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Agile Health Care Analytics: Enabling Real-Time Disease Surveillance With a Computational Health Platform
Wade L Schulz1,2, Thomas J S Durant1,2, Charles J Torre1,3
1Department of Laboratory Medicine, Yale School of Medicine, New Haven, CT, United States.
Abstract:
The ongoing coronavirus disease outbreak demonstrates the need for novel applications of real-time data to produce timely information about incident cases. Using health information technology (HIT) and real-world data, we sought to produce an interface that could, in near real time, identify patients presenting with suspected respiratory tract infection and enable monitoring of test results related to specific pathogens, including severe acute respiratory syndrome coronavirus 2. This tool was built upon our computational health platform, which provides access to near real-time data from disparate HIT sources across our health system. This combination of technology allowed us to rapidly prototype, iterate, and deploy a platform to support a cohesive organizational response to a rapidly evolving outbreak. Platforms that allow for agile analytics are needed to keep pace with evolving needs within the health care system.
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