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

Jason R. Guertin, Blanchard Conombo, Raphaël Langevin, Frédéric Bergeron, Anne Holbrook, Brittany Humphries, Alexis Matteau, Brian J. Potter, Christel Renoux, Jean-Éric Tarride and Madeleine Durand
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Jason R. Guertin: Department of Social and Preventive Medicine, Université Laval, Quebec City, Canada
Blanchard Conombo: Department of Social and Preventive Medicine, 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
Brittany Humphries: Department of Health Evidence and Impact, McMaster University, Hamilton, Canada
Alexis Matteau: Department of Medicine, Université de Montréal, Montreal, Canada
Brian J. Potter: Department of Medicine, Université de Montréal, Montreal, Canada
Christel Renoux: McGill University, Montreal, Canada
Jean-Éric Tarride: Department of Health Evidence and Impact, McMaster University, Hamilton, Canada
Madeleine Durand: Department of Medicine, Université de Montréal, Montreal, Canada

Medical Decision Making, 2020, vol. 40, issue 5, 582-595

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.

Keywords: cardiology; confounding adjustment; economic evaluations; observational studies; systematic review (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:sae:medema:v:40:y:2020:i:5:p:582-595

DOI: 10.1177/0272989X20937257

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