Ryan Mcguinness 0:07
Good morning, everybody. It's good to see everyone and a lot of fun to be here. I want to thank the LSI crew, Blake and Scott for giving us a reason to gather and organize. I'm Ryan McGuinness, and commercial general manager at Triple Ring Technologies. Triple Ring Technologies, we stand side by side with innovators and entrepreneurs, to solve hard problems, to launch breakthrough products and to build companies. So we're a big group of doers, engineers and scientists who build things. So if you or your portfolio companies need help, and access to capital, come talk to us, we'd be happy to chat. So we'll start this morning with with self introductions. And Liam, please, can you start?
Leah Braddell 0:56
Yeah, absolutely. My name is Leah Braddell. I'm currently the CEO of a seed stage startup called DataBiologics and we track patient reported outcomes on all things regenerative medicine. That's not where not where we're focused, today. I've had somewhat of a meandering career starting as a biomedical engineer and cellular molecular tissue engineering, realized research wasn't for me and medical sales was so I jumped into industry started as a field engineer in neurosurgery neurocritical care monitoring, then later moved into orthopedics, reconstruction, soft tissue regeneration, uh, but most of my career spent with Intuitive Surgical. So the early years driving the technology from infancy to adoption, I sold DaVinci systems for 10 years, and then spent almost three years as director of market access and customer analytics when I really learned to love the data. And then just a couple of years ago, started my own company consulting stem powered solutions, and now CEO of data biologics. Now, happy to be here.
Ryan Mcguinness 1:58
Thank you, Jawad, please.
Jawad Ali 1:59
Thanks. I'm Jawad Ali. I'm a full time surgeon from Austin, Texas. My clinical practice is in trauma. Robotic surgeon endoscopy, also founded Vality Partners, because reliable clinical insights shouldn't be hard to get. We empower early stage med tech startups and seed stage investors with three things. The first is the voice of the frontline clinician. So what do community surgeons, nurses techs, think about your product? How does it integrate into their workflow and environment? The second is navigating the healthcare marketplace. So understanding who's going to pay for your product or service, and what analysis you have to do so it makes sense for them. The third is charting future trends. As you all know, healthcare is changing faster than ever, how can you set yourself up to take advantage of those changes and not be disrupted by them. And we do that earliest stage to help you avoid those pain points later on.
Justin Barad 2:48
Hey, I'm Justin Barad. I actually started out my career in video games, want to be a video game developer and out of family member get ill? And I wondered, hey, maybe there's a way to use software and technology to help people. So I ended up studying biomedical engineering, wanting to invent healthcare technology, but I didn't really know how to get started. So I was asking around for advice and mentor told me if you want to invent something, you really need to understand the problem you're trying to solve first. And he thought a great way to do that was to be a doctor. So he helped me get into med school and I went to UCLA and then trained to be an orthopedic surgeon there, and then experience firsthand what I think is one of the biggest problems in healthcare today, which is how we train and assess healthcare professionals with procedures and surgery. And I got involved in virtual reality very early because my gaming background and was able to combine my two life passions of video games and healthcare and start also VR in 2016, which is the world's largest VR surgical training platform. And I also work weekends at UCLA as a pediatric orthopedic traumatologist see on the trauma.
Ryan Mcguinness 3:42
Phil Rackliffe 3:43
Yeah, hi, I'm Phil Rackliffe. I'm the president CEO of Image Guided Therapy is business within GE Healthcare. So we're on a pretty exciting run right now. I think most of you have seen that we spun out of the pureplay met imaging med tech company in January of this year, which gives us a lot of flexibility as an organization. But me personally kind of interesting, interesting career spent 15 years with big multinationals, like Boston Scientific and Baxter then decided I wanted to kind of free myself up from big company bureaucracy and went to private equity, and then did a couple of startups, so recovering startup and was here on the other side of the aisle, the last really over the last five years, and then raised a $35 million round in May of last year. And then the next day I was approached by GE for this opportunity. And so kind of interesting to go from big back to a very, very small and capital raising now back on the other side of the aisle looking to invest in various startups because we have a very active VC portfolio right now that's growing.
Ryan Mcguinness 4:44
Yeah, thank you. So we have a very good panel as you can see very broad experiences and across the continuum. So I'm excited about this conversation. So to start out, we're going to hear quite a bit in deep detail about many aspects of augmented and Virtual reality. But in my mind, the true value of these approaches is really accelerating access to life saving technologies for the for the larger patient populations, but also to help the clinicians access these breakthrough technologies. And ultimately, what we're trying to do is enhance the effectiveness of surgical teams. So that's what we'll be diving into today. And that's sort of our frame of reference. So Leah, would love to start with you. And the work that you did in Intuitive Surgical aggregating mountains of data. And this was a remarkable story. And in terms of its depth and impact that you've had, in driving adoption of high tech, breakthrough technology, in some ways, you were struggling at the edge of what was humanly possible. So could you kind of give us some background and flavor of what you were doing?
Leah Braddell 5:58
Absolutely. So I like to say that you can have 510K, you can have a white paper that gets you in the door of the hospital, but you have to make it real for the physician. First, they have to believe in the technology. But next, you have to have the entire team around them. And not just in the LR from the C suite, all the way into SPD to make it truly something they're willing to adopt. And when we think about data, you know, there's data from the robot, I spent years working with robotic data. And I love what Gretchen had to say in the in the panel just before this. So we can give surgeons lots of insights on how long did it take you to do certain tasks? What instruments did you use? You know, where should your team be standing throughout this this case, but ultimately, for them to adopt it, they have to believe it. And and I think of the Pareto Principle, right? 80/20 rule, it's 80%, psychology 20% technology when it comes to how physicians buy into to the to the technology itself. So in order to make that real, one of the things we did early on, before we had digital streaming before we had cloud access to robotic systems, we had paper, and we had log books in the operating room. And it wasn't about length of stay, it wasn't about uptime, it wasn't about skin to skin, it was how long did it take you to suture the defect? You know, what was your approach? Was it medial to lateral? How did you transect the vessel? What devices did you use, and when you start to learn, these things are introduced technologies, you also have to create that ecosystem of support. And support looks like finding the right surgeon to mentor, a surgeon who's in practice. You know, we're on the panel just before they talked about this is adopting physicians after their after residency, and they don't get that exposure to all these different, you know, technologies and different surgical approaches. So it is on the company, and those of us introducing new technology to bring the right match to them. You know, here's this physician, and I noticed you're struggling with this, or here's how I've seen other physicians handle this kind of a bleed with the technologies that you're comfortable using. So it's really the merging of psychology and technology that that allows for adoption of something like a robot, but every other technology, including regenerative medicine. That's that's what's got me excited about this new emerging field. It's the same psychology of play.
Ryan Mcguinness 8:26
Yeah, fascinating stuff. And so Jawad, can you tell us a bit about your work at Valley partners, and the gap that you feel by by asserting the practicing surgeons perspective, into tech development in the funding of med tech code?
Jawad Ali 8:40
For sure. And we talked a little bit before this session about how you come to these conferences, and that I go back to the community hospital where I practice and you think there was an AI powered robot behind every corner, and every patient was benefiting from a huge dataset and analysis. But that's not the reality that we see. You know, I mean, there's so much technology, that's really not the bottleneck and Daniel Hawkins talked about it yesterday. The problem is, you know, the commercial environment, and the clinical workflow and psychology. I think it's awesome that you think about that pretty deeply, because that's really kind of the bottleneck to these technologies. And so what we try to do is help companies understand, you know, what decisions are clinicians making, where your influence can impact outcome, right? And then how do you use that to understand what meaningful data points how it influenced that clinician? What metrics you have to show so that, you know, the hospital system or the ASU or the payer is going to pay for it? And then how do you turn that into a business model? And you know, like I said, when you can address those things earlier on, then you can avoid some of those pain points further down the road.
Ryan Mcguinness 9:53
Yeah, yeah, I mean, as we as we spoken about, technology's amazing and its bells and whistles. And the future and exciting, but very often your day starts with, is my patient properly shaved? Right? And it's that, that that intersection point of new and enabling technologies and the human element of having to deploy them.
Jawad Ali 10:17
Totally. And some of the decisions are like, pretty simple. If you take biomass index, for example, just kilograms per meter square, it's a basic measurement. But it's not nuanced for the individual patient. And it shouldn't be that hard to have an understanding of, you know, for, like, we give the example of like, you know, 63 year old Hispanic female with diabetes, like we can't just use 35 for her, and then a 23 year old, you know, athlete, the same 35. BMI is not, you know, it's not equivalent, but yet we treat it that way. Yeah, interesting.
Ryan Mcguinness 10:47
And Justin, your team is leveraging the incredibly rich data that we have today, that Leah has mentioned. And then also the challenges that that Jawad has been talking about. And so can you tell us a bit about what you're up to it Osso VR?
Justin Barad 11:02
Yeah, I mean, I think there, I kind of boil it down to four key problems that I was seeing, or, you know, continue to sort of get worse. The first is, there's just too much to learn. So kind of along the lines, what you're talking about, there's new technology, new techniques introduced at an accelerating pace. And as a surgeon, there's no way to keep up so you get spread more thin. And so you run into this jack of all trades, master of none. And I think another issue is, you don't even know what's out there. A lot of surgeons aren't going to these conferences. And so technology and technique, discovery has become a major challenge, where you don't even know what the options are, let alone having to learn those options. And that's problem number two, which is that modern surgery, modern procedures are much harder to learn. And people don't really talk about this, you know, people talk about we're like robots that are like flipping a switch. And when in fact, they're much harder to do than in like a traditional, open cold. I mean, you tell me like open colas, discectomy, or appendectomy, versus a robotic one, it just, it's much more complex, and it changes, software gets updated, and workflows change. And this is a new component, where, you know, we're having to keep up with software. And so the idea of, oh, hey, I'll just bring a surgeon to a cadaver lab haven't practiced one or two times. And then it's often months later, they're operating on a patient, which worked for simpler procedures. But now, you go into these procedures, and it's a dumpster fire, you know, and people are running to the computer and Googling and I've been there firsthand. And it's a bad experience. As a surgeon, you go, whoa, whoa, this feels unsafe, I'm going to just do what we always do, because that's safer, when in fact, they're just under trained. It's not that the device is unsafe. The third part of the problem is that we actually really have no objective assessment tool for procedural readiness. So everyone's making these sort of judgment calls are like, I feel ready to do this procedure, or someone else feels ready. But how we feel and what reality is, can be shockingly different. And we're just looking at video earlier where someone comes into a room where they feel ready compared to someone that was objectively assessed with our platform they are, and it's just it's shockingly different. And then the final component is that surgery is no longer this individual sport, where we're like a superhero. I like to think of a superhero, but you're more than I am, but and you just come into the surgery and even go to go to the golf course, maybe still go to the golf course. But it's it's a, it's a much more complex, coordinated activity with multiple stakeholders who have important parts of the procedure. And the crazy thing is you come into the OR, and oftentimes, you've never worked with any of these people before, and maybe they've never even been in your specialty before. So you know, imagine you're like at the Super Bowl, and the only person that showed up to practice is the quarterback, that would be insane, right. But that's what we're doing every day. And so there needs to be an opportunity for everyone to be able to sort of rehearse together, even if it's five minutes before the case. So that at least you as the surgeon, or the rep kind of can focus on the important parts, and not just on what everybody else is doing. And so that's what our platform is able to do. It's a $400 headset, you can use it, you carry it with you use it anytime, anywhere, training the hands on way. So you can practice on any procedure, either leading up to a case or just right before you can train with your whole team. Or you could train with a remote coach halfway around the world. And you could get objective assessment. And we have about seven peer reviewed studies at this point that show that we can improve surgical performance depending on how you measure it anywhere from 200 to 300%.
Ryan Mcguinness 14:09
Yeah, really nice. And one thing I want to touch on, after we hear from Phil is this idea of having the training follow the clinician, right. And this is something that your your solution really does.
Justin Barad 14:22
Well, I think people don't talk about portability and accessibility enough when it comes to training. So there was a study a couple years ago out of Penn and CU, where they had 30 cardiac surgery residents and this problem affects not just formal trainees, but all practicing clinicians, but this study in residents, and out of all 30, 100% of them had access to a simulation lab, and they asked them how many of you have used it in the past year and it was one out of 30 so it's we don't have enough time to go somewhere. It needs to come with us. So we can use it while we're waiting for that really painful case turnover that takes way too long, which is a whole other problem.
Ryan Mcguinness 14:57
Okay, and Phil, your company has the huge great responsibility of bringing these disruptive technologies directly to the clinicians and the patients that need the most. And so can you update us on GE Healthcare is current business and your critical role in this period of really rapid innovation?
Phil Rackliffe 15:13
And it's a it's a loaded question. But, you know, I'd say if we're going to distill it into a couple of things, a little about what we were saying around speed and efficiency, and that's going to sound a little bit like, okay, yeah, I get it. But if you look at you brought about case turnover and surgical turnover, when I see and watch surgeries in a acute care setting versus OBL ASC, you know, it's clearly night and day. The turnover is much faster, it's more streamlined, it's more efficient. And how do we think about technologies that are easy to adopt that can help enable that speed and efficiency in new lower acuity? sites of care? is an area where definitely focusing on so how do we how do we kind of meet the clinician where they're at whether that's an imaging CRM that can do essentially what a CT can do from a preoperative scan, to inter operatively see, kind of, let's say, in a spine procedure, where pedals are placed before you so the patient back up, so that you're not going to discharge them and then find out two weeks later, they were actually placed in the wrong spot. And you've got to bring it back in for a revision? How do you create technologies to give yourself as a clinician or staff confirmation that what you did is accurate. And it's going to be effective before you discharge and then have to deal with that later. But I'd say overall, kind of where we're focused on is, as GE kind of pan broadly, is really around the the data, AI elements and big because many different things. One is we sit on reams of data every day, given that we are the imaging incumbent and one of the big three that do this all day. So how do we go ahead and drive meaningful insights as part of that. And I think as it relates to VR, that you are bringing up that efficiency and speed and training a clinician early on in their career or pre a procedure is imperative. So I think having training tools like that, where you don't have to go to a sim lab, but it's right in front of you with a cost effective solution is definitely the areas that we're approaching.
Ryan Mcguinness 17:28
Yeah, and then so this this concept, I just want to open it up to the to the group, using data across the the care plan to personalize treatment. And yeah, I mean, would you like to take a stab at?
Leah Braddell 17:40
Yeah, yeah. So I think when you're talking about surgery, like personalizing a care plan, you know, there's the pregame, the Okay, what what's going on with this patient? What were the prior operations? You know, what are you expecting with the anatomy? What's your approach going to be? So that's sort of the, like, personalization of the surgery. But I loved your analogy of only the quarterback went to training. And who knows who's going to show up that day. That's that's exactly the challenge every day in the OR, because the OR staffing, they're constantly juggling this puzzle. And now with the way things are constrained, no nurse, no tech can be on for more than eight hours, right? There's, there's the overtime, there's the turnover, there's the you know, the shift change. And so you're sort of balancing these different variables that affect how the day runs, and how the case runs. And traditional stats. So in the OR, always the on time starts the turnover time, how can you affect those things? And it's not always just the technology? It's, it's how can you use the data coming from the technology? So if we take robotics, for example, and all the things that we can we can use out of that? I think surgeons are hungry for more. And and specifically, what can they do to influence their team and be able to recognize the points that they can, you know, influence, change and how the their team of team takes that approach. So for example, I was working with one of the MD Anderson affiliations for with the thoracic surgery program. And we noticed a variation between the four thoracic surgeons actively adopting moving from that approach open approach to robotics. And they reasonably had the same amount of time in the OR. But one of them was extremely frustrated, and the other like, things are moving very, very quickly. We looked closer at the data and with robotics, you can see you know, how long is your head in the console? When does it come in and out of the console? Are the instruments moving? Are they is your head in and they're not moving? What does that mean? And if your heads in and they're not moving, there's a need for the surgeon to be looking at the field. But something else is happening in the field. And typically that's an assistant in the field. And if we can we can isolate those segments, those specific activities that are happening, that gives the surgeon something they can take back to their team and say, you know, my time with my head in the console and not moving the instruments is twice as long as my partners. And we need to address that. And you go then dig, you know, the next layer deeper, well, who is at the bedside? What is their training need? What is their skill set? Was it there consistently? Are they consistently working with with the surgeon? So it really comes down to how do we use data to get very specific on the action to take not just point out, Hey, this is how you stack up on the wall, you know, your time is longer than but but what can we help you inform, to ultimately deliver because clinicians have to deliver to clinicians, nothing administrator hates more than trying to tell a doctor how to practice medicine. So data tends to stay at the very, very high level, our SSI is our readmissions our length of stay and uptime, and no other specifics after that.
Justin Barad 20:57
I think it's nice to know, definitely more transparency about data in the operating room, and like very helpful to understand how your peers are doing like, you have very little insight into that, especially if you're in the community and you're in solo practice, you don't have other surgeons around to compare yourself to. So you can get into some weird states where, you know, you're pinning an elbow and like three hours, and you think that's normal, just because no one else is around and realize it should be 10 minutes. And stuff like that actually happens. But I think one of wall, that's an important part of the feedback loop, what I always found was interesting, you know, we do something in medicine called m&m or morbidity and mortality, where we talk about things that went horribly wrong in the OR and how we could do better next time. But wouldn't it have been better to know before going into the or that something was not quite right. And obviously, you can't control for everything. But, you know, we're looking at either data from the operating room or after harm has already been done to patients, but we need more leading indicators of knowing what are the inputs into the case? How ready is the team for this case? And can we control that, so we can adjust the rest of the patient before anything's been done to them. And I think that's really exciting. And so, you know, in our area, obviously, training everyone, and proficiency is a big part of that. And but as we get sort of better planning tools and understanding, like, Hey, what is the surgical plan and is there, you know, this is going to be probably a much longer track. And I do think we have an effect on this. But everyone does surgery completely differently, and just decide whatever they want to do. And so we, we aren't comparing apples and oranges when we're looking at outcomes, because we're like, well, this joint replacement, you know, had this outcome, and this one had this one, but they're doing it totally differently. And we don't know how it's different. So there's no real, we can't like adjust something and tweak it and then see what the outcome is. So we really need a way to drive standardization. And one of the things that we've seen, it's sort of an unintended consequence of our technology. In some of the complex Spaces, we're in like electrophysiology, where there's really just no set workflow, what we have our partners telling us is that all of a sudden, when people do the VR training, they're all doing the procedures in the exact same order, in the same way all of a sudden, and no one intended for that, but it's been an interesting byproduct. So this can be a way to drive more standardization in surgery, but technology certainly is another way to do it, where it's, you got to do kind of what the software tells you. And in that order, and more and more, that's helping drive a little bit more standardization as well, which is a critical component of just knowing that when we're measuring A measuring B that those are actually variables that can can be compared.
Phil Rackliffe 23:22
I think, sorry, gonna go. Alright, I think on the on the even on the intra operative navigation, and guidance is really where we're focusing on as a company. So, you know, take, take a typical structural heart procedure, and something like maybe a mitral clip. Right now, it's very hard when the doctor places the clip, they don't have a way to understand, is it in the right spot? And is it going to act as intended? So how do we provide tools that show virtual deployment of devices before you actually deploy them to know exactly where to place them, so that pinpoint placement of devices is definitely of area, you could call it enhanced navigation. You could call it virtual deployment, many different things. But there are some technologies that are very innovative right there where we can help have a better outcome for the patient, because we know where we're going to place it before we actually release it. And then also, that streamlining of navigation tools to help a clinician demystify what they're seeing on a CT or an angio, during a procedure to help a better placement of a catheter, or guidewire or cannulation of a target vessel. To do that quicker, those things are out there. And so we're looking to add those to the portfolio.
Jawad Ali 24:43
Well, I was gonna say, you know, if you could just zoom out for a little bit. I think the most exciting thing about this time is the ability to connect all three phases. And so like in the preop phase, you have companies talking about risk stratification, optimization, things like BMI. don't even see the intraoperative phase yet so much tack, right? I mean, training is huge generalization is huge technology, obviously, you know, AR guidance, and then the post op phase, you know, care at home remote patient monitoring. But I think the real potential is when you connect all those things together, you get the information behind it, then you can have personalized insights for that specific patient. And you can understand, you know, what's specific metrics, who they have to meet, that they can realistically meet? What's the best operation for them? You know, and maybe it's a laparoscopic iPod? Maybe it's a robotic taller, and they should go to somebody else for that, you know, what's the best place to take care of them? Is it at home? How many tablets of Oxy do they need, you know, things like that. And, you know, to do that, the hard thing is you have to have interoperability, you have to have collaboration. And that's, as you heard in the last session, that's one of the weaknesses of our system. But I think the real gains, and, you know, outcomes, we're going to see only if we connect all those dots, and look at it in a holistic way.
Ryan Mcguinness 26:03
What and we discussed this earlier, I want to use you to verify some of these promising claims about what technology can do I mean, do you have the time to adopt and to utilize to its fullest extent, any of these advances?
Jawad Ali 26:21
I think good technology saves time, right? So like, it's not that I want to have to, you know, plug something into a computer and process and come by, I think I should, the patient is on my clinic appointment. And there's a dashboard, and it tells me you know, it kind of processes all the patients relevant information presented in a good way, it shows me you know, what surgery they're having, what their characteristics are, that make them a good candidate or a bad candidate. And, you know, it's easier to schedule the case and allows me to maybe loop in the team members are gonna do the case and alert them in, you know, for the training session, and things like that. So I think good tech should save time. And so, I mean, there's an adoption curve. And I think that involves buy in, right, but I think clinicians are actually hungry for those kinds of things that are going to save them time other than to deliver good care, and remove kind of the pain, right? I mean, one huge thing I'm advocate of is, what innovations can you come up with that actually improve the clinical environment for for the caregivers, you know, and I think that's going to be more and more important, as an outcome now that we've seen all these workforce shortages? Yeah, I think, you know, it's, you could have a technology like a robot or something like that, that maybe is faster or as fast, but the learning curve is the issue. And so there's a perception that it's slower when you try. And so people will not adopt, because they're like, hey, this adds time, when in fact, they were not yet proficient. And so that's why training is so critical to drive the adoption of these technologies, because you need to accelerate getting people proficient with them. So they don't think that it's slower. And they realize that they can either be faster as as fast, but you have to get them there before they come to that conclusion that, hey, this is going to slow me down, or this is not user friendly. And I think another thing for accesses, and I don't see people talking about this enough is around all these new technologies, a lot of them do need to undergo some sort of clinical trials or clinical validation. And so they're enrolling providers to use their technology with patients. But once again, these learning curves are long. And so if you have these trials, and people are under trained, you're not going to get good outcomes for those patients. And then you're not going to see the difference in improved outcomes, or whatever your value proposition is. And that seems like a huge issue. So we as patients are not getting access to technologies like renal denervation is a great example. Because they're failing these giant clinical trials, when they find out that the providers that are using them on patients had never used it before only use that once or twice, which is wild. So this this aspect of having access to scalable, measurable training touches every aspect of healthcare delivery, especially around emerging technology. And I think that there just needs to be more urgency around it. I think.
Ryan Mcguinness 29:05
Oh, well then sorry, if I can interrupt because I want to keep it moving. But there's a topic I want to touch on. And you're probably heading in that way, I hope anyway. But this this idea of adoption, I want to kind of talk about the business practicalities of getting expensive and novel technology into the clinic. And this is something that you worked on very effectively, at Intuitive. So yeah, absolutely realities of that.
Leah Braddell 29:31
The realities are exactly that the perception of the learning curve, that this is going to completely disrupt, you know, the number of surgeons I talked to or said, I'm doing five cases a day, and you're going to take me down to two, and how are we going to get there? And then of course, there's this concept of patient selection and who's the right candidate for robotics, and for proficient lap surgeons or even proficient open surgeon had been in practice 1015 years. They don't want to waste their time on things that there's so fast at, they want to apply this new technology to what the edges for them what they couldn't do before. But the reality is they have to go through the learning curve and start simple. And we can usually get them there in the first few cases and have have it be very structured, then we're going to take new approach it do these few skill sets, and then you're going to convert traditional, if, if we're trying to keep on time. But once they get that little bit of confidence in the team around them, now it's let's go to the harder case. And that's when the wheels start to fall off. And they start to get disillusioned with the technology. And then you have an administrator who's spent $3 million, starting a program, calling us to the carpet saying, what what did we do here, we're wasting time and money, I could be doing other cases. So you really have to coordinate the entire learning curve and really set the expectation and have them hear from peers who have adopted in the same way that they have. And get the entire OR cheerleaders you need a coach, you need a cheerleader, and you need and you need, you know, right, the right expectations around the learning curve.
Ryan Mcguinness 31:07
Yeah. And that's the also goes to the value proposition. And so Phil, you must face this on a daily basis. How do you drive that that knowledge around the value proposition and demonstrate it?
Phil Rackliffe 31:18
Yeah, I think it's a, when I think about what the biggest issues are today, right. So the problems to be solved, there's the workflow efficiency continues to come up. So if if we're not developing a product that's going to solve for either one of those things, then it's we shouldn't be developing the product. Now, that can be a combination of a we have something like called a command center, an operating command center that basically takes over the control of almost everything within a hospital from workflow, staffing, scheduling of patients within the OCR and shows meaningful efficiencies as far as driving more patients through and better outcomes and better staffing requirements across the organization. But I think, you know, when I think about like value propositions, anything to get at those two things is critically important to improve a patient outcome. And that's where these digital solutions and right now it's interesting for me to kind of come back and see all the technologies that are out there. And you're a little bit confused, almost, because there's so many good ideas. And and I'm just trying to keep it simple in my mind, which is easy to adopt, you know, low low hurdle. from a cost standpoint, it might be a SaaS based model or other that we can kind of layer on to what we currently have with an imaging system. And something that can easily train on kind of those three things are things that we look for in technologies, if it's overly complex, it's a long way to get from training a physician, and you got to have the rep and the rep staff in every single procedure for the first 20 procedures, and then it finally gets handed off. That's tough. So how do you use maybe tools like VR training upfront to really do that? Laying that groundwork before you go live so you can reduce that training burden? I think technologies that have a huge trading burden up front. All right, it's going to be tough.
Ryan Mcguinness 33:13
Not maybe VR training, but absolutely VR training. Would you say?
Phil Rackliffe 33:17
They help you on your value prop?
Justin Barad 33:18
I mean, that's, like doing my work for me here. Yeah, I mean, I think that we are seeing our technology, you know, being driven by these different specialties, where they're, they're hitting this threshold where the complexity, the length of the learning curve, the number of procedures available available, just sort of exceed the capacity to just sort of figure it out. And cowboy, which is, you know, what we saw in the orthopedic space, when we got started, which is really where the demand was, where there's no real, like, everything was very manuals, one to one training, you're going to cadaver labs, and the PullThru from these labs is really crazy. Because once again, you know, you, you go to the lab, your operating page, four months later, it's a dumpster fire and people don't adopt. So you, people are investing 10s of millions of dollars a year as business units and hundreds of millions dollars a year as a company. And they're seeing, you know, 10 to 20% adoption from these investments in education, which can't be tied to sales for compliance reasons. But you know, that's obviously what it is and part of the selling process. So they're like, Well, how can we get a better result from from our education pathways? How can we do it more efficiently, especially in this environment? How can we cut costs but but get better outcomes, and that's where we're seeing a lot of the adoption where the Salesforce is using it to train themselves. They're on the field using it to demonstrate to their customers, they're training the customers to drive adoption. And then on the capital equipment side, which is a huge issue is this conversation that needs to take place between the clinician and the hospital administration and value analysis committee where you suddenly have someone selling your product that is not on your team, they don't have access to your product, they're trying to describe something unbelievably complex to someone that is not a technology person. And so you know, it's you really should always like you know, show don't tell and letting people experience a technology for themselves. And that's what we always see is when someone just gets hands on with something, they go, Oh, I see this makes sense to me, I get it, what's the next step and so, you know, just helping across the board with the reps, the surgeons, the hospital administrators as necessary so that we can start to drive intelligent decision making among surgical technologies.
Leah Braddell 35:21
Well, I think, you know, an intelligent decision making round and surgical technologies, simulation is key. And I love that you guys are bringing stimulation to the physician, wherever they are. One of the things that we really struggled with, and as you know, it, maybe it's improved in the last couple of years since I left Intuitive but, you know, simulators are incredible, they're incredible technology, full immersion, 3d, everything about the procedure was fully simulated on, you know, the simple backpack for for the console. But selling those into community hospitals that are not academic centers, you know, every dollar that they spend on capital equipment has to have a justifiable ROI. And it's typically tied to revenue tied to is this going to give us more cases in the door or not. And making the case on cost reduction by improved outcomes, or improving patient satisfaction, everybody talks about the Quadruple Aim. And to me, it's just a headline, they don't actually have a great way to quantify that underneath underneath the hood. And so usually, the thing that gets cut off with a PO is the simulator. So we're left in, you know, traditional coordinating, you know, bringing in the model working with it hands on sending surgeons to case observations, really on the on the company's expense. So, so evolving, surgical simulation is critical. And it has to become mainstream in the community setting, not just in academia, because most of these physicians are adopting it in the community setting or in their practice. You know, it's no secret, I think, in this room, that academia actually are the last ones to adopt fully adopt a technology, partly because they try to serve, you know, all the flavors, because they know some of their fellows are and residents are going to go out into the rural hospital, and they're not going to have a stellar lab team that that knows how to, you know, running an efficient room, there may be by themselves working with a tech. So maybe open surgery is the only solution. So these academic programs are notorious for, you know, slow adoption of technology. And as a result, no single resident, and maybe you're experienced learning robotics in this this way, ever gets enough case experience in their residency, it's very few that come out with a level of proficiency that they're going to gain in their own in their own practice. So so it's really building that the the training mechanisms and having that tie in to the ROI and the value proposition on the technology, that's that still has yet to be really defined.
Jawad Ali 38:06
I mean, I'll say that's accurate. For me, as far as the training pathway and the community environment. I think for adoption. Again, I'll say if you can connect the dots between, you know, we did this training, we did this cases, and not just you know, operate I'm obviously is huge metric, but those patients had less when infections, those patients had lower length of stay, then I think, you know, it's going to be more palatable for admin, and or a payer or, you know, provider kind of system to shell out the dollars for it.
Ryan Mcguinness 38:32
Yeah. All right. And we only have a few seconds left in just a real quick response from each and each of you, if you could tell me what you think we'll be talking about next year at LSI? And if we could start with you, Phil, what, what's the exciting thing,
Phil Rackliffe 38:46
I would say, overall, real patient physicians stories of how AI tools and data and navigation have meaningfully improved outcomes. So we have we have a lot of anecdotal, we probably have a lot of real case studies, but I don't hear about it a lot. So I think, actually making this real, because it is the future, and it's gonna look very different than where we are the last 10 years. And it's gonna be rapid adoption of AI as we go forward. So hearing more about that, and actually, the core success stories would be
Justin Barad 39:24
I mean, I definitely think AI and Gen AI will still be part of the conversation. And I think that, you know, technology like VR and train simulation is I'm seeing it in front of my eyes being adopted at an accelerated pace, and that we'll have more data even than we already do now about how it's changing how over 300 million surgeries are performed annually. If we can improve all of those by 5% 10%. Our data shows even more that's an improvement in healthcare delivery that's very rarely seen. So I think that this is a technology that I obviously in a biased way will continue to be excited to see scale.
Jawad Ali 39:58
I mean, I hope that we can talk about and how as a society, we're starting to figure out how to use all this data and implement it, where the infrastructure makes sense. The regulations make sense. The interoperability is there. And we're seeing the reductions in health care costs. And we're seeing the improvement in health care outcomes, and the clinical environment is better. And I think those are the big picture changes that I really want what I hope to be talking about next year.
Leah Braddell 40:25
Of course, I think it will be on the topic of data. But I don't think it's necessarily just going to be how data influences AI. I think we're going to be talking about ownership and talking about licensing and accessibility to that data more more than ever, particularly with, you know, new innovations like blockchain and others that will will drive that once the crypto noise is settled down. All right.
Ryan Mcguinness 40:52
Well, thank you very much. It was a really fascinating panel and I enjoyed sitting with all of you and thank you, everyone for joining us. Please give a hand to our panel.
LSI Europe '23 in Barcelona
Expires May 19thBarcelona Registration Perk