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January 7, 2022: John Halamka, MD, President of the Mayo Clinic Platform is our Keynote guest today. What’s the promise of AI in healthcare? Why are we pursuing it? What are the challenges that remain in its adoption? Where does the technology stand in terms of transparency and useful testing ability? What are the three main problems with EHR data sets and how can we address them? How far away are we from solid clinical use cases with wrist wearables? Are we getting to real quality data that can be used? And can we call the EHR a platform? Or is it still a transactional system?

Key Points:

00:00:00 – Intro

00:06:00 – AI has a credibility problem in healthcare

00:07:30 – ​​Algorithms are mostly probabilistic, multi-tiered mathematical equations that don’t necessarily have easy explainability

00:19:00 – Is the EHR a platform? Or is it more like a transactional system with aspects of a platform?

00:20:10 – The perfect storm for innovation is an alignment of technology, policy and culture. 

00:31:35 – You can augment humans to make them wildly more productive if they’re doing review rather than authorship

Transcript

The Credibility of AI, the Future of the EHR, and the Cultural Demands with John Halamka

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This transcription is provided by artificial intelligence. We believe in technology but understand that even the smartest robots can sometimes get speech recognition wrong.

Bill Russell: [:grams of fat.:Keynote show sponsors Sirius [:In:health.com/subscribe to sign [:

Today we have Dr. John Halamka, President of the Mayo Clinic Platform with us. John, welcome back to the show.

John Halamka: Well, hey, thanks so much. When people ask me, what's the weather in Boston today? And I said, snowy, with a chance of Omicron.

ell: Oh man. So are you guys [:ty against simple infection. [:he HLTH conference. The HLTH [:

John Halamka: Indeed I was. So you remember the best part of that conference is not the speakers. It's all of the events around the conference.

thing. But you're right it's [:about the EHR as a platform. [:

I want to start with all right. So you're president of the Mayo platform. We've already covered that on the show. If people are wondering, Hey, what's John doing these days they can listen to the other show. You could give a brief thing on that. Are you still practicing medicine or just predominantly the Mayo platform at this point?

Harvard thing. It means you [:hours a year and I collate a [:

Bill Russell: You get to do it all. We are going to talk a fair amount about AI. You spoke at HIMSS last year. And you talked about the promise is bright for AI. And you talked about that there's challenges that remain for the adoption of AI. Let's start with that. Give us a little background on some of the things you talked about at the HIMSS conference.

John Halamka: Well, let me [:an AI algorithm and there's [:loped only on north American [:

But you need more than that. And that second thing, what I would say we need is test ability. So the first thing is transparency. How was it developed and where is it useful testability. So you know what, Hey Bill, I'm gonna run this algorithm against and you know when it says you're likely to wear a red shirt today.

sort of fit for purpose. And [:bility. They're a black box. [:

Bill Russell: All right. So let's break that down. Well, let's start with this. Who's developing the algorithms today. Is it predominantly academic medical centers? Is it third parties? Is it big tech? I mean who is developing these clinical algorithms within our AI models?

John Halamka: Yes. And what [:out of Google and Verily on [:. A former CEO of Google and [:I think as we see all these [:

Bill Russell: The data's really interesting to me in that we can't just pick up an algorithm from Mayo and drop it in Irvine, California, but still we're trying to develop these algorithms that are going to work. And it really depends on the dataset doesn't it? I mean, I was talking to a physician founder of an organization.

nt room. And they're feeding [:% [:adjusting for the population [:

John Halamka: Yeah. So let me describe three problems with our EHR data sets. So one would be just the fidelity of the data, and that is write a hundreds of data elements you don't know in what workflow, by whom at each institution they're recorded.

e ethnicity is recorded by a [:

Maybe it's not so wonderful. Well then let's also continue on the concept of race, ethnicity. One of the problems you have is the granularity of that data element. It doesn't really break down between, well, you're Asian. Well, are you Japanese? You're Chinese. You're Korean. You're you know my wife is Korean, right.

[:Well, the challenges were [:se guidelines and guardrails [:

So you need a much broader coalition of people, but we'll get to that in a minute. What is the promise? What's the promise of AI in healthcare? Why are we pursuing this?

strative. So, you know, as a [:es by anecdote and intuition.[:'t substances that can cause [:nything I could take and the [:'m not sure all the EHRs are [:

And so it's, you might be able to develop, it might be as limited as you can develop. At Mayo, because you've captured this kind of data in this kind of way, and you structured it and you have the data governance around it to make sure that you are doing and the training for the physicians to capture it in a certain way. But how, I mean, how scalable is that going to be?

we look at algorithms going [:er that kind of information. [:

Bill Russell: You know, John, I love the example of the simple camera in the room. And this has almost become a joke. Hey, the Fitbit, the Apple watch. But you're probably tracking this stuff.

rom solid clinical use cases [:ve predictive A fib. We have [:ayo clinic algorithms inside.[:I think you're gonna look for:consider the EHR a platform [:can have this thing that is [:

Bill Russell: So that's being driven predominantly by policy. 21st Century Cures and some financial penalties and those Catholics. So it's being driven by policy. It feels to me like it's going to be enough. It's still moving a little slow, but it still feels to me like it's going to be enough.

policy change seems pretty, [:

John Halamka: So, yes. But I describe the perfect storm for innovation as an alignment of technology, policy and culture. Right? So the fact is we needed FHIR right?

and can't be blocked, can't [:the data in. No value in the [:aid, look, you can grab your [:

I said, all right, let's, let's start. And so I downloaded their app right there in their booth. It was so simple. It pulled up like 180 different providers. You have to go through there, find your provider. Then you have to remember your login to their portal to actually authenticate that you're you to that health system.

order to pull all that stuff [:we use. It's it still has a [:ng anything here. It's, it's [:fully integrating all of my [:t for a nationwide mechanism [:

Bill Russell: Yeah. Get getting back to the EHR. What do you think the future of the EHR is? I mean, do you think it just sort of goes into the background, acts as a repository, does its transactional work great within the health system itself. It is opened up via FHIR. Or do you think there's going to be a new like ground up something that we're going to see in maybe the next five years or so?

spent time with Don Berwick? [:

Bill Russell: I have not.

John Halamka: So he was our CMS administrator, but he founded something called the Institute for Healthcare Improvement. The IHI. And Don would use the term sometimes you engineer a system to achieve exactly the result you got. Now, let's think about what we did during the meaningful use era.

immunizations and we want to [:just doing the EHR as it is [:figuring out who said what, [:int, but if if you were some [:ful use called for something [:

Here we are. The EHR market is essentially consolidated to I don't know, let's call it a half dozen players. And we're saying, all right, we're going to fund this. We're going to get to the people we're going to put the team together. Where do you start? I mean, what you just described is a great use case, but I can, I can tack on Nuance onto their DAX ambient clinical listening onto any of the six platforms that are out there today.

And I, [:on this self-built EHR in the:listening, natural language [:

It would be tough. So I think we have to take a careful look at what it is we want to achieve and engineer what we want to achieve that will require regulatory change.

chnology path and no one was [:

John Halamka: Yeah, it's high nineties, but so, but here's the issue and sometimes you have to do the wrong thing to get to the right thing. Right. So think about you may not remember the CCD and the CCDA and all these XML forms that were used as is interoperability.

Bill Russell: No. I do [:: Yeah. So we argued way back:

That anyone was oh wow, we made a horrible mistake. That API thing, it's exactly the right thing to do. Now we got there. And I think we had a market failure in the adoption of EHRs. We needed a regulatory change. And now that we've got market acceptance, we need a radical revision of how those things work.

of the day we have the great [:

This isn't even a ten-year projection. It's a three-year projection. What role do you think technology is going to play in addressing this challenge? I realize a lot of other things are going to be at play here, but I want to focus in on the technology. Do you think technology has a role to play?

logy I would reflect on. One [:en a human reviews it. Cause [:at care is delivered by EMTs [:

Well, if humans can work better, stronger, faster and each human can work on just the stuff they're uniquely qualified to do, we'll probably be able to get through the great resignation.

ly the kind of thing. That's [:d these layers of access to, [:and what you expect to see in:s, but you've addressed that [:ole or geography or familial [:ainers of it and then invite [:s, validated algorithms, new [:

Bill Russell: That's fantastic. So talk to us about the Google partnership. That was a ten-year arrangement. And if I'm not mistaken, was that two years ago that that came together or was it, was it longer than that?

John Halamka: Just finishing our third year.

ven years. What is, what does:he nature of what we want to [:entified database in Google. [:o some imaging of your brain.[:

Maybe there's something funny going on there. So they did 6 MRI sequences in my brain. They found them my third ventricle, which is a cistern of fluid in the brain is larger than a normal human. So I said, Hey, do you have any idea what the Gaussian distribution of third ventricle sizes and a normal human?

and [:to this and I'm going, Hey, [:ch is there are those in our [:ishing a pilot on this is to [:ng cryptography and advanced [:

Let's try our data set against your algorithm, see how it performs. And I can do it without having you sending me your data.

Bill Russell: So does that require me to move my data into Google's platform? No it doesn't. You're saying federated wherever.

use we're just finishing the [:

Bill Russell: That's interesting. What if I wanted that architecture that you're talking about with Google? I thought, Hey, this is pretty interesting. Move that data into that, that kind of that kind of architecture. Is that the kind of thing that you've public domain that architecture? Or is that the kind of thing that I can participate some way in that?

John Halamka: Well, [:

Bill Russell: Do they have a skew for anything? I, I wouldn't imagine.

t isn't exactly proprietary. [:

Bill Russell: John, how's the farm?

John Halamka: So far so good. You know, It's cold.

Bill Russell: In Massachusetts. Yeah I would imagine it is cold.

John Halamka: So here's the challenge, right? Keep water liquid for 300 animals when the temperature approaches zero.

Bill Russell: You just gotta keep it moving don't you?

in in Massachusetts, where I [:

Bill Russell: So do you have a team helping you? I mean, you're taking care of a lot of animals, your sanctuary for these animals. I assume you have some volunteers and some help.

John Halamka: 500 volunteers.

Bill Russell: Wow. Do you have to manage them in any way?

e facilities management, the [:

Bill Russell: Wow. The volunteers. Are they educated before they come in or do you, they're just kindhearted people that show up?

we offer courses and we have [:

And so you can put your finger in the mouth of a sheep or a goat, and you'll still have your finger. As opposed to a horse or a cow full set of teeth, don't do that.

Bill Russell: The level level one is keeping them safe, making sure they don't get injured.

he earliest entry of you can [:

Bill Russell: And this we'll close with this, but in this day and age, I'm talking to so many people that have so much going on and you have a ton going on. I mean, I, I read your name. I see. You're, speaking. You're here. You're there. You're doing a lot of stuff. Is this relaxing for you having 300 animals when you come home?

Or is this, I mean, does this, raise your, your blood pressure as, as you have to deal with that and a pretty demanding job.

John Halamka: [:scue for people? Because the [:

Bill Russell: Because those, those animals don't know that COVID is going on do they? They, they just. Man, that's I am going to take you up on that at some point, I'm going to reach out to you and say, I'm going to be in Boston at these times and see if we can coordinate. I'd love to get out there and see what you are doing out there. And the 500 volunteers, I think it would be fantastic.

John Halamka: Well, we'll [:

Bill Russell: Exactly. I would expect nothing less. Hey John, thank you again for what you're doing for the industry and thank you again for taking the time to visit with us. I really appreciate it.

John Halamka: Well, any time, stay in touch and be well.

Bill Russell: What a fantastic discussion. If you know someone that might benefit from our channel, from these kinds of discussions, please forward them a note, perhaps your team, your staff. I know if I were a CIO today, I would have everyone on my team listening to this show. It's conference level value every week of the year.

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