VIVA: Virtual Healthcare Interactions Using Visual Analytics, With Controllability Through Configuration
J\"urgen Bernard, Mara Solen, Helen Novak Lauscher, Kurtis Stewart, Kendall Ho, Tamara Munzner
TL;DR
VIVA is a visual analytics tool designed to analyze virtual healthcare usage data, enabling flexible configuration and supporting healthcare providers in improving service quality through interactive data analysis and stakeholder validation.
Contribution
The paper introduces VIVA, a novel visual analytics system with a controllability through configuration model, tailored for analyzing virtual healthcare interactions and validated through real-world case studies.
Findings
VIVA effectively supports healthcare data analysis and decision-making.
The Controllability Through Configuration model enhances system flexibility.
Case studies demonstrate VIVA's utility in real healthcare settings.
Abstract
At the beginning of the COVID-19 pandemic, HealthLink BC (HLBC) rapidly integrated physicians into the triage process of their virtual healthcare service to improve patient outcomes and satisfaction with this service and preserve health care system capacity. We present the design and implementation of a visual analytics tool, VIVA (Virtual healthcare Interactions using Visual Analytics), to support HLBC in analysing various forms of usage data from the service. We abstract HLBC's data and data analysis tasks, which we use to inform our design of VIVA. We also present the interactive workflow abstraction of Scan, Act, Adapt. We validate VIVA's design through three case studies with stakeholder domain experts. We also propose the Controllability Through Configuration model to conduct and analyze design studies, and discuss architectural evolution of VIVA through that lens. It articulates…
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