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Becker’s Healthcare Podcast
Turning Healthcare’s Toughest Operational Challenges into Breakthrough Solutions: Part 1
00:19:13
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- [00:00]
A
Hi everyone, this is Lucas Voss with Becker's Healthcare. Thanks so much for tuning in to the Becker's Healthcare podcast series and welcome to part one of our series on turning healthcare's toughest operational challenges into breakthrough solutions. And I'm so excited to be joined by Ben Fichtner. He's the America's president at UiPath and Jason Bui, who leads the healthcare industry practice also at UiPath. Both have spent years working closely with provider and payer organizations tackling the operational challenge that sit behind how healthcare actually works. And as most of you know, obviously AI is a big topic right now for health systems across the country, really across the world. But what healthcare leaders really want to know is where it's actually improving, how work gets done. And that's exactly what we'll be talking about today, what's happening on the ground right now and, and where organizations are already seeing real impact. Ben and Jason, thanks so much for being here today.
- [01:05]
B
It's so great to have you, appreciate you having us. This is gonna be fun, lots to talk about.
- [01:11]
A
I do want to kick us off just with a brief introduction so everybody knows where we are level setting us a little bit. Ben, I start off with you. For those that might not be familiar, can you just share a little bit about what UiPath does and how it fits into the healthcare ecosystem that we're seeing today.
- [01:29]
B
We've been around for a decade plus helping healthcare systems specifically, but we started in general as a task based automation tool and we've grown up from there. Right. So I think a lot of times Jason will go deeper on some of these use cases. But when you think about it, there's a ton of tasks that happen across healthcare systems, but more importantly across a ton of IT and backend systems. And we're the the technology hopefully that orchestrates and doesn't replace what's already there as it relates to EMRs or other things, but working across those things so healthcare processes can run more end to end. And what we've seen, and Jason will talk about a lot of great customer use cases that we've had, of course, is where the biggest issues are, is not just in one specific task or one specific process, but more on these highly complex end to end workflows that we've been able to help deliver significant ROI again to both payers and providers. But we're really happy to be here and really happy to dig in.
- [02:23]
A
Yeah, I'm excited to dig in as well. There's so much to talk about here as well and I Want to touch a little bit on your personal journey on this as well and how it's shaped you, right. Your journey in this space. You spend a lot of time working with provider and payer organizations. But again, you also have that personal connection which is so crucial. How has that shaped the way you think about the operational challenges health care leaders are dealing with today?
- [02:49]
B
Great question. And yeah, I grew up in a family full of physicians and I was kind of the black sheep of the family who started off actually selling capital medical equipment for GE health care. So I've been in the health care game for 20 to 25 plus years and it's been an interesting journey. I think thinking back though, around like my family's dining room table, if you will, over, over dinner. My parents oftentimes, you know, would, would compliment the certain parts of their day and they were always very, very excited for the patient and the clinical experiences. But the things that always bugged them the most, of course, was the administrative and operational strain that they had every day. And it was how do they get time back to spend more time with patients. And I think that's still ever true. Right. And I think when we think about a lot of customers, examples, and I know Jason will share a few, but one that we just touched base with. A massive provider here was talking to us about reviewing their medical records. Right. As part of their authorization decisions. And their team was spending 70 plus minutes just going through a chart to find the evidence they needed to make a decision. So that's 70 minutes they weren't spending with patients. Right. Or they weren't spending on the work that really matters. That's 70 minutes of searching instead. So using UiPath tools, they were able to cut that down to a handful of minutes, which is super, super important. Right. We want to make sure that we're doing everything we can to help folks spend as much time in the places that matter and not doing back end administrative work. And it's kind of cool to see my story come full circle right from sitting at the dinner table there to now being able to do this with, with clients on a day to day basis. Yeah.
- [04:19]
A
Giving providers a little bit more time back to care for their patients, which is so crucial, as you've mentioned. Jason, I want to touch a little bit on what we've mentioned in the intro. Right. AI is inevitable right now. The conversation is there. Everybody is talking about it. From your perspective when you're working with healthcare organizations today, what are they tackling? With AI specifically and advanced automation, what are you seeing Most.
- [04:43]
C
Thanks for the question, Lucas, and thanks again for having me on here. You know, I've been a longtime listener and consumer of Becker's content and just really appreciate what you guys are doing for the healthcare space. You're keeping everyone informed and I just love everything you're doing. So keep up the good work. But I'll start off by saying that I think it's really great everyone is talking and thinking about AI right now in healthcare, because it's already unlocking new efficiencies. And you know, these efficiencies are something that we could only dream of not too long ago. And it's what we've ultimately been waiting for in healthcare for the longest time. Right. We've been wanting more connectivity, we've been wanting better coordination and elimination of administrative functions that aren't value add and that aren't helping us focus on the patient and member. So I think that AI is going to be a really big part of this transformation as a whole and something to look forward to. But anyway, back to your original question on where I'm seeing AI being applied today. I'll have to split my response between providers and payers because I think that would be the easiest way to lay this out and just explain to folks what's happening on the ground level from what we're seeing at UiPath.
- [05:48]
A
Yeah, Jason, appreciate you breaking it down like that. That's helpful framing. Let's start with providers. What are you seeing there first in
- [05:59]
C
general at this time? They're going after large and complex processes within their organizations, and that's because it's finally possible to tackle these challenges in a meaningful way. With AI, they're honing in where there's a lot of human intervention and areas where humans just were never really meant to be facilitating the process in the first place. On the provider side of things, currently we're working with a large academic medical center to streamline the patient triage process. They came to us with this unique use case and wanted us to transform it with them. And we got on the process level to understand what's happening and we found that there's just a lot of referral documents to comb through just to make a decision on where to put the patient next and where to route them, and the types of programs that the patient needs to have wrapped around their care journey. Now, with agentic automation, the triage and decisioning can happen so much faster and the patients reach the right level of care a lot sooner because the details are finally being summarized. For the human reviewer along with recommended next best steps. This has ultimately changed the game for how we triage the patients once they're in our facilities. At another academic health system, we've helped this customer with monitoring the medication reconciliation process and then ultimately alerting clinicians when something needs attention. We saw compliance improve pretty significantly, right, going from about 85 to 95% in just a few months, which is pretty quick turnaround time for an AI use case. And what's been pretty revealing to us is that agentic automation is allowing for healthcare organizations to just be a whole lot more proactive, catching stuff before it happens, preempting ourselves and preparing ourselves for different scenarios and then engaging with the member in a big way at scale. Now that we can use AI to tap into the various channels that patients leverage. And we spend a whole lot of time in the rev cycle space at UiPath and working with our provider customers. And this is where we found most organizations are trying to apply AI first actually because it's a high volume area, complex area and always changing of the process and rules that govern it. Now we have agents that are picking up denials, analyzing it and understanding its intent and then going back into the EMR and collecting the supplemental information to resubmit this with high confidence that this will ultimately be the last transaction on this case and we don't have to worry about it any longer.
- [08:29]
A
Some unique observations there from a provider point of view. What are you seeing on the payer side?
- [08:37]
C
On the payer side of things, we're seeing them apply AI in the back office functions. This is where we see the most opportunity. Think of some of the areas like claims processing, enrollment, payment disputes, prior auth intake and review as well as just auditing important aspects of our overall operations and doing so in a much more robust fashion. They're going after like the last mile of the process where humans were always required. But they're not removing the human entirely from the equation. Right. They're designing their AI solutions with us to maintain full control and then allow for human operators to intervene at the most critical parts of the process. And in the claim space we're seeing payers leverage. You know, they're already mature automations as foundations to incorporate AI. On top of they're having a, you know, these AI agents man these work queues to drive resolutions for the less complex scenarios. And they're having these agents compare the pricing, the contract terms and identifying duplicates that are coming in and putting the duplicate aside so they can truly work on the actual claim that needs attention and then I'll just take a look at the care management space with you all. You know, everyone's been talking about applying AI in this space for the last couple of years. But now Genti AI is able to automate every step of the process. So think of the intake all the way through, reviewing medical records, through the decision support handling and then triaging it to a clinician to make a final determination. AI is playing a role in virtually every step and we're seeing that this is accelerating turnaround times pretty significantly and turning a process that is typically multi days down to minutes. So a lot of innovation happening there. And if you talk about medical records, you know, you have to really talk about the medical record summarization capabilities that we've put out there. It's been a game changer for the payer community that we work with and partner with. And this is pretty much generally where all our payer customers are applying AI first in the UM space because it just provides immediate relief to their clinicians. You know, we're able to ingest a stack of medical records and summarize it for the UM review nurse so they can being more in a validation role if you will. Right. We provide the citations for them to double check the content and the agent can also just read handwriting now structured non structured documents and images. And we've seen review times be reduced by nearly 90%. You know, so this type of innovation is what we're excited for and it's driving meaningful impact.
- [11:18]
A
And they touch so many aspects of the patient journey now too, which is so crucial. And thanks for sharing all of these great examples. Examples. I think it really encompasses how holistically AI has been applied in the healthcare space right now. Now when organizations are start working on these kinds of workflows that you've mentioned and you've touched on a little bit. How do you make those operational so that they actually become part of that day to day process?
- [11:46]
C
Yeah, good question. It's not a one size fits all. There's not one master playbook that works. Every organization is layered and designed so differently. But I the way in which to operationalize it that I've seen success in is starting relatively small and proving it out and getting buy in from the organization. Top down. We're seeing customers being most effective when the employees, the clinicians are part of the journey to roll out the AI capability. We also see the need to constantly educate the workforce. One, because the technology is changing so quickly. But two, it's new to all of and we all have different interpretations of how AI can help us and how it fits into our day to day jobs. And so we found that being repetitive and having frequent check ins is what moves the needle. And then during the change management experience, you know, we're finding that it's not as daunting or as rigorous as people initially thought. We thought we had to all become, you know, prompt engineers and learn technology and code. It's. But because it's so simple to engage with now and it's low code, nearly no code, the clinical workforce is finding that it's straightforward and they're embracing it in a much bigger way than we anticipated. And with them being advocates, we are seeing that people are rallying behind this rather quickly. And the other aspect to this is we want to ensure that people are building the right things and deploying the right things from the get go. And so it's crucial to have champions, partners in the ecosystem and domain experts that can select the right use cases to operationalize. And then you don't have to do big bang, do this in modular form, improve or apply AI into specific aspects of the workflow that you know that humans are struggling with or that there's repetitive nature to it. And you'll start to see that people will gravitate towards this and be excited about it.
- [14:03]
A
I love that you mentioned the change management aspect of this because I think it's so crucial. The leadership piece is often underrated when it comes to AI deployments and pilots, et cetera, whatever happens within a given health system. And I want to stay with the leadership perspective here a little bit because again, we hear a lot about bright shiny objects in AI. Right. There's a lot of promise around certain AI tools, especially over the, the last couple of years. And again, we know some work really, really well. Jason, you mentioned agentic AI, Right. That's applied virtually everywhere now and some just didn't work out. Ben, I'd love to stay with the leadership theme here. When leaders start seeing examples like the ones Jason described, right. What actually convinces them that this is not a bright shiny object, but it's actually real and it's going to make a difference.
- [14:52]
B
Yeah, I think it's healthy skepticism. Right. And I think the article we all were talking about called last October was 95% of AI pilots fail. Right. The one from MIT, which I kind of got to chuckle on because there's the same thing across all organizations and not just healthcare. We talk a lot about like 75% of IT projects fail in general. Right. So there should be Skepticism on some of these things. I think what we've seen and where you can know when it starts to be real is a the massive amounts of savings that we've seen from both payers and providers, and you know, their numbers, not ours, of tens to hundreds of millions of dollars a year and saving things just for operational costs. But a lot of things that just went missed right in processing paperwork or documentation or coordination across systems and all the things that they have to do to keep the system running. That's the one thing that we typically see is it's not about to Jason's point, I think he gave practical advice about how to get started. But for us, we talk a lot about the process being the hero more than the technology. And when you start to see the end to end process, become more efficient, deliver better outcomes, you know you're onto something. Right. And I think we've seen that in a handful of cases that, that Jason helped illustrate, but that's usually better than it is of like, hey, how many times are people logging into this tool or how many times are people getting better outcomes? I think what we're looking at the majority of our clients that are wildly successful is those that have taken the administrative end to end process and saying this is a hell of a lot smoother than it was a year ago. Right. And then that's when we know the change management you talked about the impact that we're having with the leadership across healthcare organizations is delivering. So I think it's a great question and I appreciate us digging in, but it's a healthy level of skepticism, I would say, for sure. And we got to continue to work at it, to make it successful for everybody that touches it.
- [16:37]
A
If you had to point to a factor that truly separates organizations and leaders that are making a difference here, what would those factors be? When you look at it from a progress perspective, what are those factors that are crucial?
- [16:55]
C
That's a great question. I'd say a really big factor in all of this is the mindset. And the mindset from the leadership level all the way down to the frontline operators. The ones that are charging ahead where I'm seeing are the ones who believe they have to disrupt themselves internally, first and foremost, and they're not sitting around waiting for the industry to be disrupted or hoping that it gets disrupted and then having to react to it and change their organization to fit the mold. And when they all commit to that mindset, they move out of this proof of concept phase and become more focused on redesigning their workloads. With AI as a native part of their processes, and real progress happens when organizations are intentional about making AI work and wanting it to work. As the old adage goes, you know, journey of a thousand miles begins with a single step, and we have to be open to trying and progressing forward even after something may not have worked out. We should then of course try again, and the number of tries will be fairly minimal. From what I've seen in healthcare, organizations will see that it'll connect and work rather quickly when they have the right domain experts in the room designing these AI initiatives. And the value is absolutely there. I think it's undeniable. We collectively as an industry need to allow our staff to explore this new technology and this new capability and incentive incentivize them to do so. To close out. I'd also say that the organizations that roll out these AI capabilities into production and do so in a controlled manner will be the ones that will witness and understand the value more clearly. So therefore they're able to make meaningful progress and compound their successes and move a whole lot quicker in the space.
- [18:36]
A
Jason and Ben, thank you so much for your time and insights today. So great to have you. And thank you to uipath for bringing us together and sponsoring today's episode. And for our listeners, UiPath will be attending Becker's annual meeting April 13th through the 16th. If you're there, they'd love to continue our conversation from today about how AI and automation can help automate and orchestrate these workflows more effectively across your organization. You can also tune into more podcasts from Becker's Healthcare by visiting our podcast page@beckershospitalreview.com.