CATALYST-The Center for the Advancement of Team Science, Analytics, and Systems Thinking, College of Medicine, The Ohio State University, Columbus, Ohio, United States.
Department of Biomedical Informatics, College of Medicine, Institute for Behavioral Medicine Research, The Ohio State University, Columbus, Ohio, United States.
Appl Clin Inform. 2021 Mar;12(2):208-221. doi: 10.1055/s-0041-1723989. Epub 2021 Apr 14.
In the United States, all 50 state governments deployed publicly viewable dashboards regarding the novel coronavirus disease 2019 (COVID-19) to track and respond to the pandemic. States dashboards, however, reflect idiosyncratic design practices based on their content, function, and visual design and platform. There has been little guidance for what state dashboards should look like or contain, leading to significant variation.
The primary objective of our study was to catalog how information, system function, and user interface were deployed across the COVID-19 state dashboards. Our secondary objective was to group and characterize the dashboards based on the information we collected using clustering analysis.
For preliminary data collection, we developed a framework to first analyze two dashboards as a group and reach agreement on coding. We subsequently doubled coded the remaining 48 dashboards using the framework and reviewed the coding to reach total consensus.
All state dashboards included maps and graphs, most frequently line charts, bar charts, and histograms. The most represented metrics were total deaths, total cases, new cases, laboratory tests, and hospitalization. Decisions on how metrics were aggregated and stratified greatly varied across dashboards. Overall, the dashboards were very interactive with 96% having at least some functionality including tooltips, zooming, or exporting capabilities. For visual design and platform, we noted that the software was dominated by a few major organizations. Our cluster analysis yielded a six-cluster solution, and each cluster provided additional insights about how groups of states engaged in specific practices in dashboard design.
Our study indicates that states engaged in dashboard practices that generally aligned with many of the goals set forth by the Centers for Disease Control and Prevention, Essential Public Health Services. We highlight areas where states fall short of these expectations and provide specific design recommendations to address these gaps.
在美国,所有 50 个州政府都部署了公开可见的新冠病毒疾病 2019(COVID-19)仪表盘,以跟踪和应对大流行。然而,各州的仪表盘反映了基于其内容、功能和视觉设计以及平台的独特设计实践。对于州仪表盘应该是什么样子或包含哪些内容,几乎没有什么指导,因此存在很大的差异。
我们研究的主要目的是编制一份目录,说明信息、系统功能和用户界面在 COVID-19 州仪表盘上的部署情况。我们的次要目的是使用聚类分析根据我们收集的信息对仪表盘进行分组和特征描述。
在初步数据收集过程中,我们开发了一个框架,首先对两个仪表盘进行分组分析,并就编码达成一致。随后,我们使用该框架对其余 48 个仪表盘进行了双重编码,并对编码进行了审查,以达成完全共识。
所有州的仪表盘都包括地图和图表,最常见的是折线图、柱状图和直方图。最常代表的指标是总死亡人数、总病例数、新病例数、实验室检测和住院治疗。如何汇总和分层处理指标的决策在仪表盘之间存在很大差异。总体而言,这些仪表盘非常具有交互性,96%的仪表盘至少具有一些功能,包括工具提示、缩放或导出功能。在视觉设计和平台方面,我们注意到软件主要由几个主要组织主导。我们的聚类分析产生了一个六聚类解决方案,每个聚类都提供了有关州群体如何在仪表盘设计中采用特定实践的更多见解。
我们的研究表明,各州在仪表盘实践中普遍符合疾病控制与预防中心(Centers for Disease Control and Prevention)设定的许多目标,这些目标是基本公共卫生服务的一部分。我们强调了各州未能达到这些期望的领域,并提供了具体的设计建议来解决这些差距。