Axe Santé des populations et pratiques optimales en santé, Centre de recherche du CHU de Québec–Université Laval, Quebec City, Canada)

  • Blanchard Conombo

    (Department of Social and Preventive Medicine, Université Laval, Quebec City, Canada
    Axe Santé des populations et pratiques optimales en santé, Centre de recherche du CHU de Québec–Université Laval, Quebec City, Canada)

  • Raphaël Langevin

    (Department of Economics, McGill University, Montreal, Canada)

  • Frédéric Bergeron

    (Université Laval, Quebec City, Canada)

  • Anne Holbrook

    (Division of Clinical Pharmacology and Toxicology, Department of Medicine, McMaster University, Hamilton, Canada
    Department of Health Evidence and Impact, McMaster University, Hamilton, Canada)

  • Brittany Humphries

    (Department of Health Evidence and Impact, McMaster University, Hamilton, Canada)

  • Alexis Matteau

    (Department of Medicine, Université de Montréal, Montreal, Canada
    Centre de recherche du Centre Hospitalier de l’Université de Montréal, Montreal, Canada
    Centre Hospitalier de l’Université de Montréal, Montreal, Canada)

  • Brian J. Potter

    (Department of Medicine, Université de Montréal, Montreal, Canada
    Centre de recherche du Centre Hospitalier de l’Université de Montréal, Montreal, Canada
    Centre Hospitalier de l’Université de Montréal, Montreal, Canada)

  • Christel Renoux

    (McGill University, Montreal, Canada
    Programs for Assessment of Technology in Health (PATH), The Research Institute of St. Joe’s Hamilton, St. Joseph’s Healthcare Hamilton
    McMaster Chair in Health Technology Management, McMaster University, Hamilton, Canada)

  • Jean-Éric Tarride

    (Department of Health Evidence and Impact, McMaster University, Hamilton, Canada
    Centre for Health Economics and Policy Analysis, McMaster University, Hamilton, Canada
    Department of Economics; McMaster University, Hamilton, Canada
    Programs for Assessment of Technology in Health (PATH), The Research Institute of St. Joe’s Hamilton, St. Joseph’s Healthcare Hamilton)

  • Madeleine Durand

    (Department of Medicine, Université de Montréal, Montreal, Canada
    Centre de recherche du Centre Hospitalier de l’Université de Montréal, Montreal, Canada
    Centre Hospitalier de l’Université de Montréal, Montreal, Canada)

Abstract

Background. Observational economic evaluations (i.e., economic evaluations in which treatment allocation is not randomized) are prone to confounding bias. Prior reviews published in 2013 have shown that adjusting for confounding is poorly done, if done at all. Although these reviews raised awareness on the issues, it is unclear if their results improved the methodological quality of future work. We therefore aimed to investigate whether and how confounding was accounted for in recently published observational economic evaluations in the field of cardiology. Methods. We performed a systematic review of PubMed, Embase, Cochrane Library, Web of Science, and PsycInfo databases using a set of Medical Subject Headings and keywords covering topics in “observational economic evaluations in health within humans†and “cardiovascular diseases.†Any study published in either English or French between January 1, 2013, and December 31, 2017, addressing our search criteria was eligible for inclusion in our review. Our protocol was registered with PROSPERO (CRD42018112391). Results. Forty-two (0.6%) out of 7523 unique citations met our inclusion criteria. Fewer than half of the selected studies adjusted for confounding ( n = 19 [45.2%]). Of those that adjusted for confounding, propensity score matching ( n = 8 [42.1%]) and other matching-based approaches were favored ( n = 8 [42.1%]). Our results also highlighted that most authors who adjusted for confounding rarely justified their methodological choices. Conclusion. Our results indicate that adjustment for confounding is often ignored when conducting an observational economic evaluation. Continued knowledge translation efforts aimed at improving researchers’ knowledge regarding confounding bias and methods aimed at addressing this issue are required and should be supported by journal editors.

Suggested Citation

  • Jason R. Guertin & Blanchard Conombo & Raphaël Langevin & Frédéric Bergeron & Anne Holbrook & Brittany Humphries & Alexis Matteau & Brian J. Potter & Christel Renoux & Jean-Éric Tarride & Madelein, 2020. "A Systematic Review of Methods Used for Confounding Adjustment in Observational Economic Evaluations in Cardiology Conducted between 2013 and 2017," Medical Decision Making, , vol. 40(5), pages 582-595, July.
    • Handle: RePEc:sae:medema:v:40:y:2020:i:5:p:582-595
    DOI: 10.1177/0272989X20937257
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    References listed on IDEAS

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