Kito Lord, MD, MBA:

So I spend hours and hours and hours combing through data, looking at our observation rates, looking at all of our information. And what I found is that, number one, is that data can tell you a story.

Jani Rad:

There's many companies out there, but what we really liked about Domo was that they were able to meet us where we were at in our technology journey, which was very, very early.

Robin Clanton:

I'm able to use AI to help, you know, as we're identifying trends and patterns with the payor denials, I'm able to use AI to create templates to push back for that situation. But you can also now create projects.

Junaid Kalia, MD:

Today we have a very special guest, Jani Rad, who is actually the CEO of Regional One Health. She is accompanied by the Chief Medical Officer, Dr. Lord, and how she is actually, they are developing this new system. As you guys know, that we here in Dallas, of course, a little bit of our, you know, bias in Texas, but we are supporting all healthcare entrepreneurs. And the idea behind it is to save lives and limbs and make sure that signal.

basically is not lost in the noise of AI. So real people who are building real solutions want to bring them to the limelight so they can actually, you guys can know and help us.

Jani Rad:

So, Regional One Health is our trauma center and hospital side. We all work for Regional One Health, the hospital. We are the oldest hospital in Tennessee, 200 years old. We serve around six states being in the Mid-South. And it's interesting as being as old as we are as a hospital, we have also tiptoed into AI and technology. And it's really cool that we are leaders in this space.

So much so that a couple years ago, this is where my part comes in. I used to serve as the director for our internal analytics department. We started doing such amazing things with innovating and leaning into tech and leaning into AI and digital technology that we started a spin-off company within the hospital. So that's actually what I'm the CEO of. didn't want to take claim of being the CEO of the whole hospital, but I am the CEO of Regional One Health Solutions, which is the digital consulting company implementation partner that sits within regional One Health.

Kito Lord, MD, MBA:

My name is Kito Lord. I'm a physician, a board certified emergency medicine and informatics. And I guess my health care journey started really in operations. I started out doing a health care fellowship in health care quality and operations and then moved in as being the ED medical director. So I got down to regional one to help improve our throughputs. And one of the things about any type of improvement is that you need lots and lots of data. And so we didn't have it. And so that's kind of started my data journey was trying to figure out where we were, where we needed to go. And so we made a lot of great improvements over the last several years in decreasing our wait times, improving our throughput, improving our patient care. And that's how I first got exposed to Domo and to some of our Regional 1 solutions. Then I moved into the other side. I got called into the principal's office and they were asking me, said, Dr. Lor, why do we have so many observation patients in the hospital? And they said something to the fact that the ED was admitting too many patients to observation status and I took that personally. So as the ED medical director, I feel like I had something to prove. So I spent hours and hours combing through data, looking at our observation rates, looking at all of our information. And what I found is that, number one, that data can tell you a story. And the story that I saw was that we were just putting patients in the wrong status. I mean, that was it. And we were keeping them in the wrong status for a long period of time. So I sat down with our CMO and some of our finance individuals and I said, hey, I could fix this for you and help improve that. And so one of the things we did was we created the Physician Advisor Program and I've been serving as a physician advisor, kind of being that conduit between administration, finance, and clinical operations, and the physicians over last three years.

Junaid Kalia, MD:

Awesome. That's a fantastic story.

Robin Clanton:

Good morning. My name is Robin Clinton and I am the director of managed care and revenue integrity for regional one health and our physician groups, both the regional one health physician group and you drop and.

A little bit about my background is I'm actually an anthropology major and then I went to grad school for medical anthropology and I just love the culture of health care. And so I started out working for another health system and decision support and then moved to managed care there and I do did the modeling and then now I do the negotiations too. So.

I guess my role is, as I've worked with everyone, is to kind of be a translator of how we get paid for the clinical services that we do.

Junaid Kalia, MD:

So important, very important, believe me. Thank you for doing your job. food on my table. So a fascinating journey of all four of you. Jani, the floor is yours again about the solution and then we're going to have more conversation.

Jani Rad:

No, sounds good. And you all are actually in for a treat because I'm going to be showing you something that we teased at AI Med. So what we actually showed at AI Med was our very, very, very first tiptoe into AI. Dr. Laura actually mentioned Domo and I do want to give them a little bit of a shout out. They are the digital technology platform that we decided to lean into and start leveraging at Regional One Health. There's many, you companies out there, what we really liked about Domo was that they were able to meet us where we were at in our technology journey, which was very, very fairly early. know, no cloud storage, all of our data in disparate systems, nothing really talking to each other. So we had data and information silos and we had people in silos. Great recipe for a lot of unknown. And so we brought them on. We were actually their very, very first hospital customer. And so through that, we started to go down this adventure of how do we do this with healthcare? know, Dr. Lord was, you know, one of our first early use cases, just kind of seeing, okay, what can we do with just surfacing data? and looking at data in a different way. That was step one. It wasn't even leaning into AI. was nothing complicated. It's let's just look at our data and have visibility into it. And then about six months ago, we decided, okay, let's play with AI. You we now start having access to these tools. And so we thought a very safe way of playing with it was through our patient experience scores tied to age caps and leapfrog. So that's the use case that we actually showed off at AI Med. It was essentially taking that data from surveys using AI and data science to essentially say, okay, what are those biggest drivers of people ranking us really low on Rate Your Hospital and really high on Rate Your Hospital? And then where AI also came in was saying, okay, well, let's read through these patient comments and flip them into real actionable interventions that nurses can do. So we've been live with that for about two, three months now, essentially since AI Med. And so they're saying, okay, Now let's take the same concept. Let's apply to something that we can see that ROI quickly. Obviously, Robin's team in finance was such an obvious answer. Like I mentioned, a big part of what we're doing is data visibility, but then what are you actually doing with that data? The first thing here was just helping them create worklists, surfacing that data that usually is locked down in all these systems that you can't see.

Robin Clanton:

When we moved to Cerner and Epic, which are wonderful and all the other EMRs, the work became a work list where the individual team members are looking at encounter by encounter. So you're missing the big picture. And to me, the most wonderful thing that RevIQ does is show us the big picture so that we can see we've got 1,400 accounts with a $480 variance. So it's using AI and Domo and Janney's magic to show us the big picture. And in doing so, we've pulled in our denial. So now we're combining our payment variances and denials. And we're able to clear out a lot of noise. Is this really a denial or is this a package service under OPPS? And so then we can remove that noise from the denial work list.

Junaid Kalia, MD:

So, Jani, I perfectly agree that the value of data and information, so this is information basically, structured data. And then you are actually moving towards now knowledge, which is where the AI comes in. So explain to me that how I'd convert this information and data into actual actionable items and how do you use AI.

Jani Rad:

That is such a great question. So you're kind of catching us as we're in the building and testing and all that, which is, which is exciting. You're kind of seeing the work in real time, which I find really fascinating. And maybe hopefully your listeners will too. So again, taking some of that, that information, that analysis, but then having AI go in and pull, Hey, these are the priority accounts that you need to work on rather than Robin's team going, okay, now I see the information. Let me add these to my work queue. AI has already done the work to say, okay, well we've already pulled out the first 10, you go ahead and add another ones too, but these are the ones that we think that if you work on, you'll have the biggest opportunity. So that's all work that's in progress, which is really exciting.

Junaid Kalia, MD:

Beautiful. mean, one of the best use cases of in general automation. mean, then the question really is that, Jani, why not just use Python script? And why actually put AI? Why even have a 0 % 1 % chance of hallucination, but you could have deterministic? So same question.

Jani Rad:

That's something that also sometimes we see with AI is that as it's being creative and especially in the healthcare world, know, when I was speaking about interventions before, it may give something different every single time. But I think that's one of the reasons why I like playing with that because we are in a space in regional One Health where we're willing to lean into that unknown just for this risk of that we may tiptoe into something.

Amazing.

Junaid Kalia, MD:

Again, love it. Fail forward. Very important for any, every entrepreneur.

Kito Lord, MD, MBA:

I think you're absolutely right in terms of you know, we're trying to be predictive and prescriptive, right? And I think that we're trying to, need AI to do that, right? And I think that's where we are now. And I think that anytime you present data in front of people, there'll be some disagreement about kind of what it means and some of the limitations of that data. You have to know the limitations of whatever platform or whatever data you're using, whether it be AI using AI or using just raw data in Excel, the same issues will continue to present themselves. And I think it's a good learning lesson that as we go step by step,

that making sure that we understand our own data internally. And then the second part about that is making sure that we have some way to have checks and balances over the AI. So at least we can look at the audit, the data real time and be able to see exactly what it's actually pulling from. I'm super excited about it. As you can probably tell, I think the next step is really how do we prevent these denials, right? And I think that's.

That makes sense. But I think we can take it a step further and say, as a physician, what could I do differently to show medical necessity? Right.

Junaid Kalia, MD:

Let me refine your pitch so that when you go to Ed's board meeting, how it's going to help. So again, we are all learning together. That's the whole goal of this podcast. We want all the entrepreneurs to be successful. But here's my question again. By the way, AI is, we talk about AI in large language models and because there's a natural language, it looks fascinating. But we have been doing machine learning for the last four years. So there's, again, there's deterministic. Pythonic scripting then there is machine learning and then there's natural language for us a natural language processing that Dr. Lord said when he's gonna present to Ed and he's gonna say Yes, you're right. Let's get you these resources. Let's move on So that's gonna be faster in terms of decision-making but Robin I already have an AI and now the word that dr. Lord suggested AI arms race How are you gonna negotiate? in the in the AI arms race

Robin Clanton:

Well, you know, what I'm seeing is I'm able to use AI to help, you know, as we're identifying trends and patterns with the payor denials, I'm able to use AI to create templates to push back for that situation. But you can also now create projects. And you for you find 20 claims with the same situation, you've already gotten AI to write you a very strong argument, you know, based on our case, and you upload that all at one time. So now we're able to push back in mass. And I'm able in negotiations to say, hey, you know, we had direct cost of $1.2 million that was uncompensated because of administrative denials, because I can see the big picture and push back that way.

Junaid Kalia, MD:

How are you going to start really pushing when Dr. Lord says that, now we need to push even further from 2 million to 20 million. How are you going to basically set up that project inside your organization to help end physicians build better?

Robin Clanton:

Well, Jani and I have an idea on that. And to me, the biggest thing we can do is build the trust back between the payers, the providers, and our patients. Right now, there's this friction between us all.

Junaid Kalia:

So beautifully put that you have to bring it back, both in terms of patients, terms of care, but also financially. What are your thoughts on AI arms race when you sit on your boardrooms of different hospitals?

Edward Marx:

This has been tremendous. And I know as a board member, I would love it for this to be happening at the hospitals where I serve on the board. So that's fantastic. Yeah. And it is AI wars, you know, us against, you know, the force and for them against the force. And yeah, it's always important to stay ahead because as you know, they have a little bit of a head start and have poured a lot more into AI capabilities than we have. The one question I had with all this, discovery, like are you how do you think about taking that discovery and going back into your own systems or your own processes and changing things, right? It's one thing to get all this information and be like, here's opportunity, here's opportunity, let's go attack that. But are you able to take some of that information, that knowledge and then bring it back into your own operations and change your operation?

Robin Clanton

Well, we've had two situations that have been really successful. One of our clinical teams said that we were working with them and now when we shared the data with the vice president of the service line, he said, what's this clinical documentation error? Why are we getting denied here? And so he took that back to the providers exactly. There's one payer that wants X diagnosis for this to be necessary medically.

And then the other one on, so we're seeing what I love about it is we're removing all the silos and working together as a team. because we all do, we want our providers to be able to treat their patients the best way they can, what's best for the patient, regardless of what the insurance company is signing that we should do.

Kito Lord, MD, MBA:

remember in residency, we had very, very little training on documentation for E coding or even for the facility side. And I don't think I realized that there were two separate coding structures up until, I don't know, my first year as an attending. And so physicians, you know, aren't really trained on that side. And then I think two hospitals understand the some of the pressures and that the physicians face in terms of documentation burden. It's over the last 10 years, documentation burden has only increased, right?

Junaid Kalia, MD:

Before I close today, feel free to add anything, any one of you, open floor for you, share anything, whatever you want to see, what is your vision, how would you like us, anyone to help, mean, Harvey can help you with the governance.

Harvey Castro, MD. MBA:

For me, it's all about the why and I know that's a little deep. I really love what you guys are doing but down to the why. Why are you guys doing this? What's your why, Dr. Lord, Jani? What's your why?

Kito Lord, MD, MBA:

I think it's getting credit for the hard work that our physicians provide for our patients. I think I see a lot of frustrated physicians, I see a lot of burnt out physicians with increasing documentation burden, not understanding why certain care is not approved. And so one of the things that drives me a lot is, how can we make it easier to deliver high quality care to our patients? How do we the administrative burden on our physicians, on the system overall in our patients and let's do the education there going forward. And so empowering our doctors to care for their patients better really drives me a lot.

Jani Rad: