Jeff Standridge: (00:01.593)
Hey guys, welcome to another, not just another episode, but welcome to another season of Innovation Junkies. My name’s Jeff Standridge.
Jeff Amerine:
Hey, it’s Jeff Amerine. It’s great to be here. I know we’ve got a great guest lined up for today, Jeff.
Jeff Standridge:
We do. We’ve got a great season and we’re kicking off this season with a, with a great guest as well. Really happy to have Dr. Kevin Sexton. We’ve known Dr. Sexton for a number of years, have worked with him in a variety of capacities. He’s not only a surgeon, he’s an informaticist. He’s a, an entrepreneur, pretty much an all around great guy. And it’s really, really good to have you with us today, Kevin.
Kevin W. Sexton:
Well, Jeff, thank you all. Um, and you didn’t tell me that I was kicking off the season. I need to lower folks’ expectations here.
Jeff Standridge:
Yes, sir. No, no, no, we, uh, we did this upright. We did this upright, having you kick it off and, and, uh, we’re going to talk about a number of topics, but before we jump into that, um, tell us, tell our listeners and, and, and remind Jeff Amerine:nd me as well, uh, what all you’ve got going on these days and where you’re spending the majority of your time.
Kevin W. Sexton:
Sure. Happy to. I’ll start with, I am a surgeon at the University of Arkansas for medical sciences. Nothing that I say represents the opinion of my employer. I spend most of my time doing abdominal wall reconstruction and hernia repairs. So that combines technology with robotics, laparoscopy, and helping to do complex operations through the smallest incisions possible. So people get home and back to their family as quickly as they can.
When it comes to entrepreneurship, I help advise a company called Hoopcare. We do get people ready for surgery as a service and the software. I help with a health tech company called Hdrop that creates a wearable to measure hydration status in triathletes. I also help a company called Qventus that works in optimizing data flow in a hospital and in an operating room. Outside of those things, I have several federally funded grants. Most of them are around developing entrepreneurial educational programs for different groups that can be, we have one through the Economic Development Association, minority business development agency for social and economically disadvantaged inventors. And then we have another that’s for postdocs scholars.
So, most of my time is spent leveraging entrepreneurial principles either in practice, applying them to healthcare technologies or in helping train the next generation of entrepreneurs.
Jeff Standridge:
Very good, very good. Well, as I’ve known you over the years, I’ve really come to think of you as a data guru and a technologist as much as I think about you as a surgeon. How did you get into that aspect of healthcare?
Kevin W. Sexton:
Yeah. I mean, it’s, I feel like this is the way a lot of us are drawn into other things. Someone recognized a talent in me that I didn’t know that I had and lifted me up into the role. Um, when I was a junior resident in surgery, I had a senior resident that said, Kevin, I like the way you think about taking care of patients. You’re, you’re very focused on math for some reason, and we need some help writing algorithms in our company to predict complications after surgery.
The guy’s name is Chris Kuzniak. And I said, Chris, I’ve never done this before in my life. He said, yeah, I know that, but I think you can. So will you give it a try? And that’s what I did. And it was one of those things that data is very intimidating, particularly if you don’t know what you’re doing. But that’s where I learned the power of transparency and honesty. Cause Chris was like, I absolutely know you’ve never done this before, but I think you can. Will you give it a try? Turns out, it, it was like learning a new language, but once you learn it, it’s really easy to not easy, but it’s more straightforward to apply the principles. And so I was using information, reading the medical literature about helping myself make decisions for patients. And all this was, was translating that into a way to talk to other people and present data to them in a way that they make a decision, usually in alignment with what you think should happen. And after that, I, um, I learned about data standards and healthcare, um, one called HL seven. I started working with that standard and then have always been around data. Um, but it all started, I think, because someone thought I could do something. I had no business probably trying.
Jeff Standridge:
Got it. Got it. So, you know, you talked about entrepreneurial programming specifically in, in, you know, healthcare and for physicians, you know, one of our observations has been that if you take someone who’s a physician or a PhD researcher who has a real, uh, healthy background in, uh, bench research and in, in even clinical research, um, it’s sometimes difficult to get them to back, back up and really begin to apply the entrepreneurial process that we try to try to apply with all entrepreneurs to really think about the problem you’re trying to solve, to think about the commercial viability of solving that problem. You run into the same things when you’re, when you’re working with physicians and other, other clinical researchers.
Kevin W. Sexton:
Yeah, you do all the time Jeff, and you know, for each individual, it’s hard to generalize and say what it is for everyone but typically what I see is that you have someone who is highly skilled in a very narrow piece right they are the world’s expert in whatever that discovery is or that invention getting them to take a step back and ask questions outside of that realm.
It’s very uncomfortable. And my experience has been that the best entrepreneurs are really comfortable being uncomfortable. Right? Like that. And so what I do when I’m working with a physician or a new investigator, like I’ll step back and ask very basic or simple questions and we’ll ramp up into getting more technical and more complex, but I’m trying to get them
almost out of their space because they know it so well. And this is different. It’s, we all know that ideas are, are cheap. It’s the execution of the idea and you can have a great product. If nobody wants it, you have a failed business. And a long time ago, I used to work at Circuit City and I sold a product called TiVo. And this makes me think of that. I don’t know if you all remember that.
Jeff Amerine:
Yeah.
Jeff Standridge:
I do remember TiVo.
Kevin W. Sexton:
But TiVo had the best features, the most memory of any digital video recording. But since you got one free with the cable subscription, no one ever bought it.
Jeff Standridge:
Mm -hmm. Yeah. Yeah. Well, um, no one except me. Um, anyway.
Kevin W. Sexton:
Me too. Me too.
Jeff Standridge:
Well, let’s transition and talk about the intersection of technology and healthcare and AI. What are you seeing out there today in terms of that intersection and how technology and AI are being leveraged to solve healthcare challenges?
Kevin W. Sexton:
Oh man, um, this is really a case of trying to drink from a fire hose. And I feel like people are throwing tons of spaghetti at the wall to see what sticks, and there are new AI unicorn company or companies with billion-dollar evaluations every week. But I think we’re missing a few things in healthcare. AI is focusing a ton on automation and automating tasks.
When we do that, we stop asking, should we be doing this task? And so we just put something in dogma and it becomes one more thing. That’s a burden on the system. So I think the other key component is we’ve had predictive systems for a long time in terms of scoring systems, how patients are going to do these fall through when it comes to implementation.
Jeff Standridge:
Mm -hmm.
Kevin W. Sexton:
Getting someone to use the tool, trust the tool, and lastly, integrate the tool into their workflow is tremendously challenging. And I think what we’re seeing in terms of a shift is more and more of these companies are trying to build a perfect solution for many different problems because of the difficulties in healthcare finance at the moment, smaller margins. Um, people are wanting to be platforms. And so they come in and they’re like, we can solve all these different problems. Oh, I’m going to be honest. No young company can do any of that. Well, it’s just too hard. You’re spread too thin. So the people that I think are finding the most success are saying, we do this one little thing really, really well. Right now, I think the examples are in revenue cycle. And you’ll see a lot of AI companies in revenue cycle for billing optimization. And they’re not trying to change documentation. They’re not trying to do anything other than say, we can help you drop the right charge and make sure that you’re compliant. So, I feel like it’s a great time and that I get to see a lot of new companies every week presenting technologies. I feel like most of them are underdeveloped when they come to be integrated into an enterprise electronic medical record. And what I mean by that is Epic is one of the larger players. So is Cerner.
Usually to be able to do that integration well, you need to have a customer that’s on one of those platforms to get that customer. You either need to have a founder that is tied into a system in some way, or usually be part of a program that helps you access those resources and then co-develop the technology with that larger partner because it’s difficult to develop a technology in the current sandbox environments for the larger EMRs.
Jeff Standridge:
Mm-hmm.
Jeff Amerine:
Follow-up question for you, Kevin. You know, beyond the growth of the EMRs and all that kind of transpired as a result of the Affordable Care Act, meaningful use, it still seems like sitting in 2024 customer journey and personal health records and, and having, and from a patient perspective, having to do repeated tasks every time you go to a new office or a new practitioner is still kind of, uh, it’s a laggard, if you will, in terms of automation, how do you see that improving a lot of patient frustration on having to answer the same questions 15 different times, depending upon what visitor, what specialists they’re seeing where’s that going?
Kevin W. Sexton:
Absolutely. Um, and it is a problem. And a lot of times, the larger EMRs are requiring use of their patient portal. So they’re actively limiting innovation in the space. Even with that, though, we’re seeing a lot of companies build bolt-ons on top of these patient-facing EMR portals, and they’re starting to build aggregation platforms. I mean, you all may have seen this, um, an Apple health kit, like when you pull up your iPhone, you can pull up different facilities that have patient portals, and it has some data aggregation, but it’s not useful information. It’s not, um, organized in a way that you would commonly see in electronic medical records for decision-making. So what some companies are doing to solve the problem is finding ways to take that EMR snapshot, structure the data, and then once the data is structured, push it into whatever format the client desires. There are remote patient monitoring companies that are starting to get into this space, and they’re pushing vital signs or whatever they’re monitoring. The thing that I like to see is that by them taking data from one system, structuring it as part of their technology, and pushing it into another, that concept’s applicable to everything. And ultimately, I would love to see people in control of their own data. Unfortunately, health systems know that by having a large quantity of a person’s data within their system, they become more likely to use that system for all of their care or for the majority of their care. Whereas I think we are hopefully in the next five to 10 years, I’m truly going to see a global market where you can take your data anywhere and when we go back to the AI question, looking at rare diseases and, um, just really uncommon presentations of illness. If you’re able to do that, you’re able to send your information to be reviewed by multiple experts and award technologies to help identify diagnoses that would be harder to make as a practitioner like myself. That’s a surgeon that would never see this in my career.
Jeff Standridge:
So other than the ownership issue between health systems, right? What has to happen technologically in order to make that, you know, I’m in a system where my primary care or even my specialist is in an epic system, and they want to refer me out to MD Anderson or to somewhere else that is a Cerner shop, you know,
What has to happen technologically to enable that to take place?
Kevin W. Sexton:
And Jeff, that’s a good question. So to answer it, I will talk a little bit about the data in an EMR. It sounds very structured, right? Lab values, we have a lot of machines, X-rays, around 80 % of the data in an electronic medical record system is in text and is completely unstructured. So the key to being able to move that data efficiently,
is to be able to structure it in some way and package what’s relevant for that clinical encounter. If you’re being referred to, let’s say, someone to have a cancer diagnosis, maybe your vaccine history is not as important to them, but they definitely want all of the path, all of the genomics, if any has been done on tumor slides, that type of thing. So there’s going to be innovation here in the near future and how we structure and label data to allow for transmission. Now there are also ways that AI is going to help us process a tremendous amount of data. Like sometimes in just scanning pathologic slides of tumors, you can create up to a petabyte of data we’ve not handled that at scale and to take it a step back and something that’s a little more relatable. Let’s say you’re a diabetic, you’re measuring blood sugar at home. We’re used to you bringing in a little log book that’s got, you know, a couple of readings every day when now you could be wearing a continuous glucose monitor. And so I’ve got numbers every six minutes. If I want them, we don’t know exactly what to do with that, how to put that in electronic medical record and there’s also some liability with that in that, OK, if there is one abnormal value in those 10,000 and I don’t act on it, and it ends up being significant, physicians or lab or in health system. So I think the keys are going to be how to structure the data and then how to analyze all of the data to highlight things for clinician review to discern the signal from the noise, so to speak.
Jeff Standridge:
Yeah. Right.
Jeff Standridge:
And so you’re thinking that that may be a role for AI there is to help figure out or how to streamline the process of figuring out what data to send and then how to package it to send.
Kevin W. Sexton:
I think so. Um, right now, most every AI program is what we call provider in the middle, just meaning they have the technology, they have the provider and then they have the patient. So the technology is all only going to be presenting information to the provider, not making a decision. And, and that’s where I think we’re going to see some regulatory changes and some optimization for automating things like having the software make treatment recommendations for common titrations, maybe insulin, maybe blood thinners in the hospital, something like that.
Jeff Standridge:
Gotcha.
Jeff Amerine:
Do you see, you know, as a follow-on as a small business owner for the past 15 years, one of the things that we see and we struggle with every year is the healthcare costs continue to go up. And we like providing the coverage for our, our employees and for our team. The Affordable Care Act was supposed to bend some of that curve, but it still seems like it’s high single-digit, double-digits every year. You would think as is true with nearly every other industry with the insertion of technology and productivity gains, you begin to get some advantage on the cost side. Where’s, where’s that going? And are we going to get any relief? Are we going to be able to do more or less? What’s your take on all that?
Kevin W. Sexton:
Yeah. I mean, it’s a struggle, right? Usually healthcare is the number two or number three cost of any organization outside of labor, which in our country, it’s just, um, it’s difficult to understand. So what I see folks doing in the space to help with innovation is first of all, matching, um, folks to the appropriate plan.
based on where they are in their phase of life. So helping them pick the insurance that’s most likely for them to serve the best purpose, help them set themselves up fiscally to do well, and then having some level of catastrophic coverage. If we look at healthcare compared to computer software, and we think about the last 20 years, right now for computer, year on year, the price of software goes down in healthcare year on year. That price has gone up two to 3%. And previously it’s been because of the higher regulatory burden and a lot of it from the lack of rapid innovation and competition that we can have in healthcare. I think the pandemic highlighted this a little bit with telemedicine programs and prior to the pandemic, you had only a couple options and the features were poor. And now we have dozens of options, all compliant. And we have many different feature sets that were iterated in the last five years, waiting rooms, screen sharing, other things that weren’t possible five years ago for most of the vendors. So we have to find some way to reduce the overhead for healthcare innovation to truly see costs go down. And right now with Medicare, only 1 .4 % of the spend is at risk and in value -based dollars. We have to see some way for that to go up so that we can both partner to be at risk for providing a level of care to someone that helps them where they are. And I think it’s difficult because we’re still focused on treating disease, not preventing disease and our system. I mean, it’s truly amazing when, and y ‘all, I’m sorry, I study history of medicine. I love it. Love to learn about it. But if you look before world war two, I mean, we had few surgical interventions. We had few things that worked well, like antibiotics. So we got really good at treating acute illness, and some things we’ve not impacted like cancer survival, some cancers we’ve improved. Others have largely been the same for the last 20 years. Heart disease is still the number one killer. So I think what we’re going to see, Jeff, is we’re going to have to be smarter about the plans that we select and support for our employees. We’re going to need to empower them earlier with ways to keep themselves healthy. And that whole space is, I’ll say it’s not at this point, what I would call evidence-based in terms of wellness programs for employees. I think employers definitely want to provide them. They’re seen as a perk. Um, but I can’t tell you giving your employees a gym membership helps prevent their risk of cardiovascular disease long-term.
Jeff Standridge:
Right. Well, let’s transition a little bit. And you mentioned some of your grant funding. I know your organization recently was, was funded by the economic development agency in their minority business development group. So tell us a little bit about the MBDA grant that you have and, and what, what you see happening there over the next couple of years.
Kevin W. Sexton:
Yeah. So this grant is part of the capital readiness program. And for us, we’re working with socially and economically disadvantaged owners to do healthcare businesses in Arkansas. And it’s, when I say healthcare, it’s loosely related to health wellness in some way. We provide a small amount of capital, but mostly mentorship, to this company for the next four years trying to get them ready to raise capital in one shape or another either through venture funding but also through federal grant programs, state grants, any assistance that we can. And like you all we’ll partner with anyone to help with that and get them the resources they need. I think the the best part about the program is the group of mentors that we’ve put together and that we’re committed to trying to improve the health in Arkansas. And one of the ways that we think we can do that is by empowering entrepreneurs in the rural areas and in the areas where the problems exist to solve their own problems. They know what they are. They know how best to solve them. We’re hoping to just give them some skills to be able to raise capital and create sustainable businesses.
Jeff Standridge:
Very good, very good. Jeff Amerine, any follow-up questions from you today?
Jeff Amerine:
No, I think that’s a pretty good tour de force, so to speak of how technology is impacting a variety of things. And it certainly does seem like the intersection between food and wellness and health access and the social determinants of health in rural areas is kind of a big deal. And it looks to me like you’re right in the forefront of a lot of that.
Kevin W. Sexton:
Yeah, I mean, it’s, um, I’m an optimist by nature, but I think it’s a really exciting time to see what’s going to be coming next. The landscape for what AI technologies are able to do is accelerating at a tremendous pace. And it’s already starting to alleviate some of the administrative burden of medicine, which quite frankly is what I like the least about my job.
Jeff Standridge:
Well, Kevin, it’s always been a pleasure and always is a pleasure to work with you in whatever capacity we find our paths crossing, which is usually fairly frequently. And it’s also a pleasure visiting with you. I love hearing you talk about the things that you’re passionate about, particularly in the healthcare technology intersection. And we appreciate you taking the time to spend with us today.
Kevin W. Sexton:
Happy to be here with y ‘all. Thanks for the invitation.
Jeff Amerine:
Yeah, thanks for joining us.
Jeff Standridge:
This has been another episode of the Innovation Junkies Podcast. Thanks for joining. We’ll see you next time.