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HRS 2023

Digital Health Apps in Cardiovascular Device Trials: A Clinician's View

Interview With Niraj Varma, MD, PhD

© 2023 HMP Global. All Rights Reserved.
Any views and opinions expressed are those of the author(s) and/or participants and do not necessarily reflect the views, policy, or position of EP Lab Digest or HMP Global, their employees, and affiliates. 

Niraj Varma, MD, PhD, discusses his session at Heart Rhythm 2023, which took place May 19-21, 2023. 

Transcripts:

I am Niraj Varma, from the Cleveland Clinic. I am going to be talking about the application of digital techniques and digital health wearables for facilitating the conduct of clinical trials. Why should this be important? Wearables are ubiquitous now and people have become very familiar with using them for clinical care, which was a result of the pandemic. During the pandemic, in-person follow-up in clinics was significantly reduced and we began using consumer-grade wearables for monitoring heart rhythm. So, both clinicians and patients became familiar and comfortable with this technique. 

As we move to clinical trials, there are significant applications. However, one of the limitations of current clinical trials is patient screening. Some patients are automatically selected as a group who can come to the center easily and for extended follow-up. This is a selected population, and one of the drawbacks with this is that these patients are often without the comorbidities that we find in the real world. This is not the real patient population that we treat. If we can include more patients, it improves the generalizability of clinical trial results. Digital health provides that link between patients who cannot come to the hospital but who can be followed for parameters such as heart rhythm; these patients can record their symptoms, entries, and adherence to medications. This is often the gap in current clinical trials. Patient selection and retention in clinical trials has often been an impediment to finishing a clinical trial. In fact, 30% of clinical trials may simply stop before the correct number of patients has been enrolled, because it is a slow and expensive process. The use of digital technologies improves that in several ways. For instance, using electronic health records (EHRs), one can screen patients to see who meets trial criteria, create a sample of the event rates that occur in real-world populations so that one can properly power a trial in the design phase, and then select those patients for the trial. These are the benefits of EHRs. When we add wearables, they can travel with the patient anywhere, so wearables can monitor the patient at home, travel, work, or recreation/vacation time and gather real-time data. Importantly, we also get nighttime data because there is continuous monitoring with many wearables. We no longer have only snapshot data on 3-month hospital visits, which is often the standard in clinical trials. So, it is a huge advantage to have continuous data. 

Data collection, patient selection, and patient enrollment can be significantly improved when properly applied. But there are limitations. However, this is still in its infancy, so we do not always understand the implications of the data that we collect during continuous monitoring. For instance, what do we do with data on atrial fibrillation (AF)? We can now collect data with a high degree of granularity, but perhaps short episodes of AF in a patient without risk factors means very little from a clinical action point of view. We need to understand exactly what the data that are being relayed with such granularity mean in terms of clinical action. AF is important, because so far, the data that I collected do not force a clinical decision according to the United States Preventive Services Taskforce. At this moment, short durations of AF do not necessitate anticoagulation. So, we must understand the impact of the data that we are collecting. In terms of follow-up, we can still collect the information for patient attendance in hospitals. We can use geofencing with smartphones, and using location data, know when patients attend clinic so we can get hospitalization and outpatient data. These have been scarcely collected in other clinical trials. We can also get interactions with hospital services with a high degree of granularity. To give an example, the Apple Heart Study enrolled a vast number of patients—more than 400,000 patients in 9 months—so we can enroll patients very quickly without a single hospital visit. We can then remotely suggest if certain investigations need to be done, and perhaps act on those investigations and follow up. A study in China showed improved patient outcomes on the basis of remotely collected data from a cohort of patients that was enrolled remotely. So, there is a huge amount of promise in this way of conducting trials. 

One of the limitations is that there are multiple stakeholders. This includes not only the clinics and patients, but also the people who manage the data, industry partners, reimbursement partners, those responsible for cyber security, and those responsible for patient data. There are several stakeholders here, and we need to be able to create a process by which all the activities and responsibilities can be coordinated. 

So, there are many challenges, but also multiple promises. I think in the future, we will be employing digital techniques in the conduction of clinical trials. This is not only to replace the current structure of our trials and supplant some of the data collection mechanisms, but also examine novel endpoints, which we couldn't do before because we simply didn't have access to those patients or that kind of information. 


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