Exploring AI and Innovation in Healthcare: A Conversation with Patty Hayward

[00:00:08] We are on HIT Like a Girl Podcast. I'm Demiradeva and I'm here with Patti Hayward. Patti, let's start with a quick intro. Can you tell us about your background and your role in healthcare? First of all, thanks for having me. I love HIT Like a Girl. It's a great podcast. A little bit about my background. I've been in healthcare IT for 25 years. I've worked for companies like McKesson, Aetna, a lot of population health work that I've done over the years.

[00:00:34] A lot of helping folks, you know, automate manual process, particularly focused on sort of the payer and provider world. I actually started my life as a scientist. So... Tell us about that. Yes, I have a master's degree in conservation biology. So I did a lot of work with fire ecology, funny enough. We can, the LA fires are always really interesting to think about. But yeah, I started my world there and then really, you know, made my way over into healthcare around solving problems.

[00:01:03] I've always taken that perspective of how can we really look through and get to the core aspect of things and then what are the variables we need to constrain and how can we work through different aspects with executive teams and things like that. So that's kind of how I ended up over in the healthcare space and, you know, have a lot of passion for change. How can we really make this system better and work better for everybody? Given your background in science, I'm curious, how much of healthcare is science versus art?

[00:01:32] Oh gosh, what a question. There's a lot of science, obviously. There's a huge amount of it. But there's also, you know, a lot of art and nuance and subtleties and things that you just have to understand and diagnose and sort of have hands on and see. So there's a lot of both.

[00:01:50] I mean, the best doctors in the world are not just reading out of a book and here's the diagnose. They understand and see the in-between space, which is kind of, I think most people look at as the art. So yeah, I think there's a lot of both. Yeah. We're here at Vive discussing what's coming with the new administration. And I'm curious from your perspective, what are the biggest policy shifts or industry changes on the horizon? And again, when it comes to policy, how much of that is science versus art?

[00:02:19] First of all, I think there's a lot of, there's some great things that I think we can see. And that's really allowing AI to flourish, which I think was a big change from the last administration and looking at, hey, let's really see what this new technology can accomplish.

[00:02:37] I think there's some good and bad with that. And I think there's a lot of meaningful purpose that I think the organizations are going to really need to think about how they employ AI in order to avoid things like bias. And obviously security is a huge aspect of a regulated industry like healthcare. We need to be good stewards of the data that we have and that we hold and making sure that that is protected. So I think there's a lot of things that need to be purposefully thought through.

[00:03:07] And I'm always very interested in talking with my partners about what it is that they're thinking about and what's worrying them. And I think those are two big areas that they're really trying to utilize while at the same time really taking advantage of what is an amazing technology breakthrough. I'm very curious, given your experience in the peer space and some of the other spaces, AI is evolving rapidly.

[00:03:31] And I'm curious, what are the most important applications of AI in those spaces that you're tracking? I tend to spend a lot of time, obviously, with patient, member, consumer experience. So I'll talk about those areas because I'm not as up to speed on sort of all, I mean, AI is everywhere. You just walk around the show floor and if you don't hit AI in the first two minutes, I think you get a penalty.

[00:03:57] But, you know, AI, especially I think the new large language models and the ability to do things like agentic AI. I mean, that's what I'm really excited about is this ability. First of all, no one likes to talk to a bot ever. I've never heard anyone go, wow, that was the best bot experience in my life. But really, the ability to actually have a conversation now with these agentic AI pieces is really great.

[00:04:21] The ability to have that, I really am excited about because what that does is allow us to take some of the easy things that we need to do and give time back to our human agents who then can solve more complicated problems. What regulatory or policy changes do you think are needed to support responsible AI adoption in healthcare? So I'm not sure about the regulatory environment like itself and what the laws need to be.

[00:04:49] As I said before, I think it's really important to think about adoption and regulate a bit of self-regulation. I am always big on we have to allow for innovation as well as protect. So the two areas, like I said previously, which are bias. With any sort of programming, the person that's programming it obviously is going to pour themselves into what they think is the right thing. Non-intentions, we need to be aware of potential biases.

[00:05:18] And then security is obviously a huge thing. And really knowing that you're interacting with generative AI, I think is important to know. So knowledge, being able to just say, look, hey, this bot is powered by, that sort of thing. So people understand and have choices about how they interact with these different health systems or with a payer or a life sciences company, a pharma company. Just understanding how your data is being used, I feel, is a really important aspect of all of that.

[00:05:47] So as we start to think about regulation, I know we're all sort of waiting to see where the federal government goes with all of this, if they do. But I do believe the states will start to have some regulation as well. There's already regulation in place in many states. So I'm sure that we're going to see, depending on where you're doing business, different aspects of that come in. I think the first and foremost has to be security.

[00:06:12] I think that's going to be the big thing is how do we keep the data safe that we're interacting with and so that it doesn't get broadcast out. There's just, you know, along with all of our great and genius innovation that's happening in industry, you're going to see a huge amount of innovation on the dark side. It's so much easier to develop these bots. And it's so much easier to develop, you know, the bad actors to develop this as well. It's no longer the guy in the hoodie in the basement who's super genius at coding.

[00:06:43] Unfortunately, you're going to unleash these tools on bad actors across the spectrum. So I'm hearing there's, I would like to double click on two of the spaces. So there's implications on the folks that are creating these applications. And I'm curious, is it about education? Is it training of like how they can remove their bias from things? Like what are the ways in which we can create better tools?

[00:07:10] And then I would also love to talk about the patient side. And so we can do things to communicate, powered by, et cetera, et cetera. But what type of information should a patient see so that they can make an informed decision whether or not to provide this information or interact with this bot? I'll take the first one first, which is how do we keep bias? How do we can be intentional about trying to exclude as much bias as possible? The great thing about these models is that they continue to learn.

[00:07:39] So I think as you have different folks involved and you have different interactions with the community, you're going to see different input coming in and you're going to be able to monitor the responses and be able to say, okay, that was probably not the experience we wanted folks to have. And be able to work through that so that we can be more intentional about taking bias out as much as possible. So I think there's some self-healing that goes on there with these models, which is fantastic.

[00:08:06] Probably better than anything we've seen to date because you just, you know, being able to feed it all of that information, I think is great. As we think about consent, I think, you know, similar to what we've done with a lot of things is allow people to sort of have checkboxes of like, okay, you know, hey, look, your data is being used XYZ, opt in, opt out. You know, you guys can decide if you want to be a part of, you know, how these things work. I think people tend to self-regulate anyway.

[00:08:34] Like if a bot comes in and you start talking to it, a lot of times people just hang up or they, you know, yell agent 4,000 times into the phone and then get to a human. And I think those are all important is to make sure that we're supporting folks regardless. I know for me, I tend to try to interact with as many bots as I can these days, which is weird.

[00:08:54] But I like to understand how folks are evolving and what they're doing and how they're programming things a little bit more differently so that I can see what we should be doing. You know, if there's anything really innovative out there. You just had a call with Delta. I love their experience. I always have. I think that, you know, they're probably one of the best when you call them and they know who you are. They know that you're calling because you have a flight that's, you know, that day. And hey, is there an impact to that flight? Let me help you reschedule.

[00:09:22] And you never have to talk to a person, which I really appreciate. Sometimes, you know, we're busy people. You're doing a lot of things and you can't always answer the phone when someone calls you back. So I like the self-service aspect of things when possible. I am very cognizant that healthcare is highly complex.

[00:09:40] And so I'm a big advocate of how do we take time back for our human agents so that they can do the things that are more complicated with our patients and our families so that they can be guided. I don't really want the ask answer thing anymore. I want us to be able to be proactive, to guide people along their journeys, to help them do the things that they should to stay healthy.

[00:10:05] And as a benefit to the health systems, that allows them to meet their goals and objectives financially, right, with these value-based care models. So I think that a lot of this technology that's come out recently is going to really help, if employed correctly, to do a lot of those things. You know, I think we're not trying to solve world peace and have everything automated. I think that's a mistake as well. So I think it's really important that we're intentional on what we're trying to accomplish and how we roll this stuff out and where we go next.

[00:10:35] You mentioned bots as one of the innovations. I'm curious, though, what the differences are between different age groups or even for women. I mean, are there things that we as women should be aware of or paying attention? Or are there certain technologies you've seen that are rooted in AI that are really helpful for women specifically? A couple of things. One is our Medicare population is becoming more and more tech savvy as we age into Medicare, right?

[00:11:04] So I think folks like my dad's age, you know, 84, 85, they're going to be less technology tolerant. And you're going to want to curate a different experience for folks that are a little older. And also just, you know, being able to see all the numbers and do all the things gets more challenging as you get older. But those that are just aging into Medicare, you know, these are the guys that invented the smartphone. You know, this myth that seniors don't like technology is not accurate any longer.

[00:11:32] But again, as you get older, I think there's more need for human interaction. You know, as far as women, most women are responsible for their family's medical care. Let's just face it. We as moms tend to call and make all the appointments for everybody, even my 25-year-old son. So it happens a lot. We still do a lot of things for our families. And I think that as we go through some of this technology, again, again, it's the, like,

[00:11:59] I want to make sure I understand where this data is going so that I can protect my family's data and information. Because you don't want your two-year-old child's social security number out there on the dark web. Because you probably won't even know that it's been stolen. So it's really important that we're protecting of those things. And that we employ a lot of the technology that actually helps us monitor that stuff, too. But I don't think that, you know, we're, at least I don't personally have huge fear that as a woman,

[00:12:28] this stuff is going to be inherently biased by the male viewpoint. But that's probably because I'm in tech and I see it and I'm not feeling that. But I think as you get into some of the other sort of cultural feeling, like if you're in a healthcare desert, if you're out there in the inner cities and those populations receive technology really differently. That's a really important thing to think through. Depending on who your target audience is and where your patients sit.

[00:12:57] People have very different viewpoints of technology at that point. As an innovator, that's critical. Yes. I'm curious as a policymaker, how should I think about this? What are some things, like what would it be if I could, if you have one message to policymakers, what would that be? As we think about the different populations, I think that it would be great to try to have some empathy for what some of these folks are going through.

[00:13:23] I'm not sure we're going to get that from this administration, but I do think it's important. And I hope that we start to look at it in a way that's beneficial, both to them and to bringing people up and allowing them to flourish, I think is really important and that we can be, I think it's going to end up being less of a policy and more of a, we have to be intentional as the caregivers in those areas. I really think that it's going to come down to the folks that are serving those patients and families.

[00:13:54] They're going to have to be the good stewards. I don't think it's going to be legislated. Yeah. And with women, how to step up and get educated and apply all the things that we're learning. Yeah. Patty, this has been amazing. I'm curious, where can our audience find and follow your work? LinkedIn is a big area. You know, a lot of the stuff goes on there and links to it. So follow me on LinkedIn. We'd love to have you involved in the conversation. Thanks, Patty. Thanks for listening.

[00:14:22] You can learn more about us or this guest by going to our website or visiting us on any of the socials with the handle HitLikeAGirlPod. Thanks again. See you soon. Again, thank you so much for listening to the Hit Like a Girl podcast. I am truly grateful for you and I'm wondering if you could do me a quick favor. Would you be willing to follow or subscribe to this podcast or maybe leave us a rating or review? Or if you're feeling extra generous, would you share this episode on your Instagram stories or with a friend?

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