Enhancing Situation Awareness in Digital Healthcare: A Visual Analytics Framework for Integrated Network and Data Security Governance
S Q G Wang, Ye Xue, Dan Wang, Rende Li · International Journal of Human-Computer Interaction · 2026
Healthcare organizations face escalating cybersecurity risks across fragmented network infrastructure and sensitive patient data, yet traditional security tools present vulnerabilities and data protections in isolated interfaces, imposing cognitive overload on security personnel. This study investigates whether visual analytics can reduce cognitive load and improve risk prioritization by unifying network attack surfaces with data asset criticality. We developed an integrated platform combining force-directed topology graphs with quantitative risk matrices, supporting semantic zooming from enterprise dashboards to device-level forensics and linked highlighting of data exposure pathways. A controlled experiment with 20 hospital security staff compared the platform against conventional multi-tool workflows. Results showed a 34% reduction in threat identification time (p<0.001), 28% improvement in risk prioritization accuracy (p<0.01), and significant decreases across all NASA-TLX cognitive load dimensions. Embedding data asset value within network topology strengthened situation awareness, demonstrating that context-aware risk communication enhances decision quality in complex healthcare sociotechnical systems.