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

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 con...

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Autores principales: Ewusie, Joycelyne E, Soobiah, Charlene, Blondal, Erik, Beyene, Joseph, Thabane, Lehana, Hamid, Jemila S
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7231782/
https://www.ncbi.nlm.nih.gov/pubmed/32494150
http://dx.doi.org/10.2147/JMDH.S241085
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author Ewusie, Joycelyne E
Soobiah, Charlene
Blondal, Erik
Beyene, Joseph
Thabane, Lehana
Hamid, Jemila S
author_facet Ewusie, Joycelyne E
Soobiah, Charlene
Blondal, Erik
Beyene, Joseph
Thabane, Lehana
Hamid, Jemila S
author_sort Ewusie, Joycelyne E
collection PubMed
description 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.
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spelling pubmed-72317822020-06-02 Methods, Applications and Challenges in the Analysis of Interrupted Time Series Data: A Scoping Review Ewusie, Joycelyne E Soobiah, Charlene Blondal, Erik Beyene, Joseph Thabane, Lehana Hamid, Jemila S J Multidiscip Healthc Review 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. Dove 2020-05-13 /pmc/articles/PMC7231782/ /pubmed/32494150 http://dx.doi.org/10.2147/JMDH.S241085 Text en © 2020 Ewusie et al. http://creativecommons.org/licenses/by-nc/3.0/ This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). 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 (https://www.dovepress.com/terms.php).
spellingShingle Review
Ewusie, Joycelyne E
Soobiah, Charlene
Blondal, Erik
Beyene, Joseph
Thabane, Lehana
Hamid, Jemila S
Methods, Applications and Challenges in the Analysis of Interrupted Time Series Data: A Scoping Review
title Methods, Applications and Challenges in the Analysis of Interrupted Time Series Data: A Scoping Review
title_full Methods, Applications and Challenges in the Analysis of Interrupted Time Series Data: A Scoping Review
title_fullStr Methods, Applications and Challenges in the Analysis of Interrupted Time Series Data: A Scoping Review
title_full_unstemmed Methods, Applications and Challenges in the Analysis of Interrupted Time Series Data: A Scoping Review
title_short Methods, Applications and Challenges in the Analysis of Interrupted Time Series Data: A Scoping Review
title_sort methods, applications and challenges in the analysis of interrupted time series data: a scoping review
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7231782/
https://www.ncbi.nlm.nih.gov/pubmed/32494150
http://dx.doi.org/10.2147/JMDH.S241085
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