Dissecting medical referral mechanisms in health services using graph neural networks
Published in The International Conference on Complex Networks and Their Applications, 2020
Recommended citation: Regina Duarte, Qiwei Han, Claudia Soares, "Dissecting medical referral mechanisms in health services using graph neural networks." The International Conference on Complex Networks and Their Applications, 2020. https://easychair.org/smart-program/COMPLEXNETWORKS2020/2020-12-03.html#talk:162210
Abstract
The medical referrals between primary care doctor and specialist affect many aspects of patient care, such as quality of care, patient satisfaction and health care costs, etc. In this work, we hypothesize that the social network of medical doctors can influence the referral process. We analyse primary-specialty referrals through transaction data over medical appointments gathered between 2012 and 2017 in all hospital centers of a European private health provider. The main objective of the study is to discover patterns and hidden mechanisms in the primary-specialist referrals to improve efficiency of health care services. First, we carry out exploratory data analysis and search for patterns or interesting features of the data and afterwords we create and analyse the doctor's social network and the referrals network. We learn the representation of the referral network using a Graph Neural Network (GNN). This work addresses the discovery of important patterns in medical referrals to, in a future work, improve the efficiency of collaboration within organizations.
BibTeX
@inproceedings{Regina20,
author = "Duarte, Regina and Han, Qiwei and Soares, Claudia",
title = "Dissecting medical referral mechanisms in health services using graph neural networks",
booktitle = "The International Conference on Complex Networks and Their Applications",
year = "2020",
abstract = "The medical referrals between primary care doctor and specialist affect many aspects of patient care, such as quality of care, patient satisfaction and health care costs, etc. In this work, we hypothesize that the social network of medical doctors can influence the referral process. We analyse primary-specialty referrals through transaction data over medical appointments gathered between 2012 and 2017 in all hospital centers of a European private health provider. The main objective of the study is to discover patterns and hidden mechanisms in the primary-specialist referrals to improve efficiency of health care services. First, we carry out exploratory data analysis and search for patterns or interesting features of the data and afterwords we create and analyse the doctor's social network and the referrals network. We learn the representation of the referral network using a Graph Neural Network (GNN). This work addresses the discovery of important patterns in medical referrals to, in a future work, improve the efficiency of collaboration within organizations.",
abstractsource = "https://easychair.org/smart-program/COMPLEXNETWORKS2020/2020-12-03.html\#talk:162210",
abstractsourcelabel = "Published abstract source",
url = "https://easychair.org/smart-program/COMPLEXNETWORKS2020/2020-12-03.html\#talk:162210"
}