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J Clin Epidemiol. 2015 Aug;68(8):950-6. doi: 10.1016/j.jclinepi.2014.12.018. Epub 2015 Mar 11.

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

Author information

1
Leslie Dan Faculty of Pharmacy, University of Toronto, 144 College Street, Toronto, Ontario, Canada M5S 3M2.
2
Leslie Dan Faculty of Pharmacy, University of Toronto, 144 College Street, Toronto, Ontario, Canada M5S 3M2; Applied Health Research Center, La Ka Shing Knowledge Institute, St. Michael's Hospital, 30 Bond Street, Toronto, Ontario, Canada M5B 1W8; Institute of Health Policy, Management, and Evaluation, University of Toronto, 155 College Street, Toronto, Ontario, Canada M5T 3M6.
3
Department of Public Health Sciences, Queen's University, 62 Fifth Field Company Lane, Kingston, Ontario, Canada K2L 3N6.
4
Leslie Dan Faculty of Pharmacy, University of Toronto, 144 College Street, Toronto, Ontario, Canada M5S 3M2. Electronic address: s.cadarette@utoronto.ca.

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

PMID:
25890805
DOI:
10.1016/j.jclinepi.2014.12.018
[Indexed for MEDLINE]
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