A team of researchers at the Veterans Health Administration in Salt Lake City suggested analyzing data from a non-invasive sensor may be able to predict a patient's risk of readmission after heart failure, according to a study published in the Journal of the American College of Cardiology.
The researchers enrolled 100 patients who had been admitted to one of four U.S. Veterans Affairs hospitals for heart failure.
For the study, the researchers used a disposable chest-adhesive multisensor patch to monitor patients for up to three months after discharge. The patch continuously recorded physiological data — such as heart rate, heart rate variability, accelerometry, respiratory rate and temperature — which were uploaded to a cloud platform for analysis.
The researchers found the analytics platform predicted patient readmissions for heart failure at a similar rate as existing invasive approaches. The researchers reported the median time between the system's initial alert and a patient's readmission was six days, based on an analysis of data from 33 patients readmitted during the study period.
The study authors concluded, "multivariate physiological telemetry from disposable wearable sensors provided accurate early detection of impending rehospitalization with a predictive accuracy comparable to implanted devices."