Hospitals look to computers to predict patient emergencies before they happen
2019-05-13 from statnews.com
CLEVELAND — Seven floors, and long odds, were stacked against John S. He was undergoing a test on the first floor of a Cleveland Clinic hospital when his nursing team — on the eighth floor — got a call, telling them the 57-year-old had developed a dangerously rapid heartbeat that was spiraling toward cardiac arrest.
It is a predicament that often ends badly. Only about 25 percent of U.S. patients survive when their hearts stop in hospitals. Crucial minutes elapse before help arrives, sometimes because alarms are missed amid the din of beeping monitors.
But the call that day didn’t come from within the hospital. It came from a darkened room in an office park several miles away, where a technician in the clinic’s Central Monitoring Unit (CMU) was watching the patient’s vital signs on a computer monitor and noticed the onset of ventricular tachycardia.
Hospital command centers have proliferated across the country in recent years, with medical centers from Oregon to Florida deploying them to tackle a range of data-monitoring tasks, such as maximizing bed capacity, calibrating staffing levels, and detecting the onset of sepsis, a life-threatening response to infection that is a common killer in hospitals.
Recent advances in artificial intelligence promise to help hospitals identify new warning signs of patient deterioration and intervene earlier in the process. Administrators of command centers at Johns Hopkins and Yale New Haven Hospital both said they are exploring the use of machine learning to deliver more timely care
The Cleveland Clinic’s ultimate goal is to give front-line clinicians notice of serious cardiac events an hour or more before they happen. That would be a significant leap forward from the system’s current capabilities. Right now the CMU can offer some advance notice of cardiac emergencies, but it is heavily reliant on technicians to pluck out the signals from massive data streams on hundreds of patients and quickly route them to caregivers.
Read more here