Problems with Evidence Assessment in COVID-19 Health Policy Impact Evaluation (PEACHPIE): A systematic review of evidence strength
Type
PreprintAuthor/s
Haber, Noah A.Clarke-Deelder, Emma
Feller, Avi
Smith, Emily R.
Salomon, Joshua
MacCormack-Gelles, Benjamin
Stone, Elizabeth M.
Bolster-Foucault, Clara
Daw, Jamie R.
Hatfield, Laura A.
Fry, Carrie E.
Boyer, Christopher B.
Ben-Michael, Eli
Joyce, Caroline M.
Linas, Beth S.
Schmid, Ian
Au, Eric H.
Wieten, Sarah E.
Jarrett, Brooke A
Axfors, Cathrine
Van Thu Nguyen
Griffin, Beth Ann
Bilinski, Alyssa
Stuart, Elizabeth A.
Abstract
Introduction: The impact of policies on COVID-19 outcomes is one of the most important questions of our time. Unfortunately, there are substantial concerns about the strength and quality of the literature examining policy impacts. This study systematically assessed the currently ...
See moreIntroduction: The impact of policies on COVID-19 outcomes is one of the most important questions of our time. Unfortunately, there are substantial concerns about the strength and quality of the literature examining policy impacts. This study systematically assessed the currently published COVID-19 policy impact literature for a checklist of study design elements and methodological issues. Methods: We included studies that were primarily designed to estimate the quantitative impact of one or more implemented COVID-19 policies on direct SARS-CoV-2 and COVID-19 outcomes. After searching PubMed for peer-reviewed articles published on November 26 or earlier and screening, all studies were reviewed by three reviewers independently and in consensus. The review tool was based on review guidance for assessing COVID-19 health policy impact evaluation analyses, including first identifying the assumptions behind the methods used, followed by assessing graphical display of outcomes data, functional form for the outcomes, timing between policy and impact, concurrent changes to the outcomes, and an overall rating. Results: After 102 articles were identified as potentially meeting inclusion criteria, we identified 36 published articles that evaluated the quantitative impact of COVID-19 policies on direct COVID-19 outcomes. The majority (n=23/36) of studies in our sample examined the impact of stay-at-home requirements. Nine studies were set aside due to inappropriate study design (n=8 pre/post; n=1 cross-section), and 27 articles were given a full consensus assessment. 20/27 met criteria for graphical display of data, 5/27 for functional form, 19/27 for timing between policy implementation and impact, and only 3/27 for concurrent changes to the outcomes. Only 1/27 studies passed all of the above checks, and 4/27 were rated as overall appropriate. Including the 9 studies set aside, we found that only four (or by a stricter standard, only one) of the 36 identified published and peer-reviewed health policy impact evaluation studies passed a set of key design checks for identifying the causal impact of policies on COVID-19 outcomes. Discussion: The current literature directly evaluating the impact of COVID-19 policies largely fails to meet key design criteria for useful inference. This may be partially due to the circumstances for evaluation being particularly difficult, as well as a context with desire for rapid publication, the importance of the topic, and weak peer review processes. Importantly, weak evidence is non-informative and does not indicate how effective these policies were on COVID-19 outcomes.
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See moreIntroduction: The impact of policies on COVID-19 outcomes is one of the most important questions of our time. Unfortunately, there are substantial concerns about the strength and quality of the literature examining policy impacts. This study systematically assessed the currently published COVID-19 policy impact literature for a checklist of study design elements and methodological issues. Methods: We included studies that were primarily designed to estimate the quantitative impact of one or more implemented COVID-19 policies on direct SARS-CoV-2 and COVID-19 outcomes. After searching PubMed for peer-reviewed articles published on November 26 or earlier and screening, all studies were reviewed by three reviewers independently and in consensus. The review tool was based on review guidance for assessing COVID-19 health policy impact evaluation analyses, including first identifying the assumptions behind the methods used, followed by assessing graphical display of outcomes data, functional form for the outcomes, timing between policy and impact, concurrent changes to the outcomes, and an overall rating. Results: After 102 articles were identified as potentially meeting inclusion criteria, we identified 36 published articles that evaluated the quantitative impact of COVID-19 policies on direct COVID-19 outcomes. The majority (n=23/36) of studies in our sample examined the impact of stay-at-home requirements. Nine studies were set aside due to inappropriate study design (n=8 pre/post; n=1 cross-section), and 27 articles were given a full consensus assessment. 20/27 met criteria for graphical display of data, 5/27 for functional form, 19/27 for timing between policy implementation and impact, and only 3/27 for concurrent changes to the outcomes. Only 1/27 studies passed all of the above checks, and 4/27 were rated as overall appropriate. Including the 9 studies set aside, we found that only four (or by a stricter standard, only one) of the 36 identified published and peer-reviewed health policy impact evaluation studies passed a set of key design checks for identifying the causal impact of policies on COVID-19 outcomes. Discussion: The current literature directly evaluating the impact of COVID-19 policies largely fails to meet key design criteria for useful inference. This may be partially due to the circumstances for evaluation being particularly difficult, as well as a context with desire for rapid publication, the importance of the topic, and weak peer review processes. Importantly, weak evidence is non-informative and does not indicate how effective these policies were on COVID-19 outcomes.
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Date
2021Funding information
National Institute on Drug Abuse
National Institute of Mental Health
National Heart Lung and Blood Institute
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