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Agile Healthcare Analytics: Enabling Real-Time Disease Surveillance with a Computational Health Platform
Wade L Schulz;
Thomas JS Durant;
Charles J Torre Jr;
Allen L Hsiao;
Harlan M Krumholz
ABSTRACT
The ongoing COVID-19 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 (RTI) and enable monitoring of test results related to specific pathogens, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This tool was built upon our computational health platform (CHP), 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 healthcare system.
Citation
Please cite as:
Schulz WL, Durant TJ, Torre CJ Jr, Hsiao AL, Krumholz HM
Agile Health Care Analytics: Enabling Real-Time Disease Surveillance With a Computational Health Platform