Wayland, Jeremy Funk, Russell J. Rieck, Bastian 2025 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. application/pdf https://folia.unifr.ch/global/documents/332242 https://folia.unifr.ch/documents/332242/files/978-3-031-88346-0_1.pdf eng info:eu-repo/semantics/altIdentifier/doi/10.1007/978-3-031-88346-0_1 info:eu-repo/semantics/altIdentifier/issn/1865-0929 info:eu-repo/semantics/altIdentifier/isbn/9783031883453 info:eu-repo/semantics/openAccess CC BY Communications in Computer and Information Science. - : Springer Nature Switzerland. - 2025, p. 1-16 Physician Referral Networks Ricci Curvature Networks in Healthcare Networks Topological Data Analysis info:eu-repo/classification/udc/004 Characterizing Physician Referral Networks with Ricci Curvature http://purl.org/coar/resource_type/c_3248