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J Clin Epidemiol. 2006 Jan;59(1):18-25. Epub 2005 Nov 7.

Explained variation in a model of therapeutic decision making is partitioned across patient, physician, and clinic factors.

Author information

  • 1Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital-Harvard Medical School, 1620 Tremont Street, Suite 3030, Boston, MA 02120, USA. abrookhart@rics.bwh.harvard.edu

Abstract

BACKGROUND AND OBJECTIVE:

Data on therapeutic decision making have a multilevel structure that can include patient-, provider-, and facility-level variables. A statistical method is presented for attributing explained variation in patient care to different levels of aggregation in a multilevel model with the aim of prioritizing and targeting quality improvement interventions.

STUDY DESIGN AND SETTING:

The proposed method is used in an analysis of adherence to evidence-based guidelines for the care of patients at risk of osteoporosis. Explained variation from a multilevel model of appropriate care is partitioned across patient-, physician-, and clinic-level factors.

RESULTS:

The combination of patient, physician, and clinic factors explained 20.0% of the variation in patient care. Individual physician effects explained 14.0% of the variation in the data; however, more than half of this explained variation could have been attributed to the individual clinic effect. Patient fixed effects alone explained 13.4% of the variation in the observed clinical decisions.

CONCLUSION:

The proposed approach is an intuitive and statistically valid method for attributing explained variation in a multilevel analysis of therapeutic decision making.

PMID:
16360557
[PubMed - indexed for MEDLINE]
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