Why AI Should Reduce Admin

Dr Andrew Greenland 0:03

So, welcome back to Voices in Health and Wellness, where we speak with practitioners and healthcare innovators about the challenges, opportunities, and ideas shaping the future of healthcare. Today we're exploring artificial intelligence, but from a slightly different perspective, rather than asking how AI could replace healthcare professionals, what if we used it to remove the administrative burden surrounding them, giving clinicians more time and capacity to focus on patient care? And could doing that not only improve efficiency and access, but also reduce one of the major contributors to provide a burnout? My guest today is Dr. James Ries, a board-certified family medicine physician, active duty US Navy provider, and healthcare entrepreneur behind 20 Mile Medical. James is developing an AI-enabled healthcare platform designed to automate much of the administrative workload surrounding clinical care while keeping the healthcare professional firmly at the center of clinical decision making. So with that, James, I'd love to welcome you to the show and thank you very much indeed for joining me this afternoon.

Dr James Ries 1:00

Yeah, thank you, Andrew, for having me. This is a great opportunity to talk about this very unique subject. So

From Paediatrics To Family Medicine

Dr James Ries 1:06

thank you.

Dr Andrew Greenland 1:06

So, James, before we get into the AI and the technology itself, can you take us back a little and what was your journey into medicine and what originally attracted you to family medicine?

Dr James Ries 1:16

Yeah, that's a great question. I actually initially wanted to be into pediatrics, but then of course, you know, as you progress through medical school and as you do all your medical rotations, you realize that, or at least some people realize, they like a little bit of everything. And they and the other thing is uh, you know, telling a patient that I'm not trained to see them is something that I just didn't uh didn't sit right with me. So family medicine was a logical good fit, you know, from from cradle to grave, you know, taking care of everyone and and not turning anyone away was such a good motivator.

Navy Medicine And Problem Solving

Dr Andrew Greenland 1:53

Thank you. And you've also combined medicine with active duty and with a naval career. And how has that experience shaped the way you think about healthcare delivery and efficiency?

Dr James Ries 2:03

Yeah, quite a different animal. Um, I was actually very interested in just uh aviation, and that's what got me into the military pipeline. But since I've been active duty, I've realized that you know providing excellent level of care, no matter where you are, is uh a different thing. Sometimes you can't control your brick and mortar environment. Sometimes you can't control where you're gonna be administering that care. And so that um really lends itself well to telehealth, certainly, but it lends itself to all kinds of um unique problems that you have to solve. So you become a problem solver, which is a really interesting way to go about it. But I'm really happy that I did. You know, um, whether you're on a ship in the middle of the ocean or whether you're in a desert, you know, things change, but the standard, you know, you want to maintain it as much as possible. So the military career has been quite rewarding, a lot of fun experiences, but I have about a year left and I'm looking forward to transitioning because uh keeping that tempo is quite difficult with a family and everything else. You know, it's it's fun, but it doesn't last forever, and that's a good understanding to

Telehealth Growth And Access Barriers

Dr James Ries 3:22

have.

Dr Andrew Greenland 3:22

Thank you. And your point about problem solving. So, at what point did you start moving from simply recognizing problems in healthcare to thinking, I actually want to build something that solves them?

Dr James Ries 3:32

Yeah, that is an excellent question. I I got into telehealth. I've been doing it for about a decade, but really it took off and piqued my interest during COVID because people had little to no access to care. Sometimes they couldn't, you know, they weren't even allowed to, you know. So um when that all changed, it made me realize that there were that there were people out there that would otherwise not access medical care unless you took down some barriers. Even getting in the car and driving is a barrier for some people. And if you provide something that can still provide them a good standard of care and good high-level care uh care, no matter where they're located, you reach a large segment of the population that would otherwise go untreated. Um, a really good example is mental health. You know, psychiatrists ask people to come to the clinic for care, and sometimes their specific phobia is leaving their house. You know, so there's a big barrier there. And there's also people that are located in the middle of nowhere, and they just really don't know what to do, even with something as simple as a cold. And um, and so that really, really piqued my interest uh when it came to telehealth. And I saw a very un untreated large pop global population of people, and that became a new problem to solve.

The Real Friction In Care Delivery

Dr Andrew Greenland 5:04

So you talked about a couple of problems that you've solved, but were there any actual frustrations from the work that you've been doing as a practicing physician that also drove you to create what you've created in the platform?

Dr James Ries 5:15

Excellent question. Yeah, I kind of missed that. Um, so when I started with COVID, um, it started basically with you know synchronized visits, phone calls, but very quickly I realized that you know the the standard was really um relied on the provider. And that variability is what gets people hurt, you know, and and the systems themselves were very incredibly inefficient to the point where just to get one patient seen, you would have to staff that whole program with customer service and pharmacy reps and you know all kinds of systems that normally wouldn't be there, and systems that become very cumbersome that now have to talk to each other. And I think that after um, after all those systems are in place and you and you have it running, it becomes expensive. And so you really have to, from a first principles type of thinking, start over, not piggyback on what's been done, but start over and think, well, how can I do this efficiently so that we're not having to lean on all that administrative burden? You know, uh the provider probably only gets about 10% of the fee. The rest goes to all the administration, all the all the uh scheduling and all the coordination. And that really is the um that's the low-hanging fruit. That's what needs to be cut first. And I think what's happening now is people are still relying on these old systems and they're trying to think how can we cut costs, how can we become more efficient? And the target seems to go to the provider first because AI is very good at writing a soap note. But whether it can administer good health care, that's a different question. And there's systems in place now that are not administering healthcare. And so you don't have to worry about that when it comes to scheduling and you know, coordination and and documentation. You know, these things can be streamlined and you don't run the risk of losing that standard of care. And and I think it's just needs to be kind of re-rethought from the ground up because we have a new system in place now.

Building 20 Mile Medical And Talora

Dr Andrew Greenland 7:44

Thank you. So before we sort of dive a little bit more into the platform on your work, could you perhaps give us a sense of what your role is and how it fits into the bigger picture of 20 Mile Medical?

Dr James Ries 7:54

Yeah, of course. Yeah, 20 Mile Medical. So I've been working with many, many platforms doing telehealth care. And I my uh co-owner is a PA. He also does this. And after a while of creating just systems for ourselves to make things more efficient and better care, better patient communication, he had said, you know, we should probably just do this ourselves because we're spending a lot of time fixing other people's systems. So he encouraged me. He actually was the catalyst for all this, and we started our own telehealth platform with all the improvements and all the patient care that we had been forcing other platforms to to fix, and we just did it ourselves. And I'm very uh grateful for that because we've done a fantastic job, and everyone is is very appreciative on the platform. While we were um while we were creating the platform, we had to um use software. And when we started using software, we realized after interviewing a dozen or more different software platforms that they were all very deficient, and they were all developed by um you know software developers, not physicians, and they were all developed with the patient uh advertising and patient facing, um, but not anything to do with the provider and how the care is actually administered. And we we landed on one client and we've been using them for a while, but man, it's they they make things very limiting for the patient-provider interaction, even as something as simple as I need to change my credit card, you know, becomes like a monumental, you know, this this mountain that we have to climb up. And I'm like, we have got to change. And so we couldn't find any. And he told me, look, you need to build this yourself. And so I started uh getting into um coding software, and I do have you know some background in that just as a hobbyist, but it's turned into quite a passion project. And while I was developing our platform, I also was developing the tools that we had been using ourselves and I implemented it, and that's where that AI layer came in. So I built the electronic health record and the AI software together in unison. And um, what is very marketable, scalable, but also increases patient care, which is the most important thing, is that AI software. So offering that same layer we put on our own EHR to other EHRs fixes a lot of those problems that we've been so frustrated about trying to reach out to patients, even if it's a, you know, I send the patient a message and I and it breaks down from there, or uh, I need the patient to know I've made a change to their chart. These are all really small administrative things that would be common sense that are just not in the in the pipeline right now. And the AI layering um fills all these holes so much nicely and it integrates very easily to any platform. And so we called the AI software Talora, and that is our um that is our AI unit that we use, and it doesn't do any medical care, all it really does is it you know formats, it takes all the patient, you know, intake and history and everything, and it presents it to the provider in one strategic location right in front of them, so they have all the information they need before they've even clicked on the patient. And um, at the same time, what it does is I've built protocols in place that are evidence-based, meaning this is the standard of care. Don't go outside of this ever. And so when a patient has something that is not safe to treat or it's contraindicated, the system will notify the provider so the provider doesn't have to go search through all the records, pull up their up-to-date or their evidence-based guidelines, it's all pulled into one picture for the provider so they can confidently say that they're treating that patient at the highest level of their medical license. And that is not a actually difficult thing to do, it just hasn't been done. And so the patient, you can spend the entire visit with the patient. You don't have to spend it in the chart, you don't have to spend it gathering data, looking up things yourself. You spend the entire visit with the patient, and that is very rewarding. It's very rewarding.

Balancing Clinics With Building Software

Dr Andrew Greenland 12:48

Amazing. So, in this new phase of your career, what does a typical day look like for you now, balancing medicine with actually building the technology?

Dr James Ries 12:56

Yes, well, a lot of after hours coding. I'm a father of three little ones. I, you know, I'm my I have some clinic days, I have some administrative days, and so my clinic days are very much reserved for just that when I'm on base and I'm treating those patients. But um, you know, there is a lot of fill time, and uh and I have the AI coding pretty much always pulled up somewhere, and there's a list of tasks that need to be completed that day. And when the kiddos are asleep in bed and and I know that the you know the dog's been walked and everything is quiet, then I get on the computer and I start doing as much coding as I can that day. That's typically my work day, which has been, you know, if you build it right from the ground up, it's gonna be a really rough couple months. And then afterwards, if you've built it correctly, the main the maintenance on that is is not so robust, you know, and you can confidently say that care is being administered correctly. And so I'm uh I'm now at that finish line. It feels very good.

Dr Andrew Greenland 14:06

Congratulations, amazing.

Dr James Ries 14:08

Yes, yes, no more late night coding sessions. Now I'm um, you know, in the process of talking to clients about why this is good for both them but also their patients and why it's very inexpensive to use, you know, and that's a unique conversation I enjoy having with clients. Is this not something that is has to be um, you know, breaks the platform's, you know, piggy bank. It's in fact, most of the time they're saving quite a bit of money because they can resolve all those crazy administrative burdens they've been hacking on to telehealth over the past decade for no good reason.

Why Replacing Clinicians Is Risky

Dr Andrew Greenland 14:48

So a lot of the healthcare conversation in AI seems to start with what can AI do instead of the doctor? I know you kind of come at this from an opposite position. Why do you think replacing the provider is the wrong problem to solve? I know you don't hold that view, but clearly it's out there.

Dr James Ries 15:03

It's the only view I really see, unfortunately, and it's uh everyone is uh applauds it. So there's a few problems with that. I'm glad you bring it up, Andrew. So um, you know, AI is designed to be user-friendly, which in most cases is great. However, if you have an AI chatbot that is forward-facing to a patient, sometimes patients don't need the treatment they're seeking, or sometimes the treatment they're seeking is harmful. There is a provider layer that needs to be with the AI at some point that um makes sure that they're getting good standard of care, you know, even if it's not exactly what they wanted. We can educate as to why this might be a better treatment plan for them. The AI tool will um make the user happy, however, that is, and that's a dangerous thing to have, right? So, you know, you have somebody that, you know, a lot of telehealth does drug and alcohol abuse, you know, and if you have someone coming in that says, Well, I'm out of my pain medicine, it's reasonable for me, right? Chatbot? Yes, it is, absolutely. And you know, I've heard stories um about AI chatbots and users uh asking it other questions outside of that clinical console, that then it just kind of goes off the rails. So it's a dangerous tool, and unfortunately, it's not scalable, you know. So if you use an AI chat tool or an AI generating tool, it may get it right a dozen times, may get it right a hundred times, but a hundred thousand times it's gonna get it wrong, and that one time it gets wrong is is when somebody gets hurt. And so the two systems at play right now in the in the world are generative AI and deterministic AI. Generative AI is something where you just let the tool do what it needs to do and it can generate based on that. Deterministic is you have protocols in place that um uh medically say, don't ever recommend anything outside of this protocol, or this patient is being seen for this clinical visit, unless an emergency symptom comes up, please only go to this. So deterministic means it's not actually a lot of AI, it's actually a lot of clinical authoring in the background that you're um telling the AI to use. And so it's determining a treatment plan based on your uh clinical authorship. And that's a different tool altogether. You're not replacing the provider, you're actually making the provider smarter and more efficient and more, you know, yeah, uh, their time is more with the patient. And the providers aren't the ones um soaking up all the cost. So you really don't need to replace them, you need to make them better and less exhausted. That's what needs to really happen uh first. If we ever get to a day where the costs have been cut so much by using AI and you really want to replace the provider, I think that's an entirely different conversation at that time. But we're not anywhere close to it. We're not anywhere close to making that leap. Um, and so we really have to resist uh you know that urge to do that.

Where Costs Hide In Healthcare

Dr Andrew Greenland 18:40

So on that point, if provider cost isn't itself necessarily the fundamental problem, where are the real inefficiencies and costs coming from that people perhaps don't know about or don't think about?

Dr James Ries 18:49

Yeah, and this might change per country, but you know, advertising cost is huge. Um, medication cost is really big. Um, you know, and AI tools can help because they can um, you know, they can search and they can uh market these things by finding pharmacies that are a little bit more cost effective or you know, those kind of things. Um the overall system of patient communication is very poor. Uh, and because it's so poor, you have to uh hire, you know, staff to do these things just to just to notify a provider that a message was sent. Whether, you know, whether or not that's relevant or not, it doesn't matter, but you have to hire a whole staff of people. And uh AI can easily notify a provider that there's a message there, you know. So that's that's one example. Um, who needs follow-ups for what reason and at what time? Uh, you know, right now there's no real AI thought process. It's I'll I'll just hire a nurse and a medical assistant to staff that full time. Um, and you know, there's a lot of processes that don't involve having to call the patient. And those processes are great for AI because um you don't need to use a human voice for that because they're not contacting the patient. And that's such as reminders for follow-up appointments, or if a lab gets put into the system, what happens with it? You know, do we need to really hire someone to click through buttons to put that in the right place? Probably not. So um the list goes on and on for administrative things happening in the background that don't even need a human voice to talk to the to the patient.

The Human Context AI Misses

Dr Andrew Greenland 20:36

And what do you think um people misunderstand about where a clinician actually creates value? Because there seems to be this kind of thing where everybody's looking, well, you know, doctor clinician versus AI. Where are people missing the point here?

Dr James Ries 20:50

Yeah, I think people are missing the point of the, you know, the tone of the visit, the tone of the patient. Um, you know, patient history that might come up at a a later time. The overall relationship from human to human is is different, and it always will be because um there's certain limitations that you can only sense as a as a human, talking to another human, or even just typing to another human. A lot of context is is uh is is taken out of context, you know. I think everyone can I think everyone can uh empathize with a text message that you send to a friend that they take the wrong tone with, and now they think they're mad, you're mad at them when really it was a sarcastic joke, you know. So there's lots of things that require a human touch. Also, um, you if you're gonna use AI to replace the provider, you're going to remove the experience that the provider has by treating human patients for many, many years. Um when I When I say that, I mean what is the patient's life like? Where do they live? Are they in the middle of nowhere? Do they live with their parents? Do they live with somebody else? Are they going through a divorce? You know, these these are small little trinkets that um need a human context. And if an AI tool is is um is just focusing on one algorithm that they're programmed to do, you're gonna miss those contexts that might change the way you treat that patient.

A Patient Walkthrough From Intake

Dr Andrew Greenland 22:31

Thank you. So let's make this tangible. Um imagine I'm a patient entering your system for the first time. Talk us through what happens um from a patient perspective so we can get an understanding of how the platform kind of fits together.

Dr James Ries 22:44

Yeah, of course. Yeah, so if you come into 20 Mile, we'll um we'll use like an urgent care as an example. So if you come into the um 20 Mile Medical with an urgent care need, you will uh click a series of service lines that are relevant to your chief complaint or the reason you're going there. Anything from men's health to mental health to urgent care. And when you click the visit to open, it will then uh triage what type of urgent care that you need help with. And then the um after you submit from the drop-down menu, you'll be presented with an intake. Uh and the intake is very robust. First, it presents a safety screen should you be here at all as telehealth, and it's things like suicidal ideation. Am I short of breath? Am I having chest pain? Those things instantly and immediately get routed to an emergency room or a 911 visit, um, which is also great because people who are waiting to go to the emergency room for their symptoms don't they get triaged faster, right? So that's one benefit that telehealth does, and it has nothing to do with profits. It's people that need to get to the emergency room but you know basically don't want to go for various reasons. They'll use telehealth first, but it's good to get told immediately that that's a symptom that need that in fact does need to go, and they're they're more likely to seek emergency care if they get triage properly. So you go through a series of safety checks, um, and then if it seems appropriate at that point, they then start filling out the details of their symptoms. We use uh the intakes are um evidence-based. So the questions we're asking have real impact on as to what treatment type that they're gonna get, whether it's an antibiotic or whether it's conservative care or whether it's a um you know a three-day follow-up or something to that degree. So they're asking uh so they're answering a series of questions, and then they'll also put in the medical history, their medications, and and all their details. Once they hit submit on that, then the AI system will um compile that data. And while it's compiling the data, it's also looking for red flags. So it's looking for things that uh the provider needs to not miss. Uh, and again, that's evidence-based items. And of course, if it you know, based on the um clinical authorship, if it you know, it will present whether the patient uh you know should be offered this form of treatment versus another. It's a recommendation to the provider. Once that's done, then the um it reaches a an awaiting room for us, and we click on the visit when it when the AI is done with uh doing what it needs to do. And when we click the visit, there's option for um you know intake uh driven, which is asynchronous, which means if the intake is robust and the patient has filled out the appropriate um you know information and there's no real risks, then we can communicate with the patient at that point. We can reach out to them and say, this is what I've uh found out and this is what I'm recommending, this is why. Um the AI will also bring up evidence-based citations uh such as you know, based on this clinical guideline that we use here at 20 Mile, you would qualify for an antibiotic course because it puts you at lower risk. Um we can then submit the prescription directly to the pharmacy within minutes and they can go directly to the pharmacy. Other uh you know, treatments we offer men's health, women's health, we do directly ship their medication to their home. And so that's something that is nice. If they need labs for whatever reason, we can also order from there. If they need to see a video visit, so to get a proper screen, we can click the video visit and it sends them a link to open and we can see them live right there on the spot. So we have a lot of tools, and that's just kind of an overall summary on how we do like a basic type urgent care um uh visit. But it's very quick, it's very efficient, and um, because those things are taken um off the table, we can spend as much time as we want chatting with the patient, which is really nice. You know, we can go back and forth uh, you know, until we're both you know very uh happy and satisfied and uh on board with the treatment plan. We send those treatment plans before we send the medication so we can say, this is what I think. Well, you know, what do you think? Are you okay with this? Do you have a good follow-up plan? And then we can send the medication that way. Um, so it's a very nice system. My providers are very happy. Yeah.

Lower Cognitive Load And Better Care

Dr Andrew Greenland 27:53

Brilliant. Well, this um ties in very nicely to my next question because on our previous conversation, you were talking about mental or cognitive load for clinicians. And obviously, you've designed something which is very good at alleviating that. Can you speak a bit more to that and and how you've managed to enable clinicians to see more patients just by reducing the cognitive load of all of that administration?

Dr James Ries 28:15

Yeah, there's a couple, there's a couple strings to pull on that. And one, you know, the first one is providers in general, you know, we get some instant gratification from helping others. And the more times that you could trigger that, uh happier we become, you know. So at first, when you ask a provider to see 20 patients an hour, they immediately go, oh my gosh, I'm gonna be exhausted. But if you design a system where they're just getting the instant, you know, feedback and the instant gratification and none of the cumbersome steps, uh, they actually prefer that. They actually feel very productive and useful and they feel like they've treated a lot of people well. Um, it all started with trying to uh make other systems more efficient. And I found that when I did that by using some of these tools, the providers were asking me personally for more patients and more hours, you know, because typically if they have to write the entire soap note or find the information or look things up, a couple hours of telehealth is enough to really wear them out. Uh, and what I found when I implemented these tools is they would go four, five hours and not be exhausted because all the information was presented in front of them and they were able to just talk to the patient. And the exhausting part is not talking to the patient, it's getting all the information. Uh, and so that's how we've taken that burden. I didn't really anticipate the whole cognitive load until I saw it, until I saw it live. I just thought it was going to be uh safer and more uh efficient and better for the patient to have this stuff taken care of ahead of time. But what I didn't anticipate is that providers were not worn out, seeing you know, 20 or more an hour. They were actually very happy with it.

Dr Andrew Greenland 30:12

So brilliant. And there is a kind of a bit of a counterintuitive thing here. Because I think when we spoke before, you said that making that interaction more efficient could actually allow the patient to receive more care rather than less. Can you unpick that a little bit for us? Because it does feel a little bit counterintuitive if the patient's only getting three minutes with the clinician.

Dr James Ries 30:30

Yeah, yeah, exactly. Um, well, if we are so focused on gathering the information, looking up guidelines, or doing these things, uh, unfortunately, our mental load is going to miss a lot of other aspects. If you present all that information at the same time in front of the provider, then it allows them the breathing room to think outside the box. And so they get a little bit more creative, but in a good way. Things like added supplements or, you know, what is your living arrangement? You know, where are you um, you know, are you impoverished? Can you afford this? These questions come up because the rest of the care is taken care of quickly. Um, and so the patient gets a much higher level of care, more uh customized care. So by using the AI layering tool, you're really um stepping outside of the traditional, you know, uh the patient fits inside this box, and this is the medicine I'm gonna give them. If you remove that, then the provider thinks, well, what else can I do? How what other things can I do? Because I got to this conclusion very quickly. And so they tend to offer more things to the patient because they feel like, well, that was that was easy. That was an easy visit. What other things can I ask? And so the patient ends up getting much, much higher level of care, a lot, a more a lot more personal, you know. We'll ask them some extra questions that we honestly, just due to exhaustion, probably never would have asked them. You know, if we spent all that time looking all those things up, we think to ourselves, okay, I need to finish this visit now so I can get to the next patient. But if all that's done for you already, uh, gives you a little breathing room. And even in even in three to you know, three to five minutes, you can ask a lot of personal questions in those few minutes if you don't have to do anything else.

Monthly Follow Ups And Fewer Pile Ups

Dr Andrew Greenland 32:32

Brilliant. I think you also gave me the example of potentially moving from quarterly follow-ups to monthly follow-ups. What sort of impact could that increased frequency have, in your opinion?

Dr James Ries 32:43

Yes, that's a good, that's a really good question. We um, you know, at first we were doing three-month follow-ups because that seems to be the standard, but when you have a system that is very efficient, it allows you to perform those follow-ups a lot sooner. Um, between your care and between your three-month visit, patients have a lot of questions that tend to build up slowly. And then during their three-month visit, they tend to overload the physician with all of those questions that they've had. If you provide them a more regular tool, it it gives them the ability to have those answered on a more regular basis. Um, and the follow-ups are uh even more efficient. And so if you're doing this on a on a scale, it's quite easy to pull that follow-up in, and then the patient um perceives that as a much higher level of of care, but like actually caring for them, not just medical care. Um, and so when we pulled the 30-day follow-ups, we felt the physicians and the providers felt like they were having a lot less questions, when really they were probably just less questions all at once. You know, and and so the providers are happier because by doing a 30-day follow-up, they're only getting a few questions. But if they're doing three-month follow-ups, they're getting inundated with a lot. And so uh higher frequency of follow-ups is a higher frequency of visits, but less questions per visit. And providers typically are happy with that.

Telehealth Shifts Toward Lifestyle Care

Dr Andrew Greenland 34:20

Thank you. So, pulling back from your own platform for a moment, what major shifts are you seeing in healthcare and telehealth more widely at the moment?

Dr James Ries 34:30

I'm sorry, repeat that question. What makes me think telehealth should be used more widely?

Dr Andrew Greenland 34:33

No, no, I think saying um pulling back from your own platform, what are you seeing in terms of major shifts in healthcare and telehealth specifically right now? Elsewhere.

Dr James Ries 34:42

Yeah. Yeah. So I think you know, telehealth has had its run when it comes to urgent care. I think COVID solved that problem a lot. It made people realize that um they could administer care uh safely from a distance. Uh, I think people, you know, bought off on that idea. And now I think um it's more concierge type model. I think people are starting to think to themselves, well, if I could get seen for a cold, well, you know, what else can I get seen for? Do I really need to go to the provider in person for annual labs? Probably not, you know, and so people are expanding their minds a little bit as to what can be accomplished over a video or a phone visit. And they really should. I mean, really, they should be critical of what's necessary and what's not. You don't want unnecessary things. That's what drives healthcare costs up. Um, and so now I'm seeing people use it for annual wellness visits, I'm uh a lot of lifestyle things, right? So people who uh would normally not be comfortable talking to a provider in person about, you know, uh sexual dysfunction are now more opt to fix that. Uh, and they are happy to do so. Uh, and so we're getting a lot more into lifestyle, right? And so we're getting into weight loss, we're getting into, you know, even you know, the changing platform and environment when it comes to peptide treatment. So people are starting to uh connect the dots as to how else can I improve my life using this because it's a lot easier, which I encourage. I think if people are seeking out ways to improve their life and they feel like they're healthy enough to not have to go to a doctor um, you know, every three months, then we can offer them, you know, we can kind of uh dial in their health, you know, this is how we get stronger, this is how we lose weight, this is how and so I think it's more a lot more lifestyle and concierge, but that's just people taking ownership of their health.

Interoperability And Learning To Code

Dr Andrew Greenland 36:47

Thank you. Obviously, building what you built is an amazing achievement. I can't believe it's all been straightforward. What have been some of the challenges and bottlenecks along the road that made it kind of um tricky?

Dr James Ries 36:58

Okay, I guess coding software, my goodness. Um, getting systems to talk to one another is a real is a real chore. You just have to do it once. If you do it once the right way, then it'll work out. But you know, overall systems they're not designed to to talk to each other. Uh, and so getting that all on one, getting everyone, every system that you code on the same page is very very difficult. Um, also just learning the process of becoming a coder from, you know, that's something that was definitely unique, and I've learned a ton. Uh, I really enjoy doing it, which is also something I learned. I did it out of necessity and I ended up really enjoying it. And so it's uh it's something that I plan to continue doing because I get a lot of satisfaction from it. Um, seeing something, you know, seeing something that you create and then seeing it live on um a patient or a website or a portal or an intake is very rewarding to me because you you did all that little hard work late at night and now you can see it actually happen, like something actually happened from all those little letters I put in, you know. So um, I'm trying to think of other things. Really just learning the system. I will say it's a lot easier to do now, you know. With AI systems, I don't think even just a year or two ago I would be able to do what I did. I think uh systems now code for you and they help guide that. You give them what your overarching goal is, your medical experience, and what you want out of the product, and it will help you to code for that. And so um, I think a lot of more people should be doing this from a physician standpoint, because the the gap between software developer and physician uh is closing. And I think that the quicker that closes, the better it is for patients. Thank

Measuring Outcomes With Better Data

Dr James Ries 39:02

you.

Dr Andrew Greenland 39:02

And from a kind of founder-developer perspective, what are the metrics you're most interested in tracking with your platform?

Dr James Ries 39:10

Yeah, so a few metrics. The nice thing about the way that we go about it and using these AI tools in the background is you're uh you're privy to a lot of data that you otherwise wouldn't track because it's too cumbersome, like patient outcomes. Um, you know, even if it's as something as like this is the number of pounds lost, or um these this percent of people had side effects on my um on my platform. You can gather data on almost any input that you want. And that is a unique experience because normally that would be quite cumbersome to try and gather. And now it can be a few minutes of coding and you can have real live feedback on process improvement, whether your programs are actually working or not, and whether the patients are are coming back, you know, and so um that's really unique. I really am I'm gonna enjoy seeing that uh blossom over time, you know, have actually having the data we can use. I think that there's gonna be a lot of um research that needs to be done on peptides and weight loss that now we have access to as long as people are using these systems correctly.

A Future Of Low Cost Care

Dr Andrew Greenland 40:26

So, what about the future? What where do you want to be in sort of 12 months' time with 20 Mile Medical? What does the future hold?

Dr James Ries 40:32

Yes, so 20 Mile Medical, we want to be, you know, we want to be in the employer space, uh, which is a unique space. I feel like the the employers are kind of uh left to deal with whatever insurance, you know, contractors that they have to deal with. I feel like uh we could take care of a population of people very well by having this data and seeing the outcomes and seeing how each individual unique you know employer um can benefit their uh their small population of workers. So I think that that's interesting um dynamic. We're just getting into that space a little bit. Um but the overarching goal and why I did all this was to eventually, and this sounds kind of crazy, but what I'm realizing is that the AI tools and an efficient platform and an efficient way to reach the patient, if you can do this correctly, the cost of actually reaching care to people becomes so minimal that I think that it can almost be free. And if I can scale Talora and 20 mile, I would like to actually start a purely free health care for telehealth that is um donation-based. Yeah, I think I can I think I can get the cost down enough, but it would be almost like a nonprofit for you know homeless or uninsured.

Closing Reflections On AI And Capacity

Dr Andrew Greenland 42:11

Wow, what an amazing um aim to be able to have. That's fantastic. With that, James, I'd love to thank you for joining me this afternoon. It's been such an interesting conversation. But I think it really reframes what we mean to when we talk about AI making healthcare more efficient, because efficiency doesn't necessarily have to mean less care, less time, or removing the clinician. If the technology can take away the grind, the documentation, the administrative workload, and the cognitive burden surrounding the consultation, perhaps the result is actually a provider who can provide more care, have more capacity to do so in the first place. So I'm very grateful for the conversation and thank you again for joining us.

Dr James Ries 42:48

Yeah, thank you, Andrew. It was fun.