Characterizing Physician Referral Networks with Ricci Curvature
This work addresses regional disparities in healthcare access and delivery for patients and providers, but it is incremental as it applies existing curvature methods to a new domain.
The authors tackled the problem of identifying systemic barriers and key indicators of healthcare efficacy in the U.S. by applying Ricci curvature measures to Physician Referral Networks, finding that these measures can detect variations in healthcare efficacy and capture regional demographic features.
Identifying (a) systemic barriers to quality healthcare access and (b) key indicators of care efficacy in the United States remains a significant challenge. To improve our understanding of regional disparities in care delivery, we introduce a novel application of curvature, a geometrical-topological property of networks, to Physician Referral Networks. Our initial findings reveal that Forman-Ricci and Ollivier-Ricci curvature measures, which are known for their expressive power in characterizing network structure, offer promising indicators for detecting variations in healthcare efficacy while capturing a range of significant regional demographic features. We also present APPARENT, an open-source tool that leverages Ricci curvature and other network features to examine correlations between regional Physician Referral Networks structure, local census data, healthcare effectiveness, and patient outcomes.