Back to Journals » Journal of Multidisciplinary Healthcare » Volume 13

Methods, Applications and Challenges in the Analysis of Interrupted Time Series Data: A Scoping Review

Authors Ewusie JE, Soobiah C, Blondal E, Beyene J, Thabane L, Hamid JS

Received 4 December 2019

Accepted for publication 17 April 2020

Published 13 May 2020 Volume 2020:13 Pages 411—423


Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 3

Editor who approved publication: Dr Scott Fraser

Joycelyne E Ewusie,1 Charlene Soobiah,2,3 Erik Blondal,2,3 Joseph Beyene,1 Lehana Thabane,1,4 Jemila S Hamid1,5

1Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada; 2Li Ka Shing Knowledge Institute of St Michael’s Hospital, Toronto, Ontario, Canada; 3Institute of Health Policy Management and Evaluation (IHPME), University of Toronto, Toronto, ON, Canada; 4Biostatistics Unit, Father Sean O’Sullivan Research Centre, St Joseph’s Healthcare, Hamilton, Ontario, Canada; 5Clinical Research Unit, Children’s Hospital of Eastern Ontario, Ottawa, ON, Canada

Correspondence: Jemila S Hamid
Children’s Hospital of Eastern Ontario, 401 Smyth Road, Ottawa, ON K1H 8L1, Canada
Tel +1 (613) 737-7600 x 4194
Email [email protected]

Objective: Interrupted time series (ITS) designs are robust quasi-experimental designs commonly used to evaluate the impact of interventions and programs implemented in healthcare settings. This scoping review aims to 1) identify and summarize existing methods used in the analysis of ITS studies conducted in health research, 2) elucidate their strengths and limitations, 3) describe their applications in health research and 4) identify any methodological gaps and challenges.
Design: Scoping review.
Data Sources: Searches were conducted in MEDLINE, JSTOR, PUBMED, EMBASE, CINAHL, Web of Science and the Cochrane Library from inception until September 2017.
Study Selection: Studies in health research involving ITS methods or reporting on the application of ITS designs.
Data Extraction: Screening of studies was completed independently and in duplicate by two reviewers. One reviewer extracted the data from relevant studies in consultations with a second reviewer. Results of the review were presented with respect to methodological and application areas, and data were summarized using descriptive statistics.
Results: A total of 1389 articles were included, of which 98.27% (N=1365) were application papers. Segmented linear regression was the most commonly used method (26%, N=360). A small percentage (1.73%, N=24) were methods papers, of which 11 described either the development of novel methods or improvement of existing methods, 7 adapted methods from other areas of statistics, while 6 provided comparative assessment of conventional ITS methods.
Conclusion: A significantly increasing trend in ITS use over time is observed, where its application in health research almost tripled within the last decade. Several statistical methods are available for analyzing ITS data. Researchers should consider the types of data and validate the required assumptions for the various methods. There is a significant methodological gap in ITS analysis involving aggregated data, where analyses involving such data did not account for heterogeneity across patients and hospital settings.

Keywords: interrupted time series, segmented linear regression, ARIMA, limitations, methods, scoping review

Creative Commons License This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at and incorporate the Creative Commons Attribution - Non Commercial (unported, v3.0) License. By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms.

Download Article [PDF]  View Full Text [HTML][Machine readable]