Hello, everyone, and thank you for tuning in into the Becker health care podcast series. Today, I am pleased to be joined Barr as we focus on payers and some of the administrative challenges they are facing in light of Cms regulations, pertaining to Medicare Advantage, including compliance with state and federal prior authorization, requirements, and interoperability and increasing transparency and accountability reporting.
These changes are accelerating the need for health health plan payers to accelerate, optimize and automate many administrative functions would some estimate to make up 25 percent of the 4700000000000.0 total health spending in the Us. Before I begin, I'm going to introduce today's speaker, Paul, Senior industry practice director of view uipath. Uipath is a enterprise scale intelligent automation platform.
That combines Id, Rpa, process mining, task mining, process, orchestration, and Ai ml based capabilities including communications mining for Nlp and unstructured data processing. Uipath customers appreciate the scalability, flexibility of the solution, along with ease of use in configuring and training ml models. Paul, thank you so much for joining us today. How are you? Thanks for happy me, Terrific. Yeah. Wonderful. What's 2 gonna started. I first wanna thank you again for joining the podcast.
He's also a bit more about yourself and a little more about you uipath. Sure. So I've actually had the privilege of serving in the health care industry now for upwards of 35 years. And I've had the opportunity to really traverse the various sectors. I started in medical education, jumped over into medical information systems. And then got into disease management, jumped over then into consulting where I spent the better part of 14 years with a big 4 firm, consulting to the various sectors
of health care. And by that, I mean, bio pharma, payers and providers really working with them to optimize their business. And then spent the last 6 years really up these this intersection of High tech and healthcare care with some of the hyper dealers leading industry strategy for companies like Google, and Amazon Aws. In terms of Uipath, and thank you for the the kind remarks in the intro, Uipath really is is a platform for innovation
and automation. And within healthcare, we see so many point solutions that exist and there's a lot terrific innovation going on. But a lot of the customers that I speak with day in and day out, and it's a big part of my role is really to beat with executives of payers specifically. And our responsibilities overseeing payers and providers in the Americas. Is really to meet with executives and understand what's on their mind relative to their strategic
transformation initiatives. A lot of business processes have been digitized, but we're capturing information, but we're really not able to unlock
the value that's contained within that information. So Uipath as a platform really serves as a unification capability that kind of meets customers where they are, can tap into the source systems they have and then begin to introduce automation, intelligent automation and some of the more advanced technologies, large language models, etcetera on the data so that it can be
freed and used in in meaningful ways. And we're finding this is really particularly relevant and applicable with a lot of the regulations that have both been published in our fourth coming from Cms and others just in terms of the challenges that payers have, and the need to really move faster in a safe and effective way leverage the technology in the right place at the right time, but then also do so in an explain in an accountable way, and we've got
some ways that we've been thinking about that. That's a little bit about Uipath. Yeah. Yeah. Wonderful. Thank you so much for giving us that explanation. So what are the major trends you are currently seeing and how are you helping our customers? Sure. So there's really 5 domains that we find ourselves talking with our customers about. And and we assist in different ways. Again, we're about meeting customers where they are and really being scaffolding, if you will to stripe across the
different systems. But medical cost management is a is a large area that we focus on. We're helping customers and everything from care pathway optimization to disease and care management. Programs. The area we've really seen a lot of emphasis recently is in the operational cost management side of things. And these our areas having to do with higher
authorization. There's been a lot of discussion around that, particularly with the Cms 0057 dash f. Regulation coming down and the adaptations needed to comply with that by 20 27. Looking at high dollar claims is another area, really the audit aspect of claims and cost
recovery. And we've got examples where we've helped customers recuperate tens of millions in over payments, in instances where they've been able to go back and and do the reviews, using automation and using machine learning and an Ai to start to look at, those. And then looking at provider credentialing, you know, keeping the records up to date, there's
a lot of paper involved, typically. The average provider will have anywhere between 3 and 5 pieces of paper that get filed every year that have to be absorbed somehow. A lot of them aren't doing it online, but there's still a remarkable amount of business that still gets conducted via effects. And we see this also in both prior authorization and in claims where the information that's coming in is is digital, but it's digital Pdf documents or or fax documents
that they have to be ingested. They have to be understood, routed appropriately and then ad educated. And then the last area that we've seen quite a bit of progress is in more of the fixed cost aspect, more technical and that is in the automation of testing. Uipath has some part of its platform, testing capabilities, and we've seen upwards of 5 x increase in throughput. By taking advantage of of the automated script writing and testing capabilities that are part
of our platform. So that's kind of the automation aspect of operational cost management.
The 3 remaining areas, member engagement tends to be a very big area, and this is around, eligibility checks, personalized communications and recommendations the provider experience, and there's a lot of talk in the industry about the ab operation, and we're doing some work around intake and correspondence and the referral networks and and working with our payer customers and our provider customers to more efficiently share information as joint stakeholders in the care
of, of a member slash patient. And then finally, you know, the area of around quality risk and compliance And again, top of mind, particularly in light of some of the regulations
that have come down. But assisting customers really, again, getting back to understanding the data they have the analytics against that, and then being able to take actions on those insights that are generated and really start to look at ways from which they can improve their business not only from compliance perspective, but then also start to mine that data to better understand their member population where the risks may be present and how they may be making adjustments
not only to their current business, but then also looking for opportunities to introduce new products and services that are gonna add more value to their end member and be more competitive ultimately in the market. Wonderful. Thank you so much for giving us that explanation. So with Ai occupying the majority of recent headlines and new advancements seemingly announced it every day,
as I'm sure you know. How are you helping customers transform their operations with automation that includes Ml, a, and L m at scale? Sure. Well, there's a lot of experimentation that's going on. You know, we're coming up. This November will be the 2 year mark when open Ai shook the world with its announcement. And and really democrat large language models to the to the general public.
There since then, there's been a lot of experimentation But we're finding that upwards of 70 percent of the pilots that are undertaken fail. And it's not for great work that's being done. A lot of it has to do with the need for training. We just announced a study. We did a global knowledge worker study we announced those results this this preceding Monday, the eleventh of June.
And that, it found upwards of 85 percent of those surveyed were not given structured training, particularly related to, the use of large language models in their business and then also looking at Ai, Ml, large language models in combination with automation. So there's there's a big gap there, and that's 1 of the learnings that that we've seen is that while the technology is interesting, there's definitely a right place and and our right time for it.
In terms of what Uipath, we spent, since 2005 when we are founded, we've been looking very deeply at at Ai and n ml. And as part of our platform, you know, there is certainly a number of different capabilities as was mentioned around the understanding of information and the context but there's something that we've built into it, which is key for regulated industries like health and financial services, and that is an Ai trust layer.
And what that really allows our customers to do is establish the guard rails and the mechanisms to explain to report, offer transparency over what these models are actually doing with respect to their their data. We're finding some some great use cases around the, what we call context branding as a part of this. And that is the model is pointed very specifically at a finite corpus of data that is approved by the customer. And, by doing so, it reduces a lot of
noise. It gives you great guard rails around and great explain ability in terms of the answers. In terms of another aspect of how we're working with customers is guard there has not been a lot of thought given to process from the standpoint of a combination of human plus digital worker. You think about how businesses have evolved since the fifties, really it's been designed hierarchical around the capabilities and in some cases limit
limitations of human workforce. And what we're finding is that as important as the technology is, there's also a change management component that's that's also needed to be looked at as part of any kind of transformation. And part of what we have intrinsic to our platform is the really the ability to look at a process digitally. And in the old days, you would typically commission a study and you would you would model out
what a process might look like. This is a way to do that basically a way to instrument a process automatically where we were point an agent at a particular process. Allow that process to be, worked across a wide disparity of workers that are that are performing that task, And then from that, using analytics derive what the optimal pathway might be. And then from that, we're able to then optimize a process.
Some cases taking things that took days and sometimes weeks and bring that down to minutes because we've understood really precisely what's being done why it's being done and then started to look at those tasks that are optimally suited for the human, like decision, like reasoning, and those things that are more done by automations, you know, things like deter logic where there are particular rules and and other mechanisms in place where you can look at facts and data and then derive
and and output. All of these things though really result in, the need for what we call human and the loop And there is a desire in healthcare care to try to automate as much as possible, but what we're finding is that by having a human in the loop, it actually accomplishes 2 things at once.
The first is as you're bringing in your process experts, the humans that have done the work and starting to introduce automations that optimize, we're able to get that expert insight and you're able to cod that expert insight in a way where essentially, the machines are ticking away a lot of the the dr or the
from from that process. And then allowing the knowledge worker or human to focus on those things that are higher order value, focusing on the member experience, focusing on truly those things that are strategically important to the business versus those things that are just simply time consuming and moving data from 1 place
to another. So we're finding that when having a human in the loop, we use machines for what they're really prayed at, which is repeatable, dependable processes, safe and effective, and then humans for the reasoning and the creative aspects in which add a lot of value to the overall experience. And then I mentioned before that the trust framework that makes makes part of it. And part of that, of course is the interoperability
across 4 systems. The nice thing about Ui uipath is we are easily able to work with all the core systems from the the source systems that you may have, the systems of records would to speak. And, either by Api or fire interfaces or even reading the screens. We we have a number of patents in our portfolio that are all about document understanding, natural language processing and, you know, the ability to truly read what's on a screen and understand what's happening at that level of granularity.
And that offers really again, our customers to back to the Guard rails conversation, be able to start to use these automation capabilities and intelligence capabilities really holistically at the enterprise level a way that's very transparent and scalable. Yeah. Yeah. Thank you so much for giving us all of that information. Paul, before I
let you go. The last thing I really wanted to ask you is, If you have any advice for our listeners who are seeking to transform and optimize how they operate with Ai led automation. Sure. And you know, there there's always this natural tendency when there's new technology. You know, first and foremost, you know, even though there's a lot of talk about Ai, large language models and so forth, it's it's a part of a larger solution. In terms of, the other elements that you
need to take action on on insight. So what we like to advise our customers as we're working with them is really focus on the right problems. Those those instead of thinking particular use cases and and the industry right now is, I don't wanna say littered, but there's a lot of standalone use cases out there, But they don't really connect anything. So we encourage our customers to really think more from a systems perspective. What does the end to end process
look like? Anything And then how can we look at that process in each sub component of that process? And where is it best work to add automation? Intelligent automation and the the different tools that are available through the platform. And then where is it best for having a human actually take care of that work. The other is there's also a rush we've seen to just simply automate what you have
in current state. And we're seeing really a resurgence and kind of this back to basics, and that is let's let's be excellent at doing simple things well. And it's everything from receiving information from our provider, processing claim, etcetera. But really simplify and streamline the process as much as possible before you really start to go down that path of trying to automate it, and orchestrated at an enterprise. And that know, certainly the right tools at
the right time for the right problem. Gen ai is a tool. Large language models are a tool, Ai and Ml. They've been around for a while. There are tools. Keyword search is a tool in These tools are effective in in particular cases. So it really requires a a thought process to be very critical thinking critically about the process asking of why questions around the process. Why is it this way? Is there perhaps a different way or a better way to go about accomplishing something.
And that leads kind of going more into an engineering principle of engineering concept around first principles, and that is really break down the processes into small digestible components. And and again, be critical and ask yourself the question if knowing what I know today, the technology I have access to the people in the training and where they are right now and the other systems that I have, what might be the right way to go
about, transforming this process. And we're finding as customers really start to take a step back and think about things more holistically. They're able to really achieve excellent results in terms of simplification and then acceleration. It's kind of inverse that people typically have gone about this. And that is they automate quickly to try to, achieve an Roi. And, unfortunately, it it it may work, but as I said before, a lot of cases
it doesn't. You know, this is a way to spend 2 thirds of your time really looking at the process and and breaking it down and then 1 third applying the technology. You know, the last bit I would say, is don't forget about change management. This is particularly now as much about the knowledge worker and the knowledge worker experience as it is the technology. You know, the tech is moving very quickly, and there's a lot of overload fatigue I would say, amongst
customers where they're... There's a new innovation or a new way of doing something literally announced
every day. But Again, kind of taking a step back, thinking critically about the process and the outcome, the business outcome you're trying to achieve, then also think about the people involved in the change management and the education, people are a little and you read the surveys and the literature suggests that generally knowledge workers a little nervous right now because they they don't quite understand where they fit in what these new automated systems might look
like. The good news is it's gonna definitely super charge, and we like to use that word, super charge their ability to add value to the business and value to the members while also taking those things that are low value or repeatable things that could be coded and take that off their plates that can think strategically and creatively. And and reason in ways that perhaps
they haven't had time to do before. And when it's brought about in that way and education has provided We find that there's greater acceptance and greater participation frankly as these programs are are rolled out within the enterprise. So there'll be some takeaways there that that I would suggest, our listeners think about. Yeah. Yeah. Absolutely. Well, Paul, that is all the time we have. For today. So on behalf of Becker
health care. I wanna thank you very much for your time and thought provoking discussion today. We also wanna thank our podcast sponsor, you uipath. For further information about Uipath, go to uipath dot com or contact paul at the address provided in the show notes. You can tune into more podcast from Becca healthcare care by visiting our podcast page at becker review dot com slash podcast.