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

被引：2468
|
作者：
Wagner, AK
Soumerai, SB
Zhang, F
Ross-Degnan, D
机构：
[1] Harvard Univ, Sch Med, Dept Ambulatory Care & Prevent, Boston, MA 02215 USA
[2] Harvard Pilgrim Hlth Care, Boston, MA 02215 USA
[3] Harvard Univ, Sch Publ Hlth, Dept Epidemiol, Boston, MA 02115 USA
来源：
JOURNAL OF CLINICAL PHARMACY AND THERAPEUTICS | 2002年 / 27卷 / 04期
关键词：
health policy evaluation; interrupted time series design; longitudinal analysis; medication use research; quasi-experimental design; segmented regression analysis;
D O I：
10.1046/j.1365-2710.2002.00430.x
中图分类号：
R9 [药学];
学科分类号：
1007 ;
摘要：
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.
引用
收藏
页码：299 / 309
页数：11
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