Larry Chinitz, MD: Tracking Heart Rhythm Data


How wearable devices and their massive patient pools have created a balancing act between mass patient arrhythmia data collection and individualized care.

Wearable devices are becoming friendlier tools to cardiologists. Regulated, downloadable apps have given physicians another asset of telehealth monitoring capability, and major real-world trials such as the Apple Heart study are breaking the mold for heart rhythm database capabilities.

But it’s important all this data collection has a payoff. In an interview with MD Magazine®, Larry Chinitz, MD, director of Cardiac Electrophysiology and clinical director of Cardiology at NYU Langone Health, explained why it’s a balancing act between mass patient arrhythmia data collection and individualized care.

MD Mag: How has telehealth advanced patient heart rhythm monitoring at NYU Langone?

Chinitz: I think this is dramatic. These changes that we have with wearable devices, subcutaneous monitors, I think they’ve transformed monitoring for atrial fibrillation. So what we've learned is that putting a monitor on somebody for 24 hours, which was the standard of care for so long, is just not adequate. You need prolonged monitoring.

And if patients can do it by managing their watch on a daily basis and getting that information—or get a subcutaneous monitor that allows us to remotely monitor them for years without them doing anything—that is transformative and has helped us in terms of management and making a diagnosis. So we encourage that to everybody who's willing to do it.

I think the advent of artificial intelligence now into some of these devices, to really look more deeply into making diagnoses and making people aware with greater accuracy—much of the problems that we have in our clinic is we manage thousands of patients remotely with pacemakers, defibrillators, subcutaneous monitors. The data comes in, and sometimes it's hard to figure out. It's not always so clear what we are seeing, and we need really improvements in that.

So I think the future, as it relates to machine learning and deep learning of some of these algorithms, will give us tremendous information—really tremendous.

What is the current state of cardiology outpatient care?

Well, I think we have the capabilities to be in a good spot. But for instance, we've had lots of issues within our medical center of making sure we define a standard of care for remote monitoring, and that we do our due diligence to make sure patients are monitored, that alerts are answered.

But we follow 7000 or 8000 patients, and we have 6 people who work full-time just doing that remote monitoring and device monitoring. So it's an effort, and it requires technology, and it requires people, and it requires resources.

So the balance of all this monitoring is that you better have the capabilities of doing monitoring—because you put a monitor on somebody, and they have an event and you’re not around to see that event, you're relying upon getting that information. Then that's a problem. I think the technology is great, but I think managing the data is going to be increasingly an issue.

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