Health systems are rushing to adopt artificial intelligence tools, hoping the technology can help them cut costs and alleviate strain on overworked providers.
But AI isn’t always easy to implement, particularly at organizations with few resources, and clinicians have plenty of concerns about inaccuracies and biased responses. Experts say that governance protocols are key to ensure models are used correctly and perform up to standard, but many providers say they’re unaware of their organization’s AI policies.
The Joint Commission is hoping its new voluntary certification program can provide a blueprint for overseeing AI. The healthcare accrediting and standards group rolled out the certification early this month in a bid to recognize organizations that can demonstrate effective data management, risk and bias reduction, monitoring and safety evaluation, and education and training.
The certification “can be understood, adopted and enabled from anyone on the spectrum of maturity in regards to where they are with governance,” said William Walders, executive vice president and chief digital and information officer at the Joint Commission.
Walders and Ken Grubbs, the commission’s chief nursing executive and executive vice president of accreditation and certification operations, sat down with Healthcare Dive to discuss the certification, its impact and how the program works for low-resource health systems.
Editor’s note: This interview has been edited for clarity and brevity.
HEALTHCARE DIVE: Tell me about the Responsible Use of AI in Healthcare certification. What are some of the things hospitals and health systems need to do to be certified?
KEN GRUBBS: Number one, making sure that there’s an appropriate governance structure in place. It really allows organizations to determine what that looks like and how they formalize it. It really is focused on patients and ensuring that it’s protecting patient safety, while also the workforce’s trust in using the technology.
There has to be effective data management, and just making sure that that data is protected, that it’s not accessed in an unauthorized manner. It really gets into that ongoing monitoring — making sure organizations have some type of registry of what products they’re using, making sure that they track changes to that, and then all of the monitoring that would go along with any program from a quality, performance improvement, and safety standpoint.
Again, it’s focused on patients. And it’s focused on making sure that there’s the ability to identify any risks, like bias or anything of that nature.
WILLIAM WALDERS: Embedded in some of [the certification] is education and training. Having role- and use case-specific training to ensure safe adoption. I think that’s overarching. It’s something health systems do well. They keep top of mind how their clinicians and others practice care, and this is a tool in their toolbox, no different than the other ones that they have to really enable and affirm safe and quality healthcare.
What do you think the impact of the certification program will be? Is this something that you’ve had a lot of interest in from health systems?
WALDERS: We’ve gotten significant digital engagement and outreach from folks seeing a need and curious how to fill it. Not only was the certification written to survive a lot of pace of change, it was written intentionally to survive the evolution of AI — flexible. Similarly around organization size and also around use case and type.
A lot of that outreach has been targeted. I’ve been asked this question in the past: ‘We have AI in our washing machines in the laundry. Does that need to go to governance?’ It’s up to you. I mean, if you ask me, no. My washing machine is not providing a clinical decision. But that’s probably the first question you should ask as part of your governance process. Is it applicable?
That’s an organizational interpretation, but that’s probably your first check. Toothbrush? No. Washing machine? No. CT scanner? Yeah, probably. And so a lot of the outreach has been there.
But let’s be clear, there’s been a bit of a gap. And we feel the obligation and commitment to safety and quality to fill that gap, and so our focus is on where AI overlaps with safety and quality. And so a lot of folks have been grateful that we’re doing something and we’re here to help.
How do you think about ensuring low-resource hospitals — small, rural, dependent on Medicaid — can effectively adopt AI? Is that something you were thinking about when developing the certification?
GRUBBS: Part of it was making sure that we were not too prescriptive, that we got the principles of safe use of AI from a governance perspective and implementation standpoint within the certification, but we allow organizations to determine what that looks like. So that allows adaptability.
The other thing is, a part of the field review was to ask organizations to give feedback to make sure that we had an understanding of what the lift would be for this certification. Based off of that feedback, we made changes as well. So I think those two things together were extremely meaningful in making sure that we were not overburdensome, but we put the absolute concepts of safety within the certification and allowed organizations to determine what model works or what framework works best for them based off of those principles.
Could you give examples of something that you thought you would have included initially, but then changed to keep the certification applicable to a broader group of providers?
WALDERS: When we first looked at this, we thought we could be a little more prescriptive on governance composition. Can we have a model? Do you look at something like an org chart? And then you realize that no, sometimes the chief operating officer is the same person who’s fixing the boiler, who sometimes is the phlebotomist, right? And so we didn’t want to be as prescriptive as deciding roles and responsibilities.
And other threads like that, just pressure testing. Put yourself in that clinic in Oklahoma. Does this work for them? And it needs to. They’re getting an AI ultrasound machine because they need ultrasound in the clinic. Could it fit that process? Is it overly prescriptive that you need seven different titles with seven unique expertises to vet the radiology aspect of a GE device? There were some deep dive discussions, and getting back to reality and accessibility was where we landed.
