Characterizing Physician Referral Networks with Ricci Curvature

Jeremy Wayland, Russel J. Funk, Bastian Rieck
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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.
用里奇曲率描述医生转诊网络的特征
在美国,识别(a)优质医疗服务的系统性障碍和(b)医疗效果的关键指标仍然是一项重大挑战。我们的初步研究结果表明,Forman-Ricci 和 Ollivier-Ricci 曲率度量因其在表征网络结构方面的表现力而闻名,它们为检测医疗保健效率的变化提供了有前途的指标,同时还捕捉到了一系列重要的地区人口特征。我们还介绍了 APPARENT,这是一款开源工具,它利用利玛窦曲率和其他网络特征来研究地区医生转诊网络结构、当地人口普查数据、医疗保健效果和患者预后之间的相关性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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