Key Strategies for Exploring Generative AI Use in Health Insurance

October 30, 2023 - Artificial intelligence has been in use in the health insurance industry for decades, but the emergence of generative AI has stirred up new questions around regulation and appropriate use of these technologies in the health insurance space.

The new tool faces a number of obstacles to integration. Namely, the lack of regulation and the overabundance of proposed bills or guidelines have fragmented the national approach to these tools so far. Additionally, there may be risks to patient data.

Despite the nebulous environment, payers can explore integration with some confidence by implementing a couple of key steps.

Kelsey Waddill:

Hello and welcome to Healthcare Strategies. I'm Kelsey Waddill, senior editor of HealthPayerIntelligence and multimedia manager for Xtelligent Healthcare Media.

What is generative AI's role in health insurance? How are regulations taking shape around this tool? And how are payers reacting to the new possibilities generative AI presents?

Today we're bringing you a conversation touching on all of these questions from HLTH 2023. At the event, we caught up with Ginny Whitman, senior manager of public policy at the Alliance of Community Health Plans--or ACHP--to talk about generative AI's impact on the health insurance space. Since we captured this on-site, the audio quality is a little different than our usual standards, but hopefully it feels like you're immersed in the energy of the conference. So let's get into the conversation.

Kelsey Waddill at HLTH 2023:

Well, Ginny, it's great to meet you. Welcome to HLTH and welcome to Healthcare Strategies! This is our first time sitting down together, so I'm excited to get to chat about a really important area that's emerging in healthcare right now, which is artificial intelligence. But before we dive into the scope of this conversation, could you just share with our audience what's your background? What is your role right now? How did you get there?

Ginny Whitman:

Absolutely. So: Ginny Whitman, I'm a senior manager of public policy here at ACHP, which is the Alliance of Community Health Plans. We represent nonprofit, regional based health insurers that are aligned, integrated in some way with a delivery system, a provider arm.

So our thesis at ACHP is that model of integration with the payer and provider provides for our better care system and care experience for beneficiaries. And so I lead our health IT policy portfolio at ACHP. That ranges from everything from virtual care to interoperability and now AI. So it's a very exciting time. It's been a great last few years ramping all this up.

I've been at ACHP for about five years, and prior to that I would say it was more in the clinical space. So I spent a few years as an emergency medical technician. I worked in an ER, doctors' offices, et cetera, and all of those experiences and how broken the system was for the patients and seeing that on a day-to-day basis is eventually what pushed me over into policy. And now I sort of feel very strongly that health IT is the thing that's going to help us solve all of those broken pieces. So very passionate about what I do here at ACHP. Yeah.

Kelsey Waddill:

Well, that's awesome. And I'd love to hear about what you're seeing payers in your space right now taking away from AI right now. Where is this technology leading? It's kind of cutting edge right now, a lot of uncertainty about where it's going to lead, but what are some of the use cases you're seeing right now?

Ginny Whitman:

Yeah, so it's a great question and I think we can create two buckets of payers in this space.

We have those that are really excited. They have taken the leap. They're doing really fascinating things in piloting different large language models for AI. So they're sort of taking generative AI and taking the bull by the horns, if you will.

We have the other half of that payer bucket, which is definitely more standard payer, risk-averse. They are very concerned about "AI snake oil," if you will. And so there's definitely taking a little bit of a slower approach, being a lot more thoughtful about what they want to integrate within their system building in-house versus who they might want to partner with in terms of vendors and sponsors and things like that. So it is a really interesting breakdown between our payers.

I also think that it's important when we're talking about AI for payers. A lot of payers have been doing artificial intelligence, have that integrated within their systems for years. It's not new. What's new is generative AI. And so that's the thing that is causing all this buzz. That's the thing that's causing all this anxiety. And so outside of these two buckets, we can sort of collectively say that they recognize AI has value. They've been using it. It's just this generative AI piece that is sort of causing the concern. And so ACHP is doing what we can to sort of assess where our members are, what they're thinking about, what they're concerned about, and how we can help them from a regulatory and legislative perspective.

Kelsey Waddill:

And just to sort of continue to lay that groundwork here for this next question, what are those concerns that you're hearing from the ones that are kind of slower to the uptake, really thinking about this more? Because like you said, this has been around, but then there's this new piece....

Ginny Whitman:

So I think a lot of it is the technology of generative AI and how it's going to interface with beneficiaries with members through different ways that you could integrate it within a payer system that it's not going to touch a member. And some of the plans that are less risk averse but still concerned about it, they recognize that it doesn't do a lot in administrative simplification and that there's value there. So the concern and the risk is having these models touching patient data, and so sure, there're privacy concerns, there're HIPAA concerns, there's all those sorts of things. I think there's less concern about things like generative AI hallucinations because again, you can sort of be really careful with the models that you're developing.

But I think mostly from a risk perspective, it's: "what are we doing right now with AI that we think is cool and exciting and has promise and what's happening in a space that is largely unregulated that will be regulated?" And it's very unclear right now what that regulation is going to look like and how it's going to affect the industry as a whole. I think there's a lot of interest right now in regulating AI very generally, but healthcare industry is different and it always will be different for so many reasons. And so what does regulation for AI as a whole mean for the healthcare industry, and how can we separate that out in a way that makes sense without creating the fragmentation of regulations that is so inherent to what we see in the healthcare system today?

Kelsey Waddill:

Yeah. Well, I wanted to get to the regulation piece because we are seeing that in the broader... There's so many lawsuits happening right now, social litigation about what should AI be able to do, shouldn't it be able to do? What are the guardrails here for this kind of a tool that seems pretty open-ended right now in terms of possibilities? And so I'm curious--I know you just said we are not able to exactly predict what the legislative space around this is going to look like, but where do you think that that's going to be going? Do you have any inklings about that?

Ginny Whitman:

I wish I had a better sense of where it was going. And I think the reason why everybody's struggling here right now is because you have a handful of senators proposing white papers, frameworks. You have the White House Bill of Rights, you've got FDA, you've got other administrative departments and entities all working on their own things. Those things inherently, they're fine. They're reasonable, right? They've got incredibly smart people helping them develop those things, but they don't work together. They're not happening under one umbrella. And so I think that's the thing that's going to slow us down. So I actually would be surprised if we saw regulation in this space relatively quickly, even though there is so much talk about it right now, because none of it's coordinated and you need it to be coordinated, especially within healthcare. So I don't see it happening anytime soon. I could be wrong, they could come out tomorrow with a bill that gets passed. I would be floored if that happened.

But especially on the congressional level, some of the conversations that we're having, it's, again, it's really this fundamental level conversation of you can't wrap up AI into one neat little package. And somebody who's using the phrase "AI" might be talking about just generative AI, whereas the person that's sitting across from having that conversation is thinking like, "All right, but AI means not just generative AI, it means machine learning, it means deep learning, and all these other things that aren't generative." And then you have on the super fundamental level, just plain algorithms. So when you're regulating just plain algorithms because you're so scared about generative AI, you're taking us back to the Stone Age and you're taking away all these tools and all these innovations and all these essential things that we need in a healthcare system.

So again, I think this is going to be a slow process. I think there are lots of people out there right now that would love for this to move full speed ahead, but I just don't see that happening.

Kelsey Waddill:

That makes a lot of sense, especially when you think about, like you said, healthcare is its own animal entirely. Maybe they'll get something out about AI generally, but then we have to deal with what about this space specifically where, like you said, patient data is involved and that's a huge risk. I guess I'm curious, what would you say to payers in both of those buckets right now in the more jumping in headfirst and in the more risk-averse bucket? If you were to address a payer for each of those, what recommendations would you be giving about moving forward in this space?

Ginny Whitman:

Yeah, it's funny you asked me that because we had a payer that said, "It'd be great if ACHP could create a risk framework for us. What's low risk and easy to do right now versus high risk and really hard to do?" And I was like, "Listen, what's risky today might not be risky tomorrow." So it's hard to sort of assess that.

So honestly, the best thing that payers can do when they're evaluating this is first of all, internally as a system, have a unified approach for how you're going to be thinking about AI, implementing it within your internal processes. And again, that might just be sort of business administrative simplification, not touching patient or member data. But if you are going to be going that route, okay, build pilots, be really thoughtful.

And I think the most important thing right now is your explainability around the systems that you're working on. Can you show that it's not a black box? Great. What are your inputs? What are your outputs? How is it functioning? And really, really well documenting that so that you're not in a position where you are getting slapped with a lawsuit for something that is just a tool, right?

That's the important thing to remember is AI is just a tool. Yes, it is artificial human-like intelligence, but it's "human-like." It's just a tool. People are still needed in this process. There's no sort of silver bullet that's going to have a system running insurers' plans for them, right? So yeah.

Kelsey Waddill:

As much as that might be a huge benefit if that was going to happen.

Ginny Whitman:

We're sort of like 20 years in the future, completely different looking healthcare system. Who knows? But yeah.

Kelsey Waddill:

Never know. Yeah. Well, just to kind of pivot a little bit, how has HLTH been so far? What have you been taking away from this experience? What brought you here?

Ginny Whitman:

Yeah, admittedly, this is my first HLTH. So yeah, next time I'll come with a game plan for sure.

Honestly, the biggest value here has just been meeting lots of different people. Sitting at breakfast, talking to a complete stranger and hearing what they're working on has been great. Lots of cool potential opportunities to work with people that were complete strangers yesterday, and now we have cool connections. So that's been incredible. Unfortunately, I haven't been able to get to as many of the sessions as I wanted to, so I was hoping to sit in some of these AI ones. No, I think it's just nice to hear and connect with the folks that are just as passionate about improving the system as I am. It's not everybody here. That's okay, but finding those people has been phenomenal. Also, this is such an aside, but I'm a new mom, and so I've been connecting with a lot of other new moms here at home and just not tech-related at all, but that has been really cool. So that was a really cool opportunity.

Kelsey Waddill:

Yeah, I saw they had a space for mother's set up. I was really excited to see--

Ginny Whitman:

Yeah, we were having new mom parties in the room.

Kelsey Waddill:

That's awesome. That's so cool. Oh, well, I'm so glad that we got to meet in person.

Ginny Whitman:

Likewise.

Kelsey Waddill:

And thank you for having this conversation with me.

Ginny Whitman:

Yeah, no, my pleasure. Thanks for sitting down with me.

Kelsey Waddill:

Listeners, thanks for joining us on this special episode of Healthcare Strategies. We hope you enjoyed it. If you have any thoughts or any questions that you'd like us to consider covering on the podcast, you can always reach out to me at kwaddill@techtarget.com. That's K-W-A-D-D-I-L-L@techtarget.com with any thoughts that you might have and I look forward to hearing from you. Don't forget to hit that subscribe button if you want to get more of our content on a weekly basis, including our other sort of edition of Healthcare Strategies called "Headlines." And if you feel so led, give us some stars and a positive review on Apple if you liked this episode. Until next time.