The Next Chapter in RCM

Hello everyone and thank you for joining today's webcast, The next chapter in RCM, building a future ready innovative Approach. My name is Brittany Turman with Optum and I will be your host today. Before we begin, Please note the following housekeeping items. At the top of your audience console are multiple application tools that you can use to customize your viewing experience. If you have any questions during the webcast, you can utilize the Q&A tool to the right of your slide deck to submit a question. Would you capture all questions and provide follow up to questions as appropriate? If you experience any technical difficulty, please click on the help tool.

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Thank you for joining this important webinar by Optum in consultation with Everest Group. As the topic suggests, we're going to be discussing the next chapter in RCM, building a future ready innovative approach. Starting with the introductions. My name is Abhishek, AKA I'm Vice President at Industry Solutions, which looks after both healthcare pair and provided ecosystem. So I'd be moderating this session and providing a fair and balanced view on the industry. I'm joined by my colleagues, Puneet and Doug. Puneet, a quick introduction from your side. Hello everybody, Puneet Maheshwari, I'm part of Optum Insight. I'm accountable for the end to end reimbursement solutions between payers and provider and also accountable for our new program which is called Optum Real, which is around real time transparency between payers and providers.

Doug. Good afternoon. I'm Doug Clovis. I'm a partner within Optum Advisory, which is part of Optum Insight as well. I have responsibility for the majority of the accounts on the West Coast from an revenue cycle advisory perspective and looking forward to the conversation today. Thanks, Vineet. Thanks, Doug. So quickly going through the discussion points, what we'll be discussing in today's webinar is what's broken in today's RCM, what intelligence really means.

We've seen this word being used very loosely today. We are going to make some sense into what intelligent means. And 3rd and most important is making intelligent RCM a reality from vision to execution. So starting off, you know, we see that revenue cycle management, which is the engine behind profitability, cash flows and experience needs to navigate the web of internal and external challenges. Right from external challenges, you see regulatory developments, you see constantly evolving pair policies and guidelines. You see rising patient expectations and staffing shortages along with internal challenges which are fragmented systems processes, complex lack of in house tech domain expertise, which we're going to be talking about also in today's webinar.

So when you look at this slide, what comes to mind, What do you think are the leading causes of friction for an RCM ecosystem? Yeah, Abhishek, look, these are in my mind all the symptoms to an underlining root cause and that underlining root cause is the lack of transparency between pairs and providers. When you have that, that leads to two big downstream implications which then manifest in, in all these considerations, the two key pieces there are one, we start from being fully aware to to really driving answers through guesswork. So majority of the RCM processes are driven by guesswork around what the payer policy is going to be, what will really happen at the coding time, what will be the response from the clearinghouse, what would be the payments in at the end state, How much does the patient owe for this particular encounter.

All that guesswork is because there's lack of transparency into the underlying decision making considerations. The second piece is just because how the processes are set today with respect to managing those those guesswork points, there's a lot of loss of information that happens from what really happened in the encounter between the patient and the wider to what was really coded in the claim. And if you think about those, those intermittent points, you realize that a real life analog interaction or encounter between the pair and between the patient and the provider then gets converted into a digitally written in English chart. You already see a lot of loss right there in terms of information from there on that's converted into a set of codes.

Again, lots of information right from English to those codes and those codes are then sent to the pair in batch format, which is then intermediately and and understood in batch. Yet another loss of information. Every point where we lose information, we then have to backtrack because decisions are going to be made based on the information that is available at that point. So I would say while all of these are real, these are more of a symptom on 2 core things, guesswork and the loss of information, mostly driven by the fundamental lack of transparency between pairs and providers. Yeah, Puneet, very nicely articulated.

I do. I do agree with you. You know, there is a need for fundamental more transparency between pairs and providers. But Doug, in your experience of advising your clients within the provider ecosystem, what do you think you know are the places which is limiting them for from getting more interaction with pairs and then working with pairs in order to overcome these challenges? Yeah, Abhishek, I'll, I'll pick up a little bit on what Puneet was talking about, about, you know, the the lack of transparency and the fragmented system is you know, when when I go out and talk with our clients, even for the, the clients that are epic clients or you know, some of the Oracle clients, you know where they have the majority of the systems together, they still have many different the bolt on systems or surround systems.

Where as Puneet was talking about the, the data degradation as you go through that and really not seeing the full picture because you have some middle revenue cycle or some front end technology to look at eligibility. And then that pulls it into the core system and really looking at how to look at the, the process flow and the data flow across the organization that gets fragmented. And then as they lose the data, then they can't make the decisions or get the, the right insight into the, the areas. So I think that's where we're still lacking, you know, as we move forward with a lot of the different areas of how do we pull all of that information together so that we can use utilize all of that as we go forward and really look at the looking at the trends.

Puny talked a little bit about, you know, some of the lack of knowledge of the, the payer rules and how do we, how do we get an intelligence into that so we can predict, you know, some of those things that are moving forward. Yeah, certainly. And I think that from my perspective also within a single provider, you have many instances of EHREMRS which don't talk to each other. That's also one of the issues right now coming to the next thing, right. So we see that for most providers the cost of RCM continues to rise and there is some analysis we put up and when we were doing the study we saw recently, right or we saw in the survey that 53% of the enterprises I'm talking about chart on the right continue to see increase in cost of RCM function.

So Doug, first to you, you know where do you see the role of technology, right, whether it's AI, RPA or even process changes in order to bring down these costs to collect of an RCM function? Yeah, Avishek, I'll, I'll kind of pick up on the other last conversation as well as I was out with a client yesterday and we, we talked about they have many different applications, which, you know, there's a cost to each one of them, but they all do a little bit different. But there's also a lot of overlap in, in the different applications that they have. And how do the, how do we get something that goes across multiple processes?

And so I don't have to have 10/15/20 different applications where I may only be using 20 to 30 to 40% of the functionality of, of those applications. You know, really looking at how do I, how do I pull all that together so they don't have a duplication, you know, across some of the, the functionality and then how do I utilize, you know, the technology that I do have to the fullest extent. And I think that's where we're missing some of that today where we don't always utilize the technology that we already have because it doesn't do you know everything it does 90%, but we, we go out and get something else to, to handle that 10%.

But then work duplicating some of the other work that's in there. So I think that's if we can do some of the vendor rationalization and consolidate that would help out. But then also as we've talked about really looking across all of the different areas and how do we have more of a, a universal data layer that how do we, how do we utilize that data, you know, more succinctly? Yeah, that's a good point. Puneet, any insights from you on this? Look, I agree with everything that that's it. The fragmentation of the technology infrastructure is clearly one area which should and would drive significant amount of efficiencies that we move forward.

I would just add one more piece to the the cost equation, which is rework of the total number of claims that are submitted, roughly 80 to 85%. Get educated in the first go, mostly approved first time denials. Depending on the system that you talk to, you'll see national averages kind of ranging anywhere from 15 to 20%. The final denial numbers are sitting at somewhere around 2 to 3%, right? So you realize that there's this, this massive chunk of 15 to 18% of claims that get reworked. Our analysis says it's more than 500 million claims annually they get reworked in the country and that rework is not just a one time rework that requires full blown full revenue cycle operation to kind of go through against those 500 million claims.

And then the back and forth that comes in between the payers and providers for those rework claims, that's a very large chunk of the based that exists in revenue cycle Management Today that can and should be addressed. The second piece I will say particularly to answer your questions around where can technology lean in, I would put it in two big buckets. 1, the rework happens mostly because rule based systems tend to fracture on corner cases. And as we start deploying AI and start bringing reasoning based systems into some of those processes, we will see a dramatic reduction in manual errors that come into those processes.

That should reduce that rework. The second piece is around moving from things that are manual today to more agentic. The technology now for the first time allows us to reason our language really, really well. And with that, we can build very sophisticated agents that allow us to take a bunch of manual processes and completely automate them within the existing infrastructure itself. Those two along with the things that Doug mentioned, I would imagine will drive significant impact on the cost curve for revenue cycle management and healthcare overall. Yeah, I think Puneet and Doug, you make interesting points, right.

And for a CFO when they are investing, they think, oh, my cost of RCM function is already very high. Do I really need another tech investment for my, you know for my to bring down my cost, right. It is sometimes tech is cost additive rather than helping and there's always a ramp up period for this. So if we go to the next, you know, so we talked about Puneet, you were I think you touched upon this, right, that technology has a very important role to play. I think also at the same point in time, process and data and AI have a very important role to play when you are rewiring the RCM playbook, right?

What is your perspective on how can providers think through their rewiring of their RCM playbook journey? Yeah, I really like the word trifecta on this one, Abhishek. The reason is because all these three go hand in hand. And I would not be exaggerating if I say that for the first time we have the capabilities to completely reimagine some of these processes that have been laid out because of the considerations of the technology that was available in early 2000s. So we started with that. We built a set of processes.

We have been living through those processes over the last 25 years. AI and the access to data is giving us this very unique opportunity of reimagining these processes, processes that are otherwise fragmented, processes which are otherwise serial and processes that are otherwise batch. And I would bring it back to the original conversation that we were having and break it into three big buckets. I think revenue cycle management has this opportunity to reimagine through the lens of 1, where are the opportunities to move from rule based systems to reasoning based systems. And these rules are anybody who has seen revenue cycle management implementations, you'll realize thousands and thousands, if not sometimes hundreds of thousands of rules coded up in those systems which need to be updated, need to be keep updated all the time based on changes.

Plus, I'm never comprehensive in the 1st place. So moving from rules to reasoning is step number one step #2 what we discussed just a few minutes ago. How do you move from manual to Agentech? Every manual process or a large number of manual processes today are ripe for reimagination to an agentic framework. And then the last one is how do we move away from batch based decisions that take anywhere from a week to a month to real time decision And that requires an ecosystem collaboration with the pair. But as that collaboration increases over time, you'll start seeing significant amount of re imagination of the process in and around real time access of information and decision making as well.

So those would be my 3 as I think about technology, process and data slash AI. Yeah, you make very interesting points, Puneet, Doug, in your experience, right? You know that the RCM function can be broken down into front, middle, back, right? And you know, they have their own entire processes together, their point, right? They have their entire data flows. Process rules are different, you know, in your conversations with providers, what are those use cases or I would say those parts of the value chain that you think are right now right for re imagination or rewiring as when you put it.

Yeah, Vishak, you know, looking at this, there are definitely areas of opportunity in the front, middle and the back. And you know, I think as Pony talked about around the denial process and really being predictive in being able to identify potential areas of denial, the cost is not only on the provider side, but it's also on the payer side. And how do we reduce the overall cost out of the system? That is one of the, the, the primary areas. But then also just as we go into and as we look at other industries, if you think about, you know, the way that we're using AI or you know, some of the conversational AI, some of the bots that are out there, we interact today every day with with the bots.

And we don't do that much in healthcare. There's a little bit of a stigma to that today because, you know, when we're sick, we don't we want to talk to a human and go through this. But I think as we're getting more and more adoption, we're going to be able to utilize some of the technology that we're seeing in other industries. But if you look at, you know, the authorizations, which is always a pain point within healthcare, that is an area that is ripe for some of the automation that we're talking about in use of AI, the denials processing, and then also the, the, the appeals management that we have around that.

So those are the top three. But then there's another area that we're we're looking at across the industry around autonomous coding and the the amount of time that we spend documenting from a physician perspective, then translating that into codes and going back and auditing that and getting denials. That whole process is very ripe for automation and the use of AIA. Lot of that is coming out today and it's only going to get, you know, better as we move from the ambulatory, the space into the inpatient area. Yeah, certainly. And I think from my perspective, like you said, payers also realize that it's a cost function for them, right and also CMS realizes so which is why we are seeing that CMS has also come up with new prioritization mandates, right, which other I think a step in the right direction in order to you know up you know increase the systemic efficiencies across both payers and providers.

So now is 1 very interesting part of the of the webinar today and you know Doug and Puneet were thinking, you know what are the right questions to ask. So the question that we have is, you know, how ready do the participants today who are part of this call thing that their RCM function is today to harness the full potential of data and AI. So we are very ready, somewhat ready early stage and not ready yet. So let me tell you what my answer could be. I think maybe the answer is we are at very early stages. What do you think, Puneet?

Yeah. Look, I mean I'm realizing data infrastructure and data fragmentation is the constraining factor in a lot of transformation today. So I'll not be surprised if it is early stage only at this point. Having said that, I will also not be surprised with some at least participants saying somewhat ready given the amount of investments that have gone in over the last 24 months around. Maturing on that data infrastructure that. Yeah, I would agree. And I think there's probably going to be a, you know, a real delineation between, you know, the the early adopters and the folks that are, you know, somewhat ready.

I don't think we will have very many very ready, but I think they'll still be a large population down into the not ready yet that are just, you know, starting the journey. But you know, they've got, you know, so many other focus areas. Abhishek, I think to your question earlier, how do you work with the CFO and the other folks to get funding for some of this? And you know, really looking at the, the total cost where yes you may have an increased cost here, but how does that take out cost in other places, you know, in the, in the revenue cycle.

So it I'll be very interested to see the results of this, but I think it'll be see a wide spectrum, but probably in the C&D for the most of the part. Yeah. So let's just give our participants maybe 10 seconds more to put in their results. I also see, and I think to your point, right, some folks, I think there is a, there's going to be a dispersion perhaps two to three years down the line, right? Then you'll start seeing a real divide between, you know, people who are very ready, maybe in fact harnessing the power of AI, basically some people who are still in the early stages.

So let's look at the results. So yeah, no surprises here. So early stages, 63% of the participants, it's good to encouragingly see that none of the participants said that we are not at all ready, right. We are still addressing the basic RCM and digital modernization needs that shows how systems and partners like Optum have also helped some of the providers come up through this digital maturity curve, right. I'm sure Doug, in your experience, if you would have asked this question 5-6 years ago, then, you know, not ready yet, also would have shown a lot of responses. Yeah.

Yeah, this is the results I like. I like those results. Yeah. And I would like to talk to some of those 15% very ready ones. They're they're definitely needing the charge and all of us can learn a lot from that. Certainly. Exactly. So moving ahead, you know, we talk about intelligent RCM, right, which is built on the right foundations data quality. I think that that's what you mentioned to begin with, right?

Second thing is what we believe is integrate, then elevate. First, AI will not work unless or until the underlying data infrastructure is in place. And 3rd, governance and compliance and 4th alignment. And in my experience, I know that alignment is the most important thing we've seen, you know, decisions with regards to building intelligent RCM platforms, being top driven. So the CFO or the VP of RCM deciding that, OK, we'll go for AI, but there is no alignment within internal teams, right? And what we feel is, you know, alignment fuels governance and governance fuels trust or earns trust. So it's a flywheel effect.

So Doug, over to you. When you look at these things right, how should ACFO or a CDO of an organization look through, you know, these basic 4 building blocks and which one do you think they should start with first? Yeah, that's a great question. You know, as I look at this and, and talk to some of the, the CF OS that that I, that I work with on a regular basis, it really is I'm going to go to the far right and really talk about alignment in that everyone needs to be, as you said, it can't be an individual effort on this.

You know, we always talk about revenue cycle being a team sport. It really does start in the clinical areas and you know, with the documentation and all of the different, you know, components that people very often think of just from a clinical perspective. But that has such an impact on, you know, the revenue cycle as we go forward. And we really need to get alignment on the overall strategy and the goals of the organization and how are we going to implement this and how are we going to stand behind this and drive it. So you know, I'll look at that.

Obviously the underlying components of the data quality and integration, those are necessary, but I think we're a number of organizations are not failing, but you know, are not going as quickly as possible because they really haven't looked in the and aligned across the organization. Because this is a this is an initiative that needs to go across the entire organization. It you know, you can do piece meal, but you're going to get very, you know, not as good results if you do that. So that's where I would start with the alignment and and the governance actually. OK.

And Puneet what? About you, I really like the push there that I think we, we internally kind of talk about clinically aware RCM as a the notion for transformation of RCM and some of the alignment points that you are making that kind of completely lines up with that. So expanding the definition of alignment beyond the CFO organization to clinical organization as well appreciate is one key tenet for success as we move forward. I'm realizing that the data and AI are not 2 separate initiatives anymore and, and they both will, you know, we support each other. As we think about where this goes from here on.

And, and I always kind of come back to the fundamental definition of RCM and, and why it is the way it is. Then if you reflect on that, you realize that revenue cycle management and for that matter, overall claims management, if you look at it through the lens of the ecosystem of their and provider is becoming and, and in reality is a reasoning problem between contracts, benefits guidelines and what really happened in my encounter. And when you look at it through those first principles, you'll say, OK, I can bring the data and AI together to reason over those 4 or, and the gaps in those processes going forward.

And and that requires very strong intent to move away from what exists today, which works reasonably OK for 85% of the cases and then start experimenting for where the the industry and the technology can can go from from there on. And if we believe that that reasoning problem can be solved, which is getting proven out in a lot of other industries and to a certain extent in some of some of the healthcare systems today, you can. You can. We are not far from a world where the multi step, multi week RCM process collapses all the way to the point of care where an ambient scribing capability can scribe what is happening in the encounter.

And autonomous coding system and an autonomous CDI system can help the providers to complete the documentation and and make sure that it's accurate taking into account downstream implications and autonomous coding system code set and autonomous billing system kind of wraps in whatever payer side rules that need to be wrapped and then sent to the payer before the patient walks out of the door. That day to me is not very far if we all start marching towards certain intentionally. Yeah, really, you know, forward-looking thoughts, Puneet, right. And my compliments, yes. I also believe that the day is not far away yet at the same point in time, I'd like to, you know, just under score the importance of governance also and compliance.

You know, at the end of the day, we are working in a healthcare industry which is regulated also at the same point in time, you have to realize that, you know, the point that you made that AI is helping and it is getting better, but yet at the same point in time, do you need to have proper governance mechanisms in order to ensure that any edge cases do not come out of the system? And over here I what we are seeing is that some of the leading enterprises are not formalizing this EI governance mandate or committee as well, right. And I think that they have a very important role to play.

And I think to Doug's point initially, it's not one man those committees have people across IIT information security partners as well, right who are actually helping in the revenue cycle management growth and of course the CFO's and the CEO's as well. So you know, good forward-looking ideas. So if we go, you know, just moving along, you know, one of the things that Everest Group is partnering with Optum is we are writing a white paper in which we are providing A blueprint or a playbook for RCM revenue cycle management strategies for 2026. It comprises of insights through the survey that we walked through and also some of the pitfalls that revenue cycle management leaders should avoid in order to extract the value from their AI initiatives or their investment initiatives.

Doug, any closing costs from your end? No, it's been a great conversation today. I think, you know, as Puneet said, you know, we're going to see a lot of changes into the near future. You know, some of the processes that we've always had very manual, they're going to be, you know, changing more towards the retail. And you know, there's still a lot of complexities in healthcare. We all know that. But I think with the new technology, I think we're going to be able to get there and very rapidly.

Thank you and Puneet. Look, historically, healthcare has been a laggard when it comes to adopting leading edge technology. Finance industry being the one, the number one, retail being #2 and healthcare being #3 in that order. I don't think that order is going to dramatically change for this, this transformation. But what I'm seeing, which is very inspiring is what used to be a decade long delay is turning into a two year, three-year delay, which which means that we'll see much faster transformation, which is very inspiring for me and something that me and my team kind of on a daily basis work on.

Thank you. So that's what we have for today. Thank you for joining the session. 30 minutes, quick and insightful session. And for folks who request a copy of this presentation, Optimum team will be reaching back to you. Thanks, Doug and thanks Doug for your interesting insights and also for the entire Optimum team. Thank you. Bye. Bye. Thank you. Thanks, Doug.

Thank you so much to all of our presenters for sharing your time and expertise with us. We'd also like to thank you, our audience, for your attendance today. We know that your time is valuable and we appreciate you being with us. We do have a post webinar survey that is available for you to take on your way out. We do appreciate your feedback. Thank you again for joining us and have a great rest of your day.