Physicians naturally form networks. Networks could form a rational basis for Accountable Care Organizations (ACOs) for defined populations of Medicare beneficiaries.
To use methods from network science to identify naturally occurring networks of physicians that might be best suited to becoming ACOs.
Using nationally representative claims data from the Medicare program for CY 2006 on 51 hospital referral regions (HRRs), we used a network science–based community-detection algorithm to identify groups of physicians likely to have preestablished relationships. After assigning patients to networks based upon visits with a primary care physician, we examined the proportion of care delivered within communities and compared our results with potential ACOs organized around single hospitals.
We studied 4,586,044 Medicare beneficiaries from 51 HRRs who were seen by 68,288 active physicians practicing in those HRRs. The median community-based network ACO had 150 physicians with 5928 ties, whereas the median hospital-based network ACO had 96 physicians with 3276 ties. Among patients assigned to networks via their primary care physicians, seventy-seven percent of physician visits occurred with physicians in the community-based networks as compared with 56% with physicians in the hospital-based networks; however, just 8% of specialist visits were to specialists within the hospital-based networks as compared with 60% of specialist visits within the community-based networks. Some markets seemed better suited to developing ACOs based on network communities than others.
We present a novel approach to identifying groups of physicians that might readily function as ACOs. Organic networks identified and defined in this natural and systematic manner already have physicians who exhibit close working relationships, and who, importantly, keep the vast majority of care within the networks.
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*Department of Health Care Policy, Harvard Medical School
†Department of Medicine, Beth Israel Deaconess Medical Center, Division of Primary Care and General Internal Medicine
‡Department of Biostatistics, Harvard School of Public Health
§Department of Medicine, Division of General Internal Medicine, Brigham and Women’s Hospital, Boston
∥Department of Sociology, Harvard University, Cambridge, MA
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Supported by a grant from the National Institute on Aging (P-01 AG-031093).
N. Christakis and B. Landon have an equity stake in a company, Activate Networks, which is licensed by Harvard University to apply some of the ideas embodied in this work. The other authors declare no conflict of interest.
Reprints: Bruce E. Landon, MD, MBA, Department of Health Care Policy, Harvard Medical School, 180 Longwood Avenue, Boston, MA 02115. E-mail: firstname.lastname@example.org.