Video Transcription
Bracy Fertig 00:02
So I am Bracy Fertig. I'm the VP of strategy and corporate development at Caresyntax. Caresyntax is a technology company that is bringing to hospitals of today the future of data-assisted surgery. I'd love to start by talking for a moment about the market within which we operate. Surgery is an enormous market. There's about $2 trillion of spend on an annual basis in Europe and the United States alone. If you look at what that means for specific ecosystem participants, surgery is top of mind, particularly for hospitals. Hospitals make about 55% of their total revenue in the operating room. And so technologies that can move the needle in surgery, of course, are very impactful for hospitals' financials and operations as a whole. Despite the scale of this industry, surgery is the second largest profit pool in healthcare outside of biopharma. It's an incredibly inefficient segment, and it faces particularly high risks for the patients who undergo surgery. Fifteen percent of surgeries, in fact, face complications, and 0.5% of surgeries lead to death, often due to medical error. We believe at Caresyntax that one of the key drivers of these risks and these inefficiencies is that there's no comprehensive data capture. There's no comprehensive digitization in an operating room. If you'll allow me to use a metaphor here, we like to compare the operating room today to the commercial airline industry. A lot of us flew to get here. If those statistics around 15% of flights face complications, or 0.5% of people who get on a commercial flight face death, often due to pilot error, no one would be here; we would not have gotten on a plane. And if you think about what the operating room of today looks like in comparison to a commercial flight, it's as if the pilot, the surgeon, doesn't quite know how many people are on the flight, has no way of communicating with the airport where they started or the airport where they'll be landing, has a bunch of really cool technologies and systems installed on their plane, but none of them talk to each other, and there's no comprehensive way to improve what you're doing because of that. And that's where we come in. In the operating room, we bring together a platform that's comprised of AI-powered software, medical-grade devices, and clinical services to make surgery safer and smarter for our customers, the hospitals, and also to support the med tech companies to better support surgeons and patients with their products. We deliver that by allowing for insights across three axes within the healthcare system: clinical, operational, and financial outcomes. We believe that only when you converge insights and improvements across all three of those axes can you develop an impactful and successful product and company. I'll talk for a little bit about what that platform actually looks like. We have an end-to-end service that brings together pre-, intra-, and post-operative improvements. So to the left-hand side, in the pre-operative space, we have a cloud-based software platform that allows for efficiencies in things like scheduling, in things like staff and equipment usage, in surgical pathways, and in better triage of patients. In the intraoperative space, we're in the OR integration business, and what that means is we take all of these disparate systems, these disparate technologies and devices that exist within the OR. We use medical-grade devices, IoT sensors, encoders, decoders, video cameras, and audio capture to bring everything together into a centralized control panel, such that doctors have the information they need from the medical records in the operating room but also can control everything that happens in this environment in a centralized fashion. We also can enable things like performance enhancement and telepresence. Finally, I like to think of our final product, our clinical data as a service product, as a post-operative solution. We take these intraoperative efficiencies that we can deliver and expand this across cohorts of patients within a hospital to improve, as I mentioned in the beginning, clinical, operational, and financial outcomes. I'll come in a moment to an example of a case study of what that looks like. One of the key ways that we set ourselves apart from other companies that operate in this space is we have this amazing engine in the intraoperative phase to collect data. So in the operating room, our platform is used across every surgery. Every surgery, every surgeon that walks into the OR, every patient that comes in, every device that's used, that data is captured by our system and can be used to deliver these insights. That allows us to do the preoperative and the post-operative pieces of our platform better because we finally, for the first time, have information about what happens in that room from end to end. I'm going to use some images as examples of what this looks like and the impact. This is what I was talking about in terms of disparate systems. Operating rooms are a physical, sometimes messy environment, and that's always going to be the case because surgery is happening in there. But if you can use our platform to take an operating room that looks like this to operating rooms that look like this with these connected systems, you can imagine how that translates pretty directly into improvements in patient care, but also in terms of the way that the clinical teams and the surgeons work together. These are actual Caresyntax installations in Martini Clinic in Hamburg, Germany, and in Mexico City. This is supposed to be a video that I don't know how to play, but I'll talk through it. This is our room cameras and the software platform that overlays this, where you have tracking of teams. We can show how teams interact and move around the room. We can track the devices that are being used and use that for things like surgical site infection prediction, where you can see how the different equipment is being touched and moved. We can look at, in a de-identified manner, the care teams and the use of the equipment, and we can use that to employ AI to identify the phase of the operation. And so where there are traveling nurses, for example, you can input your preferences, and the traveling nurses know which equipment you like to use as a surgeon and when you'd like to be handed that equipment again—these micro efficiencies that happen over time. Oh, that's how you play it. This is another example of our de-identified technology from a room camera and some of the phase identification. The next couple of slides have surgical videos, so I always like to shout that out in case people don't like that. This is an example of our AI technology for surgeons, where you have a sort of red light, green light approach as to whether it's safe to clip a particular part of the anatomy. So it's a sort of mental assistance, like a lane assist when you're driving your car. And here again is an intraoperative endoscope camera feed version of the phase detection that we showed on the room camera basis. I'd like to spend the last minute that I have talking through a specific case study relating to the type of insights that we can deliver. We did a project in a hospital in the United States that was performing ventral hernia repair at a net loss because total cost of care was so high for these patients—lots of re-operations, lots of time spent in the hospital, lots of post-operative opioid use. We could show using our intraoperative data and our clinical data as a service engine that if you better directed your procurement spend and used actually a more expensive hernia mesh for the right patients, you could not only reduce the length of stay of the patients in the hospital, you could reduce the post-operative opioid use by 54%. So really significant measures, but important for the hospital administrators in the finance department, you could actually improve the average margin per case by $15,000 and take a margin-negative intervention to a profitable intervention just by better stratifying and procuring your patients' medical devices. Using this data, I'll finish off with some quick stats about where we are. We're in 3,500 operating rooms. We collect data on 3 million annual surgeries and support care teams across 3 million surgeries, and we support 30,000 surgical users, both surgeons and the nursing and care teams around them. These are some of our customers, partners, and investors, and I'm out of time. So if anybody has any questions, I'd be delighted to answer them after separately. So thank you so much. Applause.
