FDA approves early warning system for sepsis
An early warning system for sepsis, one of the deadliest infections for hospital patients, has been approved for use by the FDA, one of the first AI-based medical tools to get clearance.
The tool, developed by Johns Hopkins University researchers and now commercialized by Bayesian Health, detects sepsis hours faster than doctors and has reduced deaths by nearly 20%.
“Pre-suspicion screening is what creates lead time, and lead time is what changes outcomes in sepsis. Once a clinician already suspects sepsis, the clock has been running-often for hours or even days,” says lead researcher Suchi Saria, a Johns Hopkins professor and director of the AI & Healthcare Lab, who began translating her lab’s research into a real-world system after losing her nephew to sepsis in 2017. “No other cleared test or device monitors for sepsis prior to clinician suspicion.”
With sepsis, every hour that sepsis detection is delayed significantly decreases a patient’s chance for survival. Sepsis is easily missed because its symptoms, such as fever and confusion, are common in other medical conditions.
To beat those odds, Saria and a team at Johns Hopkins created the Targeted Real-Time Early Warning System. The federally-funded work, which integrates electronic health records with advanced clinical AI, has helped doctors spot sepsis cases nearly two to 48 hours earlier than traditional methods.
The system is reducing sepsis mortality rates by 18% in dozens of hospitals across the United States—a significant advance in addressing a deadly immune response that claims more than 250,000 lives each year.
“It gives physicians an additional set of eyes and ears and could genuinely help save lives,” says Albert Wu, a Johns Hopkins expert in patient safety expert and a co-investigator on the work. “This is a significant milestone for Johns Hopkins and Dr. Saria’s team.”
In 2023, under the FDA’s Breakthrough Designation-a designation to expedite technologies with potential to improve care for life-threatening conditions—the technology was deployed at several health systems, including Cleveland Clinic, MemorialCare in California and University of Rochester School of Medicine, where it significantly reduced in-hospital mortality, morbidity, and length of stays for patients with sepsis.
“Few clinical AI systems can reason across the full breadth of messy, real-world hospital data and deliver guidance clinicians can reliably act on,” said Saria. “FDA approval is a regulatory first that shifts what the standard of care can be for a condition associated with roughly one in three in-hospital deaths. This represents decades of clinical AI research at Johns Hopkins translated into practice — not just models built in the lab, but technology delivered where it matters: at the bedside.”
FDA clearance also opens the door to allow hospitals using the system to receive Medicare and Medicaid reimbursement under the New Technology Add-on Payment program, that compensates hospitals for use of new technologies.
“Suchi’s work has reached a major milestone,” says Ed Schlesinger, dean of Johns Hopkins’ Whiting School of Engineering. “It’s poised to have a significant role in preventing hospital deaths and complications.”
