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Our life's work is helping you protect yours. Copics, Medical Liability Insurance delivers more than just a standard policy. Our physician led leadership team supports and protects physicians a PPS and medical facilities with expertise developed from decades of experience, CME accredited education and 24/7 hotline support from a physician, C, o, p, i, c.com, we're Copic here for the humans of healthcare, here for you

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as physicians. We're meant to be lifelong learners. This is a really exciting time in healthcare, and we should all as physicians, shape how this technology is going to be deployed.

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We chart, a business and

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medicine podcast featuring lively and informative conversations with healthcare experts, opinion leaders and practicing physicians about the challenges facing doctors and medical practices. My name is Austin Luttrell. I'm the associate editor of medical economics, and I'd like to thank you for joining us today in today's episode, medical economics senior editor Richard Peyton sat down with our sat down with Dr David carmush, an internal medicine physician and Executive Vice President and Chief Medical and Commercial Officer at lomaris, a healthcare technology company, and a newly appointed Member of the HHS healthcare Advisory Committee. They're talking about the collision of two trends, putting enormous pressure on primary care, a growing patient population with more chronic disease and a shrinking physician workforce. Dr carmush explains how he thinks about AI's role in that context, not as a replacement for physicians, but as a way to make the right thing the easy thing. And the conversation also covers value based care's promise and his persistent execution problems. What AI enabled continuous care could look like for patients outside the exam room. And what do you tell a physician who's just dipping their toe? Dr carmush, thank you for joining us, and now let's get into the episode.

1:49
Thank you for joining us today.

1:50
Thanks Richard, thanks for having me.

1:52
And today we're going to discuss some issues around artificial intelligence, AI and primary care before we get into that. Can you introduce yourself briefly and discuss your education, training and experience?

2:05
Sure. Richard, so I'm an internal medicine physician, as you mentioned, I did my my training at the University of Alabama at Birmingham, was a chief resident, and was one of the rare chief residents from an academic medical center who choose to, chose to go into primary care after after my training, I was in a multi specialty group practice of about 110 physicians independently owned about half primary care, half specialty care. For the first 15 years of my career, and really the last 15 years of my career have been in management positions across a variety of companies, starting with being the Chief Medical Officer of Blue Cross, Blue Shield of Louisiana, which is my home state where I was hired after the Affordable Care Act was passed to help change the posture of the relationship between Blue Cross and providers to be from one that was kind of frankly adversarial to one that was more collaborative, and to pay for care outcomes that were important in a world where the insurance company was going to have to guarantee issue or or cover pre existing conditions. So really learned to like the business side and thinking at scale and and working in the boardroom and working across executive relationships to to really create value. Was fun for me, and it led me down a career that took me to Ochsner in New Orleans as an executive running primary care and urgent care operations and our value based care portfolio, our ACO, our clinically integrated network, and building payer relationships, payer partnerships and employer partnerships as part of that. Did that for seven years, and then had the good fortune to be able to take those 25 years of experiences and step out into a national scale and and led Walmart health for the last three years of its existence, trying to help Walmart see if it was possible for them to build community based primary care practices inside of WalMart super centers, to kind of marry grocery and pharmacy and clinical services in an environment where people lived and where they were multiple times in a given week, lots of learnings from that we could unpack, and then took all of that and came to lumaris about 18 months ago. Lumaris is a company that, for its history, has been an operator partner for health systems and medical groups to help them manage risk contracts across multiple payers, and they were interested in this new wave of AI and generative AI specifically, and we're curious if I would be interested in helping them think about how to responsibly and effectively harness the power of these technologies to to help in their business. And so for the last 18 months, I've been on a technology. Technology journey, but really using a broad background of primary care activities across payer and health system and retailer to kind of inform my advice to the company

5:16
to kind of start out with the technology one of the technology questions, though, there have been all kinds of, you know, studies, experiments, developments using AI and healthcare and other fields, for that matter. In your own words, how would you describe the current state of AI and its best uses for primary care?

5:34
Yeah. I mean, I think to answer that, or at least understand my answer to that, maybe 30 seconds of my perspective, and that is that we're kind of at a tipping point in this country where the needs for primary care are greater than they've ever been. With the demographics of the aging population, the burden of chronic disease, there's never been a greater need for primary care, and it's at a time where the workforce for primary care is disappearing, if you think about it, over the next decade. If there's going to be 85 to 90,002 few primary care physicians, and the population needs more primary care, something has got to give. And historically that, the way we've solved for that is with team based care, maybe adding non traditional or non physician, roles to the care team, nurse practitioner, PA, care coordinator, social worker. All of those human resources are expensive and they don't scale very well. And today, there's 100 million adult Americans that don't seem to have access to longitudinal primary care. So there's a problem that it's hard to see. You know the solution being a human capital solution only so. So it's within that context that I think the way that AI and technology should be supportive is first is to extend that human workforce to allow them to enable them to take care of more patients. Frankly, if you look at panel sizes of positions in primary care over the last decade, they've shrunk. Largely they've shrunk because we've added so many tasks to the primary care portfolio that they need time to do that. And so that comes at the expense of access. And so we need to change that so that humans could take care of more. And then the second is, we just need to make it easier to do a really good job at being a primary care physician. That means removing administrative burden, but it also means removing cognitive load and things that that consume energy of the provider that could be made easier with technology. And that's that's kind of how I see it. I think across all of my jobs whenever you know, the thing that's always kind of stayed in mind as a design principle when it comes to physician invasive change, whether that's through technology or otherwise, is just make the easy thing. Excuse me, just make the right thing the easy thing. So make it easy. Er, to be a primary care physician and use technology in that way. So not to replace human, the human, the really important human component to primary care, but leverage that technology to make that job actually easier than it is today. That's kind of how we're thinking

8:16
about

8:16
it. In your introduction, you talked about your experience with some value based care, and your company also works with technology in the shift from fee for service payment models to value based models of health care. And at the national level, could you talk a little bit about Medicare's current approach to value based care?

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Sure. I mean, so, so I think at the end of the day, Medicare probably has two main flavors of value based because they have lots of CMMI programs. But there's the two main ones are have been the ACO movements, the MSSP or ACO reach now ACO lead. And the second has been Medicare Advantage, or the commercial privatization of Medicare. And really, in those environments, Medicare Advantage providers frequently are looking to create value based care payment economics for their for their network. So it's a little bit more of an indirect a way of getting at it in both Kate in both cases, the goal is to get primary care doctors to be accountable for both economic outcomes and clinical outcomes and and I think that's a laudable goal. I think it is the right way to align the needs of clinicians and patients and purchasers, whether that's the federal government or or an employer. So I think the concept of value based care, you know, is a great one. It's I've spent a lot of my career in IT. I think the challenge with it has largely been how these programs have been structured, and in some ways, the focus for success has been through things like coding and documentation or risk adjustment. Or or curating a network using actuaries to kind of say, if we got these, if we took these providers out and left these in, the performance of the ACO would be greater. Those are things that are not really getting at the heart of making people live healthier lives and reducing the total cost of care. So for me, what my focus has been, I think the challenge for value based care, and the reason the challenge, I think value based care hasn't become the prevalent and predominant model, is that, number one, there's a cost to participate in it. There's a complexity. There's an investment in technology and informatics and analytics that has to be overcome through the economics of the program. And then secondly, most doctors would say, I'm being focused on things that aren't really the most important things that really you know, if I can, if I could focus on, if I can have time to focus on helping my patient stay healthy and stay out of the hospital and stay out of the emergency department and take their medications and control their chronic diseases. Those are the things that I want to focus on. But I'm being I'm being managed to care gaps and aw vs and risk and codes and so I so we're kind of heading down the right we kind of have the right idea, and I think the execution has largely just missed the mark a bit from through the eyes. If you would ask most primary care physicians, they'd say, that's the that's their challenge with value based care.

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How do you anticipate AI programs will affect value based care for primary care physicians and and patients in coming weeks and months and years?

11:38
Yeah, I gotta, I gotta say, I'm very bullish about the role that AI can play. It just if you think about it right, if you're fortunate to have an outstanding primary care physician, you probably spend two to maybe 420, to 30 minute periods of time with them every year, and that's if you have a really good one who's accessible to you. And yet, primary care is the net result of how you live your life every day, the foods you choose to eat, whether you choose to exercise, the habits you have as it relates to alcohol or smoking or vaping or other activities, whether or not you fill your medications, whether or not you monitor your own blood pressure or your blood sugar, all of these things are really important to your your health and for most of us, our primary care physicians, even the best ones, really their support for us stops the day we walk, the minute we walk out of their door, and we're kind of left to live our own lives between visits. And then periodically we come in for check ins. Those may involve laboratory data. It may, you know, vital signs. And then sometime with the clinician, that's a construct of a world where the delivery mechanism is largely a human one, and and the constraint therefore, is how many minutes do the humans who are conducting primary care have available to them? And so the the number of touches per patient, the number of patients are limited by that human constraint. Ai offers the opportunity to totally unlock that. It, you know, the way we've thought about it is that if AI starts with an understanding of your own data as a patient, so if the EHR data is available to AI, lab pharmacy data, HIE data, claims data, potentially, if that's available, consumer data, if that data is curated to give a digital view of you as an individual, and then that data and where you are in your healthcare journey is used as the starting point for AI to interact with you on behalf of your clinician. That's an amazing advance. It allows your clinician to oversee a care model that follows you outside of the exam room and is monitoring and sensing and supporting you, and then, frankly, alerting the clinician when you're off track, so that maybe instead of waiting a random six months to come back in, maybe you are someone who needs to come back in in four months because you're going off track. On the other hand, maybe you're someone who's doing great. You're fine, like you're compliant with your meds, your weights good, your blood pressures are great, and you wouldn't necessarily need to randomly come into my office just to sit down for me to confirm that, because I would already know that. So I think it starts to unleash this notion of healthcare being reactive and episodic and siloed, to being continuous and connected and proactive. And I think I think in their physicians get to spend their human time on the patients who need it the most. And patients get the value of the support of their clinician, wherever they are, at home, at work, on vacation, and it's it's just part of it's part of your life. I think that's the promise of this technology, if used wisely in primary. Here.

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Hey, there. Keith Reynolds here, and welcome to the p2 management minute in just 60 seconds, we deliver proven, real world tactics you can plug into your practice today, whether that means speeding up check in, lifting staff morale or nudging patient satisfaction north. No theory, no fluff, just the kind of guidance that fits between appointments and moves the needle before lunch. But the best ideas don't all come from our newsroom. They come from you got a clever workflow, hack, an employee engagement win, or a lesson learned the hard way. I want to feature it. Shoot me an email at kreynos at mjh life sciences.com with your topic, quick outline or even a smartphone clip, we'll handle the rest and get your insights in front of your peers nationwide. Let's make every minute count together. Thanks for watching, and I'll see you in the next p2 management minute

15:56
when you

16:01
mentioned about the patient panel size is actually going down because primary care physicians are becoming more responsible for more conditions. I'm oversimplifying that in my terminology, but I think the reality is that just from the outside looking in, it feels to me like primary care is, in a sense, becoming a fallback in the healthcare system to where we don't have enough endocrinologists to manage type one and type two diabetes, some of that's going to go back to primary care. That's one example, and I think there's probably more. Where I'm going with this is I want to expand maybe on your thoughts here from a moment ago, to get into some nuts and bolts with doctors and patients. As a physician, you have said successful technology must go beyond surface insights to orchestrate action between the care team and the receiver. I think you touched on that a moment ago. Kind of big picture. But can you describe or give an example of how that works, or what that looks like when the patient walks into the doctor's office and then, like you said, walks back out.

17:06
Yeah, so well, you packed a lot into that question for a non doctor. That's really smart. Let me, let me, I want to, I don't want to lose the first part of your question, which was this notion of the inner the intersection of the interface between primary care and subspecialty care. It's a two way street. In some cases, primary care has gotten so busy and the agenda of primary care is so busy per patient that the bar and threshold for referral out to a specialist has been lowered especially, and I think there's pretty good evidence that non physicians, especially ones who have not been in practice very long, nurse practitioners specifically, tend to refer more readily than their physician counterparts. Largely, that's because of maybe a lack of of of just experience or training. And so what has happened is that as primary care has gotten busy, they've also they've also sent more care into the specialty world, certainly within health systems. Maybe you could argue that's even incentivized or encouraged, but, but that's the reality. What has now happened is access is a problem. Ubiquitously, it's not just an access in primary care. Access to specialist is also a problem. We were talking to a health system recently who said 30% of all of their cardiology appointments for the next 12 months are booked for patients who have hypertension. Is the problem. So if you think about it, right, Hypertension is right in the wheelhouse of primary care. And I would say, you know, 90% maybe 95% of patients with hypertension should be well managed in a primary care practice. The fact that 30% of a health system cardiology appointments are filled with hypertension business is a challenge, right? That's not the best and greatest use of a cardiologist who trained an extra three or four years after his internal medicine, his or her internal medicine training. So, so, so they would like to repatriate some of that care back to primary care, but the primary care needs help. So what could that look like? Right? Well, that could look like aI interacting with you as a patient to review whether or not you've taken your meds regularly before a visit. It could also gather your blood pressure readings. It could have taught you how to take your blood pressure at home correctly, and then could have collected your readings. It could have aggregated that data, and it could have summarized all of that back to the physician to be right in front of him as he walks into the exam room to see you, right? So that instead of spending the first five minutes reviewing your blood pressure logs and all that's already done for the clinician, right, and they can get in to the management of your blood pressure. What if that? Ai also took what was known about you and bumped it up against the world's evidence of manage of hyper, management of hypertension, and. Provided evidence based guideline directed nudges for you, for that specific patient, with a click button to the evidence, if you wanted to see it to basically said for a patient like Richard on this drug, with this condition and this renal function and these comorbidities, the evidence would suggest he should be on this drug in addition, because His blood pressure is still above goal. And here's the evidence for that. That's the That's the promise of AI making an office visit more meaningful, preparing a patient for the and a clinician for that office visit to make the best use of the time, and then harnessing technology and being able to present that at the time where at the point of care, where an action needs to be taken to say, Hey, this is something you as a clinician should, should consider so, so I think you start to see when that happens. You can imagine a world where cardiology, where primary care doctors are managing heart failure, maybe they're managing chronic kidney disease, maybe they're managing type two diabetes at least, and the referrals to endocrinologists are far fewer. I think if all of us were using AI that way, we would still need specialists. But instead of them seeing five patients to justify the one that really needs their expertise, maybe they see two patients to see the one and so that wait times become lower. They're still full, but they're not crowded with patients that would have been managed well in primary care. I don't know if that answers your question sufficiently, but that's kind of how I see the problem of specialty care versus primary care, and how AI could could be part of the solution here?

21:42
No, I think that that is really an interesting angle. And again, one that I just haven't seen. Maybe I'm not coming across the right sources, but just haven't seen a lot in the professional or gray literature talking about that back and forth between

21:57
there isn't Richard. So I think

21:59
specialty care, that's fascinating, though, too.

22:02
So So one of our one of our partners is Walters Kluwer, up to date, has been a product that probably many of your, your listeners and readers have are familiar with. Before open evidence existed, it was probably the source that most clinicians went to across the world to create to seek information on the management of patients well, Walters a partner with us at lumaris now, and they've taken their curated evidence and they've vectorized it or made it available to be leveraged by an AI tool through an API to kind of say, Hey, we could assemble a question based on our understanding of a patient. We can assemble that digitally and automate asking Walters klur for evidence and for their best guidance based on what's knowable about this patient, and then that's happening in the background, and present that to a clinician at the point of care. Walters Kluwer was over the moon when they when we talked to them about this idea, because what they've said is that the holy grail of clinical decision support is to marry the clinical information of a patient with the evidence. And historically, the physicians have been called upon to translate those two things. They have a repository of information, and they're sitting in front of a patient, and it's been left to them to think, what are the facts about this patient that I need to push into this tool to get an answer to help me guide my treatment? Well, what if we could automate that? That's that cognitive burden that I think needs to be removed from primary care, and I think that we're on the cusp of being able to actually deliver that that's not being delivered in the United States today. And so it's not that you haven't read about it, that's a net new thing, and certainly excited to bring that to primary

23:53
care. One of the things that I'm curious about here is that we know technology, over time, tends to become more reasonably priced, frankly, and right now things are can be expensive, both from a software and hardware perspective. Can you talk a little bit about cost, both for the physicians who may be using some of the programs and then, and we know that smartphones are ubiquitous in our nation, of course, but there may be some other technology that's needed in the patient end, where does that come from? Who pays for it?

24:23
Great questions. Let's start at the patient level. I mean, I'm wearing an oura ring, you know, you may have an Apple Watch. I mean, people have devices. Those are not cheap, you know. And so there is a little bit of have and have nots today. From a technology standpoint, I do think that technology companies like ours, we need to build flexible architecture so that patients, over time, can bring their own devices to bear like I don't think that any product can be built where it mandates for you to be a user of the product you have to buy you. Specific technology. But the reality of it is, there's so there's very rich data in in in wearables or remote monitoring. The challenge generally has been that providers don't have the bandwidth or time to sift through the data and make good use of it. So it's kind of an interesting phenomenon. And if you're a driven patient, and I, you know, I'm very interested in my sleep, so aura is provides a feedback loop to me every morning on how I slept that night. And there's embedded within the application tips and tricks for better sleep. I don't need a clinician. I can self manage myself on that journey. And so it's a consumer tool. I choose whether it was important, I was willing to pay for it, and therefore I get value out of it. But for things like hypertension or diabetes or heart failure, where there's a monitoring capability that, frankly, to create value, needs to be connected to a provider who is able to prescribe medications theoretically or frequently as part of the management that loop is of interest to me, and I think there's two problems to solve. One is on the provider side, you've got to make that information very easy for me to digest and to consider in my treatment. And so AI is a great tool for analyzing large data sets, normalizing it, summarizing it, and presenting it to a clinician. So check the box there on the device side. Ai allows for kind of high or low tech versions of remote monitoring. High Tech would be connected device, maybe Bluetooth enabled or cellular device that ports information directly into an EHR, and so there's a data integration activity, and that's expensive to do. The device may have an expense to it, and that's unclear. Who should fund that and how that should get paid for. There's a low tech version of it, though, which is that you can buy an over the counter Omron blood pressure cuff for $39 and very high quality. And AI can just literally ask you to read me your last 10 blood pressures. There's no deep integration. It's just literally AI communicating with you through text or voice to say, give me your blood pressures. Richard, like over the last week, can you just read them all to me? Thank you, and I store them in memory and at the right time, summarize them and aggregate them for clinicians. So, so, you know, it's a complicated question. I think over time, devices will get less expensive on average. I think product builders will build flexible architectures that will kind of be bring your own device, and we'll figure out how to take inputs in. The most important thing is, how do we connect those device to a clinician? Because digital health tools, there's many of them out there. Most of them have failed to improve health outcomes because they're not closed. Loop back to a clinician who has the ability to prescribe or intensify medical therapy when your reading suggests that that's needed

28:05
new technology. We know that there are early adopters. There's always skeptics, and primary care physicians are some of the busiest ones out there. Maybe they just haven't had time to really make a deep dive into AI yet. What advice would you give to a doctor who still is just kind of dipping their toe in the pool, so to speak.

28:22
Yeah, I think that's okay. I think, I think healthcare has benefited from slow adoption at times. I mean, there's a safety reality. This is a new, powerful technology. To the degree we turn it loose on either clinicians or or patients, we should be thoughtful and careful, and it's okay that this is going to come in phases. I think early adopters are are necessary to test and help validate these tools. And I think laggards, you know, it sounds so negative, you know, sometimes just pragmatic, and are just needing to see that evidence before they before they invest too much time. So I think that dynamic is okay. What I don't think is okay is to be a clinician in today's world and to just bury your hand in the sand around AI and pretend that this is just going to be another failed promise technology that's going to make my you know, my world better. You know, I think that doctors, even the most skeptical ones, would benefit from reading about AI, reading in the medical literature, what they can. It's okay to be skeptical, but I think being skeptical without information and without understanding and learning is challenging. It's not hard to learn about AI. You can, you can cursorily, kind of read medical journals and start to see now lots around AI. You could also go deep. You could go to Microsoft or Google or AWS and go online and have free access to AI primers and start to understand that, I think many physis. Clinicians are using an AI tool open evidence, and so they're starting to be familiar. Many are being exposed to ambient listening technology that gets them away from being on the keyboard in the exam room and starts to transcribe them. So I think, I think clinicians are seeing AI show up in their world, hopefully in ways that are, are are positive. I think it's a different thing when we start inner kind of placing AI in between a physician and a clinician that we need to be thoughtful and careful and use, you know, good judgment and require proof points to be in the market before we just adopt that as kind of the new what new standard for primary care. So I think be interested, be curious, avail yourself of an opportunity to learn more, even if you draw a line between learning and implementation and practice. I don't think anyone should you know, as physicians, we're meant to be lifelong learners. This is a really exciting time in healthcare, and we should all, as physicians, shape how this technology is going to be deployed.

31:02
I'm Richard payer, chin reporting for medical economics. My guest today has been Dr David Carmouche, it's been a great conversation, and we could talk about AI and new technologies here for another couple hours. I hope we get a chance to catch up again sometime.

31:17
Yeah, I really enjoyed the conversation. I appreciate you giving me this forum to share some of my thinking. Thanks a lot.

31:22
Once again, that was Dr

31:29
David carmush, Executive Vice President and Chief Medical and Commercial Officer at Lou Maris speaking with medical economics senior editor Richard Perry on behalf of the whole medical economics and physicians practice teams. I'd like to thank you for listening to the show and ask that you please subscribe. So you don't miss the next episode. As always, be sure to check back on Monday and Thursday mornings for the latest conversations with experts, sharing strategies, stories and solutions for your practice. You can find us by searching off the chart, wherever you get your podcasts, and if you like the best stories that medical economics and physicians practice published delivered straight to your email six days of the week. Subscribe to our newsletters at medical economics.com and physicians practice.com off the chart, a business and medicine podcast is executive produced by Chris mazzolini and Keith Reynolds and produced by Austin Luttrell. Medical economics and physicians practice are both members of the mjh Life Sciences family. Thank

32:22
you.