Comparison of physician networks constructed from thresholded ties versus shared clinical episodes

• Main Authors: Jukka-Pekka Onnela, A. James O’Malley, Nancy L. Keating, Bruce E. Landon
• Format: Article
• Language: English
• Published: SpringerOpen 2018-08-01
• Series: Applied Network Science
• Subjects: Physician networks; Episodes of care; Network communities; Medicare data
• Online Access: http://link.springer.com/article/10.1007/s41109-018-0084-1

Abstract Objective To compare standard methods for constructing physician networks from patient-physician encounter data with a new method based on clinical episodes of care. Data source We used data on 100% of traditional Medicare beneficiaries from 51 nationally representative geographical regions for the years 2005–2010. Study design We constructed networks of physicians based on their shared patients. In the fixed-threshold networks and adaptive-threshold networks, we included data on all patient-physician encounters to form the physician-physician ties, and then subsequently thresholded some proportion of the strongest ties. In contrast, in the episode-based approach, only those patient-physician encounters that occurred within shared clinical episodes treating specific conditions contributed towards physician-physician ties. Data collection/extraction methods We extracted clinical episodes in the Medicare data and investigated structural properties of the patient-sharing networks of physicians, temporal dynamics of their ties, and temporal stability of network communities across the two approaches. Principal findings The episode-based networks accentuated ties between primary care physicians (PCPs) and medical specialists, had ties that were more likely to reappear in the future, and appeared to have more fluid community structure. Conclusions Constructing physician networks around shared episodes of care is a clinically sound alternative to previous approaches to network construction that does not require arbitrary decisions about thresholding. The resulting networks capture somewhat different aspects of patient-physician encounters.