New AI sepsis detection models challenge Epic’s market position
You are reading the second part of Paying for AI, a series examining how new artificial intelligence clinical tools are influencing healthcare affordability and the long-term health of patients. Read part one here.
Five years ago, sepsis prediction software fell apart. Hundreds of hospitals have adopted an algorithm from electronic medical records company Epic that promises to alert doctors of anticipated cases of sepsis, a potentially deadly reaction to an infection that kills more than 350,000 people each year in the United States.
AI was a technical failure. Despite its results on paper, the technology didn’t work in the real world and sent so many alerts that doctors ignored them or hospitals turned them off.
Half a decade later, new models of sepsis are emerging. Epic has released a revamped version of its own algorithm. Startups are testing their models in health systems. A team uses large language models to extract signs of sepsis from clinical notes. And on Tuesday, a sepsis detection device from Bayesian Health, originally from Johns Hopkins, announced that it had received clearance from the Food and Drug Administration.
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