The Future of Remote Patient Monitoring: Overcoming Challenges and Embracing Personalized Care
A guest expert discusses how AI-driven data insights are revolutionizing health care by enabling proactive, personalized, and cost-effective interventions—helping payers reduce hospitalizations, optimize resource allocation, and improve patient outcomes before costly complications arise.
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Kent Dicks: My name is Kent Dicks, and I'm CEO of a company called Life365. This is my third company, second in health care. My last company was one of the first Interagency Oncology Task Force Fellowship (IOTF) health care [companies] called MedApps, which sold to a $5 billion publicly traded company. My background is in technology. Bringing consumer-based technology into health care, that has been my mission for the last 20 years. I've been fortunate enough to testify in front of House subcommittees on investor affairs, on Veterans Affairs (VA), on the US Food and Drug Administration (FDA), on the Federal Communications Commission. So, trying to be a thought leader in bringing new and innovative technology to the marketplace.
How can technology aid in shifting from reactive to more proactive health care to anticipate and reduce costs?
Dicks: One of the biggest things, I think, that's occurring today is that a lot of times when you're looking at traditional remote patient monitoring solutions, they're being used [too] late in the cycle with individuals. This is often because of cost, the effort in trying to deploy technology to patients, and also the engagement of the patients as well. From that, you'll see the need for what I call “shifting left” and trying to move from complex care to the middle of the hump. I always [use] a hump [with] health and wellness on one side and complex care on the other side, and in the middle of this hump is people that may be newly chronic or showing signs of becoming chronic, maybe they are pre-diabetic, maybe they have early hypertension. You don't need to have full-blown connected solutions to try to nudge these people back into existence. You just need to get little, tiny bits of data to try to influence their patterns and their behaviors to try to keep them compliant so that they don't become worse, presenting in the emergency room and being hospitalized. A lot of times that's what we're waiting for.
Data is going to play an important role in collecting valuable, actionable [insights] that can be used by artificial intelligence (AI) and machine learning systems to try to look at a vast population of people and patients to understand not just that Phil's blood pressure is going up, but [to understand] that while Phil's blood pressure going up may be relatively okay for him, it's more devastating to Kent. Kent may be prioritized higher on the list because if Kent's blood pressure goes up, previous events have shown that he's going to go to the emergency room and he's going to be hospitalized.
AI and data are going to play an incredible role in trying to make that shift from reactive care to what I call the 4 Ps, which is preventive, proactive, personalized, and prioritized care. And, by the way, I learned that Dr Leroy Hood wrote the book “The Age of Scientific Wellness” and he absolutely, 100% has coined those phrases. I'm glad that we copied off of somebody in the space that sees the exact same issue that needs to be addressed really quickly.
We can move on, but I think that this is a lot about exception-based processing and to go out and use data to try to prioritize care. It's super important to personalize care. But if I can use systems and use AI to go through and nudge somebody into compliance, maybe I can do that with 70% of our population and I don't have to wait until they get sicker before we decide to intervene; I can do it really proactively upfront.
Data truly is king, especially in scenarios like this, where you have all the puzzle pieces—you just need to put them together. It sounds like this is where the technology comes into play.
Dicks: It is, but it isn't for the doctors, right? I mean, doctors don't need to have any more data that's out there, they're already overloaded as it is. AI and machine learning are incredibly thirsty for data and can be those watchman that are sitting out there looking at the population and maybe going through and saying, "I don't see something quite right for Kent right now and his trends," days and weeks in advance. Instead of waiting for me to get sicker and present myself to the emergency room and into the hospital, maybe we schedule a phone call. Maybe we schedule a fast response team to go out to the home and say, “Listen, let's get you stabilized here a week in advance.” Why? It's not as costly. Maybe they forgot to order their medication. Maybe they can't afford their medication. You solve their problem either through social determinants of health or medical problems that are out there. And you try to avoid that migration over into reactive care.
What challenges do health systems and health care providers, in general, face when implementing these remote patient monitoring for patients with chronic diseases? How can these challenges be better overcome?
Dicks: Yeah, I think engagement of the patient is probably number 1. From that, take the field of dreams, “If you build it, they will come.” That doesn't work in health care. People are going to engage how they want to engage. Solutions that you put together can't be 1 solution fits all. [It has] to be; that's part of the piece. Personalization has to be part of it. And [somebody has] to be willing to engage in their own care on their own terms to try to get proper engagement and outcomes. And the health systems don't have a lot of time to try to go out and make sure that Kent has taken his 16 days with the readings so that they can get reimbursed to do that. Or that the patient takes their readings so they don't readmit and impact value-based initiatives or their quality scores. I think engagements [are] number 1.
It used to be cost was the issue, but the cost of technology and solutions have come down so much that you don't even think about, as a remote patient monitoring (RPM) company, to go through and try to retrieve equipment and clean it up and send it back out to somebody else. You just let them keep it from that perspective, especially if you're dealing with people that are reoccurring illnesses like congestive heart failure, that they're going to be with congestive heart failure for years from that. And you want them monitoring themselves to try to avoid those readmissions that are out there. Cost used to be it, but it's not as big a barrier anymore.
The other thing that is facing health systems is we've been fortunate enough to be involved in the VA contract for monitoring veterans. The VA is currently monitoring between 70 000 and 80 000 veterans remotely. They have about 2500 care coordinators. But the number of veterans that are getting sicker by the day is in relationship to age. We're getting older. And the population of veterans getting older and sicker is escalating. The number of care coordinators is going down to be able to service. In fact, what's the statistic? We're going to lose 800 000 care coordinators and nurses by 2027 or 2028. Technology has to play a better role in trying to bridge the gap. You don't have the ability to just say we're not going to address the issue because people are getting sicker. I would say the loss of care coordinators is a big problem in technology. You can't have an RPM system that you just throw at a health system and go here, use it, and have your care coordinators monitor the patients. There may not be any care coordinators to do that. [You have] to try to think of, “How do I engage this larger population of patients in a virtual-first presence without engaging any type of humans at the beginning?”
How can AI and machine learning be better utilized to personalize value-based care for patients, and what role does patient data play in this process?
Dicks: It’s a great question. One of the things I get on a regular basis is, “Why now? We’ve been trying this for like 20 years. And, why all of a sudden is this becoming incredibly important now?” We're getting older. We're losing care coordinators. That's one thing we already addressed. But if you look at any major inflection point through history, that has caused an invention to be able to spin off trillion-dollar industries that are out there, or trillion dollars worth of industries. Like when we had the personal computer, it spun off all these companies for financial services and gaming and everything else with it. And when we moved to smartphones, it caused Uber and Uber Eats and financial services and everything else to kind of spur from smartphones. What is [the] catalyst now that's really driving us? That is AI.
You can see what AI has done since 2022. It is exponentially growing from that and solving problems within minutes now instead of within years. I mean, Google announced that it had invented the Willow chip for quantum computing and it's 1 septillion faster than any chip on the marketplace, which means instead of us having to go through cancer profiles and models that could take literally thousands of years of computing time, hundreds of thousands of years of computing time, could basically be done in a matter of minutes. Microsoft just announced that they have found the ability to do quantum computing incredibly faster with their chip sets from that as well. The thought of implementing Star Trek holodeck, the tricorders, and having the ability to go through and do rapid analyzation within the patient, within minutes in their presence; it's now possible to do. That used to be all just nonsense in fiction, but it's not. We're now moving care much, much closer to the patient, and AI and quantum computing is going to play that role. And from my standpoint, I would say, okay, something new came out this week, this month, okay, we'll be in commercialization probably within the next 4 or 5 years from that. No, this stuff is coming out exponentially within months.
What are some of the more practical ways that health systems and providers can apply some of these insights?
Dicks: My biggest thing that I talk about is that it really started changing around 2020 when COVID made its introduction to us and everybody started getting used to telehealth. Telehealth, before COVID, started was probably an adoption of 10% or 15% of people. During COVID, it went up to like 70% because that's the only way you could see your doctor. But then it came down to around 40% of people were using telehealth. And part of it was doctors were still trying to figure out how to use electronic health records, they're trying to figure out how to monetize telehealth. I think telehealth is going to play an important role in how people connect to their doctors.
I know I just had this conversation not 20 minutes ago where I sit in front of 3 big screens and I hate to give out my history, but 6 of my friends are in the same place. They don't have general practitioners (GPs). They don't have a regular doctor anymore because the regular doctors have either gone concierge or they're making you come back and come in for an exam, come in for a test, come in for your results, because that's how they're paid. We tend to keep our specialists from that as well. But giving the choices to patients of how they want to engage in their care is a big choice. Remember, the marketplace nowadays is who makes the decisions on [how] health care is administered and spent. [Those decisions are made by] the payer and the customer. Less and less is about the provider from that. All these avenues like telehealth, the teledocs of the world [are] coming into a health system and taking patients, mainly patients that have the ability to pay. It used to be I would just go to a doctor that was probably associated to a health system and they're like a mile or 2 away potentially, unless it's a specialist. Now, teledoc systems come in and you can be virtually behind these 3 screens and you can be anywhere in the country or world. And now that health system has lost me as a consumer unless I enter their hospital. Each one of those health systems has to go out and start building a platform and a bridge out into the communities to be able to attract more patients and to be able to generate revenue from that as well.
But on the same token, we are actively moving from, and should be moving from, building billion-dollar complexes for hospital systems and building more small regional centers that are in community-based care that are hyper-virtualized out into the home to try to move care as close to the patient as possible. This technology is going to allow those health systems to be able to go through and build those connections directly from where they're at into the community itself.
One more thing, I do believe that in the next probably 5 to 8 years—it may be accelerated now with this new administration—but in the next 5 or 8 years, you're going to see probably only 12 to 15 large major health systems throughout the US that have merged or rolled up other systems within them. They'll all be payers. They will all have their own global purchasing organization. They'll all have their own form of meeting community-based care. And most likely, they're going to receive a significant amount of funding distributed from the federal government on taking care of people within those communities that they serve, right from that. And that could be the start of where a single payer comes into this all.
Is there anything that we didn't touch on that you'd like to address? Are there any follow-up notes that you’d like to leave with the audience?
Dicks: The only thing I'll mention is that I'm incredibly passionate about 2 areas. One of them is, as I said before, that we're very, very fortunate to be part of the VA innovation and working with our veterans. And we know that we've got to go from monitoring 70 or 80 000 veterans out of 18 million in the US to 10 to 20 times more than that, especially with us losing care coordinators. And we've got to be able to bundle that not only with chronic care management but also behavioral health and other things too. We're very, very fortunate to be able to work with partners that can help not only get away from just sending out devices to people, but try to come upstream and use voice biomarkers and facial acquisition of data to try to get a light amount of data to be able to get early indications if we need to intervene with somebody without shipping all this stuff out. [To] use the camera and the microphone on a device.
The other thing is we're super proud to be part of the relationship with Microsoft; Microsoft Cloud for Healthcare and Fabric. There's a big problem that health systems have when they're trying to connect into the community and to the patient's home is that they're approached by hundreds, if not thousands of vendors, that each need to go through integrations and onboarding and security and contracting and everything else with it. We're trying to solve that interoperability problem in being one connection point into Microsoft Fabric, which connects into thousands of their health systems to deliver data into the EMR and EHR on the backend, without them having to go through all those connection points. [This] allows them to get the data when they need it cost-effectively [and] to do their work as a clinician instead of being a technician.
