113 – How AI is Transforming Medical Coding & Healthcare Operations w/ Talha Haseen

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[00:00:17] Vic: Okay. Welcome to Health Further. Today, we have a really good guest, Talha Haseen. He is at Fathom, a new AI company. Well, not new company, but a company new to our audience, maybe. Talha, thanks for doing this. I really appreciate it. 

[00:00:30] Talha Haseen: Yeah, absolutely. Thanks for, thanks for having me. 

[00:00:33] Vic: So before we dive into Fathom, uh, let's talk about your background.

[00:00:38] Vic: Cause you have a pretty interesting background, a couple of turns at McKinsey with some providers mixed in, maybe tell us about yourself so the audience can get some frame of reference. 

[00:00:47] Talha Haseen: Yeah, absolutely. So one, I think it's, uh, I'm proud to say I'm Nashville native. Pretty much went to high school here, grew up here, went to college here and worked here for a while.

[00:00:57] Talha Haseen: Uh, it's always, I feel like it's getting even more rare [00:01:00] now. Uh, but I actually started out as an engineer. I studied chemical engineering and, and, uh, worked as a chemical engineer, doing everything except healthcare for maybe like, Two years. So like Greek yogurt production, automotive sector, grocery chains, store chains, and like South America, very random things.

[00:01:20] Talha Haseen: And, uh, I kind of started down this path of healthcare through, uh, VUMC Vanderbilt here in Nashville, uh, by working with like a new department there, they were starting effectively. They were looking for like. You know, someone who is, wasn't scared of math, wanted to learn a little bit about health care and kind of work hard type of thing, uh, which led to working at the mental center for a while doing population health related things and helping with a couple of Medicare ACOs and risk stratification for patients.

[00:01:51] Talha Haseen: Uh, and I kind of discovered the. Language. Go ahead. Were you at Vanderbilt? Just roughly. [00:02:00] Uh, about a year and a half, almost two years overall. Yeah, around 18. Like, 

[00:02:04] Vic: uh, five years ago. Yeah, 2018, 2019. Pre COVID. Yeah, that time. Yeah, 

[00:02:09] Talha Haseen: pre COVID. Exactly. Pre COVID. Um, but that, that was a phenomenal time. I, I actually think, Vic, like, I'd love to hear what your opinion might be.

[00:02:15] Talha Haseen: I almost, like, that experience, like, framed healthcare to me as, like, not, I mean, it is like this enormous industry in our economy, but almost framed it as like a, the intricacies of healthcare come to, like, I started viewing them as basically, uh, almost like a moral question. And the different answers we give to that, that the questions around healthcare over time, the complaint, I don't, I literally started stop looking at it.

[00:02:41] Talha Haseen: Like I look at a traditional business completely. And I think that's, that's kind of the case. It forces you to look at it a little differently given how it works, but long, long story short. Uh, that turned into, uh, you know, potentially going to grad school and then decided to go to McKinsey and McKinsey and company instead, just because I landed an offer there prior, prior to going.[00:03:00] 

[00:03:00] Talha Haseen: And then, uh, I took a little break from McKinsey to help run Envision Healthcare under their CEO and CFO, uh, out of Nashville, uh, and then went back to McKinsey after that, uh, to finish up the stint, let's call it. Yeah. And, uh, 

[00:03:13] Vic: I want to gloss over Envision too quickly. So that was during the No Surprises Act or right in the, before it or right after it?

[00:03:22] Vic: Cause obviously that was a huge change in Envision's business. What was there and how did No Surprises affect it when you were there? 

[00:03:31] Talha Haseen: Yeah, it was, it was in tow. So I worked under, uh, Jim Recton, who is now the Humana CEO. He Effectively, um, as he was coming in after the KKR acquisition and change of the leadership team, it was basically preparing for the no surprises act and all the changes that are going to happen in that provider group sector, like practice management space, the no surprises actually ended up spending an enormous amount of time on the NSA.

[00:03:57] Talha Haseen: I actually ended up building, uh, and [00:04:00] designing a lot of the processes that I envisioned from a technology perspective to do the actual dispute resolution with payers, right? Like, you can't, can't do that stuff by hand when you've got 10 million patient encounters happening every year. Uh, so some of those things it was, but it changed the way, like, it's actually really, it's, it's almost comical.

[00:04:18] Talha Haseen: I, I quite literally remember being at Envision talking about how hospital medicine contracts the Envision had with, you know, hospital systems across the U S would shift, they would need to change. And like two years later, I remember being at McKinsey on the other side of the table, the health systems basically saying all these provider groups are asking us for more money.

[00:04:37] Talha Haseen: And I'm like, well, yeah, it's because of the NSA. It's just a very, very interesting couple of years and happening. Do you 

[00:04:45] Vic: think there was a value shift in the industry, uh, through the no surprises act where I don't know, gross margin or net margin shifted from, uh, providers to payers or maybe I'm interpreting too much into what you're saying?[00:05:00] 

[00:05:00] Talha Haseen: No, I definitely think so. I think the, I would characterize it as just leverage being shifted because the way the NSA is structured. First of all, I think it's. It's a necessary law, like I, I don't think I, there's nothing against that. 

[00:05:14] Vic: Yeah, there were good intentions behind it, but it had massive ramifications.

[00:05:19] Vic: Right. 

[00:05:21] Talha Haseen: Yeah, exactly. Massive implications. Uh, I do think though, the pendulum of leverage shifted away from providers. Within that space into pairs because of the way the NSA was implemented and the and the weight specifically that's been given to the QPA and effectively how the QPA is calculated. If I get super gritty, 

[00:05:40] Vic: if I define QPA and then going down.

[00:05:43] Talha Haseen: Yeah. Great point. Yeah. So QPA was is basically. If I set up the context, right, let's say, you know, Vic is the doctor and I'm the, and I'm like the, the insurance company and Vic and I have not had an agreement. We don't have a contract in place for like, you know, uh, I'm [00:06:00] the insurance is going to pay you this much for this much of your client service or patient service that you're doing.

[00:06:05] Talha Haseen: per encounter, let's call it, or whatever CPT code. Uh, in that situation, the QPA becomes the default right answer because of the NSA. That's a super gross simplification just for, for context, but that's effectively what the QPA serves as, as this is the right answer of what you should get paid. 

[00:06:22] Vic: Right. And it really, uh, when it gave, it gave leverage to payers in the sense that They could, uh, opt out of a contract and then the QPA was going to stand.

[00:06:33] Vic: And so it, it gave more negotiating power to the payers than they had previously. 

[00:06:40] Talha Haseen: Exactly. And, and if you were a very sophisticated payer leading up to the NSA, because of the, so the QPA was calculated based on the median in network rate. That is like the approach, right? So if you were a very sophisticated pair, uh, you could lower that premature prior to the law going live.

[00:06:59] Talha Haseen: Uh, and it [00:07:00] was, I mean, it's a great arbitration. Uh, 

[00:07:04] Vic: lower it. And then if, if a health system gets frustrated and you is no longer in network, then they are getting the QPA, which is a. By definition, you have pushed it lower. 

[00:07:18] Talha Haseen: Yeah. And for frame of reference, it's lower than Medicare rates in certain geographies.

[00:07:23] Talha Haseen: So it's not like the QPA is like, Oh, it'll probably be around Medicare. It's like, no, it could be lower. It could be like 20 percent of Medicare. 

[00:07:30] Vic: Vision while they were preparing for that. And then you moved to McKinsey consulting with health systems. On how to, how to manage this, uh, new world of network negotiations.

[00:07:41] Talha Haseen: Yeah, which I, it was, it was, uh, yeah, I mean, uh, the, the McKinsey work, I always, what I did at McKinsey is basically like just pure health system strategy and growth related work. So it could be, you know, transformation related or growth strategy. So it was always something with health systems, not necessarily provider groups themselves, themselves directly.

[00:07:59] Talha Haseen: But often [00:08:00] this would come up as, you know, where we, their, you know, health systems are renegotiating, uh, contracts. And they would often, the conversation would turn towards, well, how can we just employ all of our physicians? How can you convince them that it's better to work, you know, as an employed physician, as opposed to being a contract in one.

[00:08:16] Talha Haseen: And we make that work somehow. And interestingly enough, you know, the aftermath of the NSA, a lot of larger groups such as Envision, uh, and a few others that were also located in Nashville or near Nashville. It kind of went belly up and, uh, the groups that they owned ended up being absorbed by those same hospitals.

[00:08:33] Talha Haseen: Right. It was almost like an opportunity. 

[00:08:36] Vic: Yeah. So the result was many more, uh, salary docs. 

[00:08:41] Talha Haseen: Yep. 

[00:08:42] Vic: And it's sort of a changing of the, the net, the, the negotiating power across the whole industry. 

[00:08:47] Talha Haseen: Yeah, exactly. Which is, which a few weeks, you know, a couple of, not long ago, you, the, uh, all the other pressures that are happening towards the pair unrelated to this, it's, it's kind of building into this momentous thing [00:09:00] of like, you know, pairs are terrible overall, uh, given, you know, you look at the, where the leverage might be and then also what's happening with denials and whatnot.

[00:09:08] Talha Haseen: Right. Yeah. Uh, not that that's necessarily true. It's just a sentiment thing that I definitely think is growing. 

[00:09:13] Vic: Whoever is managing the claims adjudication is always going to be in a position of the bad cop, right? That's their job to be there. Yeah. That's sort of why They are put in place. Um, and this, this American system we have has checks and balances, a lot like our legal system where, you know, there are two sides that are fighting over what the right network price should be, and in general, that kind of works as long as the two sides have equal or near equal negotiating power.

[00:09:46] Vic: And on the region, some, sometimes that's true. Sometimes it's not true in the country. 

[00:09:52] Talha Haseen: Yeah, yeah, exactly. 

[00:09:54] Vic: Okay. You're at McKinsey. And, uh, then you decide to join a healthcare [00:10:00] startup, which is quite a change from the trajectory before that. So talk to me about that decision. What did you see and fathom or what were you looking for when you jumped over?

[00:10:09] Talha Haseen: Yeah, I think it's, it's definitely, I think if I look at like my traditional career, like, uh, decision making, it's definitely a, uh, depart, it's departing from that. But. I think from the spirit of the things that I wanted to do lifelong, like, you know, longterm, it's definitely a tune to that. Like I had a couple of in between or concurrent to some of these roles, like entrepreneurial ventures that I worked on with friends, which are like small things that weren't like huge things.

[00:10:36] Talha Haseen: It was purely with the idea of like, Hey, let's do something for ourselves. It'd be kind of fun. Uh, and it'd be nice if we make some money too, but let's see. 

[00:10:44] Vic: We were talking earlier, you made a couple angel investors investments too, right? Yeah. 

[00:10:50] Talha Haseen: Yeah. So what turned out is like, I had a couple other friends who were also either, you know, in banking or consulting or actually, or, or we're software developers.

[00:10:57] Talha Haseen: And we were all, you know, doing due [00:11:00] diligences for PE firms at our current work, like either on the banking side, helping with the transaction or through consulting. And we were like, well, could we just do something similar for ourselves? Like, we may not have the data, but we can probably make some decent decisions if we make enough of them.

[00:11:15] Talha Haseen: Uh, and that, that led to, you know, putting a bunch of like around 2019 and prior to COVID. investing in a couple of companies, uh, one of which that IPO, which is kind of amazing. And, uh, and then a few others that are, that are doing fairly well. Some that actually did horrible, like there were some awful, awful decisions.

[00:11:34] Vic: That's the game, right? You're always going to have some that do well, but, but you lead with the IPO or the big winners because they're more fun. 

[00:11:40] Talha Haseen: Yeah. Yeah, exactly. Uh, so it was good. I think that kind of also gave me the, the umph of, uh, you know, the second time around at McKinsey, I kind of, Was thinking I'm either going to stay here and just go, you know, run for becoming a partner at some point, or I need to go do the thing of doing something on my own and risk the, you know, [00:12:00] if I don't achieve what I wanted to achieve, I don't, or I keep trying until I do so.

[00:12:05] Vic: Yeah, but on yourself a little bit. 

[00:12:07] Talha Haseen: Which, which honestly like it is more when I think about it and reflect, like it's actually more attuned to like how I make decisions and, and do things than I, than I used to think it is. So, um, but fathom you, you that, that specific point, um, fathom actually ran into what I was, uh, at Avis.

[00:12:26] Talha Haseen: I knew about them and I knew the, the co-founder and CEO Andrew and uh, I kind of just stayed in touch 'cause I was like my, my. Intuition was, these seem like really, really, you know, smart people working on a problem that I'm somewhat familiar with, not deeply, but. Intuitively, it made sense to me that there's the way that they were solving the problem.

[00:12:47] Talha Haseen: I was like, this is, this seems like the right way to do it. Uh, and I just stayed in touch. Uh, and then it happened so that they were looking to grow in a, in a way that I was looking to grow and decided to leave the consulting again, jump ship. [00:13:00] 

[00:13:00] Vic: Okay. So, um, you're not a founder at Fathom, but, but, uh, give us the origin story or how did Fathom roll up?

[00:13:07] Vic: Cause it, cause it's been, um, I think they're maybe eight or 10 years old. They're a little bit, they've been around for a while, but really just like coming into, uh, a lot of strength right now. So tell us the story of Fathom. 

[00:13:23] Talha Haseen: Yeah, absolutely. I'll, I'll do my best. So Fathom actually started out. So Fathom today is like an AI company that does medical coding.

[00:13:30] Talha Haseen: It started out as a company called, uh, TinyRx. And it was focused on pharmaceuticals and like, effectively getting, getting patients the right drugs at the right prices and, and so on. I, the, the co founders, Andrew and Chris, pretty quickly, I think after exploring the idea of TinyRx and taking a market, realized that this wasn't where they wanted to build a business.

[00:13:52] Talha Haseen: Or it wasn't going to have the type of impact that they wanted. You know, there's a bunch of, there's a lot of pharmacy, pharmacy companies as well. So it's very, [00:14:00] uh, lots of precipitated ideas in that space and they shifted gears and started looking at. where else they could make an impact, uh, in healthcare.

[00:14:11] Talha Haseen: This is actually within the backdrop of Google releasing the, the, the attention is all you need paper, which is around, you know, the transformer architecture, which is, which is quite literally why we have chat GPT and, and all these other models. And I, at the early stages, I think they had a hunch of, We could use this technology, uh, and with enough data, we could truly fully automate medical coding or some other administrative tasks within healthcare.

[00:14:41] Talha Haseen: And, uh, and it started off with Okay, well, who's got the most data? Let's go to billing companies. Let's go to, you know, the, the, uh, the ones that are aggregating all these, these encounters and, and see if we can build something that's meaningful. And since then, uh, it's grown into, you know, we all, you know, most of our [00:15:00] pipeline now is, is like, you know, large health systems, payers directly, effectively the consumers of that, that medical coding output, as opposed to like.

[00:15:07] Talha Haseen: Resellers of that service. 

[00:15:09] Vic: Yeah. So just to recap, make sure I'm following in, uh, 2018, 2019, 2020, when, uh, Sam Altman and Elon Musk and others were working on sort of the broader AGI LLMs for society. Um, Tiny Axe shifted to be Fathom and really focused on medical billing and coding as its primary use case for the transformer based AI models.

[00:15:39] Vic: Yeah, yeah, 

[00:15:42] Talha Haseen: yeah. Effectively, it focused just on that as a problem area, not to be kind of like. You know, the, the answer to 10 questions to everybody, but really be, we can do this one thing and we can do it better than anybody else. And, and that's what we do. Uh, and doing that with medical coding specifically, I will say [00:16:00] this since, since then, like today, like.

[00:16:02] Talha Haseen: The stack of models that is used is like is grown significantly. Like it's, there's a, there's the effectively like our, our model itself that does all the heavy lifting. Then we have, then we've started to experiment with, can we use like existing LLMs to help us with the edges? Like, is it, is it, is it easier for it to identify this element once we've gone through?

[00:16:24] Talha Haseen: So it's been like an amazing thing over the last year to, to see how it, cause it keeps continuously evolving as things get better. There's almost like this benefit of. Of, uh, the overarching investment that everybody else keeps doing, like the Sam Altman's of the world. 

[00:16:38] Vic: Yeah, 

[00:16:39] Talha Haseen: yeah, 

[00:16:40] Vic: but I think the one of the things I want to just make sure the audience recognizes, because it's why I wanted to have you on, is that, um, almost all of the existing healthcare AI solutions, except for Fathom, sort of started with a general purpose.

[00:16:57] Vic: L. O. M. And then they're fine tuned it [00:17:00] for the use case and health care that they're that they're approaching and fathoms quite different than that where you all started with developing a kind of a deep learning L. O. M. transformer based architecture around medical billing and coding specifically. And so it would be very good at writing poetry or, or writing a sales plan, but it's purpose driven for the use case you're using it for right now.

[00:17:25] Talha Haseen: Exactly. Yeah. It is driven. It is one use case of doing the actual medical coding and doing all of the medical coding, not just like one sub element of what is considered medical code. Like medical coding might have like 10 sub jobs, right? Associated with it. It's not like it's doing the whole thing. It's effectively.

[00:17:43] Talha Haseen: The goal was, quite literally, we want to be a medical coder that just sits in the cloud and can do, you know, hundreds, thousands and thousands of volume of charts without, and do it the more accurately and faster than, than any human would be able to do. 

[00:17:57] Vic: So, um, and it started in ambulatory, right? At the, at [00:18:00] the clinic level.

[00:18:01] Vic: That's, that's, yeah. So, so it's, uh, or a primary care doc or a physician group. They have, uh, a team of Medeco coders now, or they outsource it to, uh, another country or internally. And so you are, your proposition is, let us replace those people, whether they're inside the practice or outsources, so people that are reviewing the charts and then making the codes and submitting the codes.

[00:18:31] Vic: We will take that and fully automate it, um, and you won't need those people anymore. Thank you. 

[00:18:37] Talha Haseen: Yeah, or, or, uh, well, yeah, or, or you'll, you'll need them to do something else instead of do coding itself. Right. But, but exactly that it's like, we will, all of the, what we, what is like normally considered like production medical coding, like you might have like 30 people focused on this one production medical coding workflow.

[00:18:55] Talha Haseen: And it's like, well, now we only need two people to do that work, which is, you know, the stuff that [00:19:00] Fathom can't do. And then, uh, the remaining team can focus on, you know, provider education, CDI related things, all sorts of other stuff. 

[00:19:07] Vic: Fathom has a different model that again, then a lot of it comes away.

[00:19:11] Vic: It's not the co pilot sort of, we will ride alongside you and make you better at. Job instead, it is the AI is going to do all of this work and it's better than humans at certain aspects of coding. 

[00:19:26] Talha Haseen: Exactly. Yeah, it's, it's exactly, it is, it is built for that purpose. Like there is no UI for it. And there's no, even like a, you can't log in anywhere.

[00:19:36] Talha Haseen: Like it's quite literally like we. Uh, we show you that it works like with action, with, with doing coding concurrently to your existing coding operation. And then what we do is super transparently audit, like, let's say 10, 000 encounters, some, some large scale. So, you know, it's not like, you know, a backend team somewhere human coding.

[00:19:55] Talha Haseen: It's like, you know, it's, uh, some large amount and we turn it around and let's [00:20:00] say like 45, 90 minutes. And, uh, we give it back and we start doing an audit against your, like a client's existing coding, uh, All the, 

[00:20:07] Vic: all the coding for last year. And then your system will do that in 90 minutes or something like that.

[00:20:15] Vic: Very good. 

[00:20:16] Talha Haseen: Very quickly. See 

[00:20:17] Vic: like apples to apples. Okay. These are the same patients, same doc. Same interaction, same chart that would have occurred under fat. 

[00:20:28] Talha Haseen: I have like a, this is going to, I have a working vanity metric, like in one of our like internal, like, um, you know, invoice and financial documents where I basically back into like, If all of our clients had full staffed human medical coders, like how many would they need to do the volume that we were doing, and it is substantially larger than the headcount in Fathom.

[00:20:49] Talha Haseen: And we're, we're only like 70 people or 75 people right now. 

[00:20:52] Vic: Yeah. 

[00:20:52] Talha Haseen: Yeah. 

[00:20:53] Vic: So you're need 500 people to do all this code. Yeah, 

[00:20:57] Talha Haseen: right. Yeah. And it scales very quickly. [00:21:00] Like there's a, there's a very large client that's going live right now. And that's going to be like, you know, two, three X the number it is now without having to.

[00:21:09] Vic: Yeah, I mean, that's the beauty of these models is that as they get better quality and they are accurate and reliable, which is a big threshold that I want to come back to, but once they are, then you can spin up additional, additional servers, additional processes, but it's, it's, it's adding another software instance.

[00:21:31] Vic: It's not a significant cost. 

[00:21:34] Talha Haseen: Yeah, exactly. Like I think I actually think there's not a monetary cost, but there's definitely like a headache cost. Like if a health system or a provider group or who have you is, you know, changing from coding vendor A to coding vendor B and they're both human coders. It's kind of like a It's very easy for them to think about that.

[00:21:53] Talha Haseen: It's, it's very new and different to think about, Oh, we need to go through, we need to integrate with the EMR. You know, this company needs to build a [00:22:00] model. This company, we need to do this verification quality checks and whatnot. I think it's a little bit of that, add some, some, uh, friction, but I've seen over the last, like, seven, eight months, that friction go down pretty substantially.

[00:22:14] Talha Haseen: Like, people are getting very used to the idea of, okay, we want to do it differently. 

[00:22:18] Vic: Yeah. 

[00:22:18] Talha Haseen: So it's going to be different. 

[00:22:20] Vic: Yeah. And I think, uh, it seems like it's a, it's a much stronger return on investment kind of economic value proposition to the health system to be able to do a full replacement plan.

[00:22:33] Vic: As long as it is reliable and accurate, so talk about the process of Fathom. Um, we were talking earlier, it's almost an exponential curve of how hard it is to get the, you can get the first 30 percent of coding done pretty easily. It's not complicated. Anyone could really kind of quickly do it. But as you get to 50%, 70%, it gets exponentially harder.

[00:22:55] Vic: Yeah. Where is that process, how does that work and where is that Fathom [00:23:00] now? 

[00:23:01] Talha Haseen: Yeah, so Fathom's most, um, so special, so, so the, I guess like the things that really matter are like, what's the automation, which is like effectively like a recall rate of the model. Like how much can you automate and what's your accuracy, like coding accuracy with what you are automating, uh, vast majority of specialties that Fathom works for clients and actively is paid for.

[00:23:21] Talha Haseen: They're like 90 percent automation. We expect every specialty to be above 90 percent automation in the future. Um, I think the lowest ones we have is like around 70. And those are like surgeries, uh, oncology related things, lower volume stuff that is bespoke or like emergency medicine, primary care, radiology, radiology, we have a client.

[00:23:43] Talha Haseen: That's a 99 percent automation, but a health system client with radiology. And the accuracy is we, we contractually guarantee 95 percent accuracy, which is like the industry standard. 

[00:23:55] Vic: Yeah.

[00:23:59] Talha Haseen: No, I [00:24:00] mean, they can, but it's just, you would need them to spend a lot more time with each encounter. Like humans can't do 10, 000 encounters at 95 percent accuracy. And, you know, in two days, you need a lot, or you need bigger teams. But the, the, the, the thing you mentioned about like, um, automation rate about the first 30 percent or 40 percent being easy.

[00:24:20] Talha Haseen: One thing that I've seen, uh, even from fathoms competitors and also from the co founders talk about this in depth is getting to like the 50 percent automation with 95 percent accuracy, like a useful product, right? Like things that people would bill. Getting to 50 percent was not that hard. Like it was hard, but it wasn't like it was achievable going from 50, 60 range to like 90 percent or 90 percent plus vastly difficult, vastly more difficult than just getting the first 50%.

[00:24:53] Talha Haseen: And I think, and this is honestly one of the reasons I joined fathom is like the hypothesis fathom is automation [00:25:00] rates and accuracy will drive the winner, like in this market. I can't imagine any health system CFO being like, Oh, I can automate 50%. That's good enough. When they have an option, somebody else that says, well, we can do 90%.

[00:25:11] Talha Haseen: Uh, you know, you can have, 

[00:25:13] Vic: yeah. Given the, the sort of proprietary and dedicated focus of the model, I assumed there probably are great sort of benefits to scale, like as you add on new health systems, additional specialties, you get more and more, uh, inputs. And, uh, it gets stronger over time. 

[00:25:34] Talha Haseen: Absolutely.

[00:25:35] Talha Haseen: Yeah. I think that the, uh, so Apollo MDs is a, is a large medical group that all of their emergency medicine as a specialty like Fathom handles. So that gives us an enormous scope of, of emergency medicine coding for us. Right. So as we add net new emergency medicine, like every time we add a new emergency medicine client, now they benefit from the fact that we've already seen so much emergency medicine in the U S.[00:26:00] 

[00:26:00] Talha Haseen: Yeah, it's kind of a 

[00:26:01] Vic: classic network advantage that Fabulous can take advantage of, where every time you sign up another health system, it makes the base stronger and it helps you sign up that next one and the next one and you have a further mode, basically. 

[00:26:15] Talha Haseen: Yeah. Yeah, exactly. It kind of just builds this.

[00:26:17] Talha Haseen: I think we have somewhere around almost a quarter billion, little, little shy of that right now, I think, but almost there of, uh, historical patient encounters that we, that, that we've trained the model on. 

[00:26:29] Vic: Okay. And so let's talk about what you're doing at Fathom because I think you are working more on the inpatient, uh, side of things, which is very different as most of the audience will know.

[00:26:39] Vic: So, you know, it's not ICD 10, but DRG codes, which is. Is different. So where, where is the product maturity in there? What's the roadmap look like? How, how has that process? Yeah, 

[00:26:51] Talha Haseen: well, I'm doing it. I've one of the things that I actually quite remember, I literally remember sitting down, um, talking about this.

[00:26:57] Talha Haseen: Like one of the reasons I joined Fathom was like, I want to be at a [00:27:00] high growth company and get the experience of scaling something, uh, which means inherently doing a bunch of different things. So depending on the day and the hour I've got, I've got a different hat on, but. The inpatient piece is something I'm, I'm, I'm helping drive, which is, so the only piece of medical coding that Fathom can't currently do today is inpatient facility coding.

[00:27:20] Talha Haseen: So every other specialty under the sun, whether it's risk adjustment repairs, whether it's primary care, emergency medicine, facility side or the professional side, two sides of the coin for that one and any of the others we can pretty much do. Uh, the inpatient facility is the only thing that we currently can't do.

[00:27:39] Talha Haseen: And that's a way more complex than, you know, primary care coding or hospital revenue depends on that. So what I've been doing for the last six months or so is, is building, um, a consortium of design partners. So effectively about five or six health systems is, is what we imagined will end up being, uh, that.

[00:27:59] Talha Haseen: are [00:28:00] partnering with Fathom to build the inpatient product. And that, that's something we decided as an organization that we, we need to do. Like we can't build, we can't build, um, we can't build that product without a health system partner. That's going to be helping us design it because the workflows of inpatient coding, like I was actually on a bunch of calls this morning, discovering that we're full, one of the systems that we're going to be partnering with.

[00:28:23] Talha Haseen: And I was like, Oh wow, this is, this is very complex. This is so complex that I, that I imagined. A lot of people that work at this system don't fully understand what, what, like, what, how, how this is actually done, uh, the amount of teams, the amount of people, uh, the amount of technology that's used to do all of that.

[00:28:40] Talha Haseen: It's a, it's a lot of stuff going on 

[00:28:42] Vic: and it's because it touches, um, several different parts of an organization. And then, so the billing has to like pull information from different areas and, and, uh, be more integrated than, uh, an ambulatory clinic setting. It's more like we had this patient encounter and now let's bill [00:29:00] for it.

[00:29:00] Vic: Is that close 

[00:29:00] Talha Haseen: to right or no? Yeah. I think that's a part of it. That's a big part of it. A big part of it is the fact that inpatient care is very acute. You have an enormous amount of documentation. So that's one like documentation is being generated daily, multiple times a day, tests, nurse notes, physician notes, rounding that happens on each patient's.

[00:29:20] Talha Haseen: Um, and then in addition to that, there's from an administrative perspective, inpatient coding is also a massive liability pitfall. Let's like, it is very easy to go into a hospital coding or billing department and, um, effectively put yourself at risk because your policies or the way that you're coding is, does not look appropriate to, to an authoritative body.

[00:29:48] Talha Haseen: Uh, and that's never what you want, right? Like hospitals can be large hospitals are going to become targets to things like that. So I think because of that, because you have to avoid risks like that, the, the operation is really complex. Like [00:30:00] there is the revenue side of like, Hey, are we coding this accurately?

[00:30:03] Talha Haseen: Like from a clinical perspective. And then there's the side of, are we coding this accurately from a DRG perspective relative to like revenue? Are we showing that we did all the work that we did? And those two things, systems, I've noticed a lot of systems like address that differently. Yeah. Like some systems have a combined, uh, operation where everything falls under the chief revenue officer.

[00:30:23] Talha Haseen: The other systems are like, you know, this part of coding sits under quality and this part of coding sits under revenue. So it's organized a bit differently. 

[00:30:31] Vic: Yeah. And there's some systems I think have a belief that that leads to better care 

[00:30:36] Talha Haseen: because they're 

[00:30:37] Vic: separating, um, the quality of care from the drive for more revenue.

[00:30:44] Talha Haseen: Yeah, exactly. And I, and I, and I think it's, it's, it's. I mean, I see the intention of why the separation needs to exist, right? I think Mayo's has got it that way. It's completely separated out. Like it's a quality quality department. The other one's what does the final [00:31:00] coatings like a revenue revenue leader.

[00:31:02] Talha Haseen: Um, but taking that into account, right? Like if I'm going to, we're going to, Fallon's going to put out an inpatient product, right? Uh, that can do the inpatient facility coding and the workflow is way more complicated than what it would be like on primary care where you just code the chart, you send it back and you send it out the door.

[00:31:18] Talha Haseen: A lot more, a lot more complex, uh, a lot more revenue, you know, opportunity or risk associated as well in making sure things are correct, uh, and accurate. The other fun thing that, or actually you're going to say something. 

[00:31:33] Vic: No, no, give me your fun thing. I want to hear that. 

[00:31:35] Talha Haseen: One crazy thing I see about inpatient is like.

[00:31:39] Talha Haseen: The inpatient market is kind of in a chokehold, uh, from a coding perspective by 3M and Optum. Like, there's no real players that are automating or tackling the inpatient problem using modern tools or using any, any real AI. And I know every company's got AI in their name now as well. [00:32:00] But, um, like today, the inpatient, like, coding, Operation is basically throw a bunch of bodies at the problem and give them tools that are made by 3m and Optum and audit them until it's accurate.

[00:32:15] Vic: Yeah. 

[00:32:15] Talha Haseen: That's quite literally every how every operation work there. There's no like re imagining like, Hey, maybe we should, the simple cases should be fully automated and the stuff that's really complex should go through a really heavy duty review as opposed to. You know, just this one team that's going to manage everything.

[00:32:32] Talha Haseen: And the other pattern that I'm seeing is the availability of certified coders, basically people, and my mom used to be a coder actually, uh, when I was, when I was younger, uh, it's a hard job. It's a hard job and they, they don't, they're not, they don't exist 

[00:32:51] Vic: pain job. And they, yeah, people don't want to do it.

[00:32:53] Vic: Yeah. 

[00:32:53] Talha Haseen: Yeah. Well, there's not many of them. There's just not like that many because a lot, a lot of folks retired, a lot of coders [00:33:00] retired during the COVID time. And um, a lot of them, most of them aren't coming back and neither are, you know, a lot of new folks that are entering the job market, they're not necessarily looking at medical coding like it used to, they used to, let's say in the early two thousands or so.

[00:33:16] Vic: Yeah. And 3M certainly has some innovation in the platform. But Optum It's a little bit the, you know, the hen, the fox guarding the hen house a little bit. Like, I'm not sure that they are the best partner long term for health systems. They do great work and I'm sure they keep everything separated, but, but it's just a hard, uh, parent organization.

[00:33:39] Talha Haseen: Yeah. Yeah, exactly. And, and I just can't imagine Optum or 3M coming out with a solution that is like highly performant and very AI forward. I, I mean, I've seen something, some stuff from Sylventum or 3M, but, um, nothing that's kind of blown, you know, blown the market away or anything. [00:34:00] 

[00:34:00] Vic: So, um, I want to change gears for a minute.

[00:34:03] Vic: We just had, uh, last week and JP Morgan is this week. Of course, it's a busy January. But I want, uh, Elon Musk was in an interview at CES, and he said that, of course, he's Elon Musk, right? So he is trying to get things for effect, I think, a lot of times. But he said, in his view, all cognitive tasks will be able to be done by AI in two to three years.

[00:34:28] Vic: And which just floored me. Um, and so what I wanted to get your thoughts on is, is let's leave all cognitive tasks to the side. And also, let's forget about the clinical, like, actually making clinical decisions about the patient's care in the moment. I know there's some AI involved in that, but, but, um, FADM is in the administrative billing side, and a lot of the successful early tools are not in clinical, they're in administrative.[00:35:00] 

[00:35:01] Vic: How far do you think we are away from where, let's pick a number, 90%, 95 percent of those administrative services can, will be able to be done by an AI tool, like largely automated, fully 

[00:35:15] Talha Haseen: automated? Yeah, that's a great question. Did you, do you follow Qventus by any chance? The company Qventus? Yeah, I do. They just raised, like, uh, did you see that the other day?

[00:35:25] Talha Haseen: I 

[00:35:27] Vic: didn't see their raise. 

[00:35:29] Talha Haseen: They raised a series D about 105 million purpose, basically specifically for this, like agentic solutions towards all administrative tasks that could be automated at a hospital. And I'm sure that, you know, they're not doing everything for a hospital, but there's, uh, but. I think it speaks to at least the same thing that you're getting at.

[00:35:51] Talha Haseen: So if I start small medical coding, I think this is just an execution problem. Now there's no like technical or scientific risk left within that [00:36:00] administrative task. The other tasks like the faxes that hospitals still have to send some like all those things that really shouldn't have to do or there are other administrative things that nurses have to do that that could be automated.

[00:36:14] Talha Haseen: I genuinely think that stuff is going to get automated. I Maybe it's five to six years, a little longer. I haven't, I haven't dug into like what are the great tools, but I know there's an enormous amount of tools and that Cubantus investment being, you know, one example, I just can't imagine, uh, it taking longer than five, five to 10 years.

[00:36:35] Talha Haseen: Uh, given all the existing technology that we have. And I mean, I've, I've started building like little agentic systems to do small things for me, like update some Excel files based on some, you know, regular reports that are updated. Um, 

[00:36:49] Vic: yeah, it's incredible. So I think, uh, what's interesting is that there's a lot of fear and Elon talked about, you know, what are the humans going to do if all cognitive tasks are [00:37:00] done by machines?

[00:37:01] Vic: What, what are we all going to do? Yeah. That is pretty scary outside of healthcare, but as you mentioned, in healthcare, the job of coding, there's not a lot of people that are 18 years old that like, they're dreaming a lot just to go into that. And simultaneously, if we take administrative burden off of healthcare, Nurses or doctors or any of our people.

[00:37:24] Vic: That's a great thing. I mean, they they're they have a lot of stress taking away administrative duties and allowing them to focus on the patients focus on sort of care at the bedside and it could be wonderful. Um, is there a downside to that or do you think that is, that could play out in five years, eight years?

[00:37:46] Talha Haseen: I think it could certainly play out. I'm sure that there, I think there's trade-offs to it. Um, I mean, I think what you're kind of getting at is like displacement of, of jobs, basically. Right? Like things that currently exist. So here's, here's a [00:38:00] interesting, I'll, I'll answer that with an, with like a real life exam.

[00:38:04] Talha Haseen: I think. So I gave the example of my mom being a medical coder when I was a kid, right? I imagine like, I asked myself this, like, what if medical coding was not available as a job, what would she have done? Like she, she was really just like, I'm going to try to take care of, you know, do what I can for, for my family and whatnot.

[00:38:22] Talha Haseen: Uh, yeah, I, a part of me wonders if she would have been forced into it to do something that's entrepreneurial at some point, because at some point, if there's not a structured, simple path, such as, you know, it could be medical coding, it could be even all sorts of careers. Or, or things that you could do, um, folks, what's the other option left?

[00:38:45] Talha Haseen: I think the other option is like, well, I'm going to do something that I think I'm decent at, and I'm just going to go and see if I can earn money from it. Um, and, and I, I, I think a part of the, that part of that. Displacement will [00:39:00] actually stir that, increase that, the amount of folks that are at least trying to do something like that.

[00:39:06] Vic: Yeah, I think that's right. The, um, the reason I'm optimistic in healthcare as opposed to call centers or FinTech or law or some other industry is that I think, um, in person empathetic care where we're trying to help the patient, the patient. Um, live a bit, live slightly healthier life, stay on their medication, side effects that there's a lot of things that, um, healthcare staff could really be empowered to do that would be, I think, more fulfilling or as fulfilling as coding.

[00:39:44] Vic: Um, and could maybe make the job, maybe a pay is the same, but, but they're able to engage with the patient more and really sort of affect it. 

[00:39:53] Talha Haseen: Yeah. I think the scribe AI companies like the abridges or Dax nuanced that, you know, they're [00:40:00] already seeing great outcomes from that where physicians are spending so much fewer hours, um, on documentation and actually able to be like, Oh, I could probably see another patient today because I don't need to chart as much.

[00:40:13] Vic: And when they're in the room, they're not having to take as many notes and, and do their coding while they're talking to the person, which has, you know, bad customer service issues. 

[00:40:23] Talha Haseen: Yeah, exactly. Good quality impact there too. Yeah, I say that in a funny way. Like my, my girlfriend's a family med doc and she spends.

[00:40:32] Talha Haseen: a lot of time doing charting, like after hours, like really a lot of time. Uh, and just cause the patient load, uh, and she's like, well, this AI better work. Yeah. Yeah. Just quite literally waiting for it. Yeah. 

[00:40:49] Vic: Okay. So I wanted to talk through that to ask the next question, Um, if billing and coding, uh, becomes fully automated with Fathom and [00:41:00] others, the other side of the claims processing, the payer side, is also using AI and really ramping up, they might even be ahead of the health system side.

[00:41:13] Vic: And so is there going to be a, um, kind of a balance of power or even like an arms race to see who can, who can be either billing with more evidence and justification? And knowing how the payers are going to adjudicate things so that you preempt that and submit claims that are going to be paid versus the payers, um, you know, questioning things more and more often.

[00:41:37] Vic: It feels like there's kind of an arms race. What are your thoughts about that? 

[00:41:41] Talha Haseen: Yeah, I definitely think there's a, there's a bit of an AI arms race there simply because of the arms race has already existed. It just was powered by humans right on both sides of the, the, the table there. And now it's just going to be kind of supercharged for a bit before some balancing occurs.

[00:41:58] Talha Haseen: I think the, the [00:42:00] pairs have always been ahead from a technology perspective because their industry has forced them to be like, they're, You know, the date, the amount of data that they have to go through and they just simply have to rely on technology more 

[00:42:12] Vic: and more centralized in general. Yeah, 

[00:42:15] Talha Haseen: yeah, exactly.

[00:42:16] Talha Haseen: I, so I think that they will absolutely be ahead of the providers. I just can't imagine a world where they wouldn't be funny enough. I think, uh, and I mentioned this maybe the other week, there's, I know of a couple of companies, one in particular, that's doing quite well, that's still in like stealth mode.

[00:42:33] Talha Haseen: Um, they've got like, I think like eight or nine pair clients now, but, but, but all like pilots, but effectively what they're doing is helping payers benchmark their own policy, helping pair a, you know, benchmark its policies around medical necessity guidelines, which often can result in denials, uh, against other pairs.

[00:42:53] Talha Haseen: Uh, and not all pairs are sophisticated or, or have the same level of maturity with those [00:43:00] guidelines. And this is something that I just immediately see like, well, okay, if pair A starts changing their medical guidelines based on pair B's existing guidelines, which would have required, you know, 50 people to work nonstop to digest those, and now it's just, you know, two LLMs can create a summary of that in seconds.

[00:43:19] Talha Haseen: There's a faster iteration, faster pace of change that's going to occur. And if providers on the other end don't catch up, they're going, there's just gonna be an an in completable, uh, gap between the two organizations in terms of pace of change and whatnot. I, I definitely think, I, I actually get asked this all the time, even from the inpatient work that's happening.

[00:43:42] Talha Haseen: Most health system chief revenue officers or even CFOs will actually, during those partnership conversations say, how will this, how are you, how are my, where's, where's basically the denials piece of this? Uh, are you gonna do that after coding? Is that later? Where, where's it on your, your, uh, roadmap? [00:44:00] Uh, we're not gonna immediately solve that problem.

[00:44:01] Talha Haseen: We have so much to solve with just medical coding, but there are definitely other organizations that are working on it. Uh, the one that I mentioned that's doing it for payers is, is actually also doing it for providers, uh, at least for the medical necessity side. But I think we're, I actually feel like the, what are your take?

[00:44:16] Talha Haseen: You think the, the arms race is actually here? I feel like we're. We're probably like six, seven months out before we actually start seeing things in scale. 

[00:44:24] Vic: Yeah, I think it's, it's next January is my guess of when it really starts to be. I mean, the way I think about it, arms race is it, it's detrimental to not have an AI tool helping creative side.

[00:44:39] Vic: And right now I think there's a lot of, I mean, you're in the space, but my interpretation is there's a lot of taking what humans have done For years and doing that faster, cheaper, more reliably, um, maybe with slightly more depth. But I think there's going to be a time when Batham and [00:45:00] others can start to learn from the feedback that your health systems are getting from payers and whether you move into denials or you just sort of feed that back into the algorithm development to start now coding it slightly differently to optimize the revenue as opposed to optimize the amount billed.

[00:45:20] Vic: But what else is the right care about is how much cash they're getting. And then simultaneously, your friend and others will be doing the same thing on the payer side and trying to that's where the arms race comes in. They try to catch up. 

[00:45:33] Talha Haseen: Yeah, exactly. I think it's it's I feel like there's money to be made in the arms race.

[00:45:40] Talha Haseen: As in all our 

[00:45:43] Vic: picks and shovels at a gold bar. Probably better calling you a Selling, uh, picks and shovels and serving drinks in front of the gold mines, then being an armed or, you know, arms dealer. So 

[00:45:54] Talha Haseen: yeah, exactly. Uh, I, it's going to be a, I think you're, [00:46:00] I think you're right. I haven't seen, at least from, uh, I've seen the same level of like panic around or not panic, but concern around like denials.

[00:46:08] Talha Haseen: And because I haven't seen a change, I, my sense is, oh, the payers haven't released, you know, the AIs. It'd be much, much more, much more panic and concern in people's voices if there's like some deep learning model that was denying them. 

[00:46:22] Vic: Definitely. Um, okay. And then given this pace of change is really fast, how do you keep up with things yourself?

[00:46:30] Vic: How do you stay abreast of what's going on? Are there's. Are there podcasts or maybe a newsletter you read or something that you can feel around? 

[00:46:39] Talha Haseen: Yeah, your podcast. Oh, good. That's definitely one piece. If you're listening to this, 

[00:46:44] Vic: they already have that. So, uh, yeah. 

[00:46:48] Talha Haseen: Well, that's to reaffirm the decision, I guess.

[00:46:50] Talha Haseen: But, uh, other than that, there's, uh, there's a couple of great newsletters. One's called, like, TLDR. It's all tech overall, not just healthcare. I like that one [00:47:00] because it You can see a lot of things that are that are tools that are being built up that you can, you know, very easily see, Okay, this would be applicable in health care because of X, Y, Z reason.

[00:47:11] Talha Haseen: Um, the other thing that I that I like to do is keep seeing, um, how the effectively our government's reacting to AI as well, because, you know, in changes in legislation, there's a fairly substantial piece of AI that and media just commented on the other day that was released. Okay. By the Biden administration.

[00:47:31] Talha Haseen: And, and there's some interesting things there to keep, keep in mind as well. Um, funny enough, I think the easiest way, uh, has been to do it as like, no, one's really like at the bleeding edge of it. Unless maybe you're like a Sam Altman. That's happening to talk to like, you know, NVIDIA CEO about the new chips that are coming out.

[00:47:51] Talha Haseen: So you're probably not missing that much. Um, uh, 

[00:47:56] Vic: we're late adopters in healthcare. So. We, I think what [00:48:00] happens is we will watch how, uh, how consumer tech works and maybe how, uh, financial services or the, the mag seven big software guys are doing it, and then once it gets sort of some of the bugs out in his.

[00:48:14] Vic: really much more reliable than healthcare will adopt it. And so monitoring that and sort of seeing things out of the horizon that maybe are still kind of a little bit of a science project, but, but watching it evolve, I think is what. 

[00:48:29] Talha Haseen: Yeah, exactly. I pay attention to, or try to, at least is like, uh, funding rounds, like the, the Cuventa series, just, just because I almost treat that as like, okay, here's money.

[00:48:39] Talha Haseen: That's going to subsidize a pilot at a bunch of systems that will try something new. Uh, so it's worth, worth, worth, uh, at least looking at that. The other interesting thing, I feel like this is probably a little bit less relevant of staying in touch, uh, but also how folks have been talking about, uh, public markets going into the end of [00:49:00] 2024 and into 25 effectively.

[00:49:01] Talha Haseen: Like, I think it was like a big Goldman Sachs report about it being like, you know, depressed returns and whatnot. I work. I. Yeah, I think about it there too, because that type of news can't be encouraging, you know, the Q ventuses of the world to say, Oh, we should IPO in 25. Uh, it's just not setting up like the wind.

[00:49:21] Talha Haseen: I mean, maybe it's still, I don't know for sure, but I try to try to keep a lens there as well. Like what's the, what are the broad Stokes here? Are 

[00:49:30] Vic: there other countries that you think we should pay attention to? Like I'm trying to Watch, uh, the Middle East because I think, um, Saudi Arabia and UAE are doing some interesting stuff.

[00:49:40] Vic: China, of course, is always interesting, but they're hard to get any information out of. 

[00:49:44] Talha Haseen: Yeah, but you can get information. You just don't know if it'll be fair enough. I think there's a, there's an enormous amount of investment happening in Saudi, uh, and the UAE. Um, I actually have a, a really good [00:50:00] friend of mine who went to undergrad at Vandy with me, uh, who's, who's from Saudi and is, is, is provided me with like some really interesting views about, you know, how he thinks about the kingdom and the direction they're going.

[00:50:11] Talha Haseen: Um, but they're, they're spending an enormous amount of money to effectively, you know, shift their economy and AI has been a pretty significant driver of that is like recently. Um, I, there is, but from like a purely AI perspective, I feel like everybody's like a standard deviation behind the U S at the moment, like the chips.

[00:50:32] Talha Haseen: The talent, the, the, the ability to, to push it. So there's that I do think about like, what will happen from a going into 25 and well, we're going to change in administration and whatnot, what's going to happen that might happen in Europe might happen in the Middle East. That may impact us as, as an economy in general, you know, second order, third order impacts, but.

[00:50:54] Talha Haseen: Uh, but I think from an AI development perspective, unless there's, there's a, [00:51:00] we put a structural barrier in place to not allow companies to invest or move as fast as they're wanting to, uh, it feels like paying attention to the domestic pieces is a more valuable. 

[00:51:12] Vic: Yeah, I think that's right. I mean, I think you're right.

[00:51:14] Vic: We have the, the, um, hard technology, the chips. We have the talent, uh, kind of the software engineering brains, and then the financial markets too, are, are, uh, much stronger, much more risk tolerant here where you can have massive amounts of startup investment happen, which, you know, a lot is going to fail, but, but it's still that like creative destruction, just like, The American economy is incredible.

[00:51:40] Vic: I sort of keep going with that. 

[00:51:41] Talha Haseen: Yeah. And it's like such a, I'm, I'm much more naturally like an optimist. Like I'm willing to try something like even personally, like I actually think I scare my parents or I used to, uh, with that habit, but it's just, it's great to me because it's, you know, As long as you don't take those things personally as like a, as a [00:52:00] economy, it's like, that's what you need to do.

[00:52:02] Talha Haseen: Uh, like to, to keep 

[00:52:04] Vic: iterating as a, as an economy. 

[00:52:08] Talha Haseen: Yeah, exactly. Like I, I, like I, there's that big, um, GC acquisition of, uh, SUMA. Zoom. So basically like a, you know, private equity or vc, an allocator buying a hospital. I'm still, yeah, it's crazy. I'm 

[00:52:25] Vic: excited to see what they do with it. It's gonna be fun to watch.

[00:52:27] Talha Haseen: Yeah, me too. I, I'm, I feel like that might be one of the first places where they try to just be like, every administrative task needs to be done by ai or like, if it can be done by ai, it needs to be done by ai. Right. Uh. So I'm interested to see if they go that, that extreme and, and when they do, but. 

[00:52:45] Vic: Yeah, I think you and I can learn a lot from that.

[00:52:47] Vic: Whether it all works out or not, General Catalyst will be brilliant or not so brilliant, but, but we'll get to watch and learn, uh, from the side. Yeah, I think they're 

[00:52:57] Talha Haseen: doing okay. 

[00:52:58] Vic: Yeah, yeah. [00:53:00] 

[00:53:00] Talha Haseen: I mean, it'll be all right, but a couple of good investments, uh, especially with the AI stuff. Right. Yeah. So yeah, 

[00:53:07] Vic: they're, they're great.

[00:53:08] Vic: Oh, thanks for doing this. Uh, before we go give people a hand off, where can they find you? Um, maybe a website or the Fathom website or LinkedIn, uh, where, where do you, where are you? Hang out. We're safe. Yeah, 

[00:53:20] Talha Haseen: absolutely. I think Fathom, fathomhealth. com would probably be the easiest place and direct place to find me LinkedIn.

[00:53:25] Talha Haseen: Obviously, you know, tall has seen can. Find me there. Other than that, uh, I met Frothy Monkey in Nashville a lot, so. Nice. 

[00:53:33] Vic: Which, which one? Uh, like 12 South or downtown? Yeah, 

[00:53:36] Talha Haseen: yeah, I like going to the 12 South one. I'll just go there. It just gets so busy though, so you gotta pick and choose when, when and where.

[00:53:43] Talha Haseen: Yeah, 

[00:53:43] Vic: now, maybe like twice a week, so, but, but. How do you? Yeah, 

[00:53:48] Talha Haseen: no way. Is it? Yeah, that's great. Is your office? Do you have an office downtown 

[00:53:52] Vic: downtown right near TPAC? And there's a frothy. Okay. 

[00:53:56] Talha Haseen: Oh, that's perfect. Yeah, that's a great location to Yeah. 

[00:53:58] Vic: Excellent. Well, I'll put [00:54:00] this information and then I'll catch up with you and get the TLDR link so people can have the link to to your website to fathom website and your LinkedIn and this newsletter in the show notes in case they missed those.

[00:54:12] Vic: Goodbye. Transcribed But thanks for doing this, really appreciate it. 

[00:54:15] Talha Haseen: Yeah, absolutely. This is great. Thanks for having me.