JMIR Publications

ABSTRACT

Background:

The timely accessibility of big data that are readily usable by decision-makers can transform decision-making processes across health systems.

Objective:

This study enumerates the development of replicable and scalable jurisdiction-specific digital health dashboards for rapid decision-making to ethically monitor, mitigate, and manage public health crises via systems integration i.e., going beyond health systems.

Methods:

The primary approach in the development of the digital health dashboard was the utilization of global digital citizen science to tackle pandemics like COVID-19. The first step in the development process was to establish a Citizen Scientist Advisory Council via Digital Epidemiology and Population Health Laboratory’s community partnerships. Based on the consultation with the Council, three critical needs of citizens were prioritized: 1) management of household risk of COVID-19, 2) facilitation of food security, 3) understanding citizen accessibility of public services. Thereafter, a progressive web application (PWA) was developed to provide daily services that address these needs. The big data generated from citizen access of these services is set up to be anonymized, aggregated, and linked to the digital health dashboard for decision-making i.e., the dashboard displays anonymized and aggregated data obtained from citizen devices via the PWA. The data flow begins with citizens’ interaction with the services on the PWA, with data in transit being encrypted and protected with Cloudflare server ECDHE-RSA-AES128-GCM SHA256, and stored on Amazon Relational Database cloud servers. The digital health dashboard and the PWA are both hosted on the Amazon Elastic Compute Cloud server. The PWA is coded using Flutter Framework, whereas the digital health dashboard is coded using Hypertext Preprocessor scripting programming language. The digital health dashboard’s interactive statistical navigation was designed using Microsoft Power Business Intelligence visualization tool, which creates a secure connection with Amazon Relational Database server to regularly update visualization of jurisdiction-specific, anonymized, and aggregated data.

Results:

At the end of the development process, a dynamic digital health dashboard for decision-making was created to meet the needs identified by the Citizen Scientists Advisory Council. This digital health dashboard displays community health risks, as well as citizen needs in near real-time to facilitate rapid decision-making using jurisdiction-specific big data. More importantly, the key decision-makers who have secure access to the dashboard, can send delegated alerts (urgent vs. non-urgent) to the citizens within their jurisdiction to manage potential risks in near real-time.

Conclusions:

Digital health dashboards for decision-making can transform public health policy by prioritizing the needs of citizens as well as decision-makers to enable rapid-decision-making. Digital health dashboards also provide decision-makers the ability to directly communicate with citizens to mitigate and manage existing and emerging public health crises, a paradigm changing approach i.e., inverting innovation by prioritizing community needs, and advancing digital health for equity. Clinical Trial: N/A