By Joe Kita
August 1, 2024
Gil Munoz was riding his mountain bike in Altadena, CA, when he took a spill. He got up, brushed himself off, and pedaled home, thinking nothing of it. But in the next few days he developed a foot wound and his left leg swelled. He went to the emergency department at Adventist Health White Memorial in Los Angeles, where doctors found multiple foot fractures, referred him to a podiatrist, and prescribed antibiotics. Everything was under control.
Two days later, Munoz returned to the ER. He'd developed a hand tremor. He didn't look sick, and his podiatrist had told him just that morning that his foot wound looked good. Fortunately, there was an experienced triage nurse on duty who consulted KATE, a sepsis specialist. KATE analyzed Munoz's situation. Based on his blood pressure and his medical history, which included diabetes, KATE warned that he might have sepsis, a life-threatening response to infection.
But KATE isn't a doctor. Or a nurse. Or any human. KATE is one of several new artificial intelligence (AI) tools that some U.S. hospitals are starting to use. They tap hundreds of data points to warn nurses and doctors of the potential for sepsis in hospitalized patients.
Sepsis, which draws its name from an ancient Greek word meaning putrefaction or rot, affects 1.7 million people in the U.S. each year. It has long plagued hospitals. It's their top cause of death: 1 in 3 people who die in a U.S. hospital had sepsis while in the hospital. Sepsis-related hospitalizations have been rising: up 20% from 2016 to 2019 and another 16.5% from 2019 to 2021, with 2.5 million hospital stays. And it's the most expensive condition that U.S. hospitals treat.
Will AI help hospitals save people like Munoz who come down with sepsis?