Segmented regression analysis of interrupted time series studies in medication use research

Authors


 Anita K. Wagner PharmD, MPH, Department of Ambulatory Care and Prevention, Harvard Medical School and Harvard Pilgrim Health Care, 133 Brookline Avenue, Boston, MA 02215, USA. Tel.: 617 509 9956; fax: 617 859 8112; e-mail: awagner@hsph.harvard.edu

Summary

Interrupted time series design is the strongest, quasi-experimental approach for evaluating longitudinal effects of interventions. Segmented regression analysis is a powerful statistical method for estimating intervention effects in interrupted time series studies. In this paper, we show how segmented regression analysis can be used to evaluate policy and educational interventions intended to improve the quality of medication use and/or contain costs.

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