Intelligence

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

Jan 7, 2022   |   This Week: Health
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John Halamka: AI has a credibility problem in healthcare. And what I mean by that is, if you buy a can of soup, on it, it says a thousand milligrams of sodium. 500 grams of fat. 2000 calories a serving. My bet is you wouldn’t eat that soup. One hopes. You buy an AI algorithm and there’s no soup flavor. Right. You have no idea if it was developed on people like the patient in [00:00:30] front of you or not. And therefore you really don’t understand its utility, its bias, its likelihood fulfilling what you need it to do.


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.

John Halamka: So of course this is complicated and it’s quite early, so one doesn’t want to draw conclusions, but what I know about vaccine durability, Which is that the Madonna, Johnson and Pfizer vaccines have a durability of between 120 and 150 days. Now, when I say durability, I’m not referring to their prevention of serious disease or hospitalization, I’m saying durability against simple infection. [00:03:00] So just think for a moment, if in fact it was eight months ago that you got your last shot, you know, by now you’re starting to see the waning of the protective antibodies and therefore it is likely you’re going to see an infections spike as folks are that tweener period between second and third shot. So Omicron again it’s just too early to know.

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…

I see about 900 a year. I do toxicology consults across the country. I happen to have a particular expertise in poisonous mushrooms and plants. And so I am doing that virtually, which really was much easier during a COVID waiver and regulatory roll back here. And then I teach about 200 hours a year and I collate a [00:05:30] number of research projects in addition to the administrative duties. So welcome to life as an academic physician.

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: My bet is you wouldn’t eat that soup. One hopes. You buy an AI algorithm and there’s [00:06:30] no soup flavor. Right. You have no idea if it was developed on people like the patient in front of you or not. And therefore you really don’t understand its utility, its bias, its likelihood fulfilling what you need it to do 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.

So, you know that algorithms are mostly probabilistic, multi-tiered mathematical equations that don’t necessarily have easy explainability. They’re a black box.

Authors

Bill Russell

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