Remote monitoring technologies let doctors keep tabs on how you’re doing, even when you’re nowhere near the doctor’s office.

It’s been touted as a potentially revolutionary development in health care, one with profound implications for getting tangible, objective data to clinicians, in real time. And as Mintu Turakhia, a cardiac electrophysiologist who is the executive director of Stanford’s Center for Digital Health, points out, it’s not even that new of an idea — cardiologists have been monitoring heart rhythms with sensors since the 1990s.

That means there’s already reimbursement and training worked out, he said. But there are still a host of challenges, including inclusive adoption strategies, better software development, and meeting patients where they are.

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STAT’s Rebecca Robbins spoke with Turakhia, who was one of the principal investigators who led the gigantic Apple Heart study, for STAT’s Health Tech Summit this week. A transcript of their conversation, lightly edited for clarity, is below.

STAT’s Rebecca Robbins: You’ve been on the forefront of thinking about how to integrate health tech into the clinic in a way that that’s careful and inclusive and evidence-based. So I want to know what keeps you up at night? What’s your biggest concern as we rush in to digital health?

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Mintu Turakhia: What keeps me up at night is what keeps a lot of people up at night is how the world is going to change after Covid. And my lens for that is what we do at Stanford, at our Center for Digital Health, is we do think about the future. We do run a large and seminal clinical trials and we think about how we’re gonna train the next generation of digital health doctors and leaders. And at some point it’s all health. But what I think we have now is a lot to talk about. But we’ve seen the pivot to virtual care. We haven’t seen the full pivot to remote monitoring, which we’ll talk about. But Stanford, for example, went overnight with the flip of a switch to 90% virtual care. And initially, everybody loved it. Patients loved it. Doctors loved it. Allied health professionals loved it. And as things went on, we actually now realize there’s a whole new set of what I’m calling ‘last-mile problems for digital health.’ And so that’s what keeps me up at night is is what is the net effect of this? Are we actually building the right solutions? And do we really know where we need to go? And hopefully not learn it the hard way. So, for example, in some ways, if you’re sick, is remote care just delaying the need to go in? Because we haven’t figured out how to deliver complex care at a distance. And then so related to that would be, how do we do that? What are the ways that we can do that synchronously and asynchronously.

And I know another concern that you’ve raised is the question of evidence supporting these digital health interventions, particularly with respect to large scale randomized clinical trials. Could you map out that landscape for us, what you’d like to see done differently?

Yeah, I think there’s a discordance or cognitive dissonance in the world of health tech and digital health with regard to the need for clinical evidence. I mean, we you know, what’s interesting is our Center for Digital Health is in the building that formerly house Theranos. And so we have this great story to tell about the need for clinical evidence because we saw how that game played out. But the the interesting issue now is that if you look at the valuations of a pharmaceutical company — we just heard a great discussion on vaccines or other drugs — it’s tied to the randomized trial data. It’s tied to the evidence. But if you look at the valuations of the tech companies, it’s tied really to projections of revenue, which, in my opinion, are often not grounded in reality with respect to adoption of clinical evidence. And so it is important not just to do the observational study or the small pilot or to have really squishy outcomes of engagement, but to really do the hard things, to randomize patients, because that’s when you remove the problems that observational studies are fraught with. And to really look at meaningful and sustained outcomes, not six-month outcomes, but to go a bit longer. And so the good news is we’re starting to see that across the board with digital health trials and interventions.

So a lot of digital health research has historically been focused on the sort of proverbial cyclist on Sand Hill Road in Silicon Valley. You know, that’s the kind of kind of very health conscious and often wealthier person who owns lots of pricey wearables. But your group is trying to expand beyond that population, trying to develop digital health interventions for Latinx populations, for black populations, as well as for gig workers. Could you tell us about that work?

Yeah. So what I learned in our team here learned — we had a great, fabulous operation here at Stanford working with Apple and all of the partners we had for the Apple Heart study — is you open the gates for a study like that and you kind of have no idea who’s going to show up. It turned out that over an eight-month period, we enrolled over 419,000 people, all in the US. And so there are not likely 419,000 body hackers out there. There are some. And when we looked at the, you know, the trials now published, we saw that we enroll 25,000 people over the age of 65. And many, many people had real, hard comorbidities, diabetes, hypertension, heart failure, prior heart attack, to name a few. And so what we realized is actually, there is adoption. And what we’ve seen, you know, in an annual report that we do in partnership with Rock Health is that digital adoption is real across the whole U.S. There are barriers, but people are doing this. The problem is, is that the products really aren’t clinically facing a wider variety of people. And so we’re trying to think through where those use cases are. And if you look at the people who have cell phones, it’s everyone. And so how do you engage, for example, gig economy workers. We’re going through a major potential legislation change on how gig economy workers are viewed, whether they’re employees or not, or contract workers. But that has a lot of issues around health care benefits, insurance access, health care access. We know, for example, from a classic study called the London Transport Study and from studies of New York taxi drivers that they bear high cardiovascular risk for a variety of reasons. So how can we deliver care where they are? And so one example we’re working on is hypertension and really trying to design products that disintermediating their regular doctor or relationships they may have with brick and mortar. But letting that physician use this to kind of guide and optimize hypertension care. And so that that’s another, I think theme here, is disintermediation and reintermediation of clinicians.

Now, let’s dive into that theme a little bit, because I think we’ve seen a number of businesses in the digital health space that have really targeted the employer market, that have targeted insurers and kind of bypassed that typical, traditional relationship that patients have with their brick and mortar clinician. And you’re trying to think about digital health tools differently at Stanford. Could you map out that distinction for us?

Yeah. So we’re in the long haul for digital health where it really is health, and it’s not an adjacency to sort of regular health. And right now, in order to get early revenue, show viability, a product market, fit all the things you need to do as a startup. Understandably, the easiest path when a healthcare system or doctors or practices are too slow to adopt is to go around them. And so, yes, we saw a great risk management and great early, mostly observational, though nonrandomized studies of how employees are using these tools. But the current model is one of two. One is it goes around their doctor completely. And to some extent that works because you might be able to do that for diabetes or cardiovascular risk. But none of that is really getting back to the doctor in a meaningful way. So it’s not well integrated. The other area that we’ve seen telehealth take off is transactional health care. And so that’s an urgent care visit. And now it’s a Covid visit. And there’s a market for that in a marketplace. Sesame just launched their own marketplace. And what’s fascinating — I checked out their website this morning is — is how little, in terms of revenue, we’re seeing doctors willing to take for these short visits. But there’s no continuity. They’re focused and they’re transactional. And maybe that’s OK, but it really doesn’t fit into the broader, you know, landscape of what you need for health. And I think that’s the tough, harder problem to figure out, but the important one.

What’s the path for novel digital measures of health to make it in to EMR or electronic medical records where a clinician can see it and use them? Are there other reasonable avenues of getting those measures into the hands of clinicians?

So it’s a great question, but I think of it a little differently. The question is sort of, we can generate data, how do we get it to people who are trained to look at it? But what’s more important is that you have some actionable data and you are able to filter out the data that’s meaningful and actionable. And I think there’s kind of a tale of two paradigms here. The first paradigm is you can go to your local, you know, big box pharmacy and buy a blood pressure cuff. No problem. And you can get it on your own. And there’s no, you know, manual tool kit on EMR integration, those have been around before smartphones and before the Internet. There were no issues and doctors were not saying, oh, my God, we should not be selling blood pressure cuffs to patients because, you know, how do they know what to do? The same is true of diabetes to the extent that patients manage their own therapies. So the data for a clinician to actually want it has to be actionable. We really don’t want data that we can’t really use. And so part of the design spec is to figure that out. The other use case where I think is very mature is remote patient monitoring with sensors is actually not a new paradigm. I’m an arrhythmia specialist and we’ve been doing this since the 1990s. So there are implantable devices that transmit to, you know, nightstand devices and now cell phones that then go to the cloud. And that data is filtered and sent back to the clinician in an actionable way. There’s reimbursement, there’s workflows, there’s even training pathways for allied professionals to be good at this. And so we don’t see that in the current landscape of non-implantable devices. And I think that’s what needs to happen. So EMR integration is certainly important. But you know, you could argue then how can we don’t integrate someone’s social media whereabouts on the EMR, too? The data needs to be actionable at first or foremost, it needs to be presented to the patient in an actionable way. And then what we’re not seeing is building software products that are based on disease use cases, heart failure, atrial fibrillation, etc.

So I want to dive in to another audience question, and this one is on the topic of demographics of the users of digital health. What’s the narrative of digital health for an aging economy and a potential surge in poor and underserved people covered by Medicaid? Is it different from the narrative for young people and people with good insurance and access to health care?

It’s a really great question. I don’t think the need is that different. I think that it really is how we get there and that’s being done in different ways. Right. So you have a couple of things going on. You have large healthcare systems like ours at Stanford trying to figure out, you know, the whole ‘make versus buy’ argument. And we’re large enough and we have so many programmers, data scientists and a great medical center, but also a great, you know, group of faculty and engineering and everything where we don’t have to buy, we can make and we can handle it. But that’s not true of everyone. And so some people are going to build their own stock. The extreme would be a company like forward that goes top to bottom and has not vendorized pretty much anything in their stock of care, including their sensors. And then the others are gonna have to tag on. And then you have really, how do you give low cost health care in really meaningful ways where you can use the technology? And so that’s the thesis of Todd Park and Devoted Health, for example, in trying to understand if they build out a stack in a managed Medicare or Medicare HMO population, how can we reduce costs? So all of these experiments are happening and we’ll just see where they shake out. What I think is not going to work, though, is with a subscription model where you’re across different platforms and you’re paying for diseases. So, you know, I can’t go to Netflix to manage my hypertension and then go to Hulu to manage my diabetes. That is where something is going to break down. And we’re either going to need better tech- and health- platform interoperability or consolidation, which we’re already seeing with companies like, you know, Teladoc and Livongo, you know, joining forces.

So I want to ask you a little bit more about the Teladoc and Livongo merger. We’ll have executives from both companies onstage tomorrow. But I’m curious how you see that alignment and the combination of the two companies fitting in with this kind of paradigm. You describe where there’s one model that involves bypassing the traditional health care system and selling to employers and kind of having your own health care system. On the other hand, a model that tries to integrate in with a continuous provider that the patient has a relationship with in-person.

Yeah. First of all, both companies have been wildly successful at what they do, and they’ve shown great product market fit and they’ve developed products that work in those use cases. But what we’re seeing now is this theme, I think, and I’d love to hear what they say, but, you know, the opportunity for reintermediation. So you have a great virtual cure platform. And then you have a great set of disease management tools within a company. And so it makes obvious sense to put those together. The real question is, you know, how do we envision digital health working and remote monitoring? Is it going to be a parallel universe that a patient has kind of almost for their alter ego to health care, but they still anchor to a brick and mortar physician because they have insurance? I hope not. I think it all needs to consolidate. And that’s where we see this opportunity of what I think is reintermediating physicians. So physicians also, you know, may not be working for a single platform anymore. We have seen over the last 20 years now, basically health care systems, buying practices and consolidating, which gives them purchasing power. And now we’re seeing an increase of supply with a lot of these virtual solutions. So now, you know, my hope is that doctors can become free agents as part of this and really deliver care across many different platforms.

Can you provide insights into how the business model of health care needs to adapt to benefit from digital innovations?

Yeah, and that’s and, you know, we just had Ashish and other policy experts about reimbursement on — it’s very hard. You know, Ashish and many others have looked at the various payment, pay-per-performance incentives that we’ve seen, for example, in Medicare. And they they sometimes work and they have a small effect, but they often don’t work at all. So if you want to break this thing and start over, that would be great. But it’s much easier said than done. That goes all the way down to the fact that, you know, in America, the government cannot negotiate with drug companies. So brand new drug released — there’s a whole suite coming out for heart failure — are going to cost more in our country versus others. So the way to get around that has been to show better demonstration of value, for example, to managed Medicare populations, direct to consumer payment, going to employers to show value. And obviously, everyone is working around those areas. But we also have the ability for Medicaid and insurance programs where you have expansion pools where people can select where they really haven’t matured. So I think this is a long haul. And I really, truly don’t know how this is going to change. One major change could be in a post-pandemic world, depending on where people are with respect to jobs. We’ve seen unemployment numbers nosedive and start to go up as they may broker their own health care in really interesting ways. So they may get high-deductible health plans and then hedge against catastrophic illness with that. But then for a sort of the daily stuff, that runny nose, the sniffles, you know, you know, general wellness checks, they may use low-cost telehealth.

So I know it can be hard to be in the prediction game. But I want to ask you, you know, looking ahead to post pandemic world or even in the coming months to a world that is in kind of the latter stages of the pandemic as things hopefully slowly go back to normal, what are you going to be watching for? What are sort of the themes or trends with respect to remote monitoring technologies and everything else we’ve talked about today that you’re going to be monitoring?

So with remote monitoring, there is kind of new reimbursement now and it’s stable, it’s working. And we’re seeing a lot of companies kind of try to get in with that. We haven’t seen major consolidation across different areas. The cardiac stuff is happening mainly in companies whose core business is is ECG outpatient monitoring. And so we’ve not seen multiple disease states under a single solution, nor have we seen a lot of development in great software products that can work asynchronously between doctors and patients. So I think that will definitely continue. I’m really looking to see what the traction is of remote monitoring and also virtual visits. We saw virtual visits skyrocket, but in the last quarter the claims have come down. The number of people have gone down. We’ve seen more face to face. What does that steady state look like? And can we learn if we’re just going to delay the inevitable that you have to come in? Or can we think creatively on on how we can have complex diagnostics go home? Is it possible to get workers to go out and do a ECG or echocardiogram or other studies, meeting patients where they are? And can we scale something like that? Is it possible that patients can do AI-guided diagnostics themselves in a safe way where they can avoid coming in and mail things back? So I’m really interested to see how we think through those ideas and build products around them.