Current trends in the application of causal inference methods to pooled longitudinal non-randomised data: a protocol for a methodological systematic review

TY - JOUR

T1 - Current trends in the application of causal inference methods to pooled longitudinal non-randomised data: a protocol for a methodological systematic review

AU - Yeboah, Edmund

AU - Mauer, Nicole Sibilla

AU - Hufstedler, Heather

AU - Carr, Sinclair

AU - Matthay, Ellicott C

AU - Maxwell, Lauren

AU - Rahman, Sabahat

AU - Debray, Thomas

AU - de Jong, Valentijn M T

AU - Campbell, Harlan

AU - Gustafson, Paul

AU - Jänisch, Thomas

AU - Bärnighausen, Till

N1 - © Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

PY - 2021/11/12

Y1 - 2021/11/12

N2 - INTRODUCTION: Causal methods have been adopted and adapted across health disciplines, particularly for the analysis of single studies. However, the sample sizes necessary to best inform decision-making are often not attainable with single studies, making pooled individual-level data analysis invaluable for public health efforts. Researchers commonly implement causal methods prevailing in their home disciplines, and how these are selected, evaluated, implemented and reported may vary widely. To our knowledge, no article has yet evaluated trends in the implementation and reporting of causal methods in studies leveraging individual-level data pooled from several studies. We undertake this review to uncover patterns in the implementation and reporting of causal methods used across disciplines in research focused on health outcomes. We will investigate variations in methods to infer causality used across disciplines, time and geography and identify gaps in reporting of methods to inform the development of reporting standards and the conversation required to effect change.METHODS AND ANALYSIS: We will search four databases (EBSCO, Embase, PubMed, Web of Science) using a search strategy developed with librarians from three universities (Heidelberg University, Harvard University, and University of California, San Francisco). The search strategy includes terms such as 'pool*', 'harmoniz*', 'cohort*', 'observational', variations on 'individual-level data'. Four reviewers will independently screen articles using Covidence and extract data from included articles. The extracted data will be analysed descriptively in tables and graphically to reveal the pattern in methods implementation and reporting. This protocol has been registered with PROSPERO (CRD42020143148).ETHICS AND DISSEMINATION: No ethical approval was required as only publicly available data were used. The results will be submitted as a manuscript to a peer-reviewed journal, disseminated in conferences if relevant, and published as part of doctoral dissertations in Global Health at the Heidelberg University Hospital.

AB - INTRODUCTION: Causal methods have been adopted and adapted across health disciplines, particularly for the analysis of single studies. However, the sample sizes necessary to best inform decision-making are often not attainable with single studies, making pooled individual-level data analysis invaluable for public health efforts. Researchers commonly implement causal methods prevailing in their home disciplines, and how these are selected, evaluated, implemented and reported may vary widely. To our knowledge, no article has yet evaluated trends in the implementation and reporting of causal methods in studies leveraging individual-level data pooled from several studies. We undertake this review to uncover patterns in the implementation and reporting of causal methods used across disciplines in research focused on health outcomes. We will investigate variations in methods to infer causality used across disciplines, time and geography and identify gaps in reporting of methods to inform the development of reporting standards and the conversation required to effect change.METHODS AND ANALYSIS: We will search four databases (EBSCO, Embase, PubMed, Web of Science) using a search strategy developed with librarians from three universities (Heidelberg University, Harvard University, and University of California, San Francisco). The search strategy includes terms such as 'pool*', 'harmoniz*', 'cohort*', 'observational', variations on 'individual-level data'. Four reviewers will independently screen articles using Covidence and extract data from included articles. The extracted data will be analysed descriptively in tables and graphically to reveal the pattern in methods implementation and reporting. This protocol has been registered with PROSPERO (CRD42020143148).ETHICS AND DISSEMINATION: No ethical approval was required as only publicly available data were used. The results will be submitted as a manuscript to a peer-reviewed journal, disseminated in conferences if relevant, and published as part of doctoral dissertations in Global Health at the Heidelberg University Hospital.

KW - Causality

KW - Delivery of Health Care

KW - Humans

KW - Research Design

KW - Review Literature as Topic

KW - San Francisco

U2 - 10.1136/bmjopen-2021-052969

DO - 10.1136/bmjopen-2021-052969

M3 - SCORING: Review article

C2 - 34772754

VL - 11

JO - BMJ OPEN

JF - BMJ OPEN

SN - 2044-6055

IS - 11

M1 - e052969

ER -