Dr. Mark Hyman: Reimagining Healthcare with Artificial Intelligence

In this special edition of the Integrative Practitioner Podcast, Mark Hyman, MD, joins Integrative Practitioner Content Specialist Avery St. Onge for a live interview at the Integrative Healthcare Symposium to discuss how artificial intelligence and other emerging technologies will transform the practice of medicine.  

Find us at integrativepractitioner.com or e-mail us at [email protected].

Theme music: "Upbeat Party" by Scott Holmes via freemusicarchive.org and "Carefree" by Kevin Mcleod via incompetech.com.

Transcript

Avery St. Onge: Hello everyone and welcome to this special edition of the integrative practitioner podcast live from the Integrative Healthcare Symposium in New York City. I'm your host Avery St. Onge, integrative practitioners content specialist, and I'm joined by functional medicine expert in 15-time, New York Times bestselling author, Dr. Mark Hyman. Welcome Dr. Hyman

Mark Hyman, MD: Thanks for having me. 

St. Onge: So, I'm sure most people listening know who you are. But can you just start off by telling us a little bit about yourself and what you've been up to lately? 

Dr. Hyman: Well, I'm a physician, trained traditionally in family medicine. It was a real country doc for years and then worked at Canyon Ranch as the medical director really looking at how do we bring in functional medicine into clinical practices back in the 90s, ages ago, I had my own practice Ultra Wellness Center for 20 years, I started the Center for Functional Medicine at Cleveland Clinic where I'm Senior Advisor. And I'm a host of the Doctor's Farmacy Podcasts, top podcast. And most I'm most excited about my new venture which is a company I co-founded called function health designed to empower people with an AI copilot where they help by helping the access road lab data biosensors omics, everything will be in there your entire health hub. So, you'll have a very personalized predictive model for how to uplevel your health in a dynamic way over time.

St. Onge: Yeah, that's great. That's basically what we're going to be talking about today, you know, how technology is going to change the future of integrative healthcare. So, to begin, can you just tell me about the emerging technologies that you're seeing the most potential in for improving healthcare? 

Dr. Hyman: I mean, there's a convergence, a number of things that are happening in medicine and science, technology that are all making this moment possible. And think of it as the iPod moment in healthcare, where all the technologies can vary more than like, you know, we're something like Uber could happen. Yeah, which is a convergence of many technologies of payment, GPS, and so forth.

And what's happening is this sort of really merging understanding the body as a network as a system and the emergence of systems biology systems, medicine is a reimagination, of how the body is organized, and then how we need this as root causes, and how we can optimize health along the continuum from wellness to disease, or not just wait till there's symptoms or worse diseases. The second trend is, is the ability of us to get enormous amounts of data. From an omics perspective. So your genome, the metabolomic, microbiome, your podium, your epigenome and measure all these in real time, and low costs for the population to help inform them about what their personalized recommendations should be. We’re also having this era of quantified self: biosensors that are wearables, implantables, breathables, every kind of way of checking your biology in a way that's almost frictionless. That feeds data up into how you're doing real time that can predict for example, diseases, cancers COVID, long before they ever show up on a test.

And then we have the emergence of machine learning and AI, which is really only in this last year has emerged from the scientific academia where it's been sequestered. And now it's successful general public, and there's many medical applications, but being able to take you know, deep phenotyping of human biology through the systems biology and functional medicine lens through the omics revolution, quantified self-metrics, you're scraping all your EMR Dino, which is now possible through technology to basically get your entire health records from everywhere your imaging data, have that all synthesized by a machine learning AI in order to make sense of petabytes of data, and you just in your microbiome alone, there's 100,000 petabytes of data, it's an impossible amount of information for any one clinician to ever understand about a patient. And yet all the data is there, where we're basically like, just looking at very superficial things in order to try to understand what's happening in the body. And that's all changing at such a rapid pace, that I think it's going to transform healthcare and medicine. 

So, we also are seeing an era where people are wanting to be more empowered around their own health and not just rely on the healthcare system, or doctors to be the gatekeepers for understanding their biology. So, for example, until very recently, you had to go to the doctor if you wanted to get your lab work done. And then you had to try to convince them to do labs that they may not want to do we're not understand or haven't learned about it. And the costs are often extremely high because of the reimbursement system in healthcare and the way things get marked up, and it's like you can buy it, Toyota Camry, pretty much the same price on every lot in America. But imagine if that was $20 on one line, and 100,000 was on another lot. And that's kind of how healthcare pricing is. So we've managed to figure out how to get testing at scale through a network of quest laboratories and other luxury of using to get get people's biomarkers on a regular schedule for less than $500 a year, and then have a deep understanding of what's going on, all the insights from all the other data are going to be embedded in that. And the help will be really like your AI health copilot that will guide you in your life over time and be able to intersect with your healthcare providers. 

Ultimately, this this technology will allow us to understand medicine, a totally new way to make discoveries in ways we never have understood before, to see things we've never seen. And to allow both people to be empowered around their own health but also to empower healthcare providers and physicians to have an AI copilot as well, because anyone physician has seen just a limited number of patients, you know, if you're a dermatologist, have you seen billions of skin lesions? No, you've seen 1000s and 1000s. But not billions, but an AI? No would you rather have your skin lesions read by AI assistants this technology or your or your retina or your imaging and already we're seeing the you know, imaging space being taken over by AI, which was a much better job than traditional radiologists or ophthalmologist or dermatologists. And so that's coming for chronic disease and internal medicine as well. And it's one of the most exciting moments. I think we're at watershed moment just like the discovery of the internet and development intranet. It's that moment in healthcare. Right? 

St. Onge: Yeah, yeah, I can see how this new health care, you know, allows us to look at the body in in all of the different systems and see it as a whole. And that's kind of going towards the integrative medicine, philosophy. But I can also see how, you know, as we learn more about these diseases, this technology could encourage a lot of drug development and pharmaceuticals, I can see it going in that direction, too. So, where do you see integrative medicine? And this new technology intersecting?

Dr. Hyman: I mean, you know, I think, you know, maybe we sort of back up and sort of define what integrative functional alternative has, because I think it's a little confusing, I think, you know, integrative medicine was emerged as a really wonderful attempt to bring viable alternative therapies into traditional medicine practice and integrate them into the care. So for example, if you are pregnant, and you're having morning sickness, you can use acupuncture, right, or if you are having, you know, high levels of stress, you can use biofeedback, if you have certain health issues, and my respond better than traditional Chinese medicine, and these are great to integrate into healthcare. But it's not a fundamental paradigm shift. And functional medicine is really a meta view, an operating system, if you will, a way of thinking rather than a specialty or a test or a supplement. Functional Medicine is just is a methodology of thinking it's an operating system for navigating the landscape of disease, as we now understand it from the perspective of systems biology, and integrative medicine are that some of the tools, right, we may recommend the right medicine for someone might be acupuncture for a particular problem for them, I have back issues and add disk issues. And acupuncture is profoundly effective in pain relief, and better than anything else I found. So I will use that rather than a drug. But if a drug works for something else, I might recommend that it's agnostic when it comes to the therapy. And it really tries to set or define what's the right medicine for each person based on a personalized assessment of their particular unique factors. And that's what what's sort of different about functional medicine. 

So, I don't see a distinction at all between sort of integrative functional, conventional, it's all one system. So, redefine it, really from a conceptual framework. And I think that's, that's what's happening. So I think all the tools of technology AI, will, will help in drug development, animal health and probiotic development will help in supplement development and understanding that the poly phenols and foods and their bioactive compounds will lead to research in silica instead of in vitro, we're going to use large datasets that come from all the data we're collecting from people now to create different kinds of research to uplevel our understanding of the human body so I don't, I don't really like to make the distinction. This is all just medicine. And we need to find the right medicine for each person for their particular issue, not having a one size fits all approach, which is what we do now. Right? 

St. Onge: Yeah, that makes sense. I guess my question was kind of more wondering if there's such a thing as too much data, you know, in technology, is there a point where we lose sight of the basics and kind of turn towards really specific things that aren't completely necessary? 

Dr. Hyman: That’s a good question. I think, you know, we we're in an era where we're, you know, we can't forget the fundamentals of creating health, right, while bringing our exercising, how we optimize our sleep, how we manage stress, how we build our social connections, our nutrient status, our toxic load, these are all things that we can modify that are that are pretty low hanging fruit. But what's happening is it we're going to really use data to customize our approach. So, there's, you might think that eating peach is a great thing, because it's nutrient dense, phytochemical rich fruit. But if you put on a continuous glucose monitor, and I do, I might find that that pitch is fine for me, you might find that at peach actually jacks, your blood sugar up and your insulin is not good for you. So, in a sense, we're using data to create real time feedback about what's optimized, what's optimized for us, for example, we can use data around genetics and exercise to understand what types of exercise would be better for you, or what types of diets would be better for you, or whether you're more carbohydrate intolerant, or whether you have problems with saturated fat. And so it's not like sad, your fat is bad, nobody should eat it. Well, no, some people do actually thrive on it, other people don't. Some will do much better on a higher carbohydrate diet, some people don't. So, it's really about understanding how to even take a low hanging fruit of lifestyle and optimize that. But I don't think there's too much data, I think, I think it's really important to to make a distinction between data and knowledge. 

What we have, for example, with self-driving cars is data driven. Ai, which just collects massive amounts of data and then navigates based on that data. It's very different than knowledge-based AI, knowledge-based AI is informed AI by experts. In other words, it's developing knowledge graphs that are informed by expert opinion, not just, you know, random amount of data. 

So, for example, if I asked AI to cure all chronic disease, the answer would probably be to kill everybody over 10 years old. That doesn't mean that's the way it works. Right? It's true. But it doesn't mean it's the right answer for humanity. So how do we bring in human intelligence and an expertise and understanding of the right operating system. So, for example, if you design an AI system that pay no attention to gravity, it would be hard to kind of, you know, design things that actually made sense for the world. So, the knowledge base that is really informing AI based on the laws of nature, I would say the laws of biology, and I think we haven't in medicine, come up with a coherent set of laws of biology. And I think we're, we're basically emerging into an era where now with this biology, we are beginning to understand that, and functional medicine has been for the last 30 years in tempted to kind of quantify and describe the fundamental laws of nature that explain all the phenomena we see. Right. So, all the observed phenomena in the physical world, can be explained by a few number of general laws here, the law said this, but it can then explain enormous number of phenomena.

Same thing in biology, biology makes physics look like, you know, kindergarten math, it's basically so complex, that it's hard for the human mind to grasp. There's so many things happening every second, there's 37 billion trillion chemical reactions in the body every second. So there's no way any one human being could understand or comprehend or under, look at those reactions and make sense of them and their correlations, their patterns and what they mean and how to use that in clinical medicine. None of that is really possible without the help of technology. So this will not replace the doctor will not replace the economist individual deciding on what they need for their own health, but it will ultimately fundamentally change the practice of medicine, healthcare, and in a way, drive it to the future. 

Right now, it takes so long for medicine to actually change. You know, it's 20 years between the current adoption of current science into practice. Even in traditional medicine, it takes 20 years and what we're talking about is a much more dynamic paradigm shift. Buckminster Fuller was a futurist, philosopher, and thinker. And he said, “you never change things by fighting the existing reality, to change something, build a new model that makes the existing model obsolete.” And I think that's what we're doing in function health. We're building a new model that makes the old one obsolete, for example, iTunes came out, and all of a sudden, they'll be making records or CDs. I remember when you know Steve Jobs took the CD ROM out of the my laptop computer, I was furious, like, What do you mean? How am I gonna play movies? How am I gonna play my CD? And you know, he was seeing the future. And now, you know, we have streaming video all the time, we have all our music with the touch of a button and every potential album you've ever had, you don't even have to have like, cassette tapes in boxes in cases like I had when I was a kid. So I think there are these this intermediate technologies and function health, I think is is the key one and healthcare today.

St. Onge: Yeah, and like you said, medicine is slow to catch up. I feel like a lot of people have been tracking their health for a long time with these technologies, at least with like steps and you know CGM, and things like that. I mean, those are more integrated with medicine. But can you tell me more about this AI copilot because at the same time, you know, people are tracking their health, but they're also the only ones analyzing that data. And you know, not everyone has access to a doctor that can analyze this data for them. So can you tell me about, you know, how an AI copilot could kind of bridge that gap a little bit. 

Dr. Hyman: What we're seeing already for example, is AI being much better at diagnosing disease than the top positions, they're seeing, you know, med Palmy, in the past national medical boards and getting 90% of the exam, you know, we're seeing currently today AI technology is outperforming traditional doctors. 

So, I don't think it should be let loose, you know, as a sort of independent robotic doctor, but I think I think what's going to happen is that is that individuals will get a model of what's going on with their health and biology in in time, and it'll be tracked over time through repeated inputs and analyses. And that will, that will give them a hierarchical order of the things that are offered imbalanced. And that will allow them to then take the insights gleaned from all the evidence-based literature in the world, because I'm, no matter how much I read, I can't read every scientific paper that was ever published. But I can do that in a few minutes, right. So all that's going to be ingested, it's going to be informed by expert opinion, is going to be informed by all the data, hard data as well that people are getting from their biology, so their actual blood work and their genotype and so forth. And that will create a hierarchical series of recommendations based on what likely probability of different issues are and what the likely recommendations are that are going to optimize their health, the diet, lifestyle, self care, and then what medical care they might need. 

So, we might say, Oh, gee, you have this lipid profile, because we're doing lipid protein Fractionation, which is less than 1% of all festival tests on the United States say, but it's the one that should be done. And we use that with the function health panel. And it identifies, you know, high levels of insulin metabolic risk and, and then, the question is, what should you do? Take a statin, which is what the typical, probably a cardiologist recommends, but it might say, no, no, why don't we try these lifestyle things and repeat in two months? Why don't we try, for example, these supplements and have evidence for them? And why don't we potentially get an AI assisted CT, coronary angiogram, to look at the soft plaque and flame pack or non-low density, non-calcified plaque, which is a much better predictor of your risk. 

I had a patient recently who had horrible cholesterol profiles, terrified he was going to have art attack, we did a heart scan with clearly health, which is basically this diagnostic technology using AI for looking at your angiogram, and his arteries are pretty clean. And he was 65 years old. So, I'm like, Well, no use, you have some genetic protection. And despite all these terrible lipid numbers, you don't need a bunch of drugs.

So, it's really creating that level of frustration. So that then, you know, the doctors who have achieved what should I do, and actually, the doctor will be able to say, here's, here's all this data that is given to the provider in a coherent way, that provides again, a hierarchical differential diagnosis, and a hierarchical set of interventions that can then be linked to a whole ecosystem of services that help patients change their behavior and lifestyle and understand everything. So I think that the it you know, people are going to be let loose with all this information is going to be highly, rigorously validated through scientific evidence, as well as expert opinion and their own data. And we call no one studies, you know that the highest level of evidence is what we call an n of one study, which is using yourself as your own control. 

So, let's say I'm going to eat vegan diet for 12 weeks to check on my body block bloodwork, and I'm going to eat a omnivore or carnivore diet for 12 weeks and check out my biology. Like that's the best way to actually see and those are not that's not low level of evidence or anecdotes. It's called no one research, the NIH is driving a lot of this effort. So I think I wouldn't be scared about just having all this information and being set loose and being lost and not knowing what to do, because it's going to be very, very much a co pilot for your health. Yeah. Yeah, I mean, as a co pilot, it's not the pilot, right? You and your healthcare provider, but it's the co pilot. This is hey, this check engine light is on Oh, boy, this, this engine is running a little lower fuel here. We didn't put the flaps down here like, right, you need to, you need to know what's going on. I think that's that's, to me, one of the most exciting things that's gonna emerge out of this convergence of technologies that I mentioned earlier.

St. Onge: Yeah, that's an important distinction. It's not the doctor itself. It's the copilot. Okay, so I think what a lot of people hear about these new technologies, they think this sounds really expensive. Do you see these technologies realistically reaching, you know, everyday people and maybe underserved people? How do you see that? 

Dr. Hyman: Absolutely. I mean, listen, for certain segments of the population, it's not accessible, right? But it's, you know, $499, a year for over 15,000 logs with the labs check twice annually, that provide a really deep insight into your biology. And, and that's about $1.39, or 37 cents a day, which is probably less than you spend in your coffee when you go to Starbucks. And so the question is, where do you allocate your funds? Where do you get your money? What's important? I mean, health is the most important wealth, in my view, and I think people are valuing that and they're spending trillions of dollars in the self-care, wellness space, it's a multi trillion-dollar industry. So, people are spending their dollars on it. But I do think ultimately, and I think the, the, you know, the wearable data that biosensors, you know, you're able to get this stuff, very low cost. Now you're able to get, for example, your whole genome sequence used to be, you know, I think a couple of billion dollars now to sequence at first, you know, now it's a few $100. So, we're going to be able to get enormous amounts of data at very low cost. I think insurers are going to start paying for this, I think self-insured, employers are going to start paying for this. So I think once we show the economic value, which is by people using function, health, by knowing their data by working with their, their own health, by working with their providers, they're going to be able to track their, their health outcomes over time and the cost outcomes over time. So we're able to see that not only do people feel better and do better and get better, but their healthcare costs go down.

So, then all the payment systems are going to start to change and all the ways in which we practice medicine are going to change. So I believe function health is going to be the the wedge that's going to transform healthcare, and healthcare reimbursement and drive it towards true health care system, not a secure system. Yeah. And do you see this technology, maybe even expanding access to health care? 100%? So, for example, right now, you know, I don't know, maybe there's been 100,000 people have gone through some level of IFM puncture medicine training, I don't know how many people have come to the Integrative Health symposium over the years, maybe 1015 20 30,000 people, right? But But imagine having this access to billions of people. Yeah, so now there's no one on the planet who can't access Google pretty much. Or can't, I mean, I've gone to little villages in the middle of the jungle or to the Maasai warriors, and they all have smartphones, right? They don't have electricity, that I'm running water, basically, they need a little solar power. They don't flush toilets, but they got smartphones. So almost anybody on planet can now access enormous amounts of these technologies at a very low cost. And, you know, I think we're gonna see the adoption of this at scale, because it's going to allow so many people to benefit from this.

I mean, I used to work in a small town in Idaho, and they were 3500 people, five family doctors, and we were in, you know, but imagine if I had the help of, you know, AI. And when I would get stuck, I would call the local specialists in Spokane, Washington, which was a few hours away, say, Hey, I got this new name. And this is happening, I don't know what to do, and they tell me what to do. And I would just do it, and we'll be fine. So I think we're going to be able to have, you know, people across the world who are not necessarily receiving the best education or don't have access to the resources, we have to be able to get in the know, literally push the button, all the information they need to make really valuable decisions to optimize the health of their patients and to really improve their knowledge base. And what are some creative ways you're seeing these technologies being used in practice? Already, like, what can practitioners do today? What this mill functionality is available right now. So, it's, it's in beta and there's a way less than 100,000 people we've had 25,000 People go through and 3 million data points so many people are actually using the insights that are generated from their lab data printing over the last year leading up to insights, bring it to their physician sharing with them and using We'd already started help stimulate the conversations. She my vitamin D is lower God, you know, my ama is high. Why is why missing, you know, we're seeing things that we never even realized were going on in the population like 30% of people have a high AMA, which means some level of autoimmunity. 46% have high CRP, which is inflammation is the driver of all chronic disease. You know, we're seeing 90 fibers and have abnormal lipids and 80 numbers and have small lipid particles and 67 years and have some nutrient deficiency at the minimum amount, like there's a lab reference range shows not what we would say as optimal. 

And so these this information is already helping people to use this with their physicians and make decisions. I think also we're seeing integration of AI in healthcare, whether it's through radiology or ophthalmology, or dermatology or AI assisted Doctor notes, and then there's, we have a medical scribe that's now AI that sits in your concert with you and can transcribe the visit and create a soap note and reduce the burden on healthcare. So there's a lot of ways that I think AI is already starting to be integrated. But But the challenge is, from my perspective, is, it's really the, the sort of problem of

not just doing the same things better, right? I can do the same kind of medicine better, and that will maybe reduce medical errors, improve adherence, maybe create some better outcomes, but it's not fundamentally different. So it's like rearranging the deck chairs on the Titanic, right? It's like, it's like, it's like using a, you know, a supercomputer to do basic math, right? And do algebra or basic addition, subtraction, we really needed to sort of use this technology to take advantage of the revolution in science, which is the revolution of network medicine, systems, medicine, functional medicine, whatever you want to call it, I don't care. You know, Leroy hood has the entity for Systems Biology, which is, you know, at the forefront of this work. And he's got a new nonprofit research organization called phenom health. That's really looking at scraping up the Phenom have tons of people. But you know, he's working on like, trying to get 2000 people, we already in nine months in function health have 25,000 people and 100,000 people waiting to get in the door. By being here, we might have already 200,000 people's data, and literally billions of data points and be able to track them, you know, so So I think this is happening already in medicine, right? It's just really how do we how do we accelerate the adoption? And how do we, how do we sort of get that leapfrog moment?

St. Onge: Yeah, my last question. A lot of people are resistant to AI. And I imagine a lot of people in healthcare are too. So, what do you say to those people who are hesitant to embrace this technology? 

Dr. Hyman: Well, you already are, if, if you have a smartphone, they're tracking you, every social media post you do every website, you go to every call you make basically, it knows what you're doing. And it's tracking all your data, and AI is guiding what algorithms determine what feed you see on your social media. So whether we like it or not, you're getting served up ads for you know, stuff that you've I mean, I'm like, wow, that's a great, I want those shoes, you know, like I think know, me, like they know what I'm going to like. 

And so, you know, it's already being used, and people are a little more cautious about their health data. But you know, you've got your banking data online, you use, you know, your, all your financial information. I mean, who goes to the bank anymore, right? He's my smartphone, my computer to log in pay bills, make transfers and access accounts. And so really very, very much are already using this. About we don't, we don't really think about it just sort of invisible and frictionless. But it's something that I think people will start to understand is a value to them. Will there already is adoption with people wanting to know about their biology, people want to have an aura ring or a whoop, or Fitbit or their Apple Watch. They're using AC beds, or they're trying to figure out how do I get more information about my health so I can feel better and do better. And I think that lab testing and the deep genomic analysis that we're doing with function is the next stage. 

And I think, you know, there will always be people resistant, you know, there's people who still want to read paper books. You know, I was one of those guys until, you know, I took a trip for a few months, and I was like, I'm not bringing six books with me my backpack and I got a Kindle. And it's like, wow, it changed everything. Right. So I think there's always resistance to things.But I think we're going to zoom past that. And we're gonna just jump right in. Yeah, I think we're already seeing that. Yeah. Well, those were all the questions I have for you. Dr. Hyman before I let you go. Do you have anything else you'd like to add? Yeah, I mean, I just think I think I'm so excited about this moment in healthcare because I think it holds a promise to really bring a new thinking out a new set of technologies a new paradigm into into accelerated adoption across all sectors of society and healthcare. I think function health is leading this whole new health ecosystem.

I think it's really reimagining healthcare as a time of not just going when you're sick, but as a place where you can be empowered to optimize and uplevel your health. And, and I think, you know, we're in this new era, like Buckminster Fuller said, of, you know, not fighting the old system, but just creating a whole new system that makes the old one obsolete, right.

St. Onge: Yeah. Well, thank you again, Dr. Hyman, for joining me today and enjoy the rest of the conference. 

Dr. Hyman: Thanks so much for having me.

St. Onge: Thanks for listening. We'd like to thank Scott Holmes, Kevin MacLeod and AudioCoffee for providing us with our theme songs. Be sure to visit our website integrative practitioner.com or send us an email at [email protected]. Remember to like and subscribe to our show. And stay tuned for more live podcast interviews in the next few weeks.

Editors Note: Transcripts are auto-generated