Achieving Mortality Reduction Via Third-Party Remote Monitoring: Amplifying the Importance of the Latest Guidelines

© 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. 

EP LAB DIGEST. 2023;23(12):18,20.

EP Lab Digest talks with Niraj Varma, MD, PhD, from the Cleveland Clinic about new research evaluating the real-world impact of a universal remote monitoring (RM) platform. Implicity is an artificial intelligence (AI)-powered remote cardiac monitoring software platform; their platform provides critical health information augmented by AI algorithms cleared by the US Food and Drug Administration.

Could you elaborate on why you chose to focus on this topic, and how it compares or contrasts with the pre-existing literature regarding the impact of RM of cardiovascular implantable electronic devices (CIEDs)?

I have had a long interest in the RM of CIEDs, beginning almost 20 years ago when I chaired the TRUST trial,¹ which compared RM of CIEDs versus conventional care. While it was quite disruptive at the time, we found out that RM offered many advantages. This was in the setting of a randomized trial, and it took about 3-4 years before those results became part of guideline recommendations. In the 2015 expert consensus statement² from the Heart Rhythm Society (HRS), RM became the preferred method of managing patients with CIEDs. After the TRUST trial, there were several “copycat” trials showing consistent results in different countries using different manufacturers.

However, after the recommendations, we found that adoption of RM in the community was relatively modest, despite the known advantages of this technology. The patients who adopted RM had better outcomes, but almost 50% of patients in one study,³ which was published in 2015, simply never switched it on, even though they had RM-enabled devices. We tried to understand why and found that one of the major reasons was because managing virtual care such as a RM device takes a lot of invisible work. Meaning, it is invisible because it is not patient facing.

RM has been shown to reduce the number of patients who attend clinic, decompressing hospital waiting rooms and device clinics. That is a huge advantage. There is also an economical advantage for hospitals. But at the same time, there is a lot of non-patient-facing work that must be done to keep the RM clinic going. While different technologies from different manufacturers have shown the same results, from a device clinic allied professional’s point of view, managing all the different manufacturer databases, which are all individual and not interconnected, can be a lot of work.

The work is related to downloading the data, understanding the data, communicating with patients, and uploading the data into the electronic medical record. It is a lot of invisible work. We think this is a major cause of the breakdown between the recommendations to use RM in all patients and the modest adoption in the community, simply because device clinics cannot follow up.

Implicity can harmonize all the data coming in from the different manufacturer platforms and create its own set of alerts for critical events. The advantage of RM is early detection of critical events, even if the patient is asymptomatic, whether it is related to device integrity or to the disease, such as advent of atrial fibrillation or heart failure (HF). So, a clinic that is using Implicity is much more likely to be effective in managing RM simply because it is easier to use. Implicity facilitates the managing of RM data. There are other third-party platforms out there that are processing data for clinics. However, Implicity is the company that I have been working with because they follow the philosophy of using RM as an alert-based mechanism, which means that the system will alert the clinician only if there is a problem, not for routine general update data. That is the advantage of the Implicity platform.

Why is this study unique? What was the design?

The TRUST trial and follow-up studies showed that RM reduced the number of in-clinic evaluations that were required to monitor a large population of patients. Those were the primary endpoints. Next, we wanted to know whether patient outcomes were improved in terms of survival or acute admissions. The data from randomized trials have been varied, with some showing no effect and others demonstrating significant survival benefit using RM. Why is that the case? The data suggests that in the trials that controlled the alerts to prespecify the ones that were important, which were then acted on with a prespecified algorithm and treatment protocol, there was a survival benefit. Implicity uses this system.

In our observational study, we linked the Implicity-based data of patients with RM to the French national database, which is a comprehensive administrative claims database of patient outcomes, drug interventions, and patient comorbidities. We compared outcomes for hospitalizations and survival in the proportion of patients who had RM versus no-RM. Within the patients who had RM turned on, we contrasted the ones who were managed by Implicity versus standard RM, and again assessed the outcomes. Therefore, while this was not a randomized trial, it was a RM database that was linked to a national administrative claims database, so we gathered good patient outcome data.

What were the results of the study? How can they be explained?

In the first level of results, we compared outcomes between patients who had no-RM compared to patients who had RM. They were relatively balanced; there were 29,900 patients in the no-RM group and 38,000 RM patients. We corrected for covariates, including age, gender, device type, time to implant, and center volume of RM patients. RM can produce some challenges for clinics, so we looked at the center volume as a representative of experience. The patients who had the RM turned on were mainly males (75%), aged 67-68, and a larger proportion in RM was cardiac resynchronization therapy defibrillators (CRT-Ds) compared to implantable cardioverter-defibrillators (ICDs). This was a defibrillator analysis of CRT-D versus ICD proportions, or 40% CRT-Ds in all RM and 26% in no-RM. This probably represents a bias towards using RM for sicker patients. We found that in unadjusted survival analysis, patients who were committed to RM had better survival in this database.

When we corrected for the differences in the 2 populations, CRT-D versus ICD, comorbidities, etc, we found that the mortality benefit in patients with RM was about 4% improvement, with a hazard ratio of .96. Both HF hospitalizations and total hospitalizations increased, but the duration of hospitalizations was unchanged. We interpreted this to mean that patients were coming in more frequently with RM because the clinics were alerted about problems; they were treated effectively, so the duration of hospitalizations was the same or reduced in these patients. That was overall between RM and no-RM.

Then, we moved to the group who had Implicity RM versus conventional RM. Since Implicity is relatively new, we only had 2200 patients committed to Implicity-based RM. Conventional RM patients numbered almost 32,000. We found a trend to improved survival with Implicity RM. It was a trend in unadjusted analysis. When we adjusted for all the covariates, including age, sex, gender, and device type, we found that there was a significant improvement in survival, with a hazard ratio of .78 for mortality using Implicity RM. There was a reduction in hospitalizations by about 4%, a reduction in HF hospitalizations by about 5%, and accumulated duration of hospitalizations was reduced by 6%. This shows improved survival and reduced hospitalizations in patients committed to Implicity.

There is a new expert consensus about RM. Can you tell us about it?

Because of the dramatic increase in the number of patients with CIED devices, the complexity of those patients, and the complexity of devices, RM is becoming more and more important. There is also the challenge of managing these data, and these challenges are increasing. The 2023 document is a consensus statement on the practical management of the remote device clinic.⁴ It endorses that RM has a class 1A recommendation and is the preferred method of follow-up for patients who receive a CIED. Specifically, it has a class 2A recommendation for the use of third-party resources in RM.

The level of evidence is C-EO, which means expert opinion, and reflects the fact that the data are only just beginning to be presented for us. That includes our work with Implicity as well. The consensus document states that for the care of patients with CIEDs on RM, it is reasonable to use third-party resources to alleviate RM workload for staff. This reduces workload, and we have shown that it helps improves patient outcomes as well.

How do you interpret your results in the light of the new expert consensus? Do they relate?

Yes, Implicity is designed to facilitate RM workload for the clinic staff, which is exactly what the recommendation states. It is expert opinion, no data, so we provided the first data for this. We add to that by showing that patient outcomes improve as well when you use this platform. Implicity’s platform is a way of capitalizing on the powers of RM. We know from early days that when you use RM in a structured way, you can improve patient outcomes. Trials with structured plans, such as IN-TIME and CONNECT-HF, have shown improved patient outcomes. The CONNECT trial also demonstrated a reduction in hospitalizations. However, studies such as REM-HF, which had unstructured RM in terms of how those alerts should be transmitted, what the parameters were, and how they should be responded to, have shown no effect. So, we think Implicity in the real world enables that structured plan and that response mechanism to important data being transmitted by RM.

There is a trend towards more alert-based RM. What is it and why is this important?

We have used 3 monthly checks for ICDs as a routine method of evaluation, and that goes back to 25-30 years ago with the first ICDs that required 3 monthly manual capacity reforms, threshold, and battery tests, because all of those were unpredictable. But in the modern era, these devices are very reliable, durable, and can manage themselves in terms of capture thresholds, auto capture, automatic capacitor reforms. Yet, we continue with 3 monthly checks, and we layer on RM on top of that, which creates a lot of work.

Alert-based monitoring suggests that we probably do not need those 3 monthly checks. When the actionability of those 3 monthly checks is measured, it is less than 10% and it has nothing to do with device integrity or device function, usually it is a reprogramming change or a change in patient medications. So, those 3 monthly checks are not actionable. We can probably avoid most of those 3 monthly routine checks. I think we are moving into the era where we do not do routine checks; instead, we can commit patients to RM and wait for the system to alert us when the patient or the device needs to be seen. This is alert-based monitoring. It depends on a reliable RM platform and connectivity being maintained. Clinics that switch to alert-based care must ensure that connectivity is maintained. This is important because that is the method of follow-up.

It promises a huge reduction in nonactionable work, which releases device clinic staff. Resources are always finite and limited, but they can now concentrate on the work that needs to be done, the patients that need to be seen, and actionable events that might be indicated by an alert or an unscheduled event of a patient presenting to the hospital. We can avoid the routine management, which is a relic from 20 years ago or more. Therefore, Implicity platform switches us to alert-based care. Implicity permits use of alert-based care, but will still let clinics do the 3 monthly checks if preferred.

Overall, RM in the US is still not done for all patients, and all centers are not using third-party platforms. Where do we stand and how do you see things evolving?

The new document gives us a list of practical recommendations to make our RM easier to practice. It also provides recommendations to hospital administration to support RM clinics, understanding there is a lot of invisible work. Simply because there are no patients in the waiting room does not mean that work is not being done. They are being remotely connected. This is a virtual care platform, so hospital administrations need to recognize and support it. The 2A recommendation for third-party platforms is strong. For hospitals that cannot manage RM themselves, third-party platforms provide an excellent method of adhering to the guidelines and using RM. 

References

1. Varma N, Epstein AE, Irimpen A, Schweikert R, Love C; TRUST Investigators. Efficacy and safety of automatic remote monitoring for implantable cardioverter-defibrillator follow-up: the Lumos-T Safely Reduces Routine Office Device Follow-up (TRUST) trial. Circulation. 2010;122(4):325-332. doi:10.1161/CIRCULATIONAHA.110.937409

2. Slotwiner D, Varma N, Akar JG, et al. HRS Expert Consensus Statement on remote interrogation and monitoring for cardiovascular implantable electronic devices. Heart Rhythm. 2015;12(7):e69-100. doi:10.1016/j.hrthm.2015.05.008

3. Varma N, Marijon E, Abraham A, et al. LB-456088-2 Clinical impact of a universal remote monitoring platform for ICD and CRT-D follow-up from a large real-world registry. Heart Rhythm. 2023;20(7):P1095. doi:10.1016/j.hrthm.2023.04.045

4. Ferrick AM, Raj SR, Deneke T, et al. 2023 HRS/EHRA/APHRS/LAHRS expert consensus statement on practical management of the remote device clinic. Heart Rhythm. 2023;20(9):e92-e144. doi:10.1016/j.hrthm.2023.03.1525

This article was published with support from Implicity.

Disclosure: Dr Varma has completed and returned the ICMJE Form for Disclosure of Potential Conflicts of Interest. He reports consulting fees with Abbott, Biotronik, Implicity, PaceMate, HeartBeam, EP Solutions, and Medtronic.