Review Article
Interrupted time series analysis in drug utilization research is increasing: systematic review and recommendations

This research was presented at the International Conference on Pharmacoepidemiology and Therapeutic Risk Management (ICPE) in Montreal, QC, Canada, August 2013; the Canadian Association for Population Therapeutics (CAPT) Annual Conference in Toronto, ON, Canada, November 2013; and the Canadian Association for Health Services and Policy Research (CAHSPR) Annual Conference in Toronto, ON, Canada, May 2014. Participation at ICPE was supported by an ICPE Travel Scholarship, participation at CAPT was supported by a CAPT Student Bursary and the Leslie Dan Faculty of Pharmacy Student Experience Fund, and participation at CAHSPR was supported by a University of Toronto School of Graduate Studies Conference Grant.
https://doi.org/10.1016/j.jclinepi.2014.12.018Get rights and content
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Abstract

Objectives

To describe the use and reporting of interrupted time series methods in drug utilization research.

Study Design and Setting

We completed a systematic search of MEDLINE, Web of Science, and reference lists to identify English language articles through to December 2013 that used interrupted time series methods in drug utilization research. We tabulated the number of studies by publication year and summarized methodological detail.

Results

We identified 220 eligible empirical applications since 1984. Only 17 (8%) were published before 2000, and 90 (41%) were published since 2010. Segmented regression was the most commonly applied interrupted time series method (67%). Most studies assessed drug policy changes (51%, n = 112); 22% (n = 48) examined the impact of new evidence, 18% (n = 39) examined safety advisories, and 16% (n = 35) examined quality improvement interventions. Autocorrelation was considered in 66% of studies, 31% reported adjusting for seasonality, and 15% accounted for nonstationarity.

Conclusion

Use of interrupted time series methods in drug utilization research has increased, particularly in recent years. Despite methodological recommendations, there is large variation in reporting of analytic methods. Developing methodological and reporting standards for interrupted time series analysis is important to improve its application in drug utilization research, and we provide recommendations for consideration.

Keywords

ARIMA
Drug utilization
Pharmacoepidemiology
Review
Segmented regression
Time series

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Conflict of interest: None.

Funding: This research was supported by an Ontario Ministry of Research and Innovation Early Researcher Award held by S.M.C. S.M.C was supported by a Canadian Institutes of Health Research (CIHR) New Investigator Award (MSH-95364). R.J. received support from the CIHR Training Program in Bridging Scientific Domains for Drug Safety and Effectiveness.