JMIR Publications

ABSTRACT

Background:

Since the outbreak of COVID-19, activity has surged worldwide to develop dashboards as dynamic, visual tools for communicating COVID-19 data. Dashboards can inform decision-making and support behavior change. To do so, they must be actionable. What constitutes an actionable dashboard in the context of the pandemic has not been rigorously assessed.

Objective:

To explore the characteristics of public, web-based COVID-19 dashboards by assessing (i) why (purpose and users), (ii) what (content and data), and (iii) how (analysis and display) they communicate COVID-19 data, and ultimately, appraising (iv) the common features of highly actionable dashboards.

Methods:

We conducted a descriptive assessment and scoring using Nominal Group Technique with an international panel of experts (n=17) on a global sample of COVID-19 dashboards in July 2020. The sequence of steps included: multimethod sampling of dashboards; development and piloting of an assessment tool; data extraction and first round of actionability scoring; workshop based on a preliminary analysis of results; and reconsideration of actionability scores followed by joint determination of common features of highly actionable dashboards. We used descriptive statistics and thematic analysis to explore findings by research question.

Results:

A total of 158 dashboards from 53 countries were assessed. Dashboards were predominately developed by government authorities (100/158, 63.0%) and were national (93/158, 58.9%) in scope. Main findings by the study’s objectives include: (i) Only 20 dashboards (12.7%) stated both the primary purpose and intended audience. (ii) Nearly all dashboards reported epidemiological indicators (155/158, 98.1%), followed by health system management indicators (85/158, 53.8%), whereas indicators on social and economic impact and behavioral insights were least reported (7/158, 4.4% and 2/158, 1.3%, respectively). Approximately one quarter (39/158, 24.7%) did not report data sources. (iii) Dashboards predominately reported time trends and disaggregated data most often by two geographic levels and by age and sex. Dashboards on average used 2.2 types of displays, mostly graphs and maps followed by tables. To support interpretation, color-coding was common (93/158, 89.4%), though only a fifth (31/158, 19.6%) included text explaining data quality and its meaning. (iv) In total, 20 dashboards (12.7%) were appraised as highly actionable, and seven common features were identified between them. Actionable COVID-19 dashboards: (1) know their audience and information needs; (2) manage the type, volume and flow of displayed information; (3) report data sources and methods clearly; (4) link time trends to policy decisions; (5) provide data ‘close to home’; (6) breakdown the population into relevant sub-groups; and (7) use story-telling and visual cues.

Conclusions:

COVID-19 dashboards are diverse in why, what and how they communicate insights on the pandemic and support data-driven decision-making. In order to leverage their full potential, dashboard developers should consider adopting the seven actionability features identified.