Make no mistake: the hype surrounding generative AI in the healthcare sector is still going strong. Overall, the industry is excited about the technology’s potential to alleviate burnout, increase operational efficiency and improve patient outcomes — but healthcare leaders still have a lot of work to do when it comes to putting the appropriate guardrails around such a novel form of technology.
When I asked Jason Hill, Ochsner Health’s innovation officer, about the state of AI governance in healthcare, he said that the issue weighs heavily on his mind.
“I go to sleep most nights and wake up most mornings worrying about that one thing,” he remarked during an interview last month at HLTH in Las Vegas.
In his view, providers and other healthcare organizations are in dire need of standardized frameworks they can adopt to ensure their AI tools are safe and perform well over time.
“If I had millions of dollars right now to make a startup, I would create a company that could provide a quality assurance framework for AI. In my mind, it’s not a matter of if it’s going to be regulated — it’s a matter of when it’s going to be regulated, and how. The first company to market that has an established system for that — when that regulation happens, which we don’t know when it will — will be the winner,” Hill explained.
He thinks that future AI regulations will encompass two categories: the technology side and the operations side.
For the technology side, Hill thinks that AI regulations will focus on whether generative AI models are hallucinating and whether those hallucinations are clinically relevant. On the operational side of things, health systems will have to do a better job of making sure they aren’t infected with “new shiny thing syndrome,” he said.
“If cardiology comes to me and says, ‘Hey, look at this cool stethoscope thing — it actually detects valve stenosis and helps us get people into valvuloplasties.’ What I would then say to cardiology is, ‘Awesome. I need you to look at 50 of what that AI outputs a week, and then I need you to judge its effectiveness on a rating scale of 1-10.’ Then that’s going to be built into the contract — and if I don’t see those results for more than four weeks, we’re going to cancel the contract. Operational needs to have some skin in the game for if their thing works,” he explained.
From Hill’s vantage point, he would like to see hospital leaders “harness some of the hype and turn it into a commitment.”
He believes that AI governance doesn’t just apply to the safety checks that are performed before a health system decides to put a tool into practice. To him, ongoing quality assurance is just as important.
Photo: SIphotography, Getty Images
