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Patient Sharing and Quality of Care

Measuring Outcomes of Care Coordination Using Claims Data

Pollack, Craig E., MD, MHS*,†; Lemke, Klaus W., PhD; Roberts, Eric, MA; Weiner, Jonathan P., DrPH

doi: 10.1097/MLR.0000000000000319
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Background: With the goal of improving clinical efficiency and effectiveness, programs to enhance care coordination are a major focus of health care reform.

Objective: To examine whether “care density”—a claims-based measure of patient sharing by office-based physicians—is associated with measures of quality. Care density is a proxy measure that may reflect how frequently a patient’s doctors collaborate.

Research Design: Cohort study using administrative databases from 3 large commercial insurance plans.

Subjects: A total of 1.7 million adult patients; 31,675 with congestive heart failure, 78,530 with chronic obstructive pulmonary disease, and 240,378 with diabetes.

Measures: Care density was assessed in 2008. Prevention Quality Indicators (PQIs), 30-day readmissions, and Healthcare Effectiveness Data and Information Set quality indicators were measured in the following year.

Results: Among all patients, we found that patients with the highest care density density—indicating high levels of patient sharing among their office-based physicians—had significantly lower rates of adverse events measured as PQIs compared with patients with low-care density (odds ratio=0.88; 95% confidence interval, 0.85–0.92). A significant association between care density and PQIs was also observed for patients with diabetes mellitus but not congestive heart failure or chronic obstructive pulmonary disease. Diabetic patients with higher care density scores had significantly lower odds of 30-day readmissions (odds ratio=0.68, 95% confidence interval, 0.48–0.97). Significant associations were observed between care density and Healthcare Effectiveness Data and Information Set measures although not always in the expected direction.

Conclusion: In some settings, patients whose doctors share more patients had lower odds of adverse events and 30-day readmissions.

*Johns Hopkins University School of Medicine

Johns Hopkins Bloomberg School of Public Health, Baltimore, MD

Supplemental Digital Content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal's Website, www.lww-medicalcare.com.

This work was performed with support by faculty and staff at The Johns Hopkins University, where the ACG method was developed and is maintained. To help support research and development, The Johns Hopkins University receives royalties from health plans and other organizations that use the ACG software. A version of care density is included in the ACG software.

C.E.P.’s salary was supported by a career development award from the NIH National Cancer Institute and Office of Behavioral and Social Sciences Research (1K07CA151910-01A1). The remaining authors declare no conflict of interest.

Reprints: Craig E. Pollack, MD, MHS, Johns Hopkins University School of Medicine, 2024 E. Monument Street, Rm 2-521, Baltimore, MD 21287. E-mail: cpollac2@jhmi.edu.

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