The AI change management process that healthcare providers are navigating will be as significant —if not more so— than the industry’s transition to EHRs, according to Michael Meucci, CEO of Arcadia.

“If we don’t account for that transformation as part of our overall implementation cost, we’re setting ourselves up for a lackluster outcome, because you’ll have a bunch of point solutions partially implemented without meaningful adoption,” he stated in an AI strategy report released by Arcadia last month.

Below are three pieces of advice included in the report, all of which come from health system leaders.

Build a strong foundation

For a health system to achieve AI success, it must start with a reliable data lake that serves 

as a “single source of truth,” the report noted.

Building this infrastructure first is key, said Terri Couts, chief digital officer and chief information officer at Guthrie Clinic.

“We’re on our journey. Our first use case for our data lake is around population health. We’re building out that foundation, and it took a fair amount of time for me to educate my peers on the ‘why,’ and on how we use the data,” she said.

Make the most out of the tech you already have

With hundreds of AI companies selling products to hospitals, it’s easy to get fixated on the newest, shiniest models. 

Hospitals are better off taking a more strategic approach, stated Jeff Sturman, chief digital information officer at Memorial Healthcare System.

“We’re investing a lot of time and energy in the platforms we already use to figure out where they can also solve other problems for us, as opposed to saying ‘We want to go become a development shop, and figure out what we can develop ourselves’ or ‘Are there 1,000 other opportunities to fix a particular problem by going off and buying yet another solution?’” he remarked.

Sometimes innovation requires parameters 

Adherence to guidelines and standards is a must for AI deployment in healthcare — especially as the field continues to evolve at a rapid rate.

“We’re going to be mediators within our institution, where with appropriate training and appropriate attestations, we’re broadening access to data, but under certain regulatory and legal requirements. That’s our way of balancing that — broaden the workforce, but make sure they completed appropriate levels of training,” said Alex Low, director of research data hubs & CIN IT strategies at NYU Langone Health.

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