Episode Transcript
[00:00:00] Speaker A: Proactivemd.
From ProactiveMD this is Healthcare Explained. I'm Jeremy Vaynerknife.
[00:00:13] Speaker B: And I'm Vinay Patel.
[00:00:15] Speaker A: Well Vinay, we've managed to avoid this topic I think for the year and a half or so that we've been releasing these episodes. But I think it is the topic that is top of mind for everybody. It's unavoidable.
AI.
[00:00:30] Speaker B: Yes.
[00:00:31] Speaker A: What, what have you heard about AI? It's the, it's the buzzword across all sectors of our economy.
Nationally, globally.
Everybody's life has been touched by it. I mean what, Let me just ask you, where is AI impacting your life these days?
[00:00:50] Speaker B: I'll start by what I've red and it's, it's the AI apocalypse is soon to be upon us. We all will not be working and we'll have some kind of universal basic income from the machines all doing work to, to to over 500000 coding jobs have been let go or cut in the industry because they attributed to AI on the other side. I've read articles on how AI is more expensive the more you scale and it doesn't get cheaper as you scale. And no AI company is making money except for Nvidia and that the core math, the actual mathematics behind AI one it will always hallucinate because it's trying to predict the next word according to, according to the mathematical algorithm. And the algorithm is not complex enough to do sophisticated autonomous tasks. It can do simple autonomous tasks, but it will always make mistakes.
And so that's sort of the spectrum. And my personally I've seen how more and more clinicians around us are utilizing AI as a consult tool, asking questions and specifically trying on one group of clinicians asking for clinical evidence to support theories, assumptions, questions about patient cases.
And I've used it a little bit for research all the way to AI scribes and documenting notes and doing radiographic images and analyses. And so it's been all over the place. But I, but AI is coming for health care.
It needs to expand into there. There's a huge market share they'd be missing if they didn't get into it. I mean that sort of, that's sort of all the perspectives I've had on it. How about you Jeremy?
[00:02:57] Speaker A: You know I, there was a time in my life and a time in my career when I was an early adopter and over the years as I've gotten older and more and more of a crotchety old man, I think I'm less of an early adopter and I resisted For a while, the allure of AI tools, right? What can this do that I can't do myself?
But I will be honest with you, in a lot of my aspects of my professional life, I've started incorporating AI, whether it's helping me debug code faster for a data project or having AI scribes, AI note takers, be able to organize meeting notes faster than me needing to scroll through an entire transcript, or constantly trying to go back and forth between taking notes and paying attention to the folks I'm talking with. And you know, AI scribes, as you mentioned, is a, is a big area for healthcare for clinicians right now, where the, it felt like for many years the electronic medical record that they were using was a barrier between the patient and the provider. Right. It's that screen that's between them. And you know, I think it's. There's a lot of excitement right now around ways that I can reduce the administrative sides of health care, what feels like the endless stream of documentation. But I've never in my life seen a technology move and evolve as fast as what we're seeing today. And these companies, the big players like OpenAI and Anthropic and X AI, all trying to leapfrog each other.
So there's a lot of, a lot of considerations for what that means for health care. And yeah, you know, maybe it's worth diving into a couple of big announcements that came out as of the time of recording just a couple of weeks ago and those were around Open AI and Anthropic within about a week of each other, I think it was five days. You had OpenAI release or announce chat GPT for health and then you had Anthropic, makers of Claude, announce Claude for health care.
And it's not only is this huge news because these are the two probably most well known or most widely used large language models globally right now. You do have some other players in there, of course. You've got Grok with X, you've got Facebook's Meta AI, Google Gemini is another huge one.
But specifically these two that really have been kind of battling it out for a lot of supremacy both announcing these.
[00:05:30] Speaker B: New products and what I've seen from last year. And it's still around open evidence. I don't know if you've heard about that one that specifically built, it was specifically built by healthcare providers for healthcare, for healthcare to start. And it's really, it was used as an AI to get the basic clinical research or the clinical trials that have been published around clinical questions and Specifically documenting every single fact or note that it, it spits out in terms of a, what's the article is this, or what clinical trial is this linked to?
And that's been around for a while and I don't know where they stand in terms of size, but that, I.
[00:06:15] Speaker A: Mean, we're, we're at this interesting part where I don't think you can go five minutes without reading about a new AI startup. And Open Evidence is gaining a lot of traction because, and I think it, it speaks to what, you know, we can talk about with what OpenAI and anthropic are doing.
It is a recognition that healthcare, because of its regulatory environment, because of the ethics surrounding it, because of licensure issue, licensure issues, healthcare and medicine has to be treated differently than just, hey, let's just slap a large language model on top of a coding tool or a word processor, a spreadsheet.
Healthcare is unique. Healthcare is extremely complex. And if you get it wrong right, in some cases it can be life and death. And so let's talk for a minute about what the difference is between OpenAI's approach, Claude's approach, and then since you mentioned Open Evidence, I think that's a wonderful one to talk about as well. So OpenAI announced ChatGPT for health.
And what's interesting is all of these models are really trying to solve a couple of key problems in healthcare. And the number one problem is interoperability.
So despite interoperability having been supposedly a focus of regulation, and you had HIPAA and then the HITECH act and other acts that have come out from Congress to force interoperability, at the end of the day, we're still sending faxes to each other, right? That's still how a majority of documents get shared in the healthcare ecosystem. And so ChatGPT for Health is taking a patient centric approach. So the idea behind that product is going to be, as a patient, you are going to have access to a chatbot, a language model where you can feed it or give it access to your healthcare records. Maybe that's across different electronic medical record systems or portals, maybe it's other documents that you've got. And then you can use this natural language interface to ask questions that maybe previously you either couldn't ask or had to wait for an appointment or a callback to ask, for example, like, hey, is my cholesterol going up or down? Or what Was my lowest A1C last year?
Or when did I have that appointment about that rash?
So the idea is ChatGPT for health is going to be able to integrate your medical records, sit on top of that data that's all coming from different sources and then make it make sense for you as the patient. Right.
And that's different than what Anthropic's approach is with Cloud for healthcare, which is also about solving interoperability.
But you know, I, I say this as a user, both ChatGPT and Claude, ChatGPT for everyday tasks. Claude when I need a very well trained nerd by my side because if I'm doing a coding task, if I need help with debugging, you know, a SQL query or whatever the case is, I find Claude performs really well and I think that's kind of their niche in the market with Claude code and some of these other products. So Claude for Healthcare is about allowing healthcare developers, primarily healthcare developers, software companies, coders to be able to more quickly interface with different healthcare systems. So one of the key technologies that, if you've heard about fhir F H I R smart on FHIR is this interoperability layer that electronic medical records systems have and similar types of systems where it's these freely available APIs so ways to be able to connect in, to push and pull data out of those systems.
And you know, FHIR is based on the latest and greatest of HL7 standards. And so the idea is that these, these APIs, these access points into these software systems would be made so that, you know, you could rapidly develop, you know, you, whether you're working in athenahealth or Epic or you know, another system like Elation or Cerner, when you use a FHIR endpoint API endpoint for a patient record, you're going to get data that's returned as an object that's structured the same way. Right. It's kind of a universal global structure and that's the thought process. So Claude, you know, and Anthropic are saying, hey, Cloud for Healthcare is going to be able to get you to build applications on FHIR and interact with those endpoints much faster. So OpenAI consumer focus, right? Being able to ask questions about health. Claude and Anthropic taking more of a healthcare IT developer data interoperability standpoint, more at that software level. And then you mentioned Open Evidence and we actually at Proactive have begun piloting Open Evidence over the last few months because it's built with the clinician in mind. Right. So not just the healthcare company, not just the patient. What's the clinician need? Well, you talk to our clinicians, they need access to evidence based research that doesn't hallucinate. Right. Instead of having the old days of the physician desk reference sitting, 8,000 page books sitting on the desk to flip through for reference over time got replaced with online journals and Google. But this is a way to be able to have through a natural language interface get evidence based guidelines much faster from a limited curated data set of again evidence based articles. So unlike early days of Gemini of saying you should eat several rocks a day to maintain your health, it's not just pulling from random Reddit posts, but also with an AI scribe. So nobody likes documenting, nobody likes documenting, it's important to document. But having an AI scribe an ambient note taker in the exam room that's listening to the conversation and then creating a summary that then that provider, instead of having to write the whole summary or fill out templates, they get that all complete and then they just need to review it, make sure it's correct, make any edits they need to and publish. So it's about saving the provider time because as we all know, time is a precious resource for providers today.
[00:12:33] Speaker B: That's right.
Okay, so so many things to unpack there based on what's been announced.
And this isn't revolutionary in the sense that we have seen several companies iterations tackle some of these same issues.
Claude reminds me of Health Vault. I think it's Microsoft Health Vault. Keep all your information in one place, access it when you needed, just disappeared, went away, didn't, didn't work. Is this, it's just a question, is this going to be any different?
When are people going to feel comfortable telling their AI hey go ahead and access my patient portal and just have all my information.
You know, when Google was first created they said they wanted to harness or store the world's data and they've gotten pretty darn close at getting every single piece of data, especially with phones in our pockets now and they have access to so much and now is the next level AI sort of saying, well I'm this agnostic in the cloud storing of all your data and every single source of your of information to try to get you something, something personalized, relatable, something you can ask on on demand.
The, you know, sort of the dream of Apple intelligence. Which I don't know what happened with that either, but we're still waiting for that so that I can ask my phone, when's my next haircut?
And so, and so that's what Claude reminds me of. That and again, it's not, it's not new, it's not revolutionary in the Sense that the concept has been tried so many different times. Is it different this time? But are people going to be able to trust it enough to give it access to everything?
And then on the back end, you know, again, the Apple Watch or Android and Apple created these health modules, apps so that developers could easily track healthcare data. And then it was supposed to connect to a provider, connect all your healthcare information on the back end, help insurance companies and the healthcare middlemen that exist in plethora, and help your provider get access to more data. And that's really tough. It's really, you know, getting access to all that information is still very clunky and it's not integrated or interoperable in any sense of a meaningful way. Today there's a lot of data, but it's still very siloed and disparate into all these, into all these different areas.
And, and then you mentioned OpenAI and there is a human in the loop. We have to recognize that there is, is AI going to create more work or more responsibility and accountability for the human in the loop, but be giving it so much more work, volume, responsibility to review that is it humanly possible to do all that?
To your point, right in the context of AI scribes, what we saw when we went into the EMR generation or EMR world after 2010, 2012, is when a patient would go into the hospital and they'd come back and you'd get reams of paper of this discharge. But most of it made no sense because it was really just click, click, click. It's just sort of standard notes and there was very little true content in there for the provider to know what happened, what was the disposition and what was the outcome of this patient during this hospital stay. And you have to sort through thousands of pages of documentation because it was optimized for billing and not optimized for patient care.
And what are we going to see from AI scribes? Not specifically Open Evidence. I think Open Evidence is a great tool. I've used it a little bit. I think it has a great foundation, it's clinically backed, it's citing all the sources so you can double check everything.
And it's the next generation of, in my opinion, up to date. And there's actually been data now that up to date is getting worried because users are leaving their platform to use tools like Open Evidence.
And that sounds like it's the next version of that tool that we've had for so long. That was a great, again, another great resource.
[00:16:54] Speaker A: There's a couple things that I want to dig into there. And one of them was, is this just a fad? And I'm going to say I don't think it is, because I think we've already just in the last 24 months, upended our entire economy, changed the way that jobs work. And, you know, you gave maybe the utopian view of, right, we'll all do all of our work, right? The robots will be picking the, picking the vegetables, and we'll all be our own philosopher kings. Right.
I don't think our economy has caught up to that point. So I think what we are going to see is the waves of disruption that we have already across all sectors. And, you know, today I have, I have heard pitches from companies that, you know, are trying to remove the provider, the doctors and nurses, entirely and make healthcare 100% digital transaction, which personally scares me to death.
[00:17:58] Speaker B: Yes, yes, A case in point, Utah. First state in the country to allow a company called Doctronic to authorize refills on medications for chronic conditions. This is an AI autonomously deciding if you can get your medication for a chronic condition that you have based on whatever criteria they set.
[00:18:19] Speaker A: And I feel like I'm okay saying that as not a clinical provider and as somebody whose job will be easily replaceable by AI, I mean, expect a deep fake to be your next podcast co host. Right.
You know, I am worried about the companies that are trying to move so quickly because it is further dehumanizing healthcare. Now, that being said, I am a proponent of AI. I think freeing up our clinicians to be able to spend more time, more relational time with patients and less transactional time is, is a fundamentally good thing. I think freeing up corporate staff away from, you know, just hitting the same button over and over again so that they can build better systems to again feed back in and provide more time and better care to patients. I think all of that is definitely a net positive.
The other thing that you mentioned, I think is just a throwaway is around the billing side of it. And, you know, I gave a talk recently to some other technology leaders in South Carolina, were not necessarily in healthcare, around interoperability in healthcare. And some of them had worked in healthcare previously and they knew exactly what I was talking about. Others, it was, you could see kind of the look of shock on their faces when you bring up fax machines. Right. And, and those things. And so much around what is healthcare technology has been built isn't about better patient care and it's not about improving the life of the provider. It is about how do we make it the money move faster from point A to point B?
[00:19:55] Speaker B: Yeah.
[00:19:55] Speaker A: And so as a result, you know, we work with carriers all around the country and a lot of them are still running on, in some cases, cobalt mainframes from the 1970s and 80s because the system works. And at the end of the day, they just need somebody to send them an electronic, you know, message that says, pay Dr. Patel this amount of money and adjudicate that claim and get it pushed out. Right. So electronic medical record systems were developed not because patients needed better access to their data. Right. Even though they did, and they still do, but it was, okay, well, this is going to be the next step. Instead of having to fill out paper forms to be able to generate super bills to get them, we can reduce that revenue cycle by X number of days if we're just able to do it all electronically. Right. So when you hear providers complain about their EMRs or EHR systems, usually it's because all those systems started as just a faster way to get the health systems paid. Right. And things like that. And so I think right now AI is being used for that. Right. And we've seen insurance carriers get into trouble and there was, you know, accusations or allegations around United Health Care that it had just assigned a machine learning algorithm to make claims denial decisions. And they, you know, they denied that they were doing that. And I think it's, it's likely one of the many court cases that that industry is facing right now. But, you know, what is one of the first applications of a, fixing billing and coding errors. Right. So I think we're going to continue to see, if nothing else, those types of things that get the money moving in our fragmented healthcare system faster.
I think you're gonna see that early adoption and then along the way, maybe we can apply that to making the patient experience better or the provider experience better or try to improve health outcomes. That's the cynic in me.
[00:22:01] Speaker B: A corollary to that one.
There has been an equal, I don't know if you call it open source or sort of narrow use of AI to help patients as well, to help patients file healthcare appeals when they're denied directly to the insurance company, generating letters for them, asking them questions, working through how they can help get their denial appealed. And there have been a couple of those, again, I don't know, adoption and. But on the other side, there has been help directly to the patient for healthcare. I think we're still missing the clinician in all of this. And that's the second piece is that are we structurally in a society where there have been. There's so much consolidation in healthcare among health systems, among insurance carriers, among the insurance carriers that employ tens of thousands of providers.
Will the system is, is the system inherently optimized to create only efficiency and create just number go up and you know, make the billing work as fast as possible.
We really don't care about the humans to be. To be determined, to be seen. I don't know. I, I'm also a skeptic, a cynic Jeremy and I feel like we're at a point where it's we, we could go either way but I feel like there's a heavy tilting towards you know making sure all the financial as financialization of healthcare works great with AI but not necessarily the care piece.
[00:23:45] Speaker A: But I, I do. That being said, I do appreciate the companies that are outsourced outside of traditional healthcare.
OpenAI anthropic, Google, right? Yes they want the data. They always say if anything's free it's because you're the product. Right. All the various large technology companies have their own reasons for collecting data. Whether it's Amazon wanting to better sell you products, Google to better target advertising. But at the same time I think some of the, some of the positives coming out of that is you do have these companies that are trying to approach it from different ways. Right. So instead of just that traditional how do we improve the revenue cycle and speed up the revenue cycle?
You do have an OpenAI saying hey, what if somebody could actually ask, ask about their own medical records and enhance their access to it? Or anthropic saying hey, what if we could enrich the healthcare technology landscape by enabling so many more developers to be able to quickly create secure compliant healthcare applications that can access this data on behalf of patients or clinicians or whoever their customer is. So I do like the fact that we are seeing groups that are interested in something more than just moving the fee for service needle forward a little bit more, which typically comes at the, the cost of the patient provider experience.
[00:25:14] Speaker B: I have a question for you Jeremy around the development of healthcare tools or developer tools available through particularly through Claude.
Is there a platform? I'll give you an example. When Apple released the iPhone, they created a platform by creating the app store. It created a platform so that when people developed it was all integrated. It could, there was a sort of a, there was a standardization that allowed for APIs to flourish. Because you're working in this ecosystem, does something like that exist today?
I know we talked a little bit about interoperability but do you see any company that's sort of creating this platform that when we do have great access to developer tools that they can just plug and play and say, okay, we can scale faster now instead of, again, everyone working in their little cubbies and.
[00:26:05] Speaker A: It'S a great, it's a great question, Vinay. And so the short answer is yes.
However, it's not.
There's not a market leader. And the reason why is that so many healthcare IT companies, just like Google doesn't want you going outside of the Google ecosystem and Apple doesn't want you going outside the Apple ecosystem.
So, you know, you have rich marketplaces for a lot of these EMR vendors, right? Epic has their own marketplace where of course they, they get revenue for every sale that somebody does, just like an Apple App Store. But hey, it's designed to work with Epic and it's certified by, you know, Epic Review. Athena Health has the same thing. They have a rich marketplace and ecosystem of partners. But at the end of the day, does one EMR really want an app that can work with another emr, just like Apple doesn't really want you to? Right. They shut down, you know, the Amazon App store on, on iOS or I think there was that Fortnite lawsuit a couple of years ago because they're not getting a cut of that revenue. So I think the best that we have right now is the move toward more companies adopting the standards of fire, and some of that is being pushed through regulation.
So a lot of, you know, working in the IT development space for healthcare, you know, I'll look at EMRs to build a connection to one of our platforms, you know, and they have an expensive licensing fee to be able to access their APIs, unless you use the FHIR APIs, because those are free. Right. I mean, again, you have to go through a certification process. But it's because that was know there were so many incentives thrown for health systems and for providers and EHR Health IT vendors over the last 20 years or so to push interoperability.
At some point the federal government said, okay, enough is enough of building your own little interoperable walled garden that, you know, a patient who's, you know, provider A is Epic and provider B is Cerner. Can't get the two to talk to each other.
I think now you're seeing more of that movement of, you know, applications that are leveraging that interoperability sit in the middle just to put a bow on it.
It's one thing when we have technology fads, right? Maybe you made A billion dollars in crypto, maybe you lost your shirt in it. It does become a little bit more sensitive, I think, when we are talking about taking a relatively new technology, no matter how proven it is in specific use cases. These LLMs are generalized, right? That's kind of their thing and we're putting them on top. And then we do have these economic pressures to say let's remove as many humans out of the health care equation as we can because we think this AI can do it faster or cheaper. Right. Or with a high, a lower error rate or whatever the case is.
Because if we do see something similar to the market correction and it stops being the shiny new thing, we're already facing healthcare provider shortages, we're already facing massive burnout. People leaving it, leaving the whole healthcare industry.
You know what does happen if the AI focus, right, loses its luster or it can't scale at the rate that, you know, that we felt like it could reach. As you, you mentioned, some articles are pointing to, that's just, I think, a concern of making sure we're keeping, at least I'll speak for myself and our company, the relational side of healthcare alive and well and use AI to augment and to supplement but not replace. But who knows, 10 years from now we'll all be working for the robots. We're not working at all. But at least today I think it's a case of seeing where we can leverage this exciting new technology on behalf of the patient and on behalf of.
[00:30:04] Speaker B: That experience and the clinician too. Right? Yeah, absolutely right, right, right. No, 100% agree. We make this point every time when we talk to our team. We're going to use technology to make our job better and supplement as a tool just like we have millions of other tools that we use every day. It's not going to replace us because we still need a human at the end of every interaction because this is healthcare and it's inherently a human interface that's going to help people heal.
So the million dollar question to close this out, Jeremy, and you touched on this a little bit, but I'm going to point, I'm going to create a two way out for you.
So one, do you think we are in an AI bubble? And if you do, what is, how are we going to know it's deflating or popping? So what's the indication you think that there is if not, if we don't, if we're not in a bubble, then what's the case to be made for, for health care as it, as it sort of accelerates and we realize more of these like, like, you know, what do you see the future if we're sort of riding this train and it's only going up a mountain with AI being the engine, what do you think? What are your closing thoughts on that?
[00:31:19] Speaker A: So I will say I am not a student of the dismal science economics. So full disclosure, I don't think I am qualified to be able to speak to whether this is an economic bubble. But I remember the dot com bubble. Right. And yet we're still using the web, the Internet, every single day and it powers the global economy. So, you know, do I think, do I think that there's going to be a shake up with all the venture capital dollars that have been thrown around the last couple years? Yeah. Do I think that a lot of companies have basically just created products where they're licensing the use of the OpenAI or the Anthropic or Google APIs and they're just throwing their own little name and brand on top of somebody else's product? And do I think we're going to see a very rapid consolidation in the next 12 to 24 months? I do.
I've been given so many demos of something that I can see is just you just put a website on top of chat GPT and you, you know, so do I think that we're going to see further disruption? Do I think that we're going to.
[00:32:28] Speaker B: See.
[00:32:30] Speaker A: Economic volatility as a result of AI? I do. But I also was in college when we were told peak oil was going to hit by 2006 and then some engineers figured out how to do fracking for better or worse? Worse. And now we suddenly don't have this massive shortage of fossil fuels that was predicted to be the end of humanity. So I'll leave it to the economists to debate that piece.
As far as what do I think the future of health care is? I would just implore our colleagues in the health care industry, and particularly those who are entrepreneurial, to figure out, number one, how do we put this in practice for the patient?
And if, I think if we all could take that to make just healthcare better, not just faster, not cheaper, but.
[00:33:20] Speaker B: Just make it better, genuinely better for the users that interfaced with it.
[00:33:26] Speaker A: Exactly. Then I do think we're going to see a lot of exciting new AI products that are going to change the way that we can deliver it, hopefully for the better. Now, Vinay, I'll ask a million dollar question of you. If you could have AI, an AI tool, do one thing Today, whether it's as a clinical pharmacist or program administrator and leader or as a dad, whatever it is, what would you leverage AI to do? What tool do you wish existed?
Wow.
[00:33:58] Speaker B: If I had the trust and what do you call it, riskiness of allowing AI to have all of my data, like every single piece of my data, I would love to be able to have AI tell me that you sort of be, be my personal assistant and tell me, look, you know, it, it looks like you're going to be running late today. You know, do you want to send a message to your family or to your wife telling her that, you know, you're not going to make it for dinner and just be like, yes, please. Thank you for noticing that. I think that having something like a personal assistant, personal AI assistant, if I felt comfortable, if I trusted, if I was again endeavoring enough to have access to all my data to do some of that or even say, look, you have an upcoming work trip planned and you didn't optimize your benefits. Did you know, you get an extra free night or you get an upgraded room or whatever, things that you don't know yet. You have all of these, these perks that you never utilize and sort of just things something that could do that, but it would require a whole lot of access that I wouldn't be ready to give it.
[00:35:18] Speaker A: I'm with you, you know, but I'll say this. As somebody who routinely uses his own medical record to demo patient portals or virtual visits or things like that with some of our clients and partners, I've just given up. I just assume they've got my data anyway, whether I, I approved it or not. But no, Vinay, I think you're, you're spot on. For me, it would be the same thing.
We're not there yet because I can't get my Apple CarPlay to play the song or the playlist that I want it to play 100% of the time.
But yeah, I mean, just things like, you know, we've got some, had a, some home repairs that we have to get done, and during business hours, you're trying to juggle five or six different contractors or trades people to be able to get them and schedule stuff. And I would love to just be able to hand that off to an Apple Intelligence or a Google Gemini to just take care of that and tell me where I need to be. So I'm right there with you.
[00:36:18] Speaker B: That's right. And that's right. And as these systems take over more and more of our lives, and sort of create the future.
Remember to be kind to them in case they are one day our overlord.
[00:36:31] Speaker A: I will just, I will close with one quick anecdote. When my older son was probably about four, we had, you know, we, well, we still do have an Amazon echo in our, in our kitchen, which again, you just get used to the fact that you have an always on microphone. Try not to think about it too hard.
And he had said something in his four year old thing that was like, you know, be quiet, Alexa, or something like that. And I said, brendan, you, you need to be nice. You need to be nice to the robots. And, and I said, do you know why that is? And in his cute little four year old voice he goes, because they'll destroy us.
And that's my, just my most cherished moment of his early childhood. I'm like, you're absolutely right, kid. You're absolutely right.
All right, well, thanks for the lively discussion, Vinay. Hopefully we will both not be replaced on our next episode with AI Deep Fakes. But from Proactive md, this has been Healthcare Explained. I'm Jeremy Vanderknife.
[00:37:33] Speaker B: And I'm Vinay Patel.
[00:37:34] Speaker A: And we'll see you next time.
ProactiveMD.
