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

A K Wagner; S B Soumerai; F Zhang; D Ross-Degnan

doi:10.1046/j.1365-2710.2002.00430.x

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

J Clin Pharm Ther. 2002 Aug;27(4):299-309. doi: 10.1046/j.1365-2710.2002.00430.x.

Authors

A K Wagner¹, S B Soumerai, F Zhang, D Ross-Degnan

Affiliation

¹ Department of Ambulatory Care and Prevention, Harvard Medical School and Harvard Pilgrim Health Care, Boston, MA 02215, USA. awagner@hsph.harvard.edu

PMID: 12174032
DOI: 10.1046/j.1365-2710.2002.00430.x

Abstract

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.

Publication types

Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, P.H.S.

MeSH terms

Cost Control
Drug Costs / statistics & numerical data*
Drug Therapy*
Health Policy*
Humans
Longitudinal Studies
Practice Patterns, Physicians'
Regression Analysis*
Research Design