Abstract
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.
Original language | English (US) |
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Title of host publication | Pediatric and Lifespan Data Science - First International Conference, IPLDSC 2024, Revised Selected Papers |
Editors | Louis Ehwerhemuepha, Adam Kalawi, Terence Sanger, Mark Hoffman |
Publisher | Springer Science and Business Media Deutschland GmbH |
Pages | 1-16 |
Number of pages | 16 |
ISBN (Print) | 9783031883453 |
DOIs | |
State | Published - 2025 |
Event | 1st International Conference on Pediatric and Lifespan Data Science, IPLDSC 2024 - Anaheim, United States Duration: May 23 2024 → May 24 2024 |
Publication series
Name | Communications in Computer and Information Science |
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Volume | 2386 CCIS |
ISSN (Print) | 1865-0929 |
ISSN (Electronic) | 1865-0937 |
Conference
Conference | 1st International Conference on Pediatric and Lifespan Data Science, IPLDSC 2024 |
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Country/Territory | United States |
City | Anaheim |
Period | 5/23/24 → 5/24/24 |
Bibliographical note
Publisher Copyright:© The Author(s) 2025.