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

      Journal of Clinical Pharmacy and Therapeutics
      Cost Control, Drug Costs, statistics & numerical data, Drug Therapy, Health Policy, Humans, Longitudinal Studies, Physician's Practice Patterns, Regression Analysis, Research Design

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          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.

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