Clinical trial responds to hospital outbreaks using algorithm-driven technology

April 29, 2024- An automated tool that improves outbreak detection for hundreds of pathogens successfully served as an early warning system to find and respond to potential hospital outbreaks, as reported in NEJM Evidence. The large multi-state, real-world study was conducted in 82 hospitals and led by Harvard Pilgrim Health Care Institute, HCA Healthcare, University of California, Irvine (UCI) Health and the Centers for Disease Control and Prevention (CDC).

Contagious bacteria and other pathogens can spread in hospitals, increasing the risk of harmful infections in patients. While hospitals and health systems work to prevent infections and reduce the opportunity for outbreaks to occur, there is no standardized approach for detecting transmission. Early detection can lead to a rapid response that reduces the chance for outbreaks to occur.

The automated outbreak detection method was tested from 2019-2022 in a randomized clinical trial in 82 hospitals across 16 states in the HCA Healthcare system, a leader in real-world evidence-based research. Half of the hospitals implemented the automated early detection method, and the other half continued with usual care. Hospitals that were assigned to receive and respond to the automated alerts experienced a 64% reduction in the size of potential outbreaks until the trial was interrupted by the COVID-19 pandemic.

The underlying software is available for free to all hospital systems but must be integrated into their respective electronic health record system or other clinical workflow platforms.

A Trial of Automated Outbreak Detection to Reduce Hospital Pathogen Spread

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