Methods used to meta-analyse results from interrupted time series studies: A methodological systematic review protocol

Elizabeth Korevaar; Amalia Karahalios; Andrew B Forbes; Simon L Turner; Steve McDonald; Monica Taljaard; Jeremy M Grimshaw; Allen C Cheng; Lisa Bero; Joanne E McKenzie

doi:10.12688/f1000research.22226.3

Methods used to meta-analyse results from interrupted time series studies: A methodological systematic review protocol

F1000Res. 2020 Feb 12:9:110. doi: 10.12688/f1000research.22226.3. eCollection 2020.

Authors

Elizabeth Korevaar¹, Amalia Karahalios¹, Andrew B Forbes¹, Simon L Turner¹, Steve McDonald¹, Monica Taljaard^{2

3}, Jeremy M Grimshaw^{2

3

4}, Allen C Cheng^{1

5}, Lisa Bero⁶, Joanne E McKenzie¹

Affiliations

¹ School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, 3004, Australia.
² Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Ontario, K1Y 4E9, Canada.
³ School of Epidemiology, Public Health and Preventive Medicine, University of Ottawa, Ottawa, Ontario, K1N 6N5, Canada.
⁴ Department of Medicine, University of Ottawa, Ottawa, Ontario, K1H 8M5, Canada.
⁵ Infection Prevention and Healthcare Epidemiology Unit, Alfred Health, Melbourne, Victoria, 3004, Australia.
⁶ Faculty of Medicine and Health and Charles Perkins Centre, University of Sydney, Sydney, New South Wales, 2006, Australia.

Abstract

Background: Systematic reviews are used to inform healthcare decision making. In reviews that aim to examine the effects of organisational, policy change or public health interventions, or exposures, evidence from interrupted time series (ITS) studies may be included. A core component of many systematic reviews is meta-analysis, which is the statistical synthesis of results across studies. There is currently a lack of guidance informing the choice of meta-analysis methods for combining results from ITS studies, and there have been no studies examining the meta-analysis methods used in practice. This study therefore aims to describe current meta-analysis methods used in a cohort of reviews of ITS studies. Methods: We will identify the 100 most recent reviews (published between 1 January 2000 and 11 October 2019) that include meta-analyses of ITS studies from a search of eight electronic databases covering several disciplines (public health, psychology, education, economics). Study selection will be undertaken independently by two authors. Data extraction will be undertaken by one author, and for a random sample of the reviews, two authors. From eligible reviews we will extract details at the review level including discipline, type of interruption and any tools used to assess the risk of bias / methodological quality of included ITS studies; at the meta-analytic level we will extract type of outcome, effect measure(s), meta-analytic methods, and any methods used to re-analyse the individual ITS studies. Descriptive statistics will be used to summarise the data. Conclusions: This review will describe the methods used to meta-analyse results from ITS studies. Results from this review will inform future methods research examining how different meta-analysis methods perform, and ultimately, the development of guidance.

Keywords: Interrupted time series; meta-analysis; systematic review.

Publication types

Research Support, Non-U.S. Gov't
Review

MeSH terms

Humans
Interrupted Time Series Analysis*
Meta-Analysis as Topic*
Public Health*
Research Design*
Systematic Reviews as Topic*

Grants and funding

EK and SLT are supported through an Australian Government Research Training Program (RTP) Scholarship administered by Monash University, Australia. JEM is supported by an NHMRC Career Development Fellowship (1143429). The project is funded by the Australian National Health and Medical Research Council (NHMRC) project grant GNT1145273, "How should we analyse, synthesize, and interpret evidence from interrupted time series studies? Making the best use of available evidence", McKenzie JE, Forbes A, Taljaard M, Cheng A, Grimshaw J, Bero L, Karahalios A.