Transcript
0:12 Welcome back to the Stanford Healthcare AI podcast. We are thrilled to be joined by friend Eric Larson who is president at Towerbrook Adviserss venture partner at Thrive Capital, venture partner at SignalFire. He is an investor in us at qualified health as well. and really just a healthcare visionary working for 25 years being president of the advisory board and being known by many as whisperer to what is coming next in healthcare. So welcome Eric.
0:42 >> Justin it's an honor to be here with you and Matt. I obviously the world of you both and proud investor and qualified rocket ship. You guys are doing amazing stuff. So honor to be part of the pod. >> appreciate it. well there are way too many topics to discuss and even as our just pre precon conversation recording live there there's too much to go on but we have to start with maybe the most publicized recent paper on you know autonomous AI exceeding physicians that Zeke Emanuel Neil Kosa Venode Kosla wrote just a few weeks back. I I'll pull up the headline here, but Matt, as the practicing physician amongst the three of us, well, what's what's your take? Let's let's get us started.
1:30 >> I mean, so okay, so just for the audience, I'm I'm be unless you're under a rock, you've definitely heard about this paper, you've at least heard a take on it. And this is just sort of the the kind of the culmination of some I would say maybe cherrypicked to be slightly provocative, but but in terms of the the evidence that they kind of brought to bear for this, you know, largely opinion piece, but grounded in some reality. And I think we've seen some of these trends.
1:51 We've talked about some of them and they include things like when you have these AI versus physician kind of papers and then you do AI plus physician and you look at these different tasks that they ask you know folks to do in these academic papers. We keep finding that AI plus physician is actually at worse than just the AI alone which often beats you know physicians. And so it but but the conclusion that they're kind of taking this logically towards is you know should we just let AI autonomously deliver care? And you know which again very provocative. It's caused tons of hot takes and reactions. I I think of all the different reactions I've read I align probably closest with Bob Walter's response and he he wrote a really nice substack on this and he kind of called it the doorman problem. The point is is that if you narrow things down to a task, and this has happened to us in radiology since the beginning, it can beat me on looking for pneumonia.
2:46 That's like 1% of what I do, right? And I think it's the comprehensive collection of tasks that we're still not putting our finger on in terms of a benchmark. Now, the but the better question, I think, to ask is not do we just throw AI out there and have it take care of all patients. It's more how do we need to reinvent the practice of medicine so that we get the benefits of what this can deliver in terms of access to care, better knowledge, better you know prescriptions, better better care, you know, surgical decisions, whatever those things are, but then also allow us to cover the rest of the task that that we do. And and I would also argue that when you follow someone around, I think Graham Graham had a really nice talk about this. If you follow someone around in the given day, you're within within five minutes in a clinic, you're going to be like, "Oh, wait. Okay, we're going to need a lot more advancements, a lot more capability to to to do the 19 things I just saw you do in the last 5 minutes." And so, like, it's a balance to me. And I and I don't know the answer. We've been talking a lot about administrative tasks being the place to to to really focus and freeing up positions, but I'm not sure that's necessarily the right approach either.
3:56 So, I'm curious to hear what you guys think. But to me it's like there is a yes I would argue that any benchmark you can create you can hill climb and you can certainly beat humans on. The question is are these benchmarks reflective of reality to the extent that they need to be to to to draw these conclusions? And I just don't know yet. I I'm just not convinced yet on the benchmarks. >> Well maybe Justin I'll pile on. I mean I'm not a clinician so I proceed with a ton of humility here on the topic. But I do this article, this opinion piece really resonated with me and obviously we're we you know we we think the world of Venode and and Neil and Zeke we do a lot with them. I I will say that Venode has been probably the most clairvoyant technologist of the last 75 years maybe with the exception of Ray Curtzswhile in terms of his predictions him him being super vindicated in his predictions and in 20 I think it was 2016 he wrote Dr. algorithm or the 20% doctor and you know and and that was a really inflammatory piece. even though I it I I think it was it's going to prove to be totally prophetic. but but everybody sort of rose up in arms and I've noticed the node over the last few years get a lot more sort of like diplomatic and calibrated that that you know that the doctor algorithm was pretty pretty incendiary, pretty flamethrowing. now you know I think this is a really measured piece that is a metaanalysis of a lot of other industries too basically suggesting that you know in in these five cognitive domains for a clinician you know the AI is demonstrabably superior and more accurate has more fidelity to ground truth but the bigger intuition is that it's kind of this you know Gary Kasparov 1997 deep blue getting defeated and that was sort of this big epistemic kind of like shock wave. And then you know you you had this period I think the last time a human beat one of the real premier chess models was in whatever the 2000 mid 2000s. Then you had this period from 2005 to 2012 where this centaur idea and Gary Kasparov actually wrote a book about human machine sort of optimization and from 2005 2012 human plus machine was ascendant but then after 2012 the machines beat everybody and what Venode and Neil and Zeke are saying in this is that superimposing human judgment on top of a functionally verifiable domain actually degrades the accuracy of the AI and everybody's freaking out and they're they're finding all sorts of methodological flaws in the study and you know and and Matt your your commentary on it is super principled and measured but a lot of you know a lot of the online stuff has been pretty ad homum and and kind of stuff >> and and I think you know there's a real meta intuition in this which I subscribe to which is if you look at the trajectory of the cognitive ability of the AI in every epistemic domain starting with areas of functional verifiability then going to codability then things you can decontextualize you know one of our refuges used to be tribal knowledge or you know embodied knowledge or tacet knowledge but it turns out I mean Eric Boffson just wrote this amazing study your colleagues at Stanford your colleague at Stanford that a lot of the a lot of the tacet knowledge is now discoverable or learnerable learnable he uses autonomous driving as an example. So I guess where I land is I mean go ahead and find methodological flaws in this perspective piece. Go ahead and like rage against the dying of the light. But the fact is I I think we're going to see the prestige professions systematically dislocated by this everinccreasing synthetic Jupiter brain. And the implications for medicine are huge because our entire our entire organization of our $6 trillion industry has been predicated on scarcity. Scarcity of cognition, scarcity of it takes 12 years to train radiologists and therefore you can't, you know, there's no elasticities of supply. I think what Venode and Zeke and Neil are pointing to is that humanity get ready. like you are not the apex predator and and I think the implications for medicine are very good if we can steward this transition and you know and compensate these self-sacrificial physicians who spent 12 years of their life and incurred $250,000 in in academic debt. So anyway, that's my take on this. I I loved the piece. I thought it was really profound.
8:57 >> Well, I just real quick to react that before Justin you jump in. I I will say like I think that what I'm talking about is is we're falling into this we're talking about one thing in an exponential and any discussion around an exponential to me is is is hard right and I think you're much more >> looking at okay the trajectory is the slope is much more important than the snapshot right on the ground and I think it again we were I was talking to someone about this yesterday I'm a little worried we're not thinking delusional enough like even this piece to me isn't delusional enough and the reason I say that it feels to me like I did public health degree and you know one of the things we learned about exponential spread the co thing is such a beautiful example in some ways it feels like we're in that stage where remember when we were like hey if we don't let that cruise ship of co people dock we'll stop co from spreading in the US we so let's not let them dock or let's let's ground some flights and but but we already knew the exponential it was already gone like we already lost the the >> the are not >> right so like to me it's like I feel like we're having some of these debates and again they're they're useful to have and and everywhere every corner of medicine but at the same time that it's the slope that we're I'm missing and you're and you're you're looking at that as saying guys it's already it's already decided almost right you know so like we have to start reorganizing society how we think about every institution but certainly healthcare is right smack in the center of that because it it's tomorrow then the next day then the next day we're we're progressing ing at a rate that the current discussion isn't going to capture.
10:33 >> You're you're saying something really important and Justin, sorry, Matt and I are monologuing. I'm going to say something really quickly and then shut shut up. You know, Elton Morris and who was this MIT sort of, you know, luminary professor wrote this amazing piece in 1955 called Man Machines in modern times. So you can tell little anacronistic in the title, but man, machines in modern times. And what he said was that when a society is confronted with a new radical technology, it reacts in a pretty predictable formulaic way. First, it ignores it. Then, it seeks to rationally rebut it. If that fails, it mocks it and uses ad homonyms to make fun of the champions. And then only when a leader of sufficient moral authority and energy comes in and and rides in over the top does does the adaptation happen. And and I think you're going to see this with law, consulting, finance, and medicine where the guild, which is at the absolute top of the hierarchy, both in compensation and societal prestige, you know, is seeing its primacy threatened and it's going to react in this very formulaic way. And I just saw the full spectrum of this. I saw I saw people some people ignoring it, although we're past that. I saw the rational rebuttal sometimes sometimes really intellectually rigorous but mostly just like you know oh they they cited the wrong study or they didn't include a methodology section. I mean give me a break. Sorry. Are we allowed to curse on your pod?
12:11 >> and and and you know and then and then the third is mocking them. Oh this is a multi-billionaire you know and his and and his son has a company cure like they're doing the ad homonyms. you will see the guilds respond with vigor. Now, it was really smart to bring Zeke into this cuz Zeke has such credibility and you know and combination of Venode and Zeke and Neil is pretty formidable. I just think look this I'm glad this has incited this level of conversation but the to me the irreducible big thing is we have deified our intellect and that is the top of the hierarchy that that that's that's the thing that we kind of worship in a secular society suddenly we've speciated something that not just rivals but in some emerging domains and venode and others point to the five cognitive functions we're not as Good. What do we do in this world? What do we do economically? What do we do sociologically? What do we do theologically? I mean, and you know the if you if you remove scarcity, what happens to the profession? Well, it demonetizes. The more you produce of something, the cheaper it becomes. Well, the more you produce of cognition and and expertise, the cheaper it becomes.
13:31 And that's great. And you guys, you know, have been kind and listen to some of my pods. You know, when I did the pod with Dario Amade, I asked him, I like, look, there's 23.8 8 million Americans employed in healthcare and you're talking about 50% entry-level job dislocation and 10 to 20% unemployment. What is your resolution here? And he's like, I don't know. I'm thinking about the patient. >> Great answer. So, so actually in this I think my job actually on on this show with this audience is to just provoke you both and get out of the way where whereas again it's it's to find a group that is both knows healthcare and respect and understands the industry with you both and are both more AI pill than myself. and so let me push let me push you both let me push you both on on a on a few of these which is >> one I think and just to respond quickly I totally agree. I'm very happy we're having this discussion now. And it was great to have and I've had this discussion actually at a conference almost a year ago was pushing Zeke and we were trying to come up with a bet of no no like look this AI thing is real patients getting empowered in this way and he was actually pushing me on well okay Justin what is the bet we could make. I think he wanted to bet a chocolate bar or something like that. So high high stakes for what we would measure to show that it is better to show that patient outcomes are better to show that cost one talent to show something and I I I struggled with that to be candid a year ago. It seems like he has evolved quite a bit in his thinking in the power of these tools and where we're coming from this. and so it's useful to have the discussion now and to push all of ourselves to push ourselves on the employment discussions to push ourselves on the profession to push ourselves on the compensation and cost. But what are we not yet pushing ourselves on enough yet? Matt and Eric to to you both and you know I'll bring up Eric you wrote this piece on you know feel I'm gonna make a funny state almost feels outdated at the moment which I'm pushing you out of like what like two months ago you know we're talking about everything coming out on this piece and just it's just the pace of how fast things are moving and I know you're already you know writing writing something else but you wrote about this idea of healthcare's Oenheimer moment. What do we need to educate people on? Where is this going?
15:48 You know, Matt, I know you're working on something big at the moment to talk about, you know, what what does the future of the academic medical center look like? These pieces like what do we need to push ourselves on? And it's fun. Like my job now is to push you both to be unfiltered, be unfiltered with where you think things are going. And I'll say what's so hard about this is every day one of my jobs as I'm running qualified health is to have discussions with health system leaders and to describe where we're going. But one of the things I struggle with is if I go too far then I lose people. M >> if I go too far into the future for what's happening then I lose people on not maybe the person I'm speaking with will be ready there and be ready to move but they won't be able to convince their organization that this is the time to make the investment to run to move at this pace.
16:37 and so with that as background and context like to you both like what are the things where you're really pushing forward? Let's let's like really go out there because again you both are some of the people I respect most knowing healthcare and seeing where things are going, but let's push each other like where is this really going? What are the messages you really want to get out to these leaders for for what's coming? >> Yeah. Matt, you want to start? well, I mean, listen, I I think there's a there's a lot to unpack from what you said, Jess, cuz I think that going back to what we had just talked about, there's like the reality again, there's some percentage of the forecasting that is going to sound delusional because that's what you have to do in this and that's kind of been my my thesis here.
17:19 But at the same time, right now, as it stands today, are our systems able to truly take advantage of the capabilities or not? And like I think you're seeing some of this in the broader market in the less regulated the less high-risisk industries where you know a a a small company with seven people who are adept at leveraging the tools to achieve business outcomes are running circles around the large incumbents. The best example that we can point to recently is the cursor story, right? Like Microsoft in 2024 had the open AI IP, they had GitHub, and they had the leading IDE in the world, like globally.
18:02 >> You would be insane to try to go up against that combination of things and say, I'm going to build a a coding harness for a for for a model that someone else owns the IP of that's competing with me, and I'm gonna still win in the market. Like it's insane to think about, but yet that's not how it played out, right? Like the team was focused on their use case. They were leveraging the technology at every step of the way. They didn't have any legacy things to bring along with it. And they were able to execute in a way that's been obviously now shown to be quite quite preient. And so like how does that relate to healthcare? To me, we have constructed systems to Eric's point around the idea that knowledge is scarce, expertise is scarce, >> and the entire Academy was developed on that.
18:47 >> The way we teach people, the way we get evidence, the way we do peer review. And now we're in this environment where by the time the paper comes out, all the technology they were writing about is out of date. By the time I'm trying to implement something for a use case, there's a better version of the technology that is really hard to deal with in a somewhat oified structured system. >> It's a great point. >> What do you do now? Like do you need to do a instead of doing a codebased shift, do you just start fresh?
19:12 >> Yeah. And I think there's some people really doing some interesting things in that space. And Eric, I'd love to hear your point like your thoughts on this because it really is I think we're going to have to build in place build next to almost as opposed to trying to pour intelligence onto system that was exists today. >> Look, I I really resonate with what you said. I mean, I think about it as look this is, you know, you talked about the exponentials, right? This is the most exponential technology in the history of the world, right? and the obsolescence of like a framework or an idea and you know there's a lot in Oenheimer that was only released on June 15th that I repudiate and we should talk about that.
19:51 I mean you know and I'm trying I'm writing my new piece right now. I thought about you know writing like or amending Oenheimer like no forget it like this is just too going too fast. Now, I do think like Kurs is a great example in a $60 billion outcome and you know and I think that's illustrative of the insurgency right incumbents versus insurgents and there's no more you use the word oified there's no more oified like you know establishment than in healthcare I mean I think about like we have these sort of buildings in granite you know with the stone inscriptions above you know above the the entrance and you know and and you know the AMA has existed for a century and and the AHA is is similarly like you know you know deeply established and and you know I find it interesting that our most prestigious institutions like the Cleveland Clinic and the Mayo Clinic are also centinarians right that's an unnatural act in this in this sort of epic right where where you've got this Darwinian you know sort of evolutionary like competition and and so so what does the most established granite sector do when confronted with the most exponential high velocity tech in history? Well, I think you're starting to see it. I think you're seeing, you know, this sort of opposition. you're seeing this this you know this this resistance and and you know kind of this anseion regime clinging to its prerogatives and and and I don't mean to sound dismissive or disrespectful. I I I mean I feel I'm going to get the same disintermediation as everybody else, right? Like this is this is not externalizing. But to me the question Justin that you're asking really is the right one which is if the exponentials are true and if the trajectory continues unabated even if it slows down like how do we prepare what if medical expertise really does become free or moves asmmptoically toward the cost of compute right like if you think about you know what happens when the scarce resource becomes super abund abundant the organizations that were built to shepherd and stored and arbitrate and officiate this scarcity.
22:25 What happens to them? When you think about a hospital as an example, let alone a prestigious academic. You know, hospitals are a $1.7 trillion sector. They have over a trillion dollars in real estate. And the idea is you you get this geographically colllocated big you know sprawling you know in installation and you aggregate multiple specialists and you got the gastronurologist and the cardio metabolic specialists and the and the neuroscientists because you need them all colllocated because our reaction to complexity is hyper subsp specialcialization.
23:00 You know, we sort of look at the body through a straw because our beautiful biological brains can only encompass so much, you know, and and this is stylized and and and will be ridiculed methodologically, but in 1950 it took 50 years for the sum total of human medical knowledge to double. And by some estimates by 2019 was 73 days. You know, our reaction to cognitive overload is to draw smaller and smaller circles around what we know. Experts know more and more about less and less. So we create this multi-t trillion dollar bureaucracy and these edififices to bring the hype this the specialists together. Well, what happens at least in the cognitive domains? I'm not talking about optimists doing surgery or physical AI yet, but when that cognitive scarcity becomes cognitive abundance, do you need this multi-trillion dollar sort of industrial complex?
23:56 And especially I mean there's something really intrinsic about LLMs in the first instantiation, right? They sort of well they democratize expertise and and the purpose of a corporation is to take individual experts and aggregate them and coordinate them. But the LLMs are arming the rebels. They're arming the individual. I become a polymath with with my trusty, you know, super intelligence. I become a lawyer and a doctor and and and a and a consultant and and the experts can bemoone that and and it's a jagged frontier of intelligence and a jagged frontier of capability. So Perry Tao isn't getting disintermediated by this for math even though now all the airdose problems are falling by the week. I guess my point is that Justin the thing I want to think about is we spend 18% of our GDP on US healthcare. We spend $6 trillion. It's super inequitable. Our health system is great if you're rich, white, and urban.
24:54 It's not great if you're not in one of those privileged classes. What happens when medical expertise becomes free and democratized? Do the institutions that were built to guard and meter out and arbitrate the scarcity, do they continue to exist in their future, in their current forms? And I would say the answer is no. And how do we steward the transition in a thoughtful, compassionate way? That's what I'm thinking about. >> Well, well, because you both brought this up at the end, I want to push once more and then I know there's like a couple other papers and topics we could cover, but you talked about Eric just now, how do the institutions make the transition?
25:36 Matt, you talked about actually we have to build in parallel. And I guess like Eric, I want to push you on that. Can the current institutions >> make the transitions and if so what do they really have to do versus do you believe it's going to be the insurgent the cursors of the world who are going to make this make this leap >> I love it and that's right of course like and the cursor Microsoft example is is very analogous right I mean you know I I I thought Satcha was the CEO of his generation until January of 2025 when he was at Davos You can you can point the moment that he lost a trillion dollars in market cap. He's at Davos and Sam and Larry Ellison and Masa are in the Roosevelt room at the White House announcing Stargate and somebody at Davos interviews Satcha about this exploding capex and Satcha's like all I know is I'm good for my 80 billion.
26:37 Microsoft lost the race in that in that nancond. So cursor, you know, was he went against the empire, right? And and now is with the most formidable entrepreneur in the history of the world with Elon. The question is, can an incumbent self-disrupt? Can an incumbent move at the speed of an insurgent? when the insurgent is unencumbered with legacy systems with a lot of employment with having to do the change management versus just build like unencumbered you know healthcare is the most regulated latigious you know sort of incrementalist sector we have and actually as an investor I think about healthcare as that affords you a little bit of a head start to figure it out but you know incumbency is not some invariant law of nature incumbency is a head start what do do with it? And and what do you do with it in this like sacred intimate space of healthcare where if you move too fast, people die?
27:38 And and and that sounds dramatic, but it's actually quite true. I I I think if if if this weren't a global dynamic, the counterfactual would be what health system or pay or life sciences company or medtech company moves faster than its competitors. That's not the counterfactual. Counterfactual is what do you what do the authoritarian and monarchical regimes do? What are you going to see in Saudi Arabia and China? I mean, Chinua University opened its AI hospital. I'm actually going to give one of the keynotes for the DELMED opening and and you know I'm so intrigued by what we can do if you sort of start from first principles and ask the question what does AI permit us to do and if you don't have to sort of rehabilitate or reconstruct an existing organization you can you can build from scratch obviously you got to work within the regulatory regime I do think Matt That is right and you got to build in parallel and that's why you're starting to see a stratification. You know, Justin, you and I often, you know, we talk about this igopoly of of leaders, right? And the 150 CEOs that have this real sort of deterministic effect on how things play out. I am seeing a stratification. You are seeing a stratification. You're embedded with some of the real pioneering health systems. you're starting to see some of these players move ahead of their peers, but too infrequently do we have a conversation about where where are we going to be in the next several years if the exponentials continue and and that's why I'm so energized by the conversation we're having right now. I my my comments is it's like as I think about okay well listen is it and to your point there's there's a plenty of like asterisk on like just you know the reality of the regulation you mentioned that there's high risk low risk there's all kinds of different ways we could slice this but there is a hybrid you know analogy too to the cursor Microsoft which I think is probably the salesforce and very recently so again do I believe that that's the path maybe not right but like but this is like a middle ground where it's like okay I'm gonna accept the fact that most of the things that use software in the very near future are going to be agentic, right? So, we're already seeing that with the internet.
29:58 So, as a software incumbent who wants to at least maintain relevance in the exponential, I become headless and I basically invite, you know, the the barbarians at the gate all right on in, right? and and sort of like can I ride the exponential with my incumbency with my system of record and so like there's is a story here where you know because I guess what what you would say to this parallel idea is okay there's going to be an upstart ehr that's going to be a first principles health system that's going to be AI native and it's going to serve healthcare autonomously as often as it can and whatever it can that is a story that you could you could play out but I think the other version of this is does an epic or an Oracle or an existing incumbent sort come around to the concept of no longer are my users humans clicking buttons my users are going to be agentic so what is that what do I have to do to my stack to maintain the system of record you know incumbency while also delivering the value for the change to come and I don't know if any system of record is currently capable of that but that is another future for this right where again it's accepting the fact that the intelligence layer is going to be primarily operating with each other meaning agent to agent and agent to software to deliver X value and that and so what does that look like for healthare I don't know and the regulations boggle the mind >> but but the regulators are the the regulators are are are trying they're having the discussions they're inviting people to the table they typically right regulators work with the incumbents the regulators are reaching out to the insurgents to to Eric's analogies that he's using on his podcast, on his show.
31:40 And so the regulators are are moving and and so it's it is a very interesting dynamic. Eric, the one the one point I wanted to maybe disagree with slightly to your point is >> we need to have the exponential continue >> to get to this change. And that's where that's where I guess I'd like to just say like >> we are so far. >> It's a great point. We are so we could have a decade of implementing the current technology to its potential without anything improving whatsoever. A year ago we had more than enough >> to fundamentally change. We have way more than enough right now without any kind of >> Yes. Yes. And and the place to look to is just how a leading organization and I'll skip bringing up the slides, but a leading organization like an open AI anthropic or a cursor type startup is using tools versus the median versus healthcare. They are already orders of magnitude ahead on the current tools and growing. And so we don't need because I think the conversation having with leaders is oh we'll just wait it'll get better or we'll see how much it gets better then I'll figure this out. It's like, no, no, no, no, no. We already have more than enough today to be orders of magnitude ahead of where we are.
32:58 but maybe Eric, the last point, I know we've talked about a few different things and, you know, we have some positivity and, you know, maybe negativity of what's happening in the future. Eric, you brought up this point as we were getting ready on the cost >> side of healthare. And I want to pull up this paper just to make sure we can touch on it before before we end today >> of >> are we actually already doing better?
33:18 But I I'll pause here. jump into whatever you want to highlight. And then I know we have >> this paper everybody should read Cutler and Clarett. It's a Harvard paper. I think it's pre-perure review. It's still an archive. It this thing melted my brain. And the idea here is that you know I've been sort of promulgating this idea that that we can take 5 to 700 basis points off a percentage of US GDP allocated healthcare in just the next few years.
33:45 And I got I got like villainized for that, you know, and and you know, I'm I'm sort of making myself a little bit unpopular in some circles because I'm sort of saying the quiet thing out loud, which is we're a $6 trillion sector, of which 3.2 trillion is labor. You know, we employ 23.8 million people. One out of every six working adults is in healthcare. And you know, we we suffer from Bow's cost disease, right? productivity, you know, progress in manufacturing, industrials, even hospitality, things like that. Like, you know, that healthcare has to compete for labor. So, we don't enjoy the productivity bump, but we have to raise our compensation to keep people and as a result, we have to raise prices and healthcare has inexurably risen prices. And so I've been saying that you know if this is if this if AI is an industrialization of intelligence and you know just like we saved a lot of money going from branded drugs to generics or or inpatient to outpatient sight of care right this is taking scarce cognition and making it abundant and when you make something in abundant you demonetize it becomes cheaper right and so you know a lot of my extrapolations about how you take 5700 basis points were intuitions.
35:09 This paper says that we've already done it, right? And so the the paper basically says the CMS actuaries I'm going to go by memory you know in 2010 forecasted that by 2024 the US economy would consume would be would healthcare would consume 21.2% of the US GDP and represent about $6.3 trillion by 2024. The actual numbers came in 977 billion lower and 320 basis points lower. So instead of 21.2% we ended at 18%. And instead of 6.2 trillion we came in at 5.3 trillion almost a trillion discrepancy. And that over that period, that 14-year period, 2010 to 2014, 2010 to 2024, we saved $6.7 trillion that the CMS actuaries incorporating the projections of the ASA ACA predicted.
36:06 And in no 14-year period since we started tracking the data in 1960 have we seen this divergence. And relative to other OECD countries, we are actually inflecting a cost curve. And the authors with a lot of methodological rigor decompose that number and they they say technology accounted for something like 14% of it. And then sight of care shift and a healthier population and the pre-authorization and some of the the clawbacks from payers. It all sort of lomerated into this into this reduction. This is all preAI, right? I mean, and so my takeaway, Justin and Matt, is that we have a roadmap based on the most recent 14-year period for interceding and bending the cost curve. Now, there are some mitigating things. GLP1s are inflationary in the first instantiation, but they're going to be deflationary. You guys know I'm on the board of EMED. We, you know, we're about to publish some data that suggests that in a world of 10% medical inflation, employees that are on GLP1s that are adherent to it are actually seeing a 5% drop in their total health care costs.
37:29 So most technologies in healthcare when they're first introduced are inflationary, right? Because they address something that was previously unressed like a cabbage as an example. But eventually you're going to see more more cost-effective I mean a better example is total hip total knee right so for Medicare total hip total knee migration from inpatient to outpatient and other sight of care shifts in 2024 accounted for $94 billion in savings out of the 977 billion. And so I look at this study and I think this is a conceptual theoretical roadmap for how AI. So if you went from branded drugs to generics and that deflation and you went from inpatient to outpatient and that deflation I said this earlier what happens with cognition going from ab scarce to abundant. So anyway, I would encourage everybody, it's an 84page paper. It's kind of impenetrable.
38:29 Throw it into Claude, throw it into GPT56, or just read the damn thing because it is a seinal paper and I'm really shocked it's not gotten a broader readership and distribution. Look, if if if Darren Osamogloo can get a Nobel Prize for basically saying dumb stuff like AI is not going to affect productivity, I'm going to nominate these two for an economics you know Nobel Nobel Prize.
39:00 >> I I mean the best part about I think this story though honestly is that like it's the it's the repercussions of a relatively blunt instrument intervention, right? I mean, some major shifts, some major choices. And then like to your point about the GLPs that also was I mean, let's be honest, it 20year-old, 30-year-old drug, right, that we're so like there it seems like there's just so much alpha that we haven't even taken advantage of before you get into the discussion about what the techn is capable of doing today.
39:31 It's fascinating to me. And maybe there this does leave us on an optimistic trajectory that again Justin to your point the exponential stops today. Eric you know the the the current interventions are already bending the curve like maybe we do get to a place where some of the major issues about our health system as you pointed out the inequities of it are already on the right path. and and and so we can we have reason to leave this conversation super optimistic, right? And I think we're all we're all heading that direction.
40:02 >> With that, Eric, thank you so much for joining us. We could go on for hours and we we we do in other settings. So, thank you so much for being here. and we'll talk more soon. >> Thanks, gentlemen. >> Thank you.