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Employee Contact Tracing Helps Mount Sinai Control COVID-19 Spread

Analysis  |  By Scott Mace  
   November 08, 2022

Officials at the New York health system say future pandemic tracking will benefit from this digital framework.

Mount Sinai has shared details of a new employee contact tracing database developed to control the spread of COVID-19.

Writing in the November issue of The Lancet Digital Health, researchers form the New York-based health system describe the creation of the Mount Sinai Employee Health COVID-19 REDCap Registry, a cloud-based digital framework using a web application known as Research Electronic Data Capture.

The tool is intended to track and reduce the spread of the virus across the Mount Sinai Health System, which includes eight hospitals and more than 400 outpatient clinics.

The database powering the tool assigns unique identification codes for each exposure without intentionally linking each exposure to previous events for that same person or department.

In this way, Mount Sinai can associate events to assist investigations in identifying patterns of the disease's spread. This design also adjusts and responds to changes in the COVID-19 disease as variants such as delta and omicron emerge.

The Employee Health COVID-19 REDCap Registry provides secure, easy to use forms for employee health collection and workflow-monitored contact-tracing information for employees. It also provides qualitative analysis of employee interviews and integrated genomic sequencing.

So far, the initiative has yielded 50,000 employee interviews and more than 500 framework revisions, according to researchers.

The registry is available through mobile and desktop devices connected to the internet, and remote access allows integration at all Mount Sinai Health System clinics and hospitals. The web forms enable swift follow-up from employee health services.

The contact-tracing function captures employee demographics, length of quarantine, which personal protective equipment the employee used, and a recent history of testing for COVID-19. An exposure matrix provides risk scores based on the type of exposure. Supervised machine learning predicts exposure outcomes, according to the researchers.

The registry allowed Mount Sinai employee health services to trim case follow-up times from days to hours.

Scott Mace is a contributing writer for HealthLeaders.

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