Why Lab Test Ordering Stalls Outside the Clinical Workflow
A better diagnostic test still has to fit the visit. Tucker Marcheso explains why laboratory adoption starts with the ordering process clinicians already use.
MedTech · Stage 3: Discovery to Proposal · AI & Data
How can laboratories make test ordering easier for clinicians?
Tucker Marcheso says laboratories need to fit ordering into the clinician's existing workflow. His approach connects the lab once, standardizes requisition forms and presents information against criteria the provider has already agreed to use. Start with a routine task or pain point, remove manual entry and keep the doctor in control.
A clinician can agree that a laboratory offers a useful test and still never order it. The problem, Tucker Marcheso says, is often the work between that decision and the order: leaving the chart, opening another portal and entering information again. Better science does not remove those steps by itself.
Tucker is a co-founder of XYGene. He spoke with host Terry Coutsolioutsos on the Zero Friction Podcast about connecting laboratory services to clinical workflows. His team came from finance and insurance, laboratory ownership, laboratory science and urgent care. Their starting problem was that the people surrounding the patient needed one another's information but could not easily share it.
Why does another portal stop a useful test from being ordered?
Tucker describes a provider who has already agreed to use a laboratory's test. The lab then asks that provider to navigate away from the task at hand to access it. That extra movement is the obstacle his team wants to remove. He says the clinician should be able to stay in the environment where the visit is happening.
His example is a chart appearing on the doctor's screen. The software reads relevant information against criteria the provider and laboratory have already agreed on, then presents an ordering option. The doctor decides whether to order. Tucker stresses that the system is presenting an agreed process, rather than telling the doctor what to do.
That distinction matters to his approach. The lab's offer has to become easier to use without asking the clinician to surrender control of the visit.
What should be standardized before adding more laboratories?
A provider working with different labs may face different portals and different requisition forms, Tucker explains. Even when each form serves the same purpose, the provider has to learn another way to complete it. His team digitizes requisitions and creates common nomenclature so that ordering feels consistent.
He describes a doctor who wants to switch labs after a service problem. The intended experience is to choose another option without restarting a long integration project. The provider should be able to change the available test menu as needs change, rather than treating every addition as a new technical undertaking.
I need to be able to prove I can save them time.
Tucker Marcheso
Tucker uses urgent care as a practical test. If a tool will not work for a provider in that environment, he questions how useful it really is. Removing manual input is the concrete measure he keeps returning to.
Who should carry the work of connecting the lab?
Tucker says laboratories are typically his clients. Providers are already overburdened, and adding a new cost to their side would create another adoption barrier. He describes labs paying for individual integrations before knowing whether a new relationship will generate orders. His model is intended to reduce that repeated effort.
The key integration, he says, is with the laboratory information system. Once that connection is understood, his team handles connections to the lab's other partners. He describes this as changing the lab from a one-to-one relationship with a portal into a one-to-many model.
The lab can also present the service under its own identity. Tucker says the team does not want another vendor name confusing the provider relationship. The laboratory remains the organization the provider knows, while the infrastructure works underneath that relationship.
Where should a laboratory begin an implementation?
Tucker does not propose changing every process at once. He asks a lab for a pain point or something it does routinely, then starts with a small set of tasks. The team works with the lab to learn what its providers like and improve the user interface around that feedback.
He describes a light entry point in which a clinic can start ordering through a downloaded tool. Further work can remove manual steps, such as reading relevant information from an open chart and populating the requisition. More extensive integrations are possible for organizations that want them. Those are different levels of involvement, rather than a requirement to do everything immediately.
After the process works, the lab can add tests to its compendium. Tucker's aim is to reuse the established connection and ordering language. Expansion then builds on a process providers already understand.
How do you make complex results useful during a visit?
Getting an order to the lab is only part of the workflow. Tucker describes providers receiving a 56-page genomics report. Even a clinician who understands the material may not have time to read that much repeatedly during the day. His response is to ask what information the provider needs for the decision being considered.
The full report remains available. The system brings forward the information the provider previously identified as useful. Tucker says the work begins with the provider, the ordering company and the laboratory agreeing on the current process and how to simplify it.
He also describes shared visibility into whether a sample has reached a machine and whether results are ready. Rather than calling the lab for a status update, the provider can look. That is a specific administrative task he wants the connection to remove.
What role should AI play in the ordering process?
Tucker describes his company as a process business. Its AI work is aimed at making routine actions faster and reducing the time spent passing work between people. He calls the tool an assistant rather than an agent, with the doctor remaining in charge.
Trust is his larger concern. He says clinicians need to rely on the information being delivered and understand how it fits their work. Talking only to executives about adoption does not answer whether a doctor will use a tool during a visit.
For a laboratory assessing this approach, Tucker's examples point back to observable tasks: ordering without leaving the workflow, reducing repeated entry, seeing sample status and finding the relevant part of a report. The proposed value comes from making those tasks easier for the people who actually perform them.
Where this fits: stage 3 of the revenue funnel, Discovery to Proposal. Read what revenue friction is and how it is measured. See how RevRx AI works with MedTech teams.
Full episode transcript
From the episode captions, lightly cleaned. Speakers are not labeled, and the text may contain small errors. Time links play the episode from that moment.
0:00 We're the front runner for a $50 million grant. The biggest problem that I think exists is interoperability. We kind of wanted to figure out a way to get away from the EHR cartels really be able to provide the best of science at the point of care. The day changed for me when Patrick, the laboratory owner, said, "Do you know that you could actually choose your own lab? You can order a pizza more efficiently on your phone than a doctor can order a lab from a specialty lab." If you could go back to 22-year-old Tucker, what is the one piece of advice?
If it matters, it's not going to be easy. However, you should align yourself with the things that you're passionate about because that will make it feel not so hard. In medtech, the difference between a good quarter and a great one isn't always the product. It's the friction standing in the way. Broken sales cycles, misaligned teams, deals that stall at the finish line. Every leader feels it. and the best ones know how to remove it. Welcome to Zero Friction, the podcast where we go inside the minds of medte's top commercial leaders to uncover the real barriers they face, the decisions they make, and the systems they build to keep the revenue moving.
I'm your host, Terry Coutsolioutsos. Let's remove some friction. Welcome Zero Friction Podcast Nation. What a great day we have today. I have a phenomenal guest, Tucker Marcheso, and he has a phenomenal company and platform. It's XYGene and it really is about providing the best of clinical science for the point of care and primarily the laboratory arena. And so with that, I'm going to turn it over to Tucker real quick and he can give us some background on his history and and he's got a really interesting team that he's put together as co-founders and um and tell us a little bit about the company, their mission, and what they're going for. So Tucker, welcome to the show.
Thanks, Terry. Uh so hi, I'm Tucker Marcheso. I'm uh one of the co-founders of XYGene. Uh I am one of four founding partners. Uh we fix boring problems. So essentially uh we got our start. I've been uh in the world of finance and large insurance companies, CMS, Medicare. Been doing that work for almost two decades now. Uh that was kind of my inclusion into our team. But really what makes us interesting is each four of us, myself doing that work. uh one of my partners being a laboratory owner, one of them being a laboratory scientist and director and the other one being a provider in urgent care. We got together and we commiserated about uh how around the patient all those things matter but none of them talk. And so that's really where we spent the last eight years and all of my hair uh trying to figure out that problem to fix. So uh today we we have uh an interoperability platform. We kind of wanted to figure out a way to get away from the EHR
2:49 Cartels uh and really be able to uh provide the best of science at the point of care. Um I think that that's what's what I want from my provider when I sit down to a visit. My provider wants that to be able to help me during a visit. Providers and ordering physicians and and pharmacists, they got rough these days. So, you know, any little bit any little bit helps. So, we came from the process side. So from we are the people dealing with the problems on a day-to-day basis, not some kind of, you know, ivory tower looking down on the industry and thinking that we know best.
This is really a labor of love. So it's something that we did in order to free up our lives so that we could go home at a reasonable hour at the end of the workday and to at the end of the day help our our families. You know, our families need care and right now we want to be able to provide that. And if I'm going to wait for our industry in the medical to figure it out, it's another 20 years. I I don't got that kind of time.
I know. You know, it's it's funny. I I talked to a lot of founders in the medtech and the health tech space and you guys all have such a great purpose and intent around it and it's all around providing the best care. Lab is certainly a very interesting business, right? So, you have multiple different stereotypes or different types of points of care with lab. You have clinical points of care, you have at home point of care, you have laboratory point of care, you have hospital system point of care. And so, you know, how does this interoper interop interoperable system that you have, how does that work? How does it connect everything together?
Yeah. And and so that's that's kind of the the rub, right? I would say that at least in this country and and other countries that we talked to as well, interoperability is the problem. Everybody wants to be the solution, but I don't believe that you can do healthcare by yourself. I think that if I'm any company, doesn't matter. Uh if I'm not willing to meet them where they're at, then what I'm asking them to do is agree that I'm the only one that's right. So if I'm a big health record system or an LIS system, laboratory information system, or any other kind of system of record, I need them to just do their job. It's in it's in the name.
You're a health record system. be that the interoperability about like let's make this real to your listeners. When you go to your doctor and your doctor needs to uh refer you out to a specialist or maybe you moved states and now you have a new doctor, how easy was it for that doctor to get your medical records? Not easy, not fun, right? So essentially what we've decided is there needs to be a way that without having to go through this big cartel mob of of these really big companies who are demanding that you use them at a very high premium. We're saying well what happens if my doctor wants it and they need it now and they just need a simple way to do that without having to bear a big expense or a big lift technologically actually how do I get it so that the doctor has to do less and get more. So really what we've done is we kind of created an infrastructure. It it's it's new. Like everybody got so
5:47 Used to these boring problems being just the way it is and and everybody knew that there was a solution. It's just it felt too big to go after. And look, we we knew that when we went into this it was a it was a long road and it's still a long road. But but we've done it right. We took the time and now what we've done is we wanted to agree that not everybody's the same. Not no lab is the same. And we actually started our company because we got really frustrated with labs, bad laboratories. You know, I always joke that in every, you know, super villain movie that you see, they're always wearing a lab coat.
There's so much bad business out there. And there's the day changed for me when Patrick, the laboratory owner, said, "Do you know that you could actually choose your own lab?" And I was like, "No one's ever offered me a choice." You know, and and I I got frustrated because like then I started wondering, "Well, who's better? you know, who can give me a better service, who can give me a better quality diagnostic. And that's really what started getting me uh interested and involved is that, you know, consumer choice around great science, Terry. It is like Star Trek out there. Like the stuff I get exposed to every day, it's miracles of medical science. Problem is is that my doctor can't get it and and that bothers me. So, like I want to make sure that when these great advancements happen and and that they are easy to be able to access if they had a way to do it and a competent way to utilize it, I
Mean, that's a better world. I want faster testing. I want more people that are involved in in things that are going to advance science and and and like save their lives. I mean, you know, sometimes these things are not only just process problems, but they're expensive, right? like you get in the world of oncology and you're making, you know, early guesses around things, you know, versus getting some testing that could be done that could save tens of thousands of dollars in a month and maybe even save a life. So, like those are the kind of things that get my wheels turning, right? In laboratories, everybody wants precision diagnostics, but nobody's talking to the laboratories to get them involved, which doesn't make sense to me. So that's really where we focused is, hey lab, I'm going to help you get your science into a provider's workflow.
I'm going to do it in a way that's going to make it so that they use it and they adopt it and it doesn't feel cumbersome. And then at the end of that, we're going to deliver your science in a better way that gets reimbursed because that's the other thing is with insurance companies getting involved, laboratory reimbursements can be pretty low. Like some of them are 30 and 40%. And they could be a great lab, but if your doctor doesn't use it, then that great lab might go away. great test might go away.
8:19 So that's the world that we live in and that's the problems that we're trying to solve. Well, it's really interesting because you know you think about lab testing and lab diagnostics whether it's for human or or animal health or anything along those lines. I'm sure that you know when I was working at Seammens it's got to be above 85 or 90% that there's not a diagnosis being made without some sort of lab test. Right? So virtually touches every patient that has something going on that needs further diagnostics. number one.
Yes. And then absolutely and then you think about like you know let's talk about friction that's the name of the sort of the podcast. So you know we talk about you know what we like to talk about is you know the first part of the friction is what is the friction that you're trying to solve for clinicians. And so some of the things that are interesting to me, you know, you have a provider angle and then you have a laboratory angle, but I'm going to start with the provider angle because that's really the point of care and that's frankly where there's a ton of friction that goes on in terms of, you know, outside the lab test, you have a doctor's office or a clinic or an urgent care center or some some sort of type of care setting. For the most part, you have other things happening. you have other things getting in your way, whether it's physical or psychological.
And then my understanding is you have a platform that allows, you know, that clinician or caretaker, that caregiver to sort of focus in on what's going on with the patient and then have sort of a menu in front of them in order to sort of allow them to focus on getting that diagnostic test the right way. So, can you tell us a little bit about how that would work? Yeah. And and you hit it early on, you know. So, one of the big things is that we're agnostic to any system of record, right? So, whether it be at, you know, at your doctor's office or pharmacy or or a vet or shoot, even your mechanic, doesn't matter, right? Uh what we wanted to do is we want to talk together. We're plumbing. So, let's let's just paint this like it's a real visit for somebody, right? So, let's say I sit down in front of let's say you go to your doctor, Terry, and you're sitting down just for your annual exam and uh
All of a sudden your record pops up onto the doctor's screen. What our software does is the first thing that doctors got it rough right now, right? A providers, any ordering provider has a very difficult time right now. First thing I would tell you, go thank your doctor, right? The next thing I would tell you is is that in they have a limited amount of time, but they're trying to do as much as they can in that amount of time. And what all labs and diagnostic companies are trying to do is they're saying, "Doctor, I you've agreed that you want to use my test and it's better." The problem is I'm asking you to navigate out of what you're doing in order to access it. That's tough. So, we die on the hill that I don't want a portal. I don't want the doctor to ever leave their workflow or the provider leave their workflow. So, what we do is we live in that environment. And so if
11:08 Terry, you're sitting down at your doctor and all of a sudden your chart pops up based upon what the doctor wants to be able to understand about you and what uh the laboratory's agreed to do, we can read the relevant information on that and qualify and authorize an order based upon the criteria that is already agreed upon. All we're doing is we're just presenting it in a fashion that just says, "Hey, uh, Terry takes these medications." And because of that, maybe he qualifies for this test here. They qualify. Would you like to order it?
Yes. And then in that scenario, the next thing that normally happens is either the doctor manually inputs it or they give it as a test to somebody else to input it. And so what then we've done is we've uh digitized what's called a requisition form which is their ability to order the test and we've created common nomenclature. So the uphill battles that doctors have right now is their portal ititis. They have vendor fatigue. So if I got six different labs and I'm using six different offer they're asking me to use six different portals, six different requisition forms and none of them are the same. So I create a common nomenclature so everything feels the same and then they can you know change. So let's say that hey I I don't like the service of my lab. Uh I want to try somebody else that does this. Great. Without having to go through all the months of integration all and all the expenses it's just choose the other one and here's your option. Business as usual. Labs are like
Scrubs to doctors. They don't they don't want to think about them, right? They just want to they just want to use them and rely that it's going to be utilized. So from the doctor, what we're passionate about and we spend a lot of time here and it's really important for uh us that we work with doctors like in urgent care like if if he's not going to use that in an urgent care environment, well then how good am I really? I need to be able to prove I can save them time. So I'm removing manual process.
I'm giving you alerts when they want it, how they want it because you know 30 years ago there might have been 50 things that they had to think about during a visit or potentials where now there's thousands. And so as opposed to them not realistically being a machine, I am presenting them with things that they could have missed. So for me, the patient, it's better because I I'm getting more diagnostics on me. For the doctor, it's better because, hey, I might have missed something that could have been important or difficult for me to do. And for the lab, it's important because they want the ability to uh get more volume on their samples so that they can reach more doctors with good testing. And so that's kind of what's really important to us is I need your doctor to be able to have good access that can change by their choice, be able to add and change their compendium when necessary, and then if something cool
13:51 Comes along and they want to know about it or add it, they have that ability to do that without having to go through all the literally months to years worth of adoption and uh headache of of new new. It it's it's almost like an Amazon, you know, uh shop, like a PayPal kind of service where, hey, I want this. It's in front of me. You got You can order a pizza more efficiently on your phone than a doctor can order a lab from a specialty lab. And so, so your your ideal customers are clinicians and hospital providers as sort of like that that that target profile. clients our clients are typically the lab right so we uh because providers are overburdened as it is right and it's a it's a huge barrier of entry so where we do we came from labs and really what we were trying to do is fix lab problems which was how do I get labs have a tough they are say if I want to get a new doctor to use my stuff I'm
Going to have to pay you know 15 $25,000 for integration a one-time integration that's birectional with no guarantee that they're even going to order anything on the test. I just saw that happen on a very large scale where a very big lab went with a very large uh organization. It was a million dollars for a a one-off integration that was birectional. And what happened is that they couldn't get the volume turnaround quick enough to support it. And now the lab is no longer right. That is very common. Labs bear a lot of the cost, but they're on thin margins, you know. So what happens is is that we incentivize the lab in a way that reduces the lab's cost and we just come out of their their uh consumer uh cost of goods and services. So we we kind of are we tried to create a win-win environment for everybody. So doctors not burdened with cost uh we remove manual process the laboratory we're increasing their volume and getting them an easier access out
Into the industry because now they're not competing on the same thing everybody else is competing on. And then from the pharmacy at the end of it, like if there's therapeutic decisions, well, the pharmacist is the last to know and they have the least amount of voice out of everybody. So what we're doing is we're giving them a true line of sight interconnected. So everybody wins, but mostly the patient because you end up getting better care. And so this is like an app that would go to the clinician in their office or on their iPad or you know how how does that work?
Yeah. So so we have a couple levels just depending upon their interest. So the lightest lift that we would do is like if I was a lab and I wanted to get somebody used my tool uh we call it the XY Genie uh you know so it doesn't exactly grant wishes but it's close. So what what it does is we can drop that in and they could literally uh download it in I don't know a minute they could order a test if they wanted to you know dial it in for more clinic that is the clinic can download the app on Okay. Got it. into their practice. Got it. Yeah. Uh it but then ideally you know what we'd want to do is start removing manual process. So day one we could we could order a test you know a week maybe two weeks depending upon how quickly they work we can say well listen what do you want it to do. So then we can start to read screen as it comes up like the
17:04 Chart uh depending only the stuff that that makes sense. That's why we're really careful. What do you want? What do we need to get nothing else right? What do we need to get out of that? And so that way we can start populating stuff. So we can now remove some manual process. So now they're not manually inputting. The best case scenario is that we can do full integrations and sometimes we do. Uh so if I'm a hospital system and I want to fully integrate the system, awesome. I don't even need to have uh the patient up on my view. I can now scrub the entire patient list to find out who qualifies for things. So that's really helpful for people that want to do like campaigns. Uh so maybe your state initiative just opened up biomarker testing. you want to find out who in your uh who qualifies, we can scrub your entire database and present it however it is that they want. And the stuff that gets really exciting then is
If we're interconnected with multiple places. So the laboratory, the doctor, maybe even the pharmacy. Now what happens is something really cool is I'm getting real time data for the first time. Uh medical data really goes off of about 90day old payer data, you know, so they're always looking backwards where I'm near real time. So as the order happens, we know about it. As the result happens, you know about it. When it's on the machine, I know about it. Every step, it almost creates like a blockchain that's visible by all parties in the gnome. It's it's it's uh it's helpful. Okay. So, if you're a lab, whether you know, if you're clinic or a vet clinic or something like that, how does this work in terms of like if you're the one ordering? Like that's what I'm trying to kind of get to. Is it like, you know, is it sort of menu driven? you've already like the clinic and and the lab have already agreed that they have a relationship, right? So,
There's already there's already technology in place. There's already processes in place. They're already like manually ordering these tests of some sorts, right? How does this now kind of come in and make everything more efficient, more effective, more precise, smarter? So, and this is me talking to the lab. Yeah. So if if I'm the lab, so the laboratory or the the laboratory information system is the one true integration I need. I need to understand their system. What's attractive to labs is that I'm no longer they're no longer a onetoone with a portal. They're now a one to many. So I integrate with them one time and then I in I do the integrations with all of their other parties out there. So they're not hitting, you know, $15,000 chunks to get a maybe on on people ordering in, you know, 8 10 months later. Uh that's that's a hard lift, right? So from the from the lab, we we try to follow the incentive of the lab. We work on like a transactional basis up to a SAS model.
19:49 So that way uh because trying to do everything at once is difficult for any you name it, it's always difficult. So we always like to Yeah. So we always try to take the uh the land and expand approach. We say great either give me your pain point or give me something that is routine for you because and let's start with a couple of things. Let's get your providers to understand what they like. So we constantly work with the lab to improve the user interface. So uh we're working almost like a partner with the lab. So the lab is representing as themselves. They don't necessarily represent XY. They white label who it because we don't want to confuse anybody with vendors in the room. I'm Intel inside, right? So, what these guys are going to do is we're going to say integrate with us one time. Help us understand what your network is of who who's ordering for you, understand the process of it, refine the the the requisition form in order to be able to
Create common nomenclature, and then let's see how much work we can take off your provider so that when somebody qualifies for that, do you have a great relationship with them? We want no one a to steal your business and b because everybody's competing on the same stuff. So if I'm embedded into what they're doing and every time that somebody qualifies, they think about your test. You just want a lot. You're now sticky. So So it's it's really that simple. After that, it's just uh how many more tests do you want to add to a compendium and that's simple. Once it's done, we're not reinventing the wheel. We're just adding lines. So you're basically building relationships at the lab level from a technology operating system perspective and then that's sort of the center of the wheel and then the spokes are just out to the providers and the clinics where this technology is enabling the the the end user the the caregiver to order the appropriate test
As well right and and I did you know when I was talking to to Patrick your other your other co-founder like it sounds like the menu kind pops up, you can actually build a menu that's sort of smart. Yes. On the patient. Yeah. Um, which I think is something that, you know, was really remarkable to me that, you know, it it's feeding off the record off whether it's age or demographics or whether it's a pharmacological regimen that they're on that you'll have a menu of tests that pop up based upon that that patient's status or standing.
Correct. Absolutely. And it's it's important because you know we're we compliance is everything right. We have to we have to be right. The doctor is always in the steering you know they're we're never telling them what to do. We're never guiding them what to do. All we're doing is we're presenting what they're already doing. They've already agreed with this thing. The laboratory and them already have this agreement. We know they tell us what it is that they're looking for and how they want to get that. Um what's what's important you know as science is progressing like we've cracked the genome now and and the world of genomics is growing constantly and your provider has can barely keep up with their standard workload let alone learn about the newest hottest thing in genomics right so a lot of providers are also struggling now because they they're trying to find ways to stay competitive and uh so for example if I go to my doctor and I want a genomics test of some sort and they needed to order that
23:05 But they don't they don't have the confidence that they know how to interpret it or to do something with those results. Like if it comes back as a 56-page PDF result, even if they did know how to do it, they don't have time for to read through 56 pages, how many times a day? It's it's not realistic. So, what we do is we work with the provider and the ordering company, that's what's important about this, and the laboratory to discover, okay, what did we already agree to? What's your way that you do things today? And then how do we just take that and simplify the process? So now order I've uh qualified and authorized the order. I've created a digitized requisition form that self-populates. You you agree to things.
It goes to the lab. You now are reducing your cost on your services for people calling like, "Hey, is it on the machine? Is it been resulted yet?" They just look it's it's on there. If they want to see a reference, hey, it's hit the machine. Hey, it's been resulted. Here's the results. So you get a full line of sight both ways. That cuts down a lot of soft costs and calls. The next thing that it does is that when we're when it's when when it's been resulted, then if it's something complex like a genomics, I can just say, "Hey doc, out of that 56 page report, what would be important for you to know to make a medication therapy decision, for example, like instead of 56 pages, you can still have it, but you told me that out of that 56 pages, you wanted this information out of it." And I just float that to them. So, I do that in a way that makes it digestible time-wise, uh,
Resource-wise, and education wise because, and you're in this field, Terry, like you AI, everybody's arguing that, oh, AI is going to solve these kind of problems. And, and it that the reality isn't that the technology is not there necessarily. It's trust, right? That the tr the providers need to know that someone's got their back, right? And that they're not going to, hey, I want to provide good care to my my patient and I have these things, but I need to know that it's real good information. and I can trust it. And so that that is that habit that we really have to start getting into because if technology was the answer, our problems would have been solved 20 years ago, frankly. So I think that for our stake, we're trying to put more provider power back into that by giving them a trusted resource with easy access that is staples easy button, right? They just want to be able to, hey, I I need a a fast, efficient way that I can trust
That I can give my patient better care. And if something comes along that's better, I want the option to choose. So the choice is one part two. I think it's great value to that you'll have a wider, you know, you're you're the Amazon of lab testing. So you're creating access to all these tests everywhere. The other piece is is you have the operational efficiency aspect of it. you have, you know, a precision med medicine component that is potentially being delivered because your your platform understands the patient will pull up a menu that a a recommended menu for a patient sort of criteria. So, is there is there AI baked into that?
25:57 How does that happen? I mean, you must have some AI going in there somewhere, right? Yeah. So, so we're kind of a few different components. So, we have a backend, right? So, our backend is really housing all the stuff and and making the sausage. Uh then we have the middleware. So most of what uh we're talking about today is the middleware like what is the plumbing this stuff we concentrate heavily on the front end but AI is the way so we're not the we're not the brains right I let the brains be the brains I am the transmission of the neurons right so if the AI that we use is really around process we are process company all I'm saying is I want to build efficiency of process so as the provider let's say that they start using it and gain some habits because of routine testing. They do the same kind of stuff. The the tool may build some efficiencies around how how are you getting to those things faster or what
Can I do to be able to deliver better? Things like that. It we're more like a an AI assistant versus an AI agent, you know? So, it's kind of like your your your little medical buddy that you got into your pocket. So, that's going to say, well, look, and you're passing this work on to a PA and MA to do kind of anything. I'm your intermediate I'm your free intermediary that you don't have to to to broker that time and connection to get done. Your lab buddy with your lab buddy. It's you got a little lab buddy walking around with you all day long, right? You know, like this one this one, right?
I promise we're not like that uh that little um paper clip. Remember the paper clip that would come up? So, we won't be annoying like that. But uh yeah, we only we only come out when we're we're needed. Uh you know, the doctor's the doctor's always in the steering. We're there's just better ways to do it. I we know this because we did the work every day. Like I processed the claims or uh Patrick was, you know, trying to run the staff and Eric was trying to to feel the calls and Jeremy's trying to chase down the samples. And all of these things happen every single day, millions of times a day. And there isn't an exception. There isn't an exception.
And if anybody tells you otherwise, if you're out there and you're a hospital and like Epic does this or LabCore does this or you you name the the company, no, you don't. No, they don't. Everything else, how do they play with others? Ask ask others. So, what we're trying to do is if hey, if it works for you and you like it, keep doing it. But for everything else, uh here's a solution. And it will be a matter of time. We want to be we want to be uh the new way that healthcare runs. I just want to be the the infrastructure. I want a faster I want a faster freeway. I want I want better on-ramps. I want, you know, smoother roads. I just want it to be simple. It should be, you know, clear clear signs. You know, it should be simple. Like none of what I'm describing is complicated. It's It's not complicated, but there's so much to it.
28:48 It's daunting. And that's why it's never really been approached before. But we we took we took the hard road, right? Well, it's paid off. It's it's interesting because you know healthc care is slow and you know I just heard an interesting data point the other day from another um podcast yes I'm going to be having but they actually are helping hospital systems bring AI into the healthcare arena and I didn't really realize this because healthc care is usually you know drags their feet on many things when it comes to changes but from my understanding from this person is that healthc care is one of the top three vertical industry segments in the in in the world that are adopting AI today. Absolutely. And but you know, and I'll just say that there's a couple things going on with that. One is they're really not finding any cost efficiency in it yet. So they're they're not saving money, but they are they're finding new ways to make revenue and so they're being they're more effective
With revenue. What they're really finding is is that the work stress life and work life balance for physicians is changing because AI is just removing a lot of administrative repetitive burden. And so like they feel like the real cost benefit for AI is going to be actually employee retention and longevity because AI is creating that impact today. At least that's the early feedback um over the last 12 months on AI. It's really been a kind of an interesting topic conversation today. I had I I actually find that really interesting and and I even like the encouragement that it's retaining, you know, that the hard thing is to be able to retain talent uh throughout the industry. You know, I'll give you a second point of view, you know, complimentary to that is that I think that there's going to be a lot of things. So, look, there's a lot of money that's being spent on AI, period. And a lot of it's going to be
Really bad money because you know everybody's throwing a lot of a lot of AI at things with really no understanding of the adoption. And I'll give you an example uh like for your for your guests that you're going to have uh you know I'd be really curious you know how many doctors uh and are they actually talking to because talking to the seuite and adoption is one thing because you know if I'm looking at billing and simplifying those kind of things great but when I'm looking for a doctor to use AI because look there's tools available today there's tools being used today uh but the push back is a couple of them one of them is like I don't know if I can trust it that's the biggest one is like sometimes AI can hallucinate And you know who's on the hook? It's not the AI company, it's the doctor. Right. Right. And so they they have to be really mindful of that kind of stuff. So they're they are hesitant
31:19 To adopt. There's uh other tools that are happening like right now uh probably last time you went to a doctor, I'm sure they used it. They were probably talking into something, right? Which has some AI agency and to be able to speed that up. But if you ask a practitioner like take a guy at an urgent care, well they might tell you great, maybe the tool set that they want me to use is on my my cell phone. Well, I'm not going to bring my cell phone into a patient meeting.
That's that's creepy. I'm not going to do it. So, that's a no starter. But maybe they have a device that does that. Well, now they're saying, "Hey, uh, Terry, you came in here." So, they're talking into their device. Terry, you came in here cuz you got a busted knee. And then during that time that he's dictating, all of a sudden, you're like, "Yeah, you know what? My neck really hurts, too." Well, now that thing just picked up. Well, your neck hurt. That wasn't even on the the thing. Why didn't you mention that? So, I'm not saying that these problems aren't going to go away, but there is a lot in the middle to get the trust around this. The biggest hurdle that XYGene overcomes is really at the front end. I need the provider to trust that what's being delivered is uh is going to not only be appropriate, but they can rely on it.
It's going to it's CYA, right? I need to make sure that it's going to be good. And I think that that's going to be AI's biggest barrier. It's to be clear, there's no stopping it. It's going to be a part. It's a part today. It's going to be more a part of it all the time. It's just to me XYGene I want to be the the infrastructure that really good AI can run on. So if a doctor wants to use one or many, I can deliver I I I just move data, right? The fact that I'm I'm dealing with diagnostics is one thing, but I'm also delivering uh solutions. I work with companies, great companies that follow the documentation, right? So they're a documentation company or uh they deal with the billing or they deal with the um reimbursements. That's the biggest problem, right, is reimbursement. So, I'm creating a cleaner claim at the inception of the order, but I can also have that followed with documentation all the way through.
So, for better reimbursement, and I can even clean up the billing at the end. So, you know, we double and triple reimbursement rates. So, that can be a really powerful tool because the reality is money moves. Money moves all this, man. If it doesn't make dollars, no one, you know, it's it's not just you're you're not only creating a path for it, but my guess is you're probably the act, you know, again, like just because you're billing doesn't mean you get paid for it either. So there's billing accurately, billing appropriately is is always a great thing. And and I love AI because that's well, frankly, that's what my business is is is, you know, architecting solutions and removing friction with AI. And so that's that's why I love it. And I know it's not going away. And it's going to come fast, too.
It's not only coming, but it's coming fast. Right now, our administration is kind of letting AI kind of run a little bit, which is really kind of interesting, which is kind of fun, too. And, you know, I think once we get the there's a security component that I think people scratch their head on. I think there's been a couple breaches recently with some security issues, but like AI is going to happen. Um, whether we like it or whether we don't like it, you know, I think the one good thing that I'm starting to realize is that like I think it's going to create more jobs than it's going to take. I really believe that, you know, AI is not removing people from the workforce. What it's removing from the workload is the repetitive administrative things that get in the way of the important things every day. And what I think we're going to see is that people will be going to have higher valued work that they're doing every day and that AI is going to
34:37 Start consuming the low value, repetitive, low impact work that, you know, doesn't need to be done by a human. And that's that's what I like and I hope that's correct and I think that you were kind of alluding to that with the other guests that you mentioned is you know if we can get rid of a lot of the administrative burden and the bureaucratic burden best case scenario is I get more time with my provider. That's what I want, right? Is more time for discovery, more efficiency of that discovery and implementation of of therapy change. That's exciting. Like that's I that's the world that I'm hoping to get to is how do we start creating that environment? So I absolutely see that and I I couldn't agree with you more. It's impending.
Like there's there's no getting around it. It's just how do I make sure that I'm not washed out in that scenario, right? And so that's why I think that's really important for patients to build advocacy for themselves. Like I encourage good communication with your providers like you know use your charts to to communicate with them so that there's record of these kind of things. You know when you see them say thanks they got rough, right? like and if you like them uh make sure that that they have ask them hey healthcare is tough right now are you going to stay and if they're not do you have a continuity plan like I I like working with you are you are you hiring somebody that I I can know like or trust or should I start shopping right so the world of AI is also going to free up information to the consumer the patient and being that person uh let's say you go to your doctor's office and you know you've got
This issue and you've been on WebMD If I brought in a stack of papers and I said, "Hey, I lived with this. I spent a lot of time with this. I think it could be these things." Am I right? Be great if there is better ways as this stuff to takes on that it can digest that maybe previsit. Maybe you did come across something. Maybe it did help my doctor. But in today's world, if you give a stack thud report down to your doctor, you know, you could be right, but they don't have time to look. And that's that's a tough thing. You got people that want to help you, but their hands are tied because the system is broken.
Well, well, Tucker, I thank you so much. What a great conversation today. XYGene, everybody, they are on the move. They're bringing great opportunities for operational efficiency, for animal health, for human health at the clinic setting, providing value to laboratories, and we really look forward to great things. Before we go, Tucker, I always have one one question I ask every guest. And a guest is the guest question today is so Tucker, if you could go back to 22-year-old Tucker, what is the one piece of advice? Doesn't, you know, it doesn't need to be professional, doesn't need to be personal, just anything that you that one piece of advice that you would give yourself as a 22-y old. What would it be?
37:13 All right, I'm going to answer your question, but I'm going to delay by ask by uh one thing. Okay, I'll tell you why I got on to uh your podcast, Terry, is uh as and we brought up AI a little bit. Um I think that what's really interesting about you specifically and why I thought that this would be a good podcast to take is because you work designing AI systems and a lot with within healthcare, right? And we just talked about this like there's it's an impending thing. But what I found was interesting about you was the time that you took to understand the solution because that's I think the big difference of what's going to make AI successful into this healthcare space is that there still has to be the human element. People forget that you have to have the the the habits, you have to have the emotions, you have to have the understanding and the applicability about where the AI could fit. And so I
Think that that's something that I hope that your viewers uh they probably already understand this, but I think that that's a separation point. So as people are looking for AI relevance inside of the health care space, they need human interaction that can understand both sides. And I just really enjoyed the fact that you took the time to to understand something that was complex uh in a way that could ultimately help your clients in in your you know service the area. Well, thank you, Tucker. I appreciate that. And I totally agree. Like I've always been a a huge proponent that AI by itself is nothing. It really is. And so it needs to be it needs to be designed. It needs to be engineered. It needs to be thoughtfully sort of um put in place and then try just like anything else with an experiment. You you build, you iterate, you build, you iterate, you build, you iterate. And that's and the people that adopt that mentality around
AI are going to be the ones that really make an impact with it. That I couldn't agree more. And and the thing is is that it's saturated, you know, and so the real, you know, the a lot of bad money is going to be spent, but it's a lot of money. And if you can get it right the first time, I think everybody's happier. So let let me come back to what I was just I was actually just buying myself time to figure out the return.
Well, good. So if I was going to go back and give myself any kind of advice to, you know, bring myself full circle to today, I would say a couple of things. The first one is is if it matters, it's not going to be easy. However, you should align yourself with the things that you are passionate about because that will make it feel not so hard. I think that that would be the the hardest thing because I've tried I've worked and lived all over the world, you know, I've I've done multiple different industries and I've I've always kind of found my passion, but none of it ever was capitalized on.
39:57 XYGene is the first thing that I ever woke up and wanted to do. And I think that if I was to look back to anybody that's younger and ambitious uh and and industrious and and has a entrepreneurial mindset, I would say steal yourself early because the world is already changed and what you thought you knew that amount of time ago might not even apply today. So, you better be tough enough and interested enough to be able to catch up, keep up, and and do something inventive. But it sounds cliche, but you really have to follow that passion because you'll never be as successful. You know, it it's just a matter of whether it be monetary success or or you've helped some people or maybe it just made you feel like you completed a great project. I think that that's the biggest thing I would say and and I hopefully that resonates with anybody that's listening. Well, I think anybody that's listening or or watching the
Podcast is like they see your passion because it oozes out from you anyhow. But I would also just say in working with some of your other co-founders as well, that passion is equally generated by your team and it's so refreshing to see that as a group of you all coming together um and working very very effectively. It's been it's been a great you know been a great opportunity for me to meet some great people and bringing great technology to market. So so thank you for that. Yeah thank thank you Terry and I'll tell you I just thought of one last thing is uh I think I pride myself now as it's it's fun to be the dumbest person in the room right if you can surround yourself with smarter people and and be willing to learn. Man, that's a it's a humbling and wonderful feeling. So I I would I'd recommend it to anybody. And you brought up my partners. that quite often. I'm usually the dumbest guy in the room anyhow. So, I do that pretty well.
Yeah. So, so I think that that's that's the other thing. Surround yourself with good people, good partners. Life's life's too short to deal with people you don't like or don't respect. Well, there we have it, guys. Tucker Marcheso XYGene. Thank you so much. Appreciate it. And we'll close out this episode of Zero Friction. Have a great day. Thanks, Eric. That's a wrap on Zero Friction, the show built around one simple idea. Remove the barriers and the revenue will follow. If today's conversation was valuable, please subscribe and share it with somebody who needs to hear it. That's how we will grow this community. I'm Terry Coutsolioutsos, revenue architect powered by AI. Come find me at my website, myrevrx.com, and let's talk about what friction is costing you and your organization. Until next time, keep removing the barriers and keep the revenue flowing.
This article summarizes views shared on the Zero Friction Podcast. Statements are the guest’s own and are not medical, legal or regulatory advice.
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