A Web-based, Mobile Responsive Application to Screen Healthcare Workers for COVID Symptoms: Descriptive Study

Haipeng Zhang; Dimitar Dimitrov; Lynn Simpson; Balaji Singh; Nina Plaks; Stephen Penney; Jo Charles; Rosemary Sheehan; Steven Flammini; Shawn Murphy; Adam Landman

Using agile principles, we designed, tested and implemented a solution over the span of a week using progressively custom development approaches as the requirements and use case become more solidified. We developed the minimum viable product (MVP) of a mobile responsive, web-based selfservice application using REDCap (Research Electronic Data Capture). For employees without access to a computer or mobile device to use the self-service application, we established a manual process where in-person, socially distanced screeners asked employees entering the site if they have symptoms and then manually recorded the responses in an Office 365 Form. A custom .NET Framework application was developed solution as COVID Pass was scaled. We collected log data from the .NET application, REDCap and Office 365 from the first week of full enterprise deployment (March 30, 2020 -April 5, 2020). Aggregate descriptive statistics including overall employee attestations by day and site, employee attestations by application method (COVID Pass automatic screening vs. manual screening), employee attestations by time of day, and percentage of employees reporting COVID-19 symptoms