Unlock Better Decisions with Data | LSI Europe '25

David Kereiakes  0:06  
Well, Scott, thank you for another great conference here. Your team has done a remarkable job. I'm Dave Kereiakes. I'm with Windham healthcare partners, New York and Cincinnati based device, software, digital health Investment Fund, growth equity investment fund. We've been around for 18 plus years, and I have the unfortunate honor to follow Henry as a moderator here, so they don't ask me very much to give me a mic and have me ask the question. So it's kind of a unique position to be in, I imagine an uncomfortable position for the other side to be in, but we a bunch of good looking guys up here, and this may be one of the most geographically diverse panels. It may not seem that way on the surface, but we have Nova Scotia, a German based in France, an Aussie in London, and the Big Apple covered here.

David Cubbin  1:12  
I'm a homosexual as well. So I take a diversity box. That's just you might you might not notice diversity, but

David Kereiakes  1:21  
just breaking the ice right off the bat, yeah,

David Cubbin  1:25  
keeping it interesting.

David Kereiakes  1:27  
On my toes, I thought I was going to be the one throwing curve balls. Well, how about we introduce ourselves? Dave, you've already done that. Please go ahead.

Justin Ramsaran  1:36  
Justin, yeah, awesome. Name is Justin Ramsaran. I'm co founder and CEO of health mosaic. It's a digital connected medical device interoperability company with a AI based powered solution for training, the next generation of AI solutions.

Hamed Hanafi  1:52  
Hamed Hanafi, I'm the one from Nova Scotia. We have a firmware company for CPAP therapy. We use AI to predict and prevent apneas and reduce the pressure of therapy, make it more comfortable for patients, improving adherence.

David Cubbin  2:09  
My name is David. I'm Australian, based in London, and I'm a partner in a German headquartered health tech venture firm. We invest in these big thematics of digitization, Datafication, automation, of of health tech and really sort of building, you know, building the system of tomorrow series seed to be and interesting. We have sort of two halves of our business, where we we we have syndicated investments for RSP vs and we recently launched our first fund targeting 70 million in areas of diagnostics, imaging and some smart, smart med tech, and, you know, therapeutics as well. Great to be here, and it's great to see such a strong a strong turnout.

Franz Bozsak  3:08  
Franz, yeah, so Franz. So I'm the German that is based in France. You know, that's the beauty of Europe, right? Thank you for inviting me onto this, onto the stage with these wonderful panelists here. So basically, when I started building Sensome over 10 years ago, the vision that my co founder and I had was, you know, can we provide physicians during mini mill invasive procedures information they can't see today, so that they make better decisions for their patients? And you know, a decade later, we've built the smallest impedes based tissue sensor in the world that I was told was completely impossible to do. We've put it into a guide wire, and we've put it now in about 90 ish patients across three indications in stroke to help physicians make better decisions about how to get the clot out in peripheral vascular intervention to help them how to prop open arteries that are closed, and then lung cancer diagnosis to help the physicians know where to put the biopsy device.

David Kereiakes  4:12  
Well, in an important topic here, $4.7 trillion is, at least in the US, what we spend on health care. It's the third largest global economy and of itself, and when you look at a global spend and health care, clearly, arguably the largest economy and far from efficient. If you've ever been into the American health care system, I imagine the European health care system. Fortunately, I have not had that experience yet, but one thing that has been missing is the light in a dark room that can help inform greater efficiencies. Prior to joining Windham, I helped run the investment in innovation arm for the third largest non profit health system. So being in a former i. A executive inside of a large nonprofit healthcare system. It was fascinating to see the reluctance, the resistance that was thrown up by all levels to unlock these unique insights, whether cease and desist letters or do not enter. Be careful what you look for. Be careful what you ask for. Kind of responses there are. There's obvious resistance here in a field that is needing great efficiencies and advancement. So we've got three entrepreneurs, two investors. I'll start with you, Mr. Coven, help me understand as a device and software investor, makes you very unique to see across those two silos and comfortable in an operating room. Give me an idea of what you are seeing from an investment thesis where you see the future of healthcare going the resistance in between. Just walk me through how you're navigating the space, sure.

David Cubbin  6:03  
So thanks very much, David. So for us, it sort of goes without saying that data isn't, and I'm sure we all agree in the room, but you know, data isn't, isn't the goal in itself. You know, we need the data to generate actionable insights that lead to better outcomes, better outcomes for clinicians, better outcomes for patients, better outcomes for the for the system as a whole. When we consider how data is is collected, how it's utilized, how it's embedded within a company, we want it to be data first, you know, not just a an add on or a tag line. We want data to be very much the center, the sort of heart and soul of of what the companies that we invest into are doing. Because, to go back to David's point, you know, the this health systems around the world are groaning under pressure, and the only way that we can get to where we need to be as a system is through through efficiencies and improvements that will be generated through data. And so as much as as data and AI are hyped, and it's important for us as investors to see through the hype, data is still the answer. And so when we consider investments in the space, we look for companies where data is, where it's proprietary, where data is clinically, clinically backed, and where it's compounding in value. So we have, we have companies in our portfolio that that are, you know, in terms of the the outcomes that they're providing, it's not just, you know, they're not just collecting data for data sake, as I've touched on, they are leading to things like predicting hospitalization five or Six days in advance. They're reducing the number of cycles that a person needs to go through and in IVF, which is an incredibly traumatic experience for for women, as as we'd agree. So, yeah, when we consider data, it really comes down to the to the outcomes. And it sounds so obvious to you know, to be saying this, and you know to be getting up on the stage and saying this, but I still sit in some meetings with portfolio companies where, where, you know, we're discussing with investors and stakeholders in the ecosystem and and people say, Well, yeah, it's great. You've got this nice technology, but, but so what, what does it do? You know, what's the, what's the benefit, what's the tangible benefit? What's the, what's the outcome for the patient? What's the, what's the figure of the, you know, the efficiency that's being generated here. How does it improve revenues? How does it reduce, you know, reduce the the variability in diagnostics, things like that. And so those are the sort of things that that we're looking for, not just nice ideas, but genuine, genuine, genuine outcomes.

David Kereiakes  9:38  
Well, Justin Hamed, Franz, I think everybody is well aware of quality data in quality data out right? And so when you are tapping into the you're Stradling both your home as well as in the hospital, tapping into antiquated systems or being depal. Independent on the data source. How are you all navigating that to enable quality data on the front end, to allow you to power up a meaningful ROI on the back end, or something insightful?

Justin Ramsaran  10:15  
Justin, yeah, I mean, the biggest thing is a lot of these antiquated, Legacy based systems you have to work with the medical device vendors, right? And that's one of the toughest parts, is being able to get that information and being able to aggregate that and pull it together. It comes down to almost being a reverse engineer to most of these things going around a little bit and trying to be cheeky in the approach, I would have to be honest, has been the approach we've taken thus far, being able to understand those nuances, but also addressing that problem of interoperability in the next generation of life cycle development of the devices, legacy devices aren't going away, right? The ones that existed. They're going to continue the life cycle management utilization of those for the next decade to come or more. But being crafty, I think, making sure you understanding the technical nuances of what data is important is the most viable portion to start off with. So again, looking at those legacy devices, integrating the data from it requires, I would say, a maneuverability and adaptability by having to, again, be cheeky in that approach of engineering for it Amen,

Hamed Hanafi  11:22  
I would like to add on to what Justin just mentioned. So we're basically trying to go from volume to value. There is a lot of data out there, but data at the end of the day needs to be interpreted in a way that's an instrument to help patients and physicians, and it is our job to basically translate that for the physician into a platform where, you know, there's, there's a gap between what the data scientists can interpret from the data and what the physician actually trusts and it wants to utilize. So there needs to be a an interdisciplinary translation here. At the same time, not all data is good data. That data needs to be collected in a good signal to noise ratio, which is what you know, I'm sure Justin is focused on, and it needs to be diverse. And it also is not there to, you know, replace the physician. It is there to be a tool to help the physician. It augments the decision making based on the, you know, the data that it's been fed. At the end of the day, the physician will use the AI to make better decisions, catch the little mistakes that it might make, because data was not diverse when it was fed and and use it as a tool.

Franz Bozsak  12:44  
I think on our end, we're really obsessed with workflow, like we're really trying to understand the workflow as much as possible. Because, I mean you, if you want to good, if you did the collecting data is, in a way, always an additional step. And it shouldn't feel like that as much as possible, right? So we are trying to really analyze the entire workflow and see, how does our device fit in there? How can we, how can we interact with the physician in a way that he doesn't change what he's doing? I mean, changing things is always about in healthcare, right? So what can we do that he doesn't have to change anything and gets access to the information that he needs anyway, right? And so this is one, is like being obsessed with workflow, understanding it deeply, working with physicians from the conception of the device from the beginning, right? And it's the same with displaying that information then to the physician. I mean, data collection is one we talked about, interpretation is the other, right? I mean, you have so many solutions today where it's already a hard skill to get the data for the physician, and then it's an even harder skill to understand it. I mean, how, how is he supposed to work with that to make any decisions for a patient, especially in a in an emergency situation, right? And so we really work with them really, really hard, day to day to understand, okay, this is what you want to know at that point in time, and this is what you're doing. Okay, you're not going to change anything. We adapt our technology around you, basically, in order to make better decisions in the end.

David Kereiakes  14:03  
How are you better? How are you doing that? Is it bringing the physicians in with you? Is it bringing the engineers to the physician? How are you incorporating that?

Franz Bozsak  14:13  
It's exactly both. I mean, we have, we have some, some, some amazing physicians that, that we've been working with for a decade now, where, basically we in our camp company, everybody and anybody in the company has to go and see procedures at least once in a lifetime. You know, from from accounting to the engineers, the only thing, because the for me, the one thing, the moment when I'm an aerospace engineer by training and and for me, when I started going down the healthcare path, for a long time, this was a theoretical, theoretical work, until I was for the first time in the or and I saw the physician, actually, you know, helping a patient that was having a heart attack, right? And that changed something in. Need made this whole thing real. They want everybody in the company to have that same experience. And then for the engineers in particular, they need to go more than once, and they need to see these procedures. Need to stand right by, right by the side of the physician and and at the opposite we also have these physicians come to us on a regular basis. And, of course, test devices give us feedback, but also, you know, interact with the team in order to really, kind of, you know that they see how they think and the other way around. And what we've what we've seen is that when once the physician also understands the technology, it's much more able to give you pertinent feedback, right? And not just, you know, this is what I do, but actually, you know, kind of guide his feedback based on the tech

David Kereiakes  15:43  
Brian Franz, you, I think you're touching on the trust right from the physician to be able to incorporate that into their practice. Dave, you brought that up earlier. I'll throw it to you too. How do you think about the investment in building that trust with the physician, or whoever is using it, and to the other two entrepreneurs. How do you think about the investment from your side in in building that trust?

David Cubbin  16:10  
Sure. Yeah, I think that's the sort of the goal here, really with with the data that we're that we're utilizing and that we're investing into. Ultimately, the goal is to build trust across the system. And so what does that really mean in practice? It's, it's, it's trust from clinicians to act to make decisions, whether those decisions are, you know, better, safer, earlier, and that's what data can do. Trust from patients to adhere to something just, you know, to certain behaviors and and then finally, trust from the investment community that a model will scale. And that's, that's really, you know, that's really what it comes down to. And so trust is, trust is the goal, and data is fundamental to building that trust.

David Kereiakes  17:12  
So Justin Hamed, how do you think about designing the studies, or how do you think about building that trust with the physician and then the potential purchaser, because they could be two different groups constructing and rolling that out in such a way that can help with the adoption curve. Yeah.

Justin Ramsaran  17:36  
Take, from my perspective, it generally involves multiple parties. You can't just have only the clinician alone. You can't always have it siloed in the other groups across the entire domain. It requires everybody's buy in on it. Specifically, when we're looking at the way we're developing and augmenting for data sets to support this next generation of AI solutions and AI training models, we've got to get a lot of data, right? You can't de minimize and just be looking at one specific data set, be it just ventilation or just ECG, you know, types of data sets, bringing those together, you know, and unifying those, structuring it, and then creating that, you know, true paradigm is going to be important, one for trust in that area, but also being able to help scale those products, because the defensibility of algorithms is one portion of it from an investment standpoint and protecting that, but also being able to ensure that the end users are going to be able to leverage it in a proactive manner for clinical decision support and making really comes down to all of those pieces being pulled together, because if a clinician is going to believe in it, you still have to have it, and many other teams support that in order to want to integrate it and not cause more friction in house. And at the same time, someone's looking for that ROI return. So bringing those partners together, having large data sets, and then being able to actually structure that and enable it, I think, is where you kind of start to see that paradigm.

Hamed Hanafi  19:00  
Completely agree. I mean, for us, double blind at randomized trials with endpoints that are the input comes from, you know, physicians DM ES and patients making sure that it hits everything, including their clinical outcome and the market outcome with in our case, we're improving comfort. How do you quantify that questionnaire while patients are blind to, you know what, what algorithm they're trying the night of but I would even step back and say, a couple of years ago, when the algorithm was, wasn't yet, you know, frozen to go into trials. We all have family members that suffer from obstructive sleep apnea. My own father has severe sleep apnea. We start our test from ourselves and our families, and then move from there. I slept with the machine myself just you know, patients are total if you use this machine, you're gonna avoid heart attacks and heart attacks and strokes. And they say, Okay, I'll put it on. I'll try it. But middle of the night, they rip it off their mouth, literally, what happened to myself, and I had promised the company that I will bring them data the morning after and I yet ripped the mask off my face to get a few hours of sleep. So really feeling it ourselves, just like you guys explained.

David Kereiakes  20:19  
So given the varying groups in this purchasing decision when you have a device or you have software, and sometimes both, in order to pull that unique insight out of a procedure or a care plan. How do you think about the varying groups that are involved in there? Right? The physician may be different than the administrative team, which is different than the IT team. And you know, having lived inside of a provider, what could be a free pilot may even cost a million dollars for the health system and the resources required to integrate that software capability to pull unique data out of of a procedure you may be bringing your own data and insight, which then comes with, how do you construct the ROI, right? And what is the meaningful ROI that you found in the value proposition that resonates with across those groups? Or, how do you think about the sales cycle? I'll start with the entrepreneurs. Whoever is comfortable with that. I give these guys a lot of credit. I didn't show them the questions for that's that's my lack of preparation here, but they've done a remarkable job. So I'm opening it up to those who feel comfortable. I'm also rambling a little bit to give you some time. Kelvin, I would also like to hear, from the investors perspective, how do you think about valuing that value proposition, and from an investor standpoint, what resonates with you? So I'll tee it up for the entrepreneurs here.

Franz Bozsak  21:56  
I mean, we've, you know, we, in our case, the primary indication that we're going for is stroke and the thing, and I think this is, this is always a bit of a difficult thing that I when I give talks to like young entrepreneurs, I always tell them, when you go into healthcare, the issue is that you know when you when as a consumer, when you buy an iPhone, it's your own money. You buy it and you use it yourself. You know, I'm not buying iPhones, though, but you know what I mean? In healthcare, the thing is that the guy who's benefiting from what you offer, the guy who's using it, the guy who's who's buying it, and the guy who's paying it, those are four different entities, right? And to kind of need to all align them. And the big secret behind this reimbursement, right? That's when you got them all on the same page. Now, what? But that is, and one thing that I was told very early on is that, especially when you think of something like stroke, I mean, there is, there is a burden on the healthcare system itself, right? But in the end, the hospital doesn't care if, yeah, for the greater healthcare system, you are saving money down the line, right? So you always need to look very locally into so if you're in the procedure the hospital needs to gain money. It can't be the healthcare system, right? And we're in the very lucky situation that that, when you just look at numbers, if the premise that we have, which is, you know, that we enable physicians to get the cloud out faster and on the first pass, that patients should do better, and that actually also has a direct impact on the hospital, because hospital stays are shorter, things like that, right? So we've been really also obsessed in trying to understand this, analyze this, and that is the value proposition with which we go in. And then, of course, you need to prove it right. But in principle, at least we, and you said this beautifully before. It's about rendering the these procedures more efficient right, and that's the pitch that we want to do. We then need to deliver on that. Of course,

Justin Ramsaran  23:58  
I'll piggyback on part of that. There a big thing I think we've noticed, at least in the space that we're playing into, is you have to really come in at this from a consultative approach, like you truly need to understand a lot of the workflows. You don't want to impede, right, what's going on clinically, and you don't want to create more divestiture and more fragmentation, if you want to say and what's currently happening in that space. So at the end of the day, I think healthcare systems, the hospitals, the facilities, they do want access and understanding of their own data, as well, as much as we're implementing new found solutions, the important thing to them is, how can they also understand what you're showing them on those reimbursements? What are you showing them in the downstream of where these applications are going to help you know the final outcomes? But granted right now, I think a big issue is there's no true visibility sometimes for healthcare systems and hospitals as a whole to understand their own clinical data, and that, to me, can become a friction point. So being able to, like we're saying, unlocking the better decisions with the data we have here, that's the true insights that help build on these models or help build. For, again, more insights downstream. So seeing the ways that we've approached a very consultative way to engaging with what's going on in your clinical workflows, what's occurring you know, with your device usage, what's going on from procedure standpoint. Can we help your Los things like that start to really create a better talk track where you're going from this kind of retrospective perspective to now a proactive approach, because you have that insight to be more forthcoming with.

David Kereiakes  25:30  
So very Go ahead.

Hamed Hanafi  25:32  
Sorry, I thought you asked what the investment perspective also about the return of investments?

David Cubbin  25:38  
Yeah, and

David Kereiakes  25:39  
thanks for not letting Dave off the hook here.

David Cubbin  25:42  
And I'm, I'm very happy to answer that. But actually, David, you're also an investor

David Kereiakes  25:49  
with an title moderator, so it goes here. So this is

David Cubbin  25:54  
not what we agreed. No, I was I, I was very happy to throw a question back at David so that he could also share his wisdom and insights to be aware.

David Kereiakes  26:06  
I'll once so. But what

David Cubbin  26:11  
was it? Was a question, ROI, all

David Kereiakes  26:14  
right, yeah, what is the real investors? Yeah, put value on the ROI itself. What resonates? Yeah, I think

David Cubbin  26:21  
I've repeated myself over and over on this point, but it's, it's, we have a portfolio of different companies, and the ROIs is fundamentally different for each company, depending on what they're doing for for one of our companies that's in the monitoring space. Okay, it's monitoring heart rate and breathing and movement around the bed. So what? What's the ROI of that? Well, you predict hospitalization six days in advance for a hospital system where you where the hospital is charged for readmission, re hospitalization, that's that makes an enormous difference. If you're if you're getting you know, you're predicting hospitalizations earlier, you're getting to people earlier, you're solving problems earlier. That is a win, win, win scenario for for pretty much all of the stakeholders, not always, not all, not always all of them, but it ticks most of the most of the boxes. In the case of an IVF company that we've invested into the ROI. So it's, it's the world's first fully autonomous sperm selection platform. And what's the ROI of that? Well, it it reduces the number of cycles that a person will need. That's a tremendous outcome for the patient. It's a tremendous outcome for the system. For sperm banks, where they have embryologists and spermatologists working there, tremendous outcome for them where they're short staffed. You look at the IVF clinics across the United States, how many of them are advertising for, for for senior specialists, pretty much all of them. There is a massive shortage around the world sperm. I hate to say it, guys, but we are responsible for 50% of the problem here of infertility. This is not the women's fault and and so in terms of, you know, in terms of being able to, really, to automate the process, to diagnose and automate together, tremendous ROI for everyone in the system, you know, I can, I can go on and on, but it just, you know, depends another company we've invested into Caresyntax, that is a business that's all about collecting data in and around the operating room. What then? What do you do with the data? Well, it's empowering the hospitals themselves to figure out where the statistical outliers are in terms of what's working, what's not working. What are the, what are the tools that are being used, and what's the ROI on their behaviors, their micro decisions throughout the process? What's, you know, how can they fine tune everything that they're doing within the or to engender safer, smarter, better surgery, better outcomes. You know, that's the Ri you can save 1000s of dollars in a in a in a single procedure. You can reduce length of hospital stays. You can reduce the the need for for opioids, and the usage of opioids. There's so so much ROI that we can, yeah, I'll

David Kereiakes  29:53  
offer, like, since you, you teed it up for me, Dave, and once you get me going, then it's, I'll you. Easily finish. I'll tell you when it's enough. As a device investor, you either use a device in a procedure or you don't, and there's there's less variance in that. Now, when you get into the ICU or the ER, there's more noise and the patient is more variable in how they present. But in a routine procedure, you're able to own the ROI on the software side or the hybrid side, it's really hard to navigate that noise. And so two examples I'll give you in past investments that I've made. One was a company called advanced practice strategies. It was an E Learning talent management system helping to reduce medical errors in labor and delivery. That's a meaningful outcome for a meaningful cost, financial and the impact of, you know, medical error that affects the mother or the child. And every health system has these types of events. What APS did was assess on the front end, all of the clinicians on their clinical knowledge and judgment, are they willing to speak up and pull that unique insight show you who is the more knowledgeable clinician around fetal monitoring or postpartum hemorrhage, some of these areas that result in these big litigations and these big medical errors. And before APS went in, we saw what the health system knew what their events were. After they went to zero, it was such an effective tool, and they were able to own that ROI, which is to a health system million or two per event, let alone, you know, the trauma to the works force to the mother and the family and so a really meaningful business. It's not a billion dollar business, but really impactful. The other one, a company called taylormed, is a software solution that sits at the point of care and identifies patients with financial vulnerability. We often ignore the financial health of the patient. 16% of cancer patients stop their life saving care because they can't afford it. They're judging whether they should leave their family in bankruptcy or financial ruin for a few extra months of life. And that's just not, at least in the US, that's not how we should be doing it, particularly since we spend $4.7 million 93% of Americans have health insurance, highest rate in history. 33% of them skip care because they're afraid they can't afford it. And a surprise, $500 bill goes unpaid often. So tailormed sits at the point of care and identifies helps automate eligibility and enrollment and available funding programs. They're all out there, but right now, it's done manually, and bringing the financial health and that insight into the system, allowing them to engage drives better brand equity. It's something that health systems are now finally starting to talk about. It's something P and G and all consumer brands have been doing for decades now, but it's finally coming into the healthcare realm. Lowering bad debt is very impactful, obviously, to the income statements, which are very distressed at this point in time and driving greater care adherence or real material, ROIs. So that's what drove our investment thesis, in addition to how meaningful of a solution this is, and the strategic value of that too, to the next bigger player that can leverage that. But Justin to your point, which I thought was very astute. You have to package all of that up for the customer. You have to have it with a bow and with APS. We had a full system that allowed them to compare each site against other sites within their IDN allowed them compare against blue chip health systems allowed them to see and staff accordingly, based on who was knowledgeable, who was comfortable speaking up. In you know, an airline industry oftentimes the co pilot is aware of a potential crash and presumes that in the chain of command the pilot knows it, and there's a hesitancy to share same thing with a nurse and a physician, and so being able to help enable that was a meaningful part of their value proposition and what we were doing. So we've got three minutes. We can't talk about data and what you can use with it without talking about the internal application of it, right? How does it inform business decisions? I know a few of you are not commercial yet, so it's more challenging to inform a sales team that's not there yet, but I'll open it up. How are you using the data that your own business is generating to help inform some of your own decisions?

Franz Bozsak  34:59  
Yeah? I think one thing I can say, even though we're not commercial, is something very interesting that was, you know, we that we observed in one of our studies that was over hundreds of hundreds of patients, was an ex vivo study, not inpatients, but we collected data about the procedures and about exactly what we wanted to do in the future and sudden, and analyzing the different treatment arms in the different hospitals, and looking at the data, like our data sensor, they get the data, they look at this, and they're like, Oh, this is interesting. Like, I can basically see how I could make this hospital better in their performance in treating patients this compared to this hospital, for example, right? So it's really what you look at this data, and you suddenly, you like, realize, Oh my God. Like, if I give this to a manufacturer, right? I can actually guide their marketing decisions, their sales divisions of exactly how to advise the hospitals. Because, I mean, there is, you know, when you have a medical device, of course, the physicians, the one using it, and he knows best for his patient. But that doesn't mean that you can't give him some advice on how he could perform better, right? So it's really interesting. I think when you as you collect data, that things that you did not expect in any way to be visible just suddenly just jumps at you,

David Kereiakes  36:16  
yeah? So,

David Cubbin  36:18  
and that's, yeah, go ahead. And therefore data is not everyone's friend, because, because the truth will hopefully win in the end, but, but you know, sometimes it stands, you know, it stands in the way of certain decision makers, and we know where we need to get to, and data is key to that, but it's not always in everyone's best interest,

Franz Bozsak  36:50  
but I would say to that, it's all about packaging in the end, you know, it's just, how do you present that data and makes the person make the right choice in the end? Yes, yes.

David Kereiakes  36:59  
Well, happy to do a quick question from the audience, or we can call it quits here, as we're at a time, but I'm the moderator, so I can add another 30 seconds,

Audience Question  37:12  
like, just briefly. I mean, I guess to improve everything, you need the right incentives. And sometimes it seems, sometimes it seems like the incentives aren't lined up correctly from the health system, and it's so complex, because it's not just buying an iPhone, that person is maybe gets the advantage because of that, but not those people are not the direct and and so then, then ultimately, us going in, trying to sell our device, we'll just go for the largest reimbursement. Yeah, we'll just push that. There's, there's no incentive to make the system more efficient necessary. We'd like to become more efficient of our treatment. But that's just a thought.

David Cubbin  37:55  
It's, it's funny. I incentives are there for a reason, and but I do find it funny as somebody on this side of the pond listening to some pitches from companies, and like, the whole pitch is about incentives. And I'm like, so like, what do you do again, you know, what's, what's the what's your company? And it's just like an incentives pitch. And so I think there has to be a balance of chasing after the incentives, because that's, that is the, you know, that again, they're there for a reason, but also having an underlying business and a product that's sustainable in the long run, regardless of incentives. You know, I sort of hope that the in the incentives are there to guide the system into a into in a particular direction.

David Kereiakes  38:47  
But then I would add there's the incentives on the surface, but then beyond that too, which very few entrepreneurs actually dive into, and investors are aware of how the decision maker within the health system or the payer is incentivized too, and finding a friend and family on the other side, or an somebody that can advise you in how that employee, that is the champion that is making that decision is comped or not comped, incentivized or not, based on or on how the decision can be made. And so then it comes back to what Justin was alluding to earlier, is how do you package that in a manner that makes their job easier to say, Yes, this affects my compensation at the end of the day, because oftentimes it is a financial decision or a bonus related decision, or what drives them too. So with that, thank you very much for the time and for sitting in on this.