The Tech Glow Up - Fabulous conversations with innovative minds.

From Building ChatGPT for Doctors to Solving the $87B Wasted Health Tech Problem - OpenEvidence & Ardexia

• Nathan C Bowser • Season 2 • Episode 2

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Thanks for tuning in to these conversations with two founders changing the future of healthcare live from HLTH 2025.

Zachary Ziegler, co-founder of OpenEvidence, built a platform that reached 40% of practicing clinicians in just two years by centering a simple principle: every answer includes citations to peer-reviewed research. With access to 40 million papers updated daily with 10,000-20,000 new studies, doctors can verify every claim instantly. Growing 30-40% month-over-month and adding 60,000-70,000 clinicians monthly, Ziegler challenges conventional wisdom—EHRs are already a top burnout driver, forced integration isn't the answer, and physicians prefer autonomy over mandates.

Dr. Aditi Joshi, founder of Ardexia, tackles a different crisis: healthcare organizations waste $87 billion annually on contracted technology doctors never use. A former emergency medicine physician who experienced burnout twice, she moved into telemedicine and discovered the core insight—most builders don't understand how physicians actually work. You can't mandate adoption. You can only solve real problems. She's building Ardexia with validation first, burnout prevention as a foundational business strategy, and clinician expertise leading product decisions from day one.

Highlights from Zachary Ziegler at OpenEvidence:

  • Started with a Harvard PhD studying language models before ChatGPT; built "ChatGPT for doctors" with complete citation trails to peer-reviewed research
  • Reached 40% of practicing clinicians with daily active usage; adding 60,000-70,000 new clinician users monthly (30-40% month-over-month growth)
  • Philosophy: "Trust, but verify"—every answer sources from original papers so doctors can verify claims against peer-reviewed research

Highlights from Dr. Aditi Joshi at Ardexia:

  • Former emergency medicine physician who discovered during telemedicine work that technology adoption is a people problem, not just a technical problem
  • Identified the $87 billion annual cost of unused healthcare technology—five-year contracts continuing whether clinicians ever use the tools
  • Building Ardexia with burnout prevention as a foundational business strategy; validation-first approach to understanding specific pain points before scaling

The result: healthcare's AI transformation doesn't happen in the lab—it happens when builders center the people actually using the tools.

A "glow up" signifies a positive transformation, reflecting the journey of becoming a better, more successful version of oneself.

At The Tech Glow Up, we humanize the startup and innovation landscape by focusing on the essential aspects of the entrepreneurial journey. Groundbreaking ideas are often ahead of their time, making resilience and perseverance vital for founders and product leaders.

In our podcast, we engage with innovators to discuss their transformative ideas, the challenges they face, and how they create value for future success.

If you're a founder or product leader seeking your own glow up, or a seasoned entrepreneur with stories to share, we invite you to join our guest list via this link.

Zachary Ziegler:

everything that we say as part of answers is always referenced. So there's citations to everything. And so you don't actually have to trust AI at all to get value. Use Open Evidence because you can always verify, everything. And so our motto, here, is trust, but verify. And that's really central to Open Evidence.

Nathan C:

So, you ready? 1, 2, 3. Hello and welcome to the HLTH Tech Glow Up. I'm Nathan C and today I'm talking with Zachary Ziegler, co-founder of Open Evidence. Zach, it's so great to meet you. Thanks for joining me on the HLTH Tech Glow Up. Hello. Amazing. So, to get started, can you introduce yourself and the work that you're doing at Open Evidence?

Zachary Ziegler:

Yeah. So I'm Zach. I'm the co-founder and CTO of Open Evidence, we essentially make, Chat GPT for doctors. We become the fastest growing, most rapidly adopted, AI tool used by clinicians. we're now used by over, 40% of practicing clinicians with the average user using us, every day. Okay. my background is technical. I'm, I'm an AI person. Mm-hmm. I come from a PhD program at Harvard, where I was working in the pre-chat GPT days on, language models and generative modeling and all that stuff. and yeah, I got really interested in how do we make these models do something actually useful? How do we make these models like actually impact the world in a meaningful way? and yeah, ended up, you know, here we are.

Nathan C:

Were you always interested in healthcare as an application for large language models, or did that focus come out of the research that you did in building, the idea?

Zachary Ziegler:

Yeah, so ultimately what motivates me is just making useful stuff. That's always been just the thing to just really make things that people love and people use. And what struck me early on, myself and my co-founder Daniel, was that, healthcare sits in this space that is, In so much red tape and bureaucracy. when we were getting started with this, it was one of these last very obviously yellow taxi cab era style, industries, Where even as consumers, it was wild to us that if you want to know what is the science actually the breast resource is, WebMD. Mm-hmm. Which is crazy because it is literally a meme. right. That you go to MD and you ask, but you have, and it'll tell you you have cancer. Yeah. and, and the, what the, the shame is, is that there's so much that we know as a species. I don't think people appreciate how much medical knowledge exists and how much research exists. there's 40 million papers. There's. 10 to 20,000 new or updated papers every single day. It's an enormous amount of literature.

Nathan C:

almost like a YouTube. I mean, that's a similar content. Sure. Fee. Yeah, that's right.

Zachary Ziegler:

huge amount of, context area, and yet there's no real ability to access that knowledge. And so we made Open Evidence to be kind of a bridge between people who have needs, whether that's, originally kind of when we were. Considering this, for WebMD kind of consumer stuff, but very quickly, you know, really, focused on the physician side. and providers, to bridge the gap between providers who need access to the, best, information and the best care. And that information that really does exist in the home. That's amazing.

Nathan C:

Could you, for the sake of those who maybe aren't in the health tech space, talk about your data sources and, how you collect the research and, what is it like for a doctor to use, Open Evidence?

Zachary Ziegler:

Yeah. So, we pull data from a bunch of different sources and we do it in a bunch of different ways. Probably the most important data that we work with is our first party content partnerships. we have, partnerships with, the New England Journal Medicine jama, and a whole bunch of, societies as well. these are the absolute top of the top, the biggest gold standard for, clinical information. This is where the. Best phase three clinical trials are published, and really the most kind of world changing, aspects of, of medical knowledge exists. So it's really important that we have, those deep partnerships. we're able to kind of show and use figures, especially in multimedia from those which are really cool. and we're working on kind of further collaboration with those as well.

Nathan C:

That's like dimensions that audio or like other modes. Might miss out on Yeah. like, speaker's, slides and some recorded CTA thing or something. amazing. So, my kids are like ultimate AI skeptics. Yeah. And, I've even heard at the show, right, people talking about, hallucinations are real. I'm sure you've addressed it, but I'm hoping you can talk to, like what are the risk factors for being an AI layer for like medical research and information, especially like when you're working with doctors and advising or, you know, kind of. Affecting how they're making decisions about care.

Zachary Ziegler:

so the way that we approach this problem is we focus on search essentially. Is the answer, right? There's traditional approaches, chat BT might imagine, right? Which is like big black box, throw some questions and just like hope that you get good answers. We take a very different approach, which is essentially the bottom up to that top down. So we, we really, at the end of the day, we do search. That's what we do. And so what that means is when users have questions or clinical cases, we will find the exact right sentence, paragraph, we see our job as really being searched, just surfacing those pieces, to humans. And then largely what we use, kind of what people today think about AI for it is, making really great search and then also providing a layer of fluency and conversation on that just for a kind of convenient experience. And so what that means is that everything is from the bottom up. Everything is about, You know, true what humans have said, what humans have written, what humans have published and gone through peer review. And then also the side effect of that, which is just as important, is that everything that we say as part of answers is always referenced. So there's citations to everything. And so you don't actually have to trust AI at all to get value. Use Open Evidence because you can always verify, everything. And so our motto, here, is trust, but verify. And that's really central to Open Evidence.

Nathan C:

Do on the platform side, you potentially have, this is like just riffing. ability to understand how frequently doctors are actually clicking in to those references. Is that something you're able to talk to at all?

Zachary Ziegler:

don't know the exact number, but it's, it. It is really quite frequent. it's, you know, it's, it's really important, right? if you're a doctor seeing a patient, you are responsible for making the decision. There's nobody else. And so Open Evidence is a place that people go because it's just, one layer of support. That's a really common kind of use case. but at the end of the day, the stakes are high. There's someone there in someone's life, right? In principle, in the worst case. And so, having that ability to look through and double check and go to the references and see, exactly what the, original source material said. I can't imagine practicing using any kind of AI tools without that foundational support.

Nathan C:

The, I would say that like one of the themes I've been seeing at health, like overall Yeah. Has been like ai, but there's still a human. Totally. And in many cases that's part of like the rebuttal page for an AI product. Yeah. Right. Like, but there's a human in line or we have this person, or there's a trans. Later. And what, what I kind of find really elegant about what you're describing is that the human involved is the customer, is the doctor doing the search? And so it's built in to the work flow that the human is always gonna be at the front. Yeah, because you're not necessarily like asking for a diagnosis, you're not asking, right. Like you're asking for the research. You're asking to get right to the specific thing that I really want to address. First and then that ability to have a conversational. interface to the research, for somebody who can make a decision.

Zachary Ziegler:

Yeah.

Nathan C:

And, I'm sure people much, I'm not even gonna get into the, like, models can hallucinate even if they're day like. there's something, but I love that there's a safety layer and just like an elegant, a simplicity of the technology That align very well, in this model. So it's,

Zachary Ziegler:

very cool. There are, questions, whatever concerns when AI is framed in a way that is kind of about replacing humans, right? Mm-hmm. And that's when you start getting into like, okay, we're gonna start with some human in the loop thing. Mm-hmm. And eventually we're gonna remove that and replace that human with position. That's really not at all how we think about this, right? We really think about this AI as just a tool that is. Supportive of physicians. we don't think about it in terms of replacing. we also don't even think about it truly in terms of even saving time. There's, another common thing is like, AI is gonna save time for physicians. And the reality is that's, then what happens is immediately, health systems just start compressing schedules and giving more and more, patients to each physician. So what we think about at the end of the day, or maybe they play wordle well, there's no guarantee that it's. Go into efficiency or, physician lines are hard enough. Yeah. You don't, these, for-profit hospital, these are efficiency machines. They're just going to, any amount of save time really just increases, the amount of patients people have to see. So, what we care about and what we focus on truly with Open Evidence. Is, how do we make doctor lives easier? How do we make it just not faster, but just truly easier to do their job?

Nathan C:

There's a little bit that you hinted at about like leveraging information to combat some of the challenges of the weird. Investment structure in healthcare, that I'm not even gonna touch, but is like super cool, like some very interesting ideas. so thank you for that, Zachary. This is like, such a cool technology and to have 40% of practitioners in a daily, actually, how long did it take you to get to daily use, like.

Zachary Ziegler:

Yeah, well we, so we started about two years ago. Mm-hmm. Releasing Open Evidence. But it's really just in the last year that we have absolutely exploded and taken off. We've been growing about 30 to 40% month over month. so, you know, in our early days that was, small numbers. But the nature of exponential growth is all of a sudden that gets very big, very fast. we're adding 60 to 70,000 clinicians, per month at this point. and it's fantastic. we, you know, we're thrilled to be making a difference and to be making, really fantastic tools.

Nathan C:

60 to 70,000 a month gets. To millions really fast. Yes. That's cool. amazing. so let's, let's go a little bit bigger. let's look at the industry. Look at why we're here. the podcast we're on right now is the HLTH Tech Glow Up. A Glow Up is a notable rebirth, a transformation looking at the healthcare industry, like you're already solving some of these core problems and like working on some of these hot issues. I'm. Curious what's, what's the perspective, what's the goals that you have, for healthcare, for practitioners? what's the big audacious goals, that you have for healthcare and health tech, in the next six months to a year?

Zachary Ziegler:

Yeah. Well, I think it's this really interesting moment where it feels like kind of all the dust has been kicked up and there's questions around like, how to describe, play into things, right? How do, clinical copilots play into things? Does integration matter? Does integration not matter? Right. And so I think, you know what I'm, what I'm really intrigued by is like where, you know, how does this all land? Kind of like what is, what, as this kind of normalizes into, into physician flows, like, you know, healthcare is an enormously varied, so. Base, right? It's not just one thing. Practice looks like enormously different, in many different situations. And so I think there's, it's a really exciting moment where it's never been easier to build AI tools, right, or to build, any tools at all with just how fast it is, increasingly to build products. and so I think it's a really interesting opportunity to, run as fast as we can at building the most useful tools for physicians, to make stuff that really find the places that can help every physician. I'm especially really interested, for our part in, you know, how far can we push these models? How far can we push medical reasoning? How far can we push, medical intelligence? Can, you know, is there anything like that really starts to approach medical super intelligence that we can, that we can build with a con with. The, with the, you know, foundation of the literature and guidelines and practice information. but as we especially level up reasoning and, and, and those sorts of capabilities. So that's what I'm really excited about. those are, we're working on some of that stuff and we'll see, see, can, is

Nathan C:

there, not to pin you down to any of these specific goals, but for medical super intelligence, what would be the first problem you would go solve?

Zachary Ziegler:

Well, the reality is I think it's a big spectrum, right? There's Open Evidence like is super intelligent from a like. in specific instances, right? The ability to, have 40 million papers condensed into one tool that you can kind of query from and get access to is something that,

Nathan C:

an executive summary is pretty good.

Zachary Ziegler:

can't do that, right? So there is, there is something that a lot special about that. But there are also plenty of aspects that I don't think we're gonna recreate for a very long time, right? I think human intuition, physician intuition, and experience is so important and so critical. I think we'll figure out how to mesh, continue to mesh those pieces.

Nathan C:

Yeah. that's gonna be my new ai. Amazing. you kind of actually answered, a little bit about the Glow Up for Open Evidence. You teased this question that like I have to come back to, are integrations important or are they not? do you have an opinion on that?

Zachary Ziegler:

I think they're okay. I don't think they're existential, I don't think they're critical. You know what, when I talk to clinicians, what I hear is the core value, the core thing that is really important is being able to just get fast answers, fast, trustworthy answers to questions, right? The idea that you can pull out your phone when you're standing outside the patient room, ask a really challenging but important question and get an answer right away, that is easy. It's that ease of use. I think that's the thing that we always push for ease of use and low barriers. I often cite ease of integrations as the fastest path Yeah. To ease of use. Yeah. And like meeting customers where they are. Yeah. but if you're in a world where you can build AI tools quickly and a doctor actually doesn't mind pulling out their phone to like get the answer that they need in the moment, and maybe that's their preference. change it if it's not, if it's not broken in healthcare especially, right? Like physicians are essentially just like. they are force fed EHRs, and it's like, you know, one of the most like interesting, well cited facts that I keep coming back to, and it's just like I, it keeps bo bopping around in my head is that like EHRs themselves are cited as like one of the top three causes of burnout by physicians, right? I mean, one. Crazy profession to live in where the technology that your administration is often forcing on you is the very thing that is like, I have to click all these buttons. It's a huge pain in the ass. Why do I have to do this? and so for physicians specifically, I don't think they all. Love their existing EHRs, and I'm not sure they're like, boy, what I really want is more, eh, HR. You know what I mean? Yeah.

Nathan C:

EHRs are the TPS reports. Health tech is what I've just learned there. Zach, you're pushing on some of the conventional wisdom that I like to talk about in a couple different areas. Yeah. I'm trying not to be upset about it. Let's jump to the next thematic question as a diversion. The theme for the show this year is Heroes and Legends, and I'm using it as an opportunity to ask people about the mentors, heroes and others, both in healthcare and in innovation. Sometimes just having one person believe in you and say, keep going, can, like, have transformational effects. And so I'm using this opportunity to try to get to those stories. Are there people who, or organiza, you know, heroes, legends in any way that have inspired you on your journey as an innovator?

Zachary Ziegler:

well not, not, maybe not quite mentor specifically because I never met this person. but in terms of, A guiding figure. Yeah. I think a lot about, Steve Jobs. Yeah. and specifically in the healthcare sense. Oh. Because, do you know what the technology that was the fastest adoption technology before Open Evidence was among physicians?

Nathan C:

based on the context, my guess is gonna be the Apple Watch iPhone. Okay.

Zachary Ziegler:

that was, you know, like we're in now with this AI movement where there's, so much, happening so quickly. Right. In so much, like I said, up in the air and changing. That was a previous period where, there was this. introduction of new technology. I was just talking earlier with some positions that were talking, when they got their first iPhone. First it was an iPod Touch and then an iPhone, and what a change that was to, level up from textbooks to all of a sudden, still set of content, but just have that right there in your pocket. and so, you know, that's a. Cool. kind of like precursor in a lot of ways that mirrors a lot of this, but, you know, and then just as an individual, right? Like Steve Jobs is absolutely incredible and I think he has some of the best, kind of philosophies for building a company, for innovating. And, and, yeah, he, he's absolutely. Inspirational figure for, for how to build things for real and make things in practice.

Nathan C:

I love that there's like a, I love Steve Jobs as a hero there because there's this like uncompromising quality and focus on design. Yeah. So, last question, and it's totally optional. What year was that adoption? I dunno. Dr. Lee. We are like, one minute I have

Dr. Lee Glasser:

to go on the

Nathan C:

call.

Dr. Lee Glasser:

I'm er, I was friends with Danny. Okay. Yeah. And I'd love to talk you, it's a former Chief Medical CMS and I know a lot of work. Amazing. And reasoning and writing. Yeah. Yeah. How to educate the next generation of yeah. Talked to George Daley about, I dunno if you know George? No. Harvard Medical School. Oh, okay. Yeah. So your team has my number. Okay,

Zachary Ziegler:

Yeah.

Dr. Lee Glasser:

Okay.

Zachary Ziegler:

Awesome.

Dr. Lee Glasser:

heard you spent some time with Danny.

Zachary Ziegler:

yeah, my co-founder for Luxury. He became your friend. He was special person. Yeah.

Nathan C:

Smartest

Zachary Ziegler:

man I've ever met. Hey you.

Nathan C:

Hell yeah. Harvard Connections live on the Glow Up last question, Zach, and it's totally optional. Do you have a spicy healthcare hot take?

Zachary Ziegler:

I don't know actually if this is a hot take. But I think that AI is only going to extremely, positively impact all of our lives. there's so much, concern and fear, right? And anxiety around ai. Is it taking people's jobs? is it leading to ai slop, If you go on the internet, it's almost exclusively negative, right? Open Evidence shows that there are ways for it to literally save lives, right? for it to impact the world at a very large scale in a way that's extremely positive. It's very easy to be negative on stuff and it's very easy to point out problems. I think we'll look back a year, two years, three years, and certainly much farther than that and see this as a really important step function for the whole world. I see that in the clinician space for Open Evidence. I see that as an engineer in coding tools. and I think as this percolates farther through to society and people start. Seeing the reality every day as part of their jobs. It's going to be very clear just how positively beneficial AI can be for the whole world.

Nathan C:

I'll take it. some of that sentiment reminds me of some things that, Alvin Wang Graylin, talks about. I don't know if you're familiar with Alvin, he's a, former leader at HTC, but very much, interested in AI in this direction. Zach. It's been fantastic, to chat with you. Thank you so much for sharing some of your very busy day. Yeah. here at HLTH and, you know, just fantastic work. I think, that optimism of how powerful AI can be has gotta be partly a product of. How incredibly successful you've been able to be in the last four years, building with it. Right. And while many of us are still trying to find our paths, you're here trailblazing, with outcomes and like centering doctors in a way that a lot of folks seem to have a hard time doing. So Bravo. Well thank you and thanks for joining us on the Health Tech Glow Up. Thanks for having me. Amazing. We got one last thing. We're just gonna clap it out. Okay. 1, 2, 3. Amazing. So one, two. Awesome. Hello and welcome to the Health Tech Glow Up. I'm Nathan C, and today I am talking with Aditi Joshi of Ardexia. Aditi it is so good to see you. Thanks for joining me on the Health Tech Glow Up.

Aditi Joshi:

Thank you. Thanks for having me. And hello everybody.

Nathan C:

Amazing. Can you introduce yourself and the work that you do at Ardexia?

Aditi Joshi:

Yes. Thank you for calling me an icon. I'm gonna live off that now, but

Nathan C:

yeah,

Aditi Joshi:

so this is a new company for me, and we've known each other for a few years, we know what we want to do for healthcare, but it's just not happening. So looking back at like what everything I've built and I realized that it's. We've got great technology. People really want to help healthcare. We have leadership and laws and everybody's involved, but we still haven't been able to really get doctors who want to use it successfully. There are health systems, there are government programs, there are clinics. People are sitting on technology that isn't being used. And so I thought to myself over these last 12 years. What has worked, what have I seen actually work to get doctors to actually want to use it. And that's what we're doing and we're fixing.

Nathan C:

Are you able to share what it is you've seen that doctors actually want to and do use?

Aditi Joshi:

Yes, I will say that. the biggest problem is that people don't really understand how doctors work. The biggest take is that we don't really have bosses. We have people who have oversight, but once you're at the standard of care, we don't really have bosses. We are able to see our patients and decide what we wanna do. We have to do the right thing for them, but that's it. So you can't actually go into a health system. You can't be like, Hey everybody, you've gotta use this tool. If there's a tool that already works and is great for patient care, you cannot force us to do it. It's just not happening. You have to look at what are the actual pain points? What do we want better for patient care? What is the actual behavior and psychology of the doctors at that practice that's stopping them from using it? What are the real pain points? Who's the leadership? You gotta think about all of those things.

Nathan C:

My suspicion is like, just for the sake of example, right? Like a podiatrist and a oncology doctor are gonna have incredibly different drivers, even though they might sort of have some of the same credentials or you could put the same labels on them.

Aditi Joshi:

Yes.

Nathan C:

so what's your approach for helping technologies better understand and activate doctors?

Aditi Joshi:

So I put it out, I looked at my playbooks and it just basically. Put it out there, and I figured, all right, these are the steps that you need to take. So the first thing we have to do is actually validate it. And I'll tell you, Nathan, I know it works. I have done it multiple times, but I need to make sure that it works in this context. And then once I do it, I'm gonna build an app around it. So looking for any tech co-founders, if you know anybody who might be interested.

Nathan C:

interesting. Have, this is totally like, curiosity around innovators and the choices they make in, excited circles. There's a lot of people that say you don't need a technical co-founder anymore because you can prototype and. Create a number of like proof of value apps with AI code assistance. what's your thoughts as a founder?

Aditi Joshi:

I'll say that AI has come really far and it's actually really exciting what you can do with it. But I will fully admit this. I have taken on a very ambitious, complicated problem, and so I did actually try creating an. App using the playbook that I did. it does part of it, but it does not get everything that I want. And so I know that I'm gonna need somebody who has a little bit more experience to make exactly what I'm looking for to do.

Nathan C:

Yeah. along with that intuition and that experience. Right. Like back to the, the top, like, I've done it before. I've seen what works. I'm, I'm curious, you're kind of multihyphenate. You've got these many strengths. what was that, origin story, that moment that inspired you to kind of take this innovation path when you have so many tools at your disposal?

Aditi Joshi:

Oh, yes. So I'll say that in general. Emergency medicine, we tend to be innovative because we have to think on our feed. We have to really make sure that. We're going in the right direction, and if it's not, we gotta change paths. But really my story was I got burnout and I really could not work in the emergency room at the level that I was doing or the amount of time that I was spending there. And so I was looking for other things and I applied for a telemedicine company and I just really loved what they were trying to do. And I will tell everybody this, You cannot just try to escape your burnout by going into a field like this unless you actually love it. I actually loved it. I found it useful. I understand how we improve access to care. I saw patients, I have multiple stories where I helped them and really understood what it's like for patients at home, which I don't see in the hospital setting. And it really gave me an understanding of what technology can really do to help people in their homes.

Nathan C:

So let's look at the conference and the setting that we're in, sort of dive in, to HTLH itself. I use the idea of a glow up or a noticeable transformation or a rebirth. As a way to talk about goals. Mm-hmm. and how we grow into the future. Thinking at the industry level, and maybe it's for doctors, maybe it's a little bit larger. what's the glow up that you're wanting to see in the healthcare and health technology space?

Aditi Joshi:

So, yeah, in the health technology space, I am seeing this glow up and I want more of this.

Nathan C:

I like this.

Aditi Joshi:

There's a lot more clinicians here and they have a real voice, and there's a lot of clinician builders, founders here. Not just, you know, on the exec team, not just advisors. There's actual builders and founders. That's really important because for so long we were told we're not good at business, we're not good at speaking on these topics, and I think we're getting past that where we don't actually have to have those. Skills we can find co-founders, we can find those skills just like everybody else does, right? I love that. I'm seeing that trend.

Nathan C:

So for those who might be watching the tech glow up who aren't familiar with healthcare technology, I think it might be shocking. Honestly. Oh, sure. That doctors, yeah. Haven't always been involved in some of the tech innovation. A lot Of the tech innovation that has happened to date. Yes. And that a lot of solutions kind of solved technical, physical, clinical kinds of problems, but weren't necessarily even including, to your point at the top Yes. That people are supposed to be using the tools Right. And saving them time.

Aditi Joshi:

Yeah. I was shocked too when I found this out, but it was like, it's been a long time that this has been going on.

Nathan C:

I've also heard, the voice of doctors, the voice of nurses. The voice of patients. I can see the lounge From here. that is one of the things that this event fair, is very good at centering, like literally giving prime center booth space. So boosting it everywhere. Props to HTLH.

Aditi Joshi:

Yes.

Nathan C:

Alright, so let's bring it in. Mm-hmm. entrepreneur, newly started company. Six months can be a lot of time, can also be a very little amount of time at this stage. What's the glow up that you're looking for? to make it our next year in the next six months. So first things first. Yeah. I've had burnout twice this time. I'm not, I'm gonna build. So that's the first thing I'm doing. yes, exactly. You gotta plan for it.

Aditi Joshi:

yes, you have to plan for it. I'm saying this right now, and so when we talk about six months, I'm not gonna say, all right, I'm gonna have this all done by six months. What I'm gonna say is, in that time, I wanna know how those problems are really affecting doctors. All of my research in there, and starting that validation. If it's done, that'd be amazing, but at least getting into that validation portion. And hopefully I'll have that tech co-founder and least some ideas on the tech co-founders out there who might be interested in this problem.

Nathan C:

Hell yeah. I'm always gonna be excited when somebody's like, I'm gonna be doing more research. I'm hoping to be at this. I knew that I couldn't start a business that was going to burn me out and support my family in the way that I wanted to for the business, and so can't burn out. Can't burn out, have to have balance. Have to be mentally healthy as part of the business plan. Like it's in the foundational values for how Awesome Future is supposed to run. Yes. Because how else am I gonna protect it as a CEO and as the only employee right now. Yes.

Aditi Joshi:

Yeah.

Nathan C:

so true.

Aditi Joshi:

I love that you did that and you put in the business plan because if you burn out, you can't actually build anything. You're not grounded. You have no energy to do it. And I know myself, I'll just be too hard on myself and really want to do something.

Nathan C:

Yeah. But your brain cannot think strategically and creatively if you're in fight or flight.

Aditi Joshi:

That's true,

Nathan C:

When you're in the wrong part of the brain, it's true. Like you're physically not capable. You can't hustle your way through that. It's like a physical meat barrier, and I love it. so Aditi, the theme for health this year is Heroes and Legends. I think this is a fantastic opportunity to ask CEOs, leaders, product founders, innovators, who are those mentors and heroes that encouraged you along the way, Like sometimes it can take just one person believing in you, in your idea. In your potential. So who helped you get to the point where you are?

Aditi Joshi:

And I love this question and there's been so many people, but I will say that, what probably some of the ones I can really think of that really. Help me. Were the ones that recognized that telemedicine is important. They may not have been in telemedicine, but colleagues who were like, we want you to be the voice and we want to make sure that you actually grow this out. And I've had multiple ones. My boss at Jefferson, my colleague at Jefferson, who also made sure I had, more, opportunities to write papers and do research. I mean, all of that. Really made me realize that I can do this. But I gotta say, you know, and this is such a cliche answer, but I remember even when I wrote my book, like I remember thinking all of the patients that I saw, because I will tell you I have like memories of certain patients and I just was like, oh my God, I remember how it helped you and I remember what this did for you, both from the emergency department and on telemedicine visits and really all of that. It's really why I do it, because otherwise, I mean, this is a hard problem.

Nathan C:

those stories of the people that you were able to help and learn from, stick with you no matter what. Yes. and how cool that it's like the people that you were able to help and engage on their health journeys now coming back as like advisors and encouragement. I love that so much.

Aditi Joshi:

Thank you. I love that.

Nathan C:

Yeah. So on a total tone shift, do you have any spicy ideas you're willing to share with us?

Aditi Joshi:

Absolutely, and I don't know if you know, it's a spicy, but I'm gonna say that I. I'm seeing AI everywhere and it's like, honestly, it's lost. Its meaning. There's no differentiation. And so for me, when I'm walking around, I'm like, okay, well you're using AI now I need to know what you're doing with it, what kind of AI you're using.'cause like I'm gonna tell you, I've been talking to people and I've been trialing things out. And if your base or back end AI or LLM doesn't have certain features, it is missing out on some of the ambient ai. It is taking things out of context, it's giving wrong answers. So just what kind of AI are you using and then how are you using it? Because I don't wanna hear about AI anymore, I wanna know what it's actually doing. Everybody has ai, so tell me something different.

Nathan C:

Tell us about your outcomes.

Aditi Joshi:

Yes, yes,

Nathan C:

please. I love that. That's amazing. Aditi, Nathan, we've got the mic. We've got the opportunity to share anything you'd like about Ardexia, what you're looking for in the next few months.

Aditi Joshi:

I would love to know if anybody is really looking on how to improve this. I wanna talk to you. Not even necessarily for the validation or even as a client, but I wanna hear your stories. I wanna know what's going on.'cause really this is the problem I want to solve. I wanna make, I wanna make these tools usable by clinicians and that hospitals will actually adopt them and continue to do it.'cause if we don't use'em, they're just gonna go away. They're just gonna sit there unused on a shelf and patients are not gonna get the care that we can deliver through technology.

Nathan C:

Do you have metrics on. The cost or the lost value of like digital transformation that's unused. Billions in healthcare.

Aditi Joshi:

Billions.

Nathan C:

It's probably trillions.

Aditi Joshi:

It's 87 billion.

Nathan C:

It's at least, okay.

Aditi Joshi:

per year, they've contracted, so you're looking at not only the investment, but how much they're losing in a hospital by not using and seeing patients and getting reimbursed for that. Care.

Nathan C:

A five year contract is a five year contract. Even if the nurses don't touch it in the EHR.

Aditi Joshi:

That's right. Ooh. Right. I'm gonna actually,

Nathan C:

a five year contract is a five year contract. Even if the doctors don't touch it in the ehr.

Aditi Joshi:

that's true. And everyone, I'm not gonna throw nurses under the bus, doctors and nurses. it's not even us doing it. If we, doctors will turn these tools off if it's not useful. and you have to actually talk to them. And figure out why it's not useful and then fix it. Most doctors don't have time. They're not gonna sit here and just like try to fix it for you. They're just gonna stop using it. That's actually what happens.

Nathan C:

Literally turn it off. This is wasting too much of my time to learn.

Aditi Joshi:

Exactly.

Nathan C:

Oh, I'm so glad I asked that follow up. Thank you, Aditi. It has been such a fantastic pleasure to check in and to see everything that you're doing at Ardexia. The research foundation, that desire to drive outcomes and actually make a difference and help your peers also make more of a difference, right? With the tools that we've already bought, is such an incredible mission. I hope we can have a follow up in a year so we can hear more. Yes. About everything you've been building.

Aditi Joshi:

I would always love to follow up with you, so let's do it. Thank you for having me, Nathan.

Nathan C:

Yes. And now we gotta clap it out. Okay. 1, 2, 3.

Aditi Joshi:

Thank you. Thank you. Have fun.