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New H3 index predicts physician referral networks using three-hop analysis

Researchers have developed H3, a novel healthcare three-hop index designed to improve the prediction of physician referral networks. This method models indirect referral pathways through intermediate physicians, incorporating degree-based normalization and a redundancy penalty to reduce noise from hub-dominated topologies. Evaluations using Medicare data show H3 outperforms existing heuristics and deep learning baselines in both contemporaneous and temporal referral link prediction, offering a transparent and decomposable solution. AI

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IMPACT Improves healthcare coordination by enabling more accurate prediction of physician referral patterns.

RANK_REASON This is a research paper detailing a new method for predicting physician referral networks. [lever_c_demoted from research: ic=1 ai=0.4]

Read on arXiv cs.LG →

COVERAGE [1]

  1. arXiv cs.LG TIER_1 · Zhexi Gu, Jiaxin Ying, Xu-Wen Wang, Can Chen ·

    H3: A Healthcare Three-Hop Index for Physician Referral Network Prediction

    arXiv:2605.02150v1 Announce Type: cross Abstract: Accurate prediction of physician referral links is essential for optimizing care coordination and reducing fragmentation in healthcare delivery. However, existing computational methods, ranging from triadic closure heuristics to g…