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Cerner exec talks about AI technology in healthcare and EHRs

How will EHRs evolve once AI is involved? A Cerner exec discusses how this is already beginning to happen.

Many health IT experts have discussed potential -- and real life -- use cases for AI technology in healthcare. John Glaser, senior vice president of population health at Cerner Corp., an EHR vendor based in Kansas City, Mo., discusses one other use case: how AI will affect and transform the use of EHRs. Here's a hint: Usability of EHRs will be much more seamless.

He also divulges how Cerner is using AI technology in healthcare, as well as how he thinks AI will affect the role of the healthcare CIO.

How do you see AI and EHRs working together? What would that look like?

John Glaser: Right now when [a physician goes] to order a prescription or you go to document, let's say, on a patient, the machine -- because you've got to document this, that or the other -- ... asks you the same questions, like if someone has diabetes regardless of the nature of the diabetes, and what's been done before. So ... you have the AI that says 'I'm only going to document the stuff that is really tailored to this patient and their particular issues ... and I'm going to populate with stuff I already know. I'm going to go ahead and take care of a bunch of the documentation and I'm going to focus [the physician's] documentation on key items'. That's one way we do it. Really tailor ... so they don't waste time documenting stuff that's irrelevant or that's not going to be useful.

If you can take time out of these kinds of things and reduce clicks then we'll have made progress with usability.
John Glasersenior vice president of population health, Cerner Corp.

The second thing we have, and this is still early, ... you're in the room examining your patient, the machine is pulling data from the EHR ... it's looking at activities, what screen you go to as the doctor, it's listening to the encounter, so it's listening to the discussion and it's pulling up key phrases and this, that and the other, and it's watching the interaction. It's actually seeing you listening to the patient's chest or looking in the patient's ear. But based on the system watching the conversation and listening to the conversation and pulling out the data it actually generates the documentation automatically. It's still early, but it looks pretty darn promising ... through recognition of voice and recognition of images and movement and it will actually automatically generate this. Anyway ... [with usability] it's the fact that ... if you can take time out of these kinds of things and reduce clicks, then we'll have made progress with usability.

What is Cerner doing with AI technology in healthcare?

Glaser: [What] I just mentioned of listening to the encounter that we are doing. We've done it in our own clinic and now we've done it with two customers who have extended it into their own clinics. So it's AI because it's doing visual and voice recognition and bringing all the data together and doing ... pattern recognition to create diagnosis. So we're doing that. We are doing where we look at very, very large amounts of data and say to what degree can we really tell whether treatment A is better than treatment B. ... You and I probably both know that half the time a patient doesn't pick up their medication. So the question is, how do we motivate them? You use AI to arrive at the right motivational strategies. People motivate differently. We're doing that.

How will AI change the role of the healthcare CIO?

Glaser: In a way the role doesn't change. That's always been a part of the role whether it's the internet or mobility, now AI. Your job is to take these big technology trends and interpret them correctly and help your team, the organization, [with] how to apply them. ... That part of the role hasn't changed. What is different here is now I have to deal with people who are data scientists, you know big algorithm developers. I have to think about, golly, in my systems I might have tens of thousands, hundreds of thousands of little pieces of AI scattered through all my systems, how in the world do I manage this? Keep it current, you know, keep it up to date? ... So I now have a management challenge. To keep all the logic and algorithms current and up to date and also making sure, do we know that they're doing any good? Making care any better? ... I now have to think about different kinds of people like data scientists, and I now have a different management challenge.

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