A year and a half ago, Bob Berbeco was doing what most health system CIOs know all too well. He was fielding AI pitches, launching pilots and watching vendor promises accumulate. Then he decided to stop.
For most rural hospitals, the AI playbook has meant implementing lightweight, targeted tools to ease administrative strain and expand access to care. Mr. Berbeco, CIO of Mahaska Health, a critical access hospital in Oskaloosa, Iowa, instead halted the isolated experiments his team had in motion, not because the technology wasn’t promising, but because the organization hadn’t yet defined what it actually needed.
“We just stepped away from isolated bolt-on AI pilots. We had some in motion. We decided to stop those, and we stepped back to process and replace the approach that we had. We want to be intentional. We want it to be a governed workflow type approach. We want to have a process around it,” Mr. Berbeco said during a recent episode of the “Becker’s Healthcare Podcast.”
The pause produced two things: a center of excellence and a commitment to AI build.
“We ended up with a center of excellence that was focused on AI, like a brainstorming group, where a few of us get together and we talk about what are the opportunities that we have in our organization that AI could be good at,” Mr. Berbeco said. “That has helped us a lot. That’s the first start. Just start with that need and assess that need. Determine where you want to focus.”
From there, the organization charted two parallel tracks. The first runs through Epic, which is building out three AI capabilities — Penny, Emmy and Art — covering distinct functional areas within its platform. The second is more unusual for a critical access hospital: Mahaska is building its own proprietary AI system.
“We are piloting our own AI system where we’re building it internally,” Mr. Berbeco said. “I’m blessed to have someone here on-site that actually has a lot of experience doing these things, so he’s building it. And we’re going to focus on things like, mostly insurance, denial reduction, knowledge base, a staff augmentation for our coding people. So not using AI to replace anyone, but using AI to augment knowledge that we have with our coding and the processes that we have within our coding.”
Mr. Berbeco sought a clinical leader to give input on AI – someone the organization could have kept narrowly defined by clinical function. The person he found came from a surprising place, and was able to do a lot more than he initially imagined.
“The person who is building our AI system is a nurse practitioner. He has a clinical background. Some leaders would put him in that box and say, this is only someone who does clinical stuff,” Mr. Berbeco said. “But we noticed the talent and the interest that this person had. So let’s go ahead and give them resources. Let’s feed that knowledge, feed that interest, feed that passion they have, and we’re realizing the benefits of it.”
The internal build is still in progress. But for a hospital operating on critical access margins, developing AI expertise from within is transformational.
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