Smarter Decision Support For Value-Based Success w/ Radial CEO, Thaddeus Fulford-Jones

Is smarter decision support the key to unlocking value-based success?

In this episode of the HealthBiz Podcast, Thaddeus Fulford-Jones, CEO of Radial, joins host David Williams to explore how Radial’s AI-powered decision support software merges cutting-edge data science with clinical best practices to enhance patient outcomes, reduce costs, and optimize value-based provider operations.

Thaddeus Fulford-Jones' book recommendation: Reservations for Nine by Dr. George Beauregard

🎙️⚕️ABOUT HEALTHBIZ PODCAST
HealthBiz is a CareTalk podcast that delivers in-depth interviews on healthcare business, technology, and policy with entrepreneurs and CEOs. Host David E. Williams — president of the healthcare strategy consulting boutique Health Business Group — is also a board member, investor in private healthcare companies, and author of the Health Business Blog. Known for his strategic insights and sharp humor, David offers a refreshing break from the usual healthcare industry BS.

🎙️⚕️ABOUT THADDEUS FULFORD-JONES
Thaddeus Fulford-Jones is the Co-Founder & CEO of Radial (www.radialcare.com), a healthtech company leveraging AI and machine learning to improve patient outcomes and financial performance in value-based care. Radial develops next-generation decision support tools that help organizations target the right members with the right interventions at the right time. Previously, Thaddeus was the Co-Founder and CEO of Locately, a location analytics firm that pioneered mobile-based consumer insights. He holds a PhD from MIT, where his research focused on complex systems and modeling. Throughout his career, he has been passionate about applying technology to solve critical challenges in healthcare and beyond.

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Transcript

David: 0:00

Transitions of care are critical moments in a patient's journey, but they're often chaotic, costly, and harmful to health. Well, what if data and AI could make transitions smarter and smooth? Hi everyone. I'm David Williams, president of strategy consulting firm, health business group, and host of the health biz podcast, where I interview top healthcare leaders about their lives and careers. My guest today is Thaddeus Fulford-Jones, CEO of Radial. His company is reinventing care coordination and real time decision support for value based care with the goal of delivering the right care for the right patients at the right time. Do you like this show? If so, please subscribe and leave a review. Thaddeus, welcome to the Health Biz Podcast. Thank you for having me on the show. So we're going to talk a lot about Radial and what's going on there now, which is a lot of terrific stuff. Uh, but I want to hear a little bit about how you got to this spot and love to start with just your background, your upbringing, you know, what was your childhood like? Any influences from childhood that stuck with you through your career?

Thaddeus Fulford-Jones: 1:09

Yeah, definitely. So I grew up in London, in England, and actually my father was a medical doctor. So he worked in the National Health Service, also known as the NHS. And various other relatives were also broadly in health and social care professionals. So, long history among my relatives of people in teaching, nursing, for example. And actually, when I was a teenager, I did a work experience placement at an NHS hospital just outside London. That was an experience that was definitely memorable and eye opening. And I think anybody who's sort of spent time in England knows that definitely the National Health Service has its fair share of problems. It's far from perfect. Budget limitations, waiting lists, etc. Those are some of the major issues. But also too, there's lots of positives about it. The National Health Service is universal healthcare. And most people, I think, in the United Kingdom would say that's a very good thing. And thanks to the NHS, everybody has access to care if they need it. And another part of that, of course, is that the NHS, by definition, does total population health. Because if you have a limited and fixed budget for the entire nation's healthcare, then you have to figure out how to spend it wisely. to achieve the best results possible. They've been learning how to do that for a very long time, and they've got very good at it. And fundamentally, the answer is to invest in all things preventative. So that starts with primary care, social resources, focusing on that helps prevent much bigger problems in the future. And that's how they help avoid high cost hospitalizations, specialist visits, nursing homestays, etc. So, in summary, I would say growing up I was definitely sort of exposed to people who truly dedicated themselves to being part of the caring professions. And then as a result of being in England, I certainly came to appreciate the importance and the value of access to care for everybody.

David: 3:04

Got it. Very interesting. Yeah. When I was a teenager, I worked actually at a VA hospital, Veterans Administration Hospital in Washington, DC, uh, with some researchers and we were, we were actually doing some work on clinical decision support using decision tree analysis with the mumps programming language. So we may have been doing similar things in different places. So fascinating. Yeah. So what did you do in terms of school? Because I think eventually you found yourself on this side of the pond and we may have first interacted just after you were finishing up.

Thaddeus Fulford-Jones: 3:33

I think that's right, yeah. So I came to America at the age of 18 for undergrad. And I was originally thinking, of course, that I'd just be in this country for a few years, but instead, it was the start of a much longer journey, and here I still am, based in Massachusetts, and so I studied computer science, various different engineering disciplines, along with that, ended up doing a PhD at MIT. And many people know that MIT is just a phenomenal place for innovation. I loved my time there. And I think one of the things that MIT is really famous for is there's a culture of really translating innovation into impact. And so many people do that specifically through startup building. So when I was at MIT, I got connected with this remarkable community of alums, mentors, teachers, people who are sort of real experts in entrepreneurship and who have a lot of experience building startups and understanding what that journey is like. I got to compete in business plan competitions. I took classes, seminars, workshops. Basically a foundational education in how to build startups, or at least the theory of it. And I think for the first time I started to develop a vision of what it could look like for me personally to embark on a career that combined innovation with real world impact. And so when the time came and I finished my PhD, that vision is sort of what drew me away from considering a career in academia. To really jumping into startup building in a more serious way.

David: 5:07

So, you know, you had this experience in, in England in terms of the, uh, you know, universal care and mission driven elements and all those that you learned at, at MIT. And I know at Radial, you're applying it for the greater good. What was your, was your first startup also uplifting mankind? Well,

Thaddeus Fulford-Jones: 5:24

maybe in a small way, or maybe in a different way, or maybe not really at all. I'm not entirely sure. But it was a company that we founded called Locately. And my co founder Eric was actually my housemate at the time, a fellow MIT grad student. And it was a really interesting moment in time because iPhone had been launched just a few years prior. And so for the first time, people were starting to think about how to use data generated by these powerful little computers that. We're quickly becoming commonplace. And we realized that based on our technical background, we had this sort of unique and very timely opportunity to use tech that we knew how to build, to mine massive volumes of GPS data, location data from these new. Always on very user friendly smartphones. And so here's what Locately did. Our technology allowed market researchers to gain a better understanding of consumer behaviors, specifically around shopping. And it was one of the first sort of very practical and useful applications of a field that eventually burgeoned and now it's called location analytics. And so how it worked is we would invite shoppers to download our app onto their phones and we'd give them rewards, things like gift cards, prizes for anonymously sharing their location with us and completing surveys about their shopping experiences. And our customers were some of the biggest consumer goods manufacturers, PepsiCo, Coca Cola company, Procter Gamble and others. And Locately ended up being very successful. was acquired by a global market research firm. The technology scaled up, including beyond the U S. And after staying with that acquirer for a few years, my co founder and I were ready to start building a new venture. And that's what led to Radial. And I think what really inspired us was this idea that we knew how to build technology and we built a first startup successfully. And that learns a lot about. What it's like to build a company in the real world, but we were certainly motivated to try and apply some of that in ways that could be beneficial in health care and have a more obvious societal impact. And we wanted to ask that very important question. Are there ways that we could use technology to make health care better, both for the provider and for the patient? And at that time, the sort of really big wave of momentum that was clear to us and that got us excited was value based care. Because it felt like value based care was the first real opportunity for the United States healthcare system to start moving away from this outdated legacy fee for service approach and truly start delivering on the promise of better outcomes for lower total cost. And I think what we recognized is that. Technology would need to play a really big role in making that possible.

David: 8:16

So as you say, you know, value based care is something that you, since you founded Radial has increased and there's been kind of the, the goal, at least of, uh, CMS, which runs Medicare in particular. And what that requires, I think is a, you know, a bunch of changes, but one of the things is for providers to use some new sorts of tools, including what you're building. And I'm wondering, what are some of the challenges And opportunities for providers in adopting some of those tools, which, which now are also including things like, you know, AI driven decision support, which is, you know, kind of come across as a, as a relatively new thing over the past few years and people are grappling with it. But what, what are the challenges and opportunities there? I

Thaddeus Fulford-Jones: 9:00

think from my perspective, the main challenge is that providers generally are very overwhelmed. And AI is a field that is just moving so fast. So maybe I can give you a real example that paints the picture. In late February this year in Denver, two of my colleagues from Radial, they were faculty at a pre conference workshop that was actually about AI's role in hospice and palliative care. And this was a really big, prestigious conference. It was the annual assembly of hospice and palliative care. And Radle was there in partnership with some of our friends and colleagues from Mass General Brigham, which is one of our customers. The audience was just a group of brilliant clinicians, palliative nurses, doctors, really motivated to get thoughtful about and understand the future of technology and what it meant for their field. And one of the things that I thought was really terrific that my Radle colleagues did to kick off the session was they asked a question, almost like an icebreaker question, and they asked, what does AI make you think of? It was one of those phone based surveys where people fill in the results on the phone and the results pop up on the big screen for everyone to see. And the word cloud that resulted, it definitely included some really positive words. Words like helpful, efficiency, potential. But also too, there was the word scary, there was the phrase ethical challenges, somebody even typed in Skynet, which got a few laughs from the audience. And uh, the reason I like this example is I think it really captures perfectly the duality of AI in healthcare today. There are some really awe inspiring possibilities, but there's also this mentality of cautious curiosity, which I think is appropriate. And what we find when we talk with providers and payers across the nation, Is that it's really important to address and understand these very real fears and challenges alongside providing a clear understanding of what the opportunities are providers and payers that are overwhelmed as it is and AI just means so many different things to different people. It can be so confusing. There's so many nuances, even the basics of what is generative AI versus machine learning, and is it AI if it's not looking like a chat bot? I think our opportunity at Radial is first and foremost to really listen, and then to help guide people and have these honest, nuanced, forward thinking conversations that address people's concerns, which are very real. And also educate on how to mitigate those concerns given everything else going on.

David: 11:36

It's interesting to hear what you're saying about kind of the individual's perspective on AI. I was listening to discussion I was having with somebody about something going on with an academic medical center on the West Coast. And they said there was a vascular surgery clinic and they had come up with this great AI based model to predict who might have an embolism after surgery. And they went off of this. product to, uh, the surgeon, the, uh, the physicians that take care of the patient after surgery, but they're worried about a stark law violation because if they offer it and then the, actually the outcome of that is to refer the patient back to the surgeon, that could be an issue. And at the same time, uh, if they've got this, uh, predictive model going on, uh, within the surgery group and they don't share the results and then some patient does have embolism, you know, then during discovery, you're going to come back and find that out. So the, the. The outcome of that in 2025 is squelched. So it is interesting that a lot of things that would make sense that you would want as a patient are being held back, not just because of perception or concern, but also just because of some of the structural issues that are within healthcare today. Absolutely.

Thaddeus Fulford-Jones: 12:41

Yeah, no, that's a really good, great point. And I think there is a lot of complexity in healthcare generally, and that comes from legal and compliance in addition to the more individual level question as well. So I think that's a really good illustration.

David: 12:54

One of the things that value based care kind of requires or encourages is a move away from care in expensive facilities toward more community based care or home based care. And I'm wondering, um, the impact there of technology, uh, on that balance between things that are done in, let's say a hospital versus in the home or, you know, lower acuity setting in general.

Thaddeus Fulford-Jones: 13:20

Yeah, I'd love to share a patient story maybe from one of our customers, which is Maine Health. And so they're the biggest hospital network in the state of Maine. And they're really big into value based care. They have 300, 000 plus covered lives and various ACO type contracts, including The Medicare Shared Savings Program, and, uh, in December, one of Maine Health's physician executives actually did a HIMSS New England case study that talked directly about Maine Health's results from using Radial's AI decision support technology for next site of care. So that's a product that we have called Placement. And what Placement does is it helps entities that are in value based care contracts. Avoid these unnecessary and, as you pointed out, often high cost rehab stays at nursing homes for seniors. And the way it does that is by proactively flagging exactly which patients could instead safely go home, and typically that's with visits from a nurse or a physical therapist. And one of the slides that MaineHealth presented in this case study was a real story of one of their patients, so a gentleman in his late 70s. who was admitted to Maine Medical Center, which is their flagship hospital, for a pretty serious exacerbation of a chronic condition that he had. And what Radial's placement AI decision support technology did was automatically detect that under standard practice patterns, so if we did nothing different than usual, this patient would probably get discharged to a nursing home. But actually, according to the data, he could and should go home instead with visiting nurse and physical therapist. And we call this type of situation on the border because the discharge plan isn't obvious to the care team in the hospital. It's one of those situations where it could go either way. And that's one of the areas where AI can be really beneficial because the Radial placement decision support tool flagged this patient in real time and basically brought it to the attention of the care team that this is someone they should focus on. The technology also provided a plain language explanation to explain why, so what are the reasons and drivers that this patient could do just as well or better in the home setting. And actually in this specific instance, there were a couple of different therapy evaluations. that reinforced what the technology was saying about this patient being on the border. So specifically, physical therapist in the hospital went into the patient's room, did a consult, recommended a nursing home. They said the patient needs supervised rehab sessions to regain balance and strength after the hospital stay. By contrast, there was another professional who came in to do their evaluation, an occupational therapist, and they actually said the opposite. They recommended home care. So they said the local home health agency has capacity and is able to provide home based visits as often as daily and so the user of Radial within the main health system, they were able to point out not just what the technology says, but also shine a light on these. mismatched PT and OT evaluations, call that out to the hospital care team. And through that, they were able to get some really good collaboration and also concretely drive something called early mode, early mobilization. So early mobilization is exactly what it sounds like. It means helping the patient get out of bed sooner than would otherwise happen often supervised by PT and nursing staff. And the reason you do early mobilization is to prevent deconditioning. So that way when you get to day three, day four of the hospital stay, patient's ready for discharge, you'll actually have options rather than it being a foregone conclusion that the patient needs to go to a nursing home for rehab. And in this case, the results for this particular patient were terrific. The team worked together, came up with a safe discharge plan, got the patient discharged home, set up the home health visits, and that was successful. No readmissions and a savings to the Accountable Care Organization of around about 20, 000 because these facility based days, as you noted, are extremely expensive. And the best thing is the patient got to go home, which is where they wanted to be in any case to complete their recovery.

David: 17:37

So you raise a number of interesting points. First of all, congratulations on having those sort of results and having them published. That's really, I know. Uh, a great goal that we talked about, um, before. So in describing that, um, you know, you noted that the, the tool will explain its reasoning essentially, and point to the specific evidence. And one of the, uh, one of the things that I think AI has noted for, and maybe LLMs in particular, are it's like, it comes out with something that's amazing and sounds amazing, but you don't really know, you don't know at all where it's coming from and you don't know whether to be confident in it. Uh, or not, and so, so the first point is it sounds like what you're doing is you're, you're providing the analysis to say, like, where did the reasoning come from? So you're showing that and then, then someone can look at it and then presumably they could say they can make their own adjustment based on, okay, well, I know this person is very experienced or maybe this other one has a financial incentive. Or whatever, or you just get them to work it out. But I'm also wondering about like a small study that I got a lot of, uh, notice, I think like in the New York times about, you know, comparing how well does, uh, how well does the clinician do alone, clinician with AI or AI alone. And I think the worst example was a clinician. with AI. So, what happens when you provide the results and the reasoning, does that always lead to good things, or can it actually lead to more problems if people start questioning the results and making their own adjustments?

Thaddeus Fulford-Jones: 19:08

Yeah, that's a great question. I saw that study as well, and I agree that it was a bit, uh, non intuitive and a bit puzzling why those results were achieved in that specific situation. I will say that every AI deployment is different. And so we always try to evaluate on a case by case basis and really understand what are the results and what are the difference makers as a result of our technology. Specifically, I will say that one of the advantages that we have as a company is that we. built out our technology in a very robust, scientifically based anchored way. We started out actually with funding from the National Science Foundation and NIH. So the first several years we were very much in research mode and our foundational realization, I think behind the development of our technology. Was that the legacy approach of risk stratification that on its own really isn't enough to win at value based care and we found that one of the key difference makers in addition to the A. I. Was providing human understandable language. That explains the reasoning and allows people to work with the AI and understand where it's heading rather than leaving it to be a black box. So much more than just a score or an assessment or a red, green, orange. Check like pattern. We try to explain what's the reasoning and allow people to make the decision in a way that supported. So our technology isn't making decisions for clinicians. It's decision support to guide them to see a fuller picture. And ultimately, I think what we focus on is the results. Are we consistently able to deploy our technology? across different settings, whether it's hospital based or an entire ACO within the community, physician led perhaps. And are we consistently demonstrating better performance versus the status quo? That's always the gold standard. Unfortunately, we've been able to do that with case studies and conference presentations, as you mentioned, consistently over the past several years.

David: 21:18

One of the things that I like about Radial is the focus on post acute care because that's where there's a lot of cost and a lot of variability. So if you're doing something from a value based, um, from a value based perspective, there's more opportunity there than elsewhere. And although a lot of areas of medicine are pretty weak on their use of evidence based care, post acute has been particularly like that because a lot of the, a lot of the decisions are made. Based on convenience or what they think that the, uh, patient's family wants or whatever, um, and not based on good data. So it's nice to see, uh, you making some progress, uh, in that area. You mentioned the different, uh, settings where the platform has been deployed, whether it's, uh, an acute care setting, like a hospital or whether it's with. Um, and ACO. Are there other sorts of settings? How do you think about the universe of places where the Radial platform makes sense?

Thaddeus Fulford-Jones: 22:13

Well, it's interesting. You mentioned post acute and definitely where Radial started was very much in the transitions of care space from acute to post acute care. But actually today our offerings are much broader than that. We have an entire platform called Radial Care which uses AI for many different opportunities that entities face when they are taking risk on a total population of covered lives. So definitely our sweet spot is with Provider based ACOs and payers, but foundationally our technology helps reduce medical expenditure all around this broader theme of centralizing more care in the home setting. That's not just about avoiding costly stays at nursing homes. It's also about avoiding unnecessary ED visits. Or, uh, readmissions. So avoiding unnecessary readmissions back to the hospital. It's even about social determinants of health and addressing SDOH challenges for members that might be leading to a lot of this unnecessary or low value utilization of care. And so as an example, in our work with one of the nation's largest physician led ACOs, CareMax, our technology helped achieve millions in savings while also reducing readmissions by 25%. very much. Another example, Mass General Brigham, they shared a case study last year at the National Value Based Payment Summit Conference, and that highlighted a 24 percent boost in palliative consults and improved consideration of hospice. Again, millions in savings accrued to their Medicare Accountable Care Organization as well, but that's from helping Patients who are approaching end of life enroll timely in hospice so they avoid the unnecessary or low value care that often comes with repeat utilization of hospital, nursing homes, other type of facility. So, to summarize, radial care, yes, does have a focus on highlighting opportunities for care to be delivered in the home setting, as opposed to facilities, but today it goes a lot broader than just post acute and just that one moment of transition from acute to post acute setting.

David: 24:22

You mentioned social determinants of health, and I've noticed you've been doing some work and some publishing. Uh, on that. So I'm, I'm curious about how addressing social determinants factor in to making the platform actually work beyond sort of just a nice thing to do. I saw something about an area deprivation index as well. I was interested in, in how all these things, uh, relate. I think a

Thaddeus Fulford-Jones: 24:45

few years ago there were general questions and good questions about to what extent addressing SDOH is helpful in healthcare. I think today it's much more widely accepted that SDOH is important and addressing social determinants really makes a big difference in health outcomes. And because of that, we built SDOH capability in a way that underlies all of the different radial AI decision support tools. It's usually important because it really does make a difference in determining outcomes. And by automatically tracking and incorporating these risk factors, we allow our users to address social determinants of health and also prevent inequities in care. And also the element is helping care teams to proactively address these social risks that might otherwise lead to avoidable hospitalizations or poor follow ups. So, it's part of that broader theme of delivering the right care to the right patients at the right time. Also, too, part of the radial care platform is our social determinants of health decision support module. And that's to not only identify where SDOH challenges exist for patient, but also very proactively explain what a care manager should do to address them. So, it's really foundational to all of our work.

David: 26:09

You started announcing a number of partnerships. Uh, we're, we're just in March of 2025, but I see two so far bamboo health and HDI. Uh, what are those partnerships and, you know, what's the point of, uh, of putting them together?

Thaddeus Fulford-Jones: 26:24

These are actually both really exciting partnerships and in pretty different ways. So I'll start with Bamboo Health first of all. They have a platform which is called Pings and that delivers real time care intelligence. So think live notifications every time a patient has a care transition, like arriving in the ED or starting a short term stay at a nursing home, getting hospitalized. And by combining. The radial care AI decision support with bamboo pings that allows us to help customers who are in value based contracts to ensure patients get the care that they need by shining a light on the real time aspect of their total patient journey. So it's sort of. Combines the power of what we've built, the radial care platform with the bamboo nationwide network and all of this very rich real time data. And then separately, our partnership with HDI. They're a really interesting company. They're the leader in healthcare data integration. And so they have this very robust technology infrastructure. that turns almost any type of healthcare data into analytic ready feeds. And concretely, what that means is that radial care can now be swiftly and easily deployed for any value based care population. We started out just with traditional Medicare ACO, especially MSSP and REACH, but today that extends to value based Medicare Advantage, commercial, even Medicaid contracts as well.

David: 27:48

Great. All right. Well, there's much more to discuss here and I look forward to following. Your progress, but I have a final question, not necessarily related to what we've been speaking about up to this point, and that's for a book recommendation. Any good books that you've read lately or really at any point, anything you'd like to recommend for our audience?

Thaddeus Fulford-Jones: 28:06

Yes. So one book that I'm reading right now, actually, was just released very recently, started March 2025. It's called Reservations for Nine. A doctor's family confronts cancer, and the author is actually a longtime friend and supporter of Radial, Dr. George Beauregard, and he's himself a value based care thought leader as well. He leads one of the largest and most successful physician led ACOs in Connecticut, and the story is actually that George lost his son Patrick to early onset colorectal cancer when Patrick was just 32 years of age. And so it's a deeply personal, just sort of really well written tribute to Patrick and the entire story and their journey of cancer. It concludes themes of loss, resilience, but also, and this is probably the most important part and the reason I'm Glad to have the opportunity to tell your audience about it. It's a call to action about the rising incidence of these really terrible early onset cancers. A lot of people don't realize this, but especially among people in their 20s and 30s, these early onset cancers have been significantly accelerating in terms of incidence rates, especially over the past couple of decades. Nobody really understands why that is. But it's one of those situations where awareness and early detection can save lives. So it's definitely something that I encourage all listeners to read, share, help spread the word. Because something can be done, early testing and monitoring, and also importantly, not ignoring symptoms. A lot of people believe that cancer is just something that happens to the very elderly. But unfortunately, given this trend, that's actually swiftly becoming a real problem for much younger people. And that's something that we can do something about.

David: 29:53

Well, we'll make sure to include that, uh, in the notes so it gets the most circulation possible. Thank you. Well, that's it for yet another episode of the health biz podcast. If you like what you heard, I hope you'll subscribe on your favorite channel. I've been speaking today with Thaddeus Fulford Jones, CEO of Radial. Thaddeus, thanks so much for your time today. Thank you for having me on the show.