A Visual Analytics Framework for Inter-Hospital Transfer Network of Stroke Patients

Abstract

Effective inter-hospital coordination is crucial in improving the stroke treatment process and outcomes. The introduction of endovascular thrombectomy (EVT) further emphasized the importance of coordination. Although previous studies considered various clinical data besides stroke in terms of the network structure between hospitals, a majority of these studies performed only quantitative analyses instead of topological analyses. This study proposes a new framework (PatientFlow) for constructing a network based on stroke patient transfer data and performing exploratory analysis. The proposed framework can visualize the network structure among hospitals at the national level and analyze the detailed structure through dynamic queries. The hub-and-spoke structure for each cluster derived through community detection can be compared visually and analyzed quantitatively using network measures. Further, the relationship between regions can be analyzed by aggregating the transfer of patients by province. PatientFlow allows medical researchers to perform an exploratory analysis to understand the network at the national, provincial, and community levels with multiple coordinated views.

Keywords

• inter-hospital coordination
• community detection
• hub-and-spoke structure
• stroke patient transfer data
• endovascular thrombectomy (EVT)