The Johns Hopkins expert details recent advances in remote cardiovascular care and research, and explains how the field will continue to evolve.
The field of cardiovascular telemedicine care has expanded rapidly, with the emergence of digital capability brought on by screening and monitoring tools, a consumer embrace in wearables and heart health tracking devices, and the health care system coverages of virtual care in the immediate wake of COVID-19.
Navigating what’s permanent and what’s still lacking in this evolving field is a novel problem for frontline and prescribing clinicians.
HCPLive recently spoke with Seth Martin, MD, MHS, Director of the Advanced Lipid Disorders Program and the Digital Health Lab at the Johns Hopkins Ciccarone Center for Prevention of Cardiovascular Disease. Martin shared valuable insight into how preventive cardiology has benefitted from booms in virtual screening and monitoring capability, the need to continually address clinically comorbid and demographically unique needs and limitations in cardiovascular telemedicine, and how big data is helping to tailor LDL cholesterol measurements.
HCPLive: Since the beginning of COVID-19, in which cardiovascular subspecialties have we made the most impactful advancements in telemedicine and remote monitoring screening? Which subspecialties need greater improvement still?
Martin: Yeah, so COVID-19 had a big impact on the way we deliver care. Certainly early on in the pandemic, there was this rapid shift to telemedicine and now we've kind of gone back to more of a hybrid model of sometimes telemedicine, sometimes in-person. But the field of preventive cardiology I think was very well-positioned for this increased uptake of telemedicine and in fact, I would point folks to a statement we came out with very early on in the pandemic, from the American Society of Preventive Cardiology, where we had a group from the ASPC come together and think about how telemedicine could be used in the field of preventive cardiology and how that could improve continuity of care. And although there was that initial focus on what was happening at the time with the pandemic, I think it has a lasting kind of relevance because this idea of telemedicine really was about giving access to care, preventive care, and not having interruptions in preventive care.
Even before the pandemic, and after the pandemic, these interruptions in preventive care can happen for a lot of reasons. You know, things come up in patients’ lives; it's not necessarily easy to drive to the hospital or the clinic to engage in preventive care. So having this more flexible model of being able to connect with your care team, with your preventive cardiologist and other members of the care team, is a great way to be able to be checking in on your lipid numbers, escalating therapy, adding on non-statin therapies, arranging for follow-up with the lipid numbers, and patients don't actually need to come into clinic. So, the preventive care model I think is one of those areas that the pandemic certainly had a big impact, and it's going to continue to shape the way that we that we deliver preventive care.
HCPLive: How does the continually emerging presence of comorbid conditions including obesity, type 2 diabetes, and renal disease—as well as therapies indicated to treat across the spectrum of these diseases—impact our mobile cardiovascular health research and strategies?
Martin: Well, thank you for asking about mobile cardiovascular research and strategies. So you know, this is an area that I'm very passionate about. I do think that we're heading towards a future where mobile technologies are going to really make a bigger and bigger impact in the way that patients engage with their care. They understand the risks and the comorbidities that they're dealing with and what they can do about them, and mobile technologies can provide tools to take better care of oneself. And it can enhance the way that patients engage with clinicians. And the way that kind of interfaces with comorbidities is I think we have to be mindful of the whole patient, because if we develop mobile strategies that deal with one thing, such as lipids—as important as lipids are, if we just deal with one thing, but we forget about the whole patient, it becomes too narrow of a strategy, I think. And then patients end up having to go to additional apps or mobile strategies for other comorbidities. And the technologies aren't necessarily talking to each other.
So I think what we're looking at is a future where there's a more holistic approach with mobile strategies. They can have a focus on a particular area that's particularly relevant to someone—certainly, lipid management and somebody who just had a heart attack is particularly relevant. But looking at the big picture, there's going to be more than that for that patient success. And so as we think about these comorbidities like diabetes, hypertension, kidney disease, we need to be taking that into account as we develop a holistic strategy.
HCPLive: What is the emphasis of diverse patient populations—both demographically and clinically—in mobile cardiovascular health assessments? Can more be done in this space?
Martin: Thinking about diverse populations, that kind of brings to mind the term health equity—making these mobile solutions available for everyone to take advantage of the benefits of these technologies and to have the best opportunity to achieve their best possible outcomes, their best possible cardiovascular health. So I've been very fortunate to collaborate and learn from colleagues in the Johns Hopkins Center for Health Equity. And we've really been working a lot to understand the digital divide that some people have, more or less technology, but also that tends to align with access to certain clinical services. And we've put a lot of focus into cardiac rehab services where older patients, women, underserved minorities are traditionally less likely to participate in cardiac rehab. And similarly, there can be this divide with access to technology.
So in order to address this, I think we need to first understand the problem, but also develop strategies to give access to devices. So that may mean loaning devices or giving smartphones, wearables, blood pressure monitors, and so forth. But also, coaching services, so that patients—even if they have them—they may not be able to use them easily. But also designing apps in a way that fits into as intuitively as possible. But even when you do that, I still think there's a need for coaching on top of that. So those are some of the strategies that we're taking to make sure that the solutions we develop are available to meet people where they are, and those people coming from all sorts of different ages, sexes, rate, ethnicities, neighborhoods, and so forth.
HCPLive: Your team at Johns Hopkins has recently been behind research into the various LDL-C and lipid screening and measurement practices used by clinicians. What is the importance of providing guidance for clinicians navigating all these available strategies to monitor patients?
Martin: Well, you know that LDL cholesterol is central in our research in the guidelines and our clinical practice, and it guides the decisions that we make on a daily basis with our patients—whether we're going to go up on the lipid therapy, if we're going to add on an additional therapy to get that LDL cholesterol down to ultimately reduce the risk of heart attacks and stroke. So it's really critical that we have accurate measurements. And so we've had a lot of focus on making sure that those reports coming from laboratories have the most accurate determination of LDL cholesterol, we've been able to develop a new method or equation that provides more accurate LDL cholesterol levels. Whereas older approaches have underestimated LDL cholesterol at low levels, which could lead to under treatment, we've been able to solve that problem through the use of big data and recalculating LDL in a way that's more individualized—moving from us sort of what I call "one size fits all approach" where everyone sort of has the same equation, to applying an equation that adapts to somebody's lipid profile to get the most accurate results.
I think this is really critical because that data point is going to guide big decisions that could be a matter of life and death. And so that's why I feel it's really important that we have the most accurate results and we standardize that across labs. Unfortunately, there's been a bunch of other different equations that have popped up, which may not provide as accurate results, and I think clinicians should be mindful of which equation is being reported. And I'm happy to talk more about this topic, but I know we're up on time.