← Becker’s Healthcare Podcast
Becker’s Healthcare Podcast
Richard Clarke, Chief Data and Analytics Officer and Board Member at Highmark Health
00:18:08
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Transcript21 lines
- [00:02]
A
@ Athenahealth, we know your ambulatory practice wants healthier a healthier business, healthier care teams, and healthier patients. But the complexities of modern healthcare tech make it hard for you and your care teams to focus on what matters most. That's where athenahealth can help our AI native all in one solutions reduce administrative burdens, streamline billing and payments, and deliver critical insights when clinicians need it most. That means fewer clicks, more time for patients, and stronger bottom Practicing medicine is complex, but running a practice can be that much simpler. With Athenahealth, see how simpler is healthier at athenahealth.com.
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B
This is Laura Deardo with the Beckers Healthcare Podcast. I'm thrilled today to be joined by Richard Clark, Chief Analytics Officer at Highmark Health. Richard, it's a pleasure to have you on the podcast today.
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C
Yeah, Laura, thanks so much for having me. Glad to be here.
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B
Absolutely. Well, I'm excited for our discussion because I know you're doing so much at Highmark Health, and really it's an exciting time to be in healthcare right now. But before we dive into our broader discussion, I'm wondering, can you tell us a little bit about yourself and your background?
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C
Yeah, sure. Would love to do so. So, yeah, as you mentioned, I'm the Chief Analytics Officer here at Highmark Health. We're a large diversified healthcare company based in Pittsburgh, Pennsylvania. So I have a Blue Cross Blue Shielder branded health plan, Allegheny Health Network, or a hospital system, a dental company, United Concordia, Dental Stop Loss, and a technology firm. I've been here for about 10 years. Prior to that I was at McKinsey and Company for about a decade. And prior to that I was trained As a neuroscientist, PhD was studying memory and movement disorders. So it's been kind of exciting lately to go back to maybe some of those early PhD days to be thinking about neural networks and some of the work that we were doing back then are so relevant now for enterprise concepts.
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B
Absolutely. Wow, that's an amazing background and it really sets you up for success, as you mentioned, in today's world and really was coming to the forefront with technology, AI and more. So I'm curious, what are the top two to three issues that you're focused on right now? What's top of mind for you?
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C
Yeah, there's just so much going on, as you kind of have mentioned, and there's many days I feel like this kind of wave of new technology and generative AI is just so, you know, custom fit for a lot of the challenges that we are you know, facing in health care. And certainly there are, you know, there are a lot, you know, very focused on, you know, affordability, you know, these days. And so we're working really hard from an AI perspective on how we can, you know, deliver more efficient and kind of better experiences for our members. So lots of, lots of focus in terms of, you know, things like our, you know, call center. Of course, we're also really focused on, you know, ambient listening and how we can roll that out kind of not only, you know, in the clinical setting at Allegheny Health Network with our partnership with a bridge, but also, you know, in other settings. Right. In terms of our care management in the health plan or in our, you know, call center. And then, you know, finally we're really focused on just building AI literacy across the entire company. Right. How do we bring these tools to all 40,000 plus employees across Highmark? Through our partnership with Google Cloud. And a lot of the work that we're doing with, again, kind of bringing not only generative AI chat, but kind of bring your own data through some of our scalable rag models and eventually kind of bring in a gentic AI to all of our employees.
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B
That's amazing to hear and really cool to have that opportunity to look at the technology, see how it's evolving so quickly in the space, and then find those healthcare applications, both on the clinical side as well as on the operational side, that make the biggest difference. And I'm curious, from your perspective, talking about building that AI literacy across the company. I know that's easier said than done. What are some of the things that you've done at Highmark that truly have made a difference in helping the whole team understand AI and how it can be useful to them?
- [04:08]
C
Yeah, well, I'm not sure we're all the way there, but I appreciate that. And, you know, it's something I'm really proud of and something we've been very focused on. I would say it comes down to, you know, two or three things. Right. So one is we were very quick to establish an AI center of Excellence that is, you know, it is in my organization. But, you know, we've been very, really clear that AI is a team sport. Right. And it's something that everyone needs to participate in. And that AI COE has been working really hard, really, as a broad adoption effort to kind of upskill folks in terms of capability. So we have AI consultants that are working with our various areas to kind of bring AI into their strategies. We've established a AI Ambassador network where we're giving you know, folks within the different business areas, functional areas, kind of specialized training to make sure that they both understand the tools, understand our processes, help navigate things like responsible AI governance, tell stories, tell a ton of stories, success stories, you know, because one thing we find is that the kind of horizontal capabilities are so powerful here where we identify how someone solved a certain problem. There's certainly someone else at the company has a problem that looks the same, that they can benefit from that knowledge. And then finally, you know, from a leadership perspective, you know, we believe that role modeling is so important, right. And so we've done a lot of work in terms of bringing, you know, again, stories and examples to our all employee leadings, to our leadership meetings. We do tons of town halls to, to not just as I tell the team all, all the time, don't tell people we're funny, tell them a joke. So we show people how these things work, do a ton of hands on keys. And finally, from an incentive perspective, you know, all VPs and up at our company have a go, you know, creating innovation and impact within their area using generative AI, you know, and that's kind of contemplated in their annual performance review. So we're really trying to hit all those dimensions of giving people the skills and capabilities, kind of role modeling and showing them how it can be done and then supporting that with the incentives, you know, required to really make people jump in and say, hey, you know, kind of I have to be part of the innovation, not just wait for it to happen to me.
- [06:20]
B
I love that it seems such a proactive way to go after the transformation and make sure that the team has ownership over what they're doing. And like you said, really jumping into that innovation, I think that can sometimes be a struggle, but I love that mindset and approach to really scale in a meaningful way. Now I think too, you know, when we're looking at AI and bringing that into an organization, another point of discussion that we hear a lot about is making the right decisions on investments and, you know, looking at how do you measure the success of some of these AI technologies that you're bringing on board. So what does that look like for you at Highmark? How do you think about the performance of different AI technologies in generative AI and then how it impacts the organization overall?
- [07:02]
C
Yeah, this is such a important topic. Right. You know, obviously the topic of ROI is kind of on everyone's mind and you know, yes, of course we, you know, measure that. We do take a real portfolio approach. Right. And there are plenty of things that we do with these tools where, you know, it would probably take us more time to try to measure the impact than it would just enabling it to happen. And so again, you know, from a broad adoption perspective, we're just looking at that total body of work and saying, is that kind of giving us a higher return than the investment? And we see, you know, significant ROI there, 3 to 1, 5 to 1, kind of in that range, not to mention the kind of strategic capabilities that it gives us. And then, you know, when we then go after big use cases, obviously then we can kind of on a more use case basis, get very serious about roi, thinking about, well, what is the benefit from experience? What is the benefit benefit from, you know, cost reduction or kind of revenue increase making care more affordable. And you know, I think that's the real next horizon here of, you know, we have lots of proven use cases around, you know, productivity, around efficiency, around experience. And you know, can we get to the point where it can create kind of meaningful improvements in affordability from a medical cost perspective? I think that's the next, you know, the next horizon for us. And you know, the other thing we talk a lot about is, you know, how do we, how do we think about partnership here, right? And everyone has the kind of the build versus buy decision, which, you know, is certainly, you know, challenging. And I guess the, the only thing I'll provide there is that for us at least it's really not like a binary decision. Right. We're really trying to make sure that we have a nimble system where we can be testing various options, bringing in kind of what we think works best right now, but recognizing that everything is moving so quickly that in six months that that thing might not be the best. And you know, we're going to have to have a nimble system where we can swap out solutions, where it's okay if we built something in, in six or nine months, there's a better kind of commercial option, then we'll get rid of that and swap it in. And you know, that's both a kind of technology ecosystem question, but it's also a mindset question of how can everyone kind of get okay with that and how can we be nimble enough to, to kind of not lock into decisions? I'll tell you, that has been a shift, especially with how fast everything is moving.
- [09:26]
B
I can imagine. So, I mean, you know, it's just been like the speed of lightning almost to see how the technology has evolved and then creating that mindset, you know, that mindset shift, as you mentioned, is Huge and a challenge. Now, looking ahead, what are some of the big opportunities that you see for growth? How are you continuing to help the organization and your leadership team see what needs to happen to be that kind of technology, technology forward organization that I know you want to be?
- [09:54]
C
Yeah, you know, there's not to just jump on the kind of hype cycle on it. But truly agentic AI is, you know, is a step change. Right. And we can all see the potential and you know, we've had some success with some, you know, single use agents. But how do we really prepare both our employees to be thinking agent first and how we can redesign workflows using agents. But then how do we prepare our infrastructure, you know, to enable that, you know, these agents are only going to be as good as the tools and systems that they can access. So how do we, you know, take these legacy systems and make them accessible? How do we kind of take our workflows and make them, you know, accessible to AI agents? And then, you know, that's just thinking internally. But then how do I think the real, the real step change is going to be when we start having interactions with personal agents that it feels inevitable are going to be created in terms of, you know, personal health agents, et cetera, et cetera. So I think there's a whole body of work and we have an entire cross functional team stood up thinking about that, both from kind of a tech risk, you know, compliance perspective, but also from kind of an opportunity perspective from the customer patient, you know, lens. Right. Where are those opportunities to really reimagine the interface between either payer and patient, between payer and provider, between provider and patient, you know, et cetera, et cetera. And I just think there's a tremendous amount of transformation and impact that is possible there. But I also don't want to kind of oversimplify how the challenges that we're going to have to, you know, solve to really get there.
- [11:50]
B
Absolutely, that makes a lot of sense and you know, really an amazing picture that you're painting when you think about agentic AI, when you think about the possibilities. But then looking at the risk, looking at the challenges, I can imagine, you know, trying to make sure you've got everybody aligned around the same vision in moving forward in a smart way. What do you need to do? What are some of those challenges that you are seeing and how are you planning now to overcome them?
- [12:15]
C
Yeah, I mean, part of this is just getting at bats, right? Like how do we get to iteration quickly, how do we get to market with some of these because there's the conceptual framing of the problem. But you know, the, the problems become much kind of more clear and frankly solvable when you're, you know, actually doing it. And so for us that means let's pick some lower risk use cases where we can get out there and put these agents to work. The problems then like I said, reveal themselves and then it's all about how quickly we can move through them and prepare our then for maybe some of the more challenging use cases. Right. And by that I mean, you know, how can we pick internally facing, kind of operational, with low kind of financial risk transactions to figure out a lot of this to then move to that inevitable place where we actually have agents interfacing with our members and patients on clinically related topics. And so I think, you know, that for us is the biggest thing is how do we get to that iteration. And then some of the challenges that are emerging, right, are exactly. You know, there's technology infrastructure problems, right. We all sit on these massively legacy systems. So how do you make those available for agentic workflows? There's new platforms and technologies that we need to procure, right. Agent development platforms as well as kind of orchestration, you know, layers. And then probably like in all of these things, the most challenging are the kind of people, cultural issues. How do we kind of redesign workflows, how do we redesign roles, right. How do we prepare our managers for, for managing this hybrid digital and human workforce? And we're talking a lot about that. But you know, that's really going to become much more real again, like I said, when it's starting to be done right, when we get to the true kind of iteration, you know, step. And so for us it's all about setting that up. How do we capture learnings, how do we disseminate learnings? Hopefully, how do we not, you know, repeat the same mistake twice? Because for sure there'll be plenty of those mistakes. So like I said, the two words that we are so focused on are spe iteration. Right. And that's where we're going to kind of keep our focus.
- [14:20]
B
That makes a lot of sense. Thank you so much. This has been such a fascinating conversation and really forward looking at as we appear into healthcare and think about it in a more smart and strategic way. Now, before we wrap up, I wanted to ask one more question on leadership. What do you think it will take in order to lead a thriving organization over the next two, three, five years? You know, looking ahead, I know it's hard to see exactly how things will shape up. But from your perspective. Perspective, what do leaders need to do and to be right now in order to build that kind of organization that can thrive in the future?
- [14:53]
C
Yeah. Like you said, it's so hard, Right. Because things are moving so quickly. I guess I. I would keep it very simple and just say two things. Right. It seems like the dominant strategy right now is a adoption of a mindset of continuous learning and a growth mindset. Right. And, you know, I think it's so important that there's still some external orientation of leaders, again, that kind of having a growth mindset, having a mindset of continuous learning, just to go out and see. See the state of the possible and figure out how can we bring that into our organization. So that's, you know, that's certainly one that I think is absolutely critical. I'm reading more articles and kind of seeing more demos now than I have, you know, historically. Thankfully, I have things like deep research and other tools that make that kind of easier. You know, for me, you know, the second would be like, like I said, iteration and practice. Like, folks need to be using these tools themselves. I don't know how you can expect, you know, your organization to go through this transformation if you're not transforming yourself. Right. So I spend a lot of time also thinking about how to walk the walk, you know, on that, and then finally just keeping the customer centricity there. Right. It's one of our core values is customer first. And so how do we think about, you know, the value that we're creating for our customers? How do we think about the jobs, you know, their jobs to be done, that we're making easier, you know, for them. And I think if you bring those things together, right, that kind of mindset of continuous learning with the customer centricity, that that in general can deal with any of the kind of disruption and innovation, you know, that is out there. Obviously a little easier said than done, especially when everything's. Things seem so busy. But if you're not carving out the time to do those things, I think, you know, innovation might pass you by.
- [16:45]
B
And nobody wants that. Richard, thank you so much for joining us on the podcast today. This has been a really fun conversation. I've learned a lot, and I appreciate your passion and energy for the field. Thank you again and look forward to connecting with you again soon.
- [16:57]
C
Yeah, and thank you so much for having me. Like you said, this is exciting times and, you know, hopefully we'll keep the dialogue going. So thanks, Laura. Appreciate it.
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B
It.
- [17:06]
A
At athenahealth we know your ambulatory practice wants healthier a healthier business, healthier care teams, and healthier patients. But the complexities of modern healthcare tech make it hard for you and your care teams to focus on what matters most. That's where athenahealth can help our AI native all in one solutions reduce administrative burdens, streamline billing and payments, and deliver critical insights when clinicians need it most. That means fewer clicks, more time for patients, and stronger bottom lines. Practicing medicine is complex, but running a practice can be that much simpler with Athenahealth. See how simpler is healthier@athenahealth.com.