@article{Wagner2002,
  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.},
  added-at = {2023-02-03T11:44:35.000+0100},
  author = {Wagner, A K and Soumerai, S B and Zhang, F and Ross-Degnan, D},
  biburl = {https://www.bibsonomy.org/bibtex/2a8413213765a01a657e00f720643a6c9/jepcastel},
  city = {Department of Ambulatory Care and Prevention, Harvard Medical School and Harvard Pilgrim Health Care, Boston, MA 02215, USA. awagner@hsph.harvard.edu},
  interhash = {0b5b996ced26beeca4cd259c1a614e0f},
  intrahash = {a8413213765a01a657e00f720643a6c9},
  isbn = {0269-4727},
  issn = {0269-4727},
  journal = {Journal of clinical pharmacy and therapeutics},
  keywords = {Physician'sPracticePatterns DrugCosts DrugTherapy ResearchDesign Humans CostControl DrugCosts:statistics&numericaldata LongitudinalStudies RegressionAnalysis HealthPolicy},
  month = {08},
  note = {4332<m:linebreak></m:linebreak>LR: 20061115; PUBM: Print; JID: 8704308; ppublish;<m:linebreak></m:linebreak>Sèries temporals},
  number = 4,
  pages = {299-309},
  pmid = {12174032},
  timestamp = {2023-02-03T11:44:35.000+0100},
  title = {Segmented regression analysis of interrupted time series studies in medication use research.},
  url = {http://www.ncbi.nlm.nih.gov/pubmed/12174032},
  volume = 27,
  year = 2002
}

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