New analytics engine helps identify patients with AFib

The Food and Drug Administration has approved new technology for an analytics engine that detects atrial fibrillation.


The Food and Drug Administration has approved new technology for an analytics engine that detects atrial fibrillation.

The system uses a patch with biosensors on patients’ clothing; the patches continually generate streams of data that can inform a physician about how well the patient is doing.

“Once a patient leaves the hospital, a clinician’s ability to track progress traditionally has been limited,” says Steven Steinhubl, associate professor of genomic medicine at the Scripps Research Translational Institute in La Jolla, Calif., and a cardiologist.

The patch captures physiological data via Bluetooth technology, with the data run through an algorithm that can identify the presence or non-presence of atrial fibrillation.



FDA clearance of the analytics engine, from software platform vendor physIQ, “is ushering in an era where advanced personalized physiology analytics applied to continuous biosensor data can give clinicians the insight they need to drive down re-hospitalizations and accelerate our pace towards personalized precision medicine,” Steinhubl adds.

Also See: FDA clears mobile-based AFib algorithm

The analytics engine is named PinpointIQ and is available for use on patients discharged from a hospital, skilled nursing facility or enrolled in a home health program. Vendor physIQ conducts analytics on behalf of the client and identifies, based on the captured physiological data, if there are any signs of arrhythmia.

Data from wearables is sent to an Android phone app and then to a cloud storage center, where the analytics are done. Analytics sort through the data and identify patients for whom additional treatment actions may be appropriate. In essence, these analyses conduct triages of patients to determine if an intervention is warranted by calling the patient or getting the patient to a doctor, says Gary Conkright, CEO at physIQ. “We build a personalized image of each patient, turning data into insights,” he explains.

Steinhubl says the focus of the technology is to improve care to individually treat a patient, not just a population base. “We focus on using digital technology to transform healthcare to a more individual and precise way to compare you-to-you,” he says. Everyone has a different heart rate. But if there is a 10 percent increase in the heart rate, it could be a sign of early infection.”

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