Jurgen Bernard, Mara Solen, Helen Novak Lauscher, Kurtis Stewart, Kendall Ho, Tamara Munzner
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引用次数: 0
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 configuration, both that specified by a developer or technical power user and that constructed automatically through log data from previous interactive sessions, as a bridge between the rigidity of hardwired programming and the time-consuming implementation of full end-user interactivity. Availability: Supplemental materials at https://osf.io/wv38n.
在COVID-19大流行之初，HealthLink BC （HLBC）迅速将医生纳入其虚拟医疗服务的分类流程，以改善患者的治疗效果和对该服务的满意度，并保持医疗保健系统的能力。我们介绍了可视化分析工具VIVA（使用可视化分析的虚拟医疗保健交互）的设计和实现，以支持HLBC分析来自服务的各种形式的使用数据。我们将HLBC的数据和数据分析任务抽象出来，并将其用于VIVA的设计。提出了扫描、行动、适应的交互工作流抽象。我们通过与利益相关者领域专家的三个案例研究来验证VIVA的设计。我们还提出了通过配置的可控性模型来进行和分析设计研究，并从这个角度讨论了VIVA的建筑演变。它阐明了由开发人员或技术高级用户指定的配置，以及通过以前交互会话的日志数据自动构造的配置，作为硬连接编程的刚性和耗时的完整最终用户交互性实现之间的桥梁。获取途径：补充材料：https://osf.io/wv38n。
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