The group, which includes researchers from the University of Utah Health and VA Salt Lake City Health Care System, claims that the system could help avert up to one in three heart failure readmissions in the weeks following initial discharge from the hospital.
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Josef Stehlik, lead author of a study on the technology published in Circulation: Heart Failure said: "This study shows that we can accurately predict the likelihood of hospitalisation for heart failure deterioration well before doctors and patients know that something is wrong.”
The researchers followed 100 heart failure patients, average age 68, who were diagnosed and treated at four different hospitals. After discharge, these patients wore an adhesive sensor patch on their chests 24 hours a day for up to three months. The sensor monitored continuous electrocardiogram (ECG) and motion of each subject.
This information was transmitted from the sensor via Bluetooth to a smartphone and then passed on to an analytics platform, developed by PhysIQ, on a secure server, which derived heart rate, heart rhythm, respiratory rate, walking, sleep, body posture and other normal activities. Using artificial intelligence, the analytics established a normal baseline for each patient. When the data deviated from normal, the platform generated an indication that the patient's heart failure was getting worse.
Overall, the system accurately predicted the impending need for hospitalisation more than 80 per cent of the time. On average, this prediction occurred 10.4 days before a readmission took place.
"There's a high risk for readmission in the 90 days after initial discharge," said Stehlik. "If we can decrease this readmission rate through monitoring and early intervention, that's a big advance. We're hoping even in patients who might be readmitted that their stays are shorter, and the overall quality of their lives will be better with the help of this technology."
The researchers are now planning a large clinical trial that will not only use the system to alert doctors of changes in a patient's condition but also track if early intervention based on these alerts lead to fewer rehospitalisations for heart failure.
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