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VIVA: Virtual Healthcare Interactions Using Visual Analytics, With Controllability Through Configuration
IEEE Transactions on Visualization and Computer Graphics
|August 15, 2025
Summary
A new visual analytics tool, VIVA, was developed to analyze virtual healthcare service data. This tool supports HealthLink BC in optimizing patient care and system capacity during the COVID-19 pandemic.
Area of Science:
- Health Informatics
- Data Visualization
- Human-Computer Interaction
Background:
- The COVID-19 pandemic necessitated rapid adaptation of virtual healthcare services.
- HealthLink BC (HLBC) integrated physicians into triage to enhance patient outcomes and system capacity.
- Effective analysis of service usage data is crucial for optimizing virtual healthcare delivery.
Purpose of the Study:
- To design and implement VIVA (Virtual healthcare Interactions using Visual Analytics), a visual analytics tool for HLBC.
- To support HLBC in analyzing diverse usage data from their virtual healthcare service.
- To improve patient outcomes, satisfaction, and preserve healthcare system capacity.
Main Methods:
- Abstraction of HLBC's data and data analysis tasks to inform VIVA's design.
- Development of the VIVA tool incorporating the Scan, Act, Adapt workflow.
- Validation of VIVA's design through case studies with domain experts.
- Proposal of the Controllability Through Configuration model for design study analysis.
Main Results:
- VIVA provides a framework for analyzing virtual healthcare interactions.
- The Controllability Through Configuration model offers a method for evaluating design studies.
- Architectural evolution of VIVA was analyzed through the lens of configuration.
Conclusions:
- VIVA effectively supports the analysis of virtual healthcare service data.
- Configuration serves as a bridge between programming and end-user interactivity.
- The study provides insights into optimizing virtual healthcare services through visual analytics.
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