Speaker 0: Hi, everyone. This is Lucas Voss with Becker's Healthcare. Thanks so much for tuning in to the Becker's Healthcare podcast series. It's great to have you. Today, we're talking about how health plans can build scalable high performance infrastructure to support growing complexity, enable AI, and stay ahead in the certainly rapidly evolving landscape that we're all facing right now.

And joining me for today's discussion, very excited to have him is Rob Duffy. He's the chief technology officer at HealthEdge. Rob, thanks so much for being here today. It's great to have you.

Speaker 1: Yeah. Welcome, to Ben's point. Thank you very much. I really, really appreciate the opportunity to talk to you today.

Speaker 0: Yeah. Absolutely. I do wanna start with introductions here really quickly before we hop into the meat of this conversation. If you just wanna briefly introduce yourself, who you are, what you do at HealthEdge, and, what's going on with you.

Speaker 1: Amazing. So I'm Rob Duffy. I'm the chief technology officer at HealthEdge. My role is really to execute on it on the product road map in the most efficient and the high velocity way. And what we do is we, you know, as an engineering team, we really think about how we can leverage AI, how we can leverage cloud native infrastructure, how we can leverage all the things that are out there and available to us to really scale our operations and meet our customers through their scaling journey and make sure that they're getting the most leverage out of, the underlying technology and then also AI and anything that we build, from an AI perspective.

So HealthEdge, for those those of you that aren't familiar with us, we are a, initially, we were a core admin platform, that does claims processing. We're a company called HealthEdge at the time. We acquired three other companies, GuidingCare, utilization management, and care management platform, Source, a, payment integrity platform, and then Wellframe, a member engagement platform. And then recently, we merged with Healthproof, who are a business process as a service, organization. And together, we have become HealthEdge's combined entity.

And what that enables us to do is provide claims processing as a commodity to our customers. And what we can do because of our scale and because of our technology and because of our labor arbitrage, we can actually guarantee outcomes, guarantee the same claims processing outcomes for a a discounted rate, than the the ability for our our plans to actually process on their own. So, you know, on a per member per month basis, we are able to guarantee the same outcomes from claims processing to our customers, and do that at a discount. And the large portion of that, obviously, which we'll talk about in a little bit here is not only scale, but also, our ability to leverage AI in order to make bring more and more efficiency to the claims processing and claims operations.

Speaker 0: Yeah. I was gonna say we'll we'll walk through the way this works here in a little bit detail, but you mentioned something very important, which is high velocity. It's it's a high velocity market. Certainly, when we talk about, again, that rapidly evolving landscape, I'd love to touch on this a little bit more because, again, we know that health plans are dealing with a lot of pressure, right, growing membership, complex care models, and then you add regulatory demands onto that, I I think it's really crucial. From where you're sitting right now, what does it actually look like when a health plan's claims processing infrastructure starts to buckle under all of this weight that we're experiencing right now?

Speaker 1: I mean, you look at at any health plan right now, you know, medical loss ratio shooting through the roof either through, you know, very expensive drugs, more utilization, you know, people just getting, an aging population or even people getting smarter about their health care. I mean, the the impact of AI and chat GPT has meant that people are actually now going and sort of self diagnosing and seeing doctors where they where they wouldn't have seen before. So utilization is increasing. You know, cost of drugs is increasing. And then you have this interesting dynamic where on the revenue cycle management side of things, providers are using AI to code, their claims more effectively, and that's causing an increase in the in the the medical loss ratio.

So you you think about that bucket of, you know, cost. There's really increasing in in terms of, the the MLR for our for our payers. And And then the other bucket of cost is the administrative loss ratio, which is like, how much does it just cost to own and operate the plan, process claims, do everything? And that bucket, I think, is just absolutely ripe for for disruption from AI tools, from automation, from scalable modern platforms. And that's really what we wanna bring to health care plans is a is a platform for scalability and a platform for innovation.

And one where we can innovate on behalf of our customers and invent things using, all of the tools that are available us today to us today from an automation perspective, from an AI perspective, and just continually drive that ALR cost down so that our our plans, our customers can, you know, redivert some of those savings back to, you know, better health care outcomes, better customer, better, you know, patient experience, and really maintain their business and maintain their margins in the face of increasing it a lot.

Speaker 0: You mentioned innovation, which is certainly really crucial work from where you're sitting. You're innovating every single day. That's part of your job. You at HealthEdge and you certainly your team as well, you've reached an incredible milestone specifically with AWS, which most of our listeners are obviously familiar with, a big player in the space, in a single instance handling the equivalent of 40,000,000 members. And, again, you cut that latency by more than half at that same time while also going through that process.

Can you just walk us through what this meant for you? And, again, because you improved scale and speed at the same time, which is really, really hard to do.

Speaker 1: Yeah. And, you know, we made a decision to go all in with AWS, about eighteen months ago now. We said, hey. There's no point I was pursuing a multi cloud strategy. It's just diluting not only our purchasing power, but also the partnership opportunity we have with our cloud provider.

And part of that was an acknowledgment that going all in with a with a single provider would also enable us to get really, really familiar with everything that would that provide that, cloud provider was able to offer us and really develop deep expertise and partnership with them in order to bring these outcomes to our customers. And we very early on realized that, you know, we've been pushing the boundaries of scalability using a physical hardware mindset. Right? And then we can we were previously in a private cloud and a data center virtualized there. And whenever we thought about scalability, it was like, you know, let's buy some more machines, long lead time, larger machines, whatever.

Right? We we we would scale to the point where we could afford the infrastructure and and, you know, it's expensive infrastructure when it's in in a data center. So we would so we're thinking about it in a in a very non high performance compute way and then more of a sort of, like, horizontally scaling traditional data center way. When we moved to the cloud, all of a sudden we were able to take advantage of some new, you know, AWS silicon, the Graviton chips, the high performance compute instances, and we're able to dynamically scale them to meet the demands of our application and drive where we were able to scale to way beyond where we had previously been able to. And I think that's just a a a a a great indication of how deeply partnered we are with AWS and then also the the ability for that partnership to bring true scalability and and true outcomes for us from a technology perspective.

And you mentioned the latency there. I mean, really, you know, AWS is a a has deep expertise in how to get their infrastructure to talk to each other and how to, you know, continuously fight against the speed of light to to to bring latency down between their their applications and between their services. And that really shows when you look at things like the network IO, the latency, the disk. You know, we had our our database administered getting a bit technical, but we had our database administered administrator, incredible lady called Manu. And she was, like, having a little bit concerned about the IO.

And then after we routed, the the ability to write information to the disk, and then after we moved to the cloud, she was like, oh, wow. We're gonna be fine. This is amazing. It's it's much better than we're able to achieve. So I I think, you know, maintaining your own infrastructure, you can do well.

I think moving to a a cloud hyperscaler and really leaning into one cloud hyperscaler, you can do amazing and great things with them because they will also invest in you, and you can invest in that partnership together.

Speaker 0: Applying this to the use case in and of itself, just as a quick follow-up here. Right? Why does the single instance that you just described make such a difference from a day to day operations perspective? What difference does it make for day to day operations?

Speaker 1: So traditionally, for a health plan, you would have different lines of businesses, maybe different regions on multiple different core admin platforms. So you have the the the same system, sometimes a different system, sometimes the same system, but a different version of the same system running in multiple places across across the organization. And for us, when we're trying to bring down the cost of operations and we're trying to commoditize claims processing and really sort of continue to lower the cost of operations, having multiple different systems and multiple different tools and multiple different instances really means that you can't get economies of scale or leverage from the investment that you have in that technology. And the same is true for for any plan. You know, if you look at a plan that, has been around for any length of time, there's gonna be many, many different systems, and they're gonna be thinking about this consolidation into one.

When you can consolidate all these different things into one, it brings a tremendous amount of efficiency, and it brings a, you know, it it brings lower cost in the long run because you're not maintaining multiple different systems. You're not maintaining multiple different workforces that have to integrate with these different systems. You can get a single view of your data. You can start to talk about events across these, diff, you know, the different customer life cycles that are triggering things on your data platform. You don't have to worry about integrations.

Like, each of these systems has to be integrated with up to 120 different inside internal tools. Right? So now all of a sudden, if you have 10 systems, you have 1,200 integrations that you have to maintain. You're shuffling data everywhere from different things. So it's really a a a grand simplification of the internal architecture of the health plan and the and the claims, operating system.

And that enables you to do much more interesting things with AI, with data, with your visibility into, you know, how your business is performing with the latest BI tools that you can query with natural language. And it removes this sort of diaspora of systems that are very hard to integrate and and gather intelligence out of and and provides you really with an edge to continuously optimize your business and continuously, you know, reduce the cost of outcomes.

Speaker 0: A lot of leaders are pointing to that piece specifically, the integration part and the infrastructure piece as a crucial enabler for health care as we move into 2027 and beyond. If that's not the case, then organizations are going to have an issue moving forward. And I wanna stick with that theme a little bit because, again, I feel like especially with AI, and you've talked about the AI native enterprise, so to speak. Right? How does that infrastructure work then lay the groundwork for organizations to have AI driven automation in place?

And, again, just touching back on on what we've just talked about, what's the risk of Healthfence that just try to bolt on, and they're not establishing that infrastructure that we've just talked about.

Speaker 1: Yeah. There's a lot of really great demos out there for, you know, AI startups that will bolt something on top of the system of record. You know? And they'll they'll get to a really good, yeah, you know, demo maybe in a couple of weeks, and they'll show you it. And I'll be like, this is proof concept, and you'll get really excited about the fact that that that this could actually scale out across, you know, the entire the the entire set of use cases that you want to deploy this tool in.

And the reality is it that it's not gonna it's not gonna scale out because, ultimately, you have the system of record. And in order for you to expand all the use cases, you would have to, you know, take the data that's in the system of record and march out. And it's like it it becomes it becomes a nightmare anything beyond the first one or two use cases. And, you know, we believe that by deeply integrating AI into our platform and by providing a platform that is equipping AI tooling on top of the system record and inside the system record, you can get much more efficiency out of that, and you can get a much higher return on your investment from AI. And you can do it a lot faster than if you're just still marshaling all these different tools and you're trying to, you know, add bolt ons on top of the system of record.

So our belief is that we can move incredibly quickly to your point earlier on about velocity in deploying AI capabilities to, you know, reduce the amount of dependence we have on on humans and human effort clicking through UIs and and moving information left and right, then we can very, very rapidly bring a truly integrated AI toolkit that is deeply connected to the system of record. And again, that that single, platform and single instance enables us to do that. We can build, you know, these these tools that enable AIs to consume information, enable AI agents to act within the within the system of record, and work in in concert with each other and with all of the other systems in the ecosystem rather than being something that's sort of bolted on from the outside.

Speaker 0: Realistically, how much time do we have then to rethink these legacy payer platforms before we hit that hard ceiling. Right? And from your perspective, from the conversations you were having with health system leaders across the country, what are the questions that leaders need to ask right now that they need to ask their technology partners to avoid running into some of the issues that we've highlighted?

Speaker 1: You know, I might I tie it back to the the performance of the company. Right? Like, when you think about and if everything that we do in technology, it's really about reducing the cost of operations. Right? Like, it's how we continually driving down the operating costs.

And if I was a, you know, a business leader at a plan, the real question I would be asking is, are we going to be able to accelerate the savings that we want to realize in our administrative loss ratio fast enough to keep up with the competition? And are we gonna be able to invest enough in it to be able to deliver true outcomes and true value, or should we partner with someone who's gonna do that and who's gonna guarantee that that cost is gonna come back and who's gonna continue to invest with the best and brightest and get, you know, huge leverage out of partnerships with AWS much broader than individual plans would be able to and and hitch onto that wagon. And I think, like, that that's the way I'd be thinking about it. So can I internally develop the skill set and rapidly ship and, you know, put all the pieces in place to guarantee that my business is gonna stay healthy and that my administrative spot for ratio is gonna continue to decline, or why not partner with someone who's gonna guarantee that? And then I can focus on things like member engagement, health care outcomes, marketing, you know, taking care of the population.

Speaker 0: Because if you do that, then you're not going to run out of runway in 2026 and 2027. We're just very crucial, especially in health care. Rob, it's so great to have you on. I just wanna give the floor to you too. Is there anything else that you wanna touch on?

I know we've we've hit on a lot of numbers here. Again, I feel like this is about confidence for health plans, but just wanna hear any final thoughts that you have for our listeners.

Speaker 1: No. I I think, you know, it's always a pleasure to come on the on the Beckett's podcast and and talk about the the future and the future of AI. And it's a very exciting but also scary time. You know, there's excitement in the possibility, but there is the fear of not moving fast enough. And, you know, what we do is help our plans and help our customers feel like they're moving fast enough.

And I think that brings an enormous amount of excitement and energy to to our customers and ourselves.

Speaker 0: Velocity is the word of the day for us today. Rob, so great to have you. Thanks so much for your time. Thank you. Take care.

We also want to thank our podcast sponsor, HealthEdge. You can tune in to more podcasts from Becker's Healthcare by visiting our podcast page at beckershospitalreview.com.