Analysis of the U.S. patient referral network

• DOI: 10.1002/sim.7565
• Publication Date: 2017-12-05T10:30:32Z
• Authors: Chuankai An; A. James O'Malley; Daniel N. Rockmore; Corey D. Stock
• Keywords: Social and Information Networks (cs.SI); FOS: Computer and information sciences; Physics - Physics and Society; Databases, Factual; 91D30 (Primary), 05C82 (Secondary); FOS: Physical sciences; Computer Science - Social and Information Networks; Physics and Society (physics.soc-ph); Centers for Medicare and Medicaid Services, U.S.; United States; 3. Good health; 03 medical and health sciences; 0302 clinical medicine; Physicians; Cluster Analysis; Humans; Computer Simulation; Medical Record Linkage; Practice Patterns, Physicians'; Referral and Consultation; Algorithms

In this paper, we analyze the US Patient Referral Network (also called the Shared Patient Network) and various subnetworks for the years 2009 to 2015. In these networks, two physicians are linked if a patient encounters both of them within a specified time interval, according to the data made available by the Centers for Medicare and Medicaid Services. We find power law distributions on most state‐level data as well as a core‐periphery structure. On a national and state level, we discover a so‐called small‐world structure as well as a “gravity law” of the type found in some large‐scale economic networks. Some physicians play the role of hubs for interstate referral. Strong correlations between certain network statistics with health care system statistics at both the state and national levels are discovered. The patterns in the referral network evinced using several statistical analyses involving key metrics derived from the network illustrate the potential for using network analysis to provide new insights into the health care system and opportunities or mechanisms for catalyzing improvements.