A carregar...
Publicação
Dissecting the primary to specialist referrals using graph neural networks: exploring the relationship between physician experience and primary to secondary care physician referral patterns
| Nome: | Descrição: | Tamanho: | Formato: | |
|---|---|---|---|---|
| 1.65 MB | Adobe PDF |
Autores
Orientador(es)
Resumo(s)
The healthcare referral system affects all points of the healthcare ecosystem – access to
care, patient satisfaction, physician utilization and healthcare costs. The state of these variables
plays a critical role in determining healthcare efficiency. In this paper we dissect the medical
referrals from primary to secondary care in Florida in 2015 and tackle them from three
perspectives – influence of physician experience in referral choice, relationship between
physician referral choice and Medicare spending, and pattern detection given different referral
windows. To accomplish our goal of identifying patterns in primary to secondary referral
mechanisms, we use Graph Neural Networks (GNN) unsupervised model to learn the vectoral
representation of our physician nodes and their properties in the network. This work provides
new discoveries on factors that influence the referral patterns and can be used to make better
decisions when aiming to improve the efficiency of referrals.
Descrição
Palavras-chave
Graph neural networks National provider identifier Physician referral network Medicare