All righty. Okay, perfect. Thank you very much. So Patrick, on the U.S. MedTech team, glad to be here. And thank you so much to Jay and Pete, both for coming to join as CFO and CEO of GE HealthCare, respectively. I've got some fun disclosures for everyone. morganstanley.com/researchdisclosures. Rush your way there for exciting disclosures that you'll probably never read, but that's fine. And by all means, reach out to your Morgan Stanley sales rep if there's anything else you need. And I think, Pete, you were looking to do maybe a couple of opening remarks, then sort of open it up, if that works for you.
Yeah, sure. No, look, thanks, Patrick, for having us. Thanks for joining us this afternoon. For those of you that don't know GE HealthCare, and many of you do, but we're obviously a new company, came out January fourth, spinning out as really the first company coming out of the General Electric company, with just some tremendous assets. I mean, we're a company that is focused on helping facilitate precision medicine through our focus on precision care. And we'll talk, I'm sure, a lot about some of the different things that are going on. In many ways, the innovations that are happening in the industry, either in pharmaceuticals or within interventional devices, we typically play, as some of—as well as some of our peers, a major role in helping facilitate the diagnosis, the planning, the execution, follow-up.
You know, there's an unparalleled amount of these new procedures that are coming in that we haven't really seen. So if you think of our business, you know, about half of the business is imaging equipment. So everything that you can think of, from interventional cardiology to number one 1 surgical C-arm used in all types of outpatient procedures through top positions in CT, MRI, Nuc Med, and then a business that's focused on many things to run the operating rooms in the hospital. So one of the largest monitoring franchises in a time period when monitoring is really evolving pretty quickly with AI and capabilities.
Anesthesia platform that's very large, as well as, number one ultrasound platform, and we can talk a little bit about how that's evolving with miniaturization and also AI, that, you know, in the future, most of your primary care physicians, if not all, are going to have a handheld ultrasound, and what that means for better care, but all that changes the ecosystem. And then we're a little bit different from most companies, that we actually have a pharmaceutical injectable, a component to our business, focused on imaging agents that help make better images and diagnostics. Big chunk of that's contrast agents. Another part of that's called molecular imaging agents, and that's kind of the fuel that's used to actually see how certain tumors are progressing or regressing in the future, better cardiac imaging. And so that's the combination, which is, which is GE HealthCare.
The core underpinning around that, that we think there's a great opportunity, Patrick, is around our services business, and particularly our future with digital and artificial intelligence. One of the things we've doubled down on is the investments in the work that we're doing in machine learning. And so our new CTO came in after many years with Amazon, interventional cardiologist. We built out our team and just think that companies like ours have a really interesting opportunity to play a much bigger role than just our spot area within, you know, imaging or diagnostics, but actually, again, facilitating broader precision health. With that, maybe you can jump into the Q and A.
Perfect. Thank you. Maybe starting with imaging, just given the size of the segment, thinking somewhat longer term, you touched on some of the key themes there, you know, whether it's AI or the service work or, continued development in emerging markets and things like that. For you, what can you pick out, like, one or two of the things that you're most passionate about, that you think could drive the overall category forward in terms of growth?
Yeah, no, I think the overall category piece is kind of what I opened up with, and this is a little bit of rising tide lifts all boats, and then maybe I'll talk a little bit about our positioning. But, you know, I started out in imaging and stuff, you know, 30 years ago in my career and saw some of the uptake of how the growth took place. You know, I remember the scenarios of where imaging, particularly MRIs, were called out, that the rising cost of healthcare was tied to too many MRI images back in the 2000 window.
You know, what's interesting, if you play it forward now, with the rise of so many capable drugs, immuno-oncology, as an example, this idea of theranostics, like in Novartis's new Pluvicto drug, the potential drugs with Alzheimer's, all of these drugs now are needing more assistance to either desi- to actually position in dosing, follow up on risk, or diagnose. And the cost to do imaging is significantly a more higher value to see if it's working or how it's working than the total cost of the drug. If you play that forward from 15 years ago, that's the difference. If you want to run an economical health system and also drive better outcomes for patients, that's it.
Come to our device, you know, brothers and sisters, whether it be structured heart and what you need to do to take a look at how those devices have done. Image guided, it might be, it might be a transthoracic, esophageal probe. It might be other types of intravascular imaging. All of those things I think, you know, really say for the next X years, we should see some very good demands. As today, I think most of you know, the backlogs of patients waiting to get an imaging study so they can get one of these drugs or procedures is, in many cases, at record levels in different markets around the world. For us, in particular, I think, you know, this whole rise of molecular imaging, where you have these specific imaging tracer agents...
matched up in the PET/ CT world, PET /MR world, I think we're just seeing the beginning of that. MR, you know, what we've been able to do with deep learning integrated in some cases where we needed to kind of catch up to competition and features, we actually closed the gap, and I would argue, in some cases, surpassed with the deep learning modules, and there's so much more to go there. And then I think the future of CT and photon counting, we could talk about if you'd like, I think there's some really interesting things happening. But the core underpinning, I'd say, for all of us in this space is, it's just been a great feeder of outstanding pharmaceuticals and devices that are driving the need for our products to have better outcomes and honestly, better productivity.
I definitely want to touch on photon counting in a second, but historically, you know, some of the technological innovation that happened in, like, the old school, big iron. I'm thinking of like, when you had the CT slice wars in the early 2000s and 3 Tesla on the MR side, the industry sort of struggled to get paid for that. But the difference, I guess, now is on the software side. So how, how are the conversations with customers going around AI and things like that, and making sure that you guys get appropriately compensated for what is ultimately a much better product than it used to be?
Yeah, I think it's a great point. I think, look, in many of those windows that I was there, you know, it was a spec on spec kind of of a war, and you were building more Swiss Army knives. I think in today's world, particularly where, again, you have a drug that if it's working or not, is gonna cost $100,000 or $50,000, and to be able to get the right framing of the right patient or diagnostic, you know, to actually have a device that can do that well, and if you pay a little bit more for that in the spectrum of total cost, it's actually a significant savings.
I mean, I would submit to you that for all of us that are in this space, if you buy a CT scanner for $1 million and it lasts for 10 years, and you're doing 40 patients a day, it's still one of the best economic deals in all of healthcare when you look at what it actually does. But I think in today's scenarios, what's really kind of different is that, you know, we, as a company, are definitely a lot more outcome-focused. So I just use the AIR Recon DL and MR. What we've been able to do with deep learning is to be able to boost signal-to-noise without any type of smoothing algorithm work, be able to actually then, because of that, take a 10-year-old system, take the image quality to what's state-of-the-art today.
Yeah.
Which for many of our customers, what you don't want is some two new systems that are better, and the other ones that aren't, and you're not using the fleet, but at the same time, get 50% faster throughput. So the throughput alone, when you look at what we're charging for that, and you have a backlog versus buying a new system, that the build-out of a new room in a big city is gonna cost you twice as much, that's what's really played out. But our focus of our organization has become, over time, more and more clinical focused on our selling because we've had to. And if you can really help a customer solve a problem, they're willing to pay a little bit more for that because they really see the connection with value.
You've, you've sort of alluded and mentioned, you know, the clinical side, obviously Alzheimer's. Perhaps for those in the room who might be less familiar with what's going on there and how your tracer business plays, and maybe if you could give some sort of context to the opportunity for GE there.
Yeah. So in Alzheimer's, I think we're all aware of what, you know, the two major companies out are doing right now. They're Biogen and Lilly and others that have drugs that are in their pipeline, first drugs that are showing promise of actually slowing down progression. But unlike other drugs, where there might be a basic companion diagnostic and you move on, because of the components of these, you actually are having to use a bunch of companion diagnostics in the case of imaging to go into it. So, for example, you need to be able to not only just understand if someone has amyloid beta plaque, but the quantification of it.
And the way you can do it, and the way this is done in the clinical trials, was in PET CT, you actually inject a radioactive isotope, an F-18 derivative. We have an approved product called Vizamyl, which actually highlights and color the amount of plaque on that. And you look at that, and there's clear ranges for what that means, and then you're a candidate for the drug. Obviously, there's windows coming up to that. Once you're injected the drug, there are a few, what they call ARIA or potential risks of the drug in certain patients, and that could be some brain swelling or microbleeds in a smaller percent of the population. So the on-label indication is that after each of these injections, you would do an MRI.
So if you think about that, unlike a normal regular drug, you'd say that's an infusion drug, you'd go to the normal infusion area separate from the imaging. Now, as a hospital system, you need to think about how you coordinate that. Do I have adequate capabilities on my PET CT? Where do I get my tracers? Keep in mind, tracers are radioactive. We make them in Arlington Heights, and we ship around the whole world, and also out of our European facility. And those tracers are actually then timed to actual delivery. So you need to have that structure in place.
Then in many cases, you have to think about, if my patient lives not in the downtown, do I want them to come down there to get the follow-up MRI, or do I want to have it in those areas? And so we're working with customers on how to think about their footprint. You know, if you have 28 hospitals, 30 outpatient centers, how do you want to set that up? So that's just a simple example of a new drug that's coming out, and for it to be effective and the uptake, the locations of their infusion centers, the imaging, and the availability of the diagnostics comes into play. And I think we're gonna see more examples of that in the future, but this is where we will play a pretty significant role.
Maybe before we move on to sort of photon counting, Jay, you know, GE HealthCare, in a way, a fresh company. You're a fresh set of eyes as well to the company in some ways. And there's, you know, a reasonable part of the equity story that's associated with margin improvement and efficiencies and that side of things. Any, like, early observations of how you found things, of opportunities for, you know, efficiencies or cost savings, or just observations you've had as you started?
Sure. I think it's great we spent the first few minutes on so much about innovation, because for me, what's been most intriguing since I've joined, are the innovation pathways and the innovation story that Pete's been talking about. You know, our products play an essential role and an increasingly essential role, in the future of healthcare. So just thrilled to be part of that, and also just struck by how significant, an impact we can have. And so that's great. As far as margin goes, yeah, I, I believe that we have a real margin expansion opportunity. The team outlined on the Investor Day, high teens to 20% in the midterm, and we feel very good about the overall program and what we're doing to drive that kind of margin expansion.
It really comes down to three things: pricing and commercial execution, new products, and then cost. Cost relates to a few different things. We have really significant efforts in our, what we call, our variable cost productivity initiatives, and this is like what's going on in the plants and how you ship product around. I've been very impressed with the program that we're running on this, and the ability to drive continued and sustained cost improvements. But then secondarily, there's a whole host of costs as a new public company that we can get after. How you standardize, how you think about your IT costs, as a public company. There's a lot of opportunities that we have there. So, you know, as I said at the beginning, compelled by the innovation opportunity, but I think it's backed up by a solid margin transformation plan.
And then along the way, we're intensely focused on free cash flow. I think one of the things I've been impressed with is this idea of 85% free cash flow conversion. I think that's quite good for a healthcare company. We'll want to continue to maintain or improve those levels, while at the same time, really transform the margin of the company. I think it hangs together as a very nice story.
Most healthcare companies are pretty dreadful at focusing on cash conversion, so-
Right.
It's definitely a differentiator. And then on the topic of innovation, obviously, photon counting, specifically within CT, it's an interesting area, obviously extremely nascent. You know, most of your peers aren't really present in any meaningful way, even on the development side in that market. How are you thinking about the opportunity for that growing over time, and how much, I guess, of the long term, the overall CT construct could end up being photon counting in base, do you see?
Yeah. Patrick, I mean, for the folks listening that don't know, I mean, this is a significant disruptive change in how you make a CT image. In the spirit of high tech, you know today, when you make an image, it's basically a kind of a negative projection of what X-rays made it through your body, and there's this calculation off something called Hounsfield units. This literally is a detector that can count every photon of radiation coming through into buckets. You can imagine that in a given rotation, there's, you know, mass terabytes of data to do there. There's been a lot of innovation, there's been a lot of focus on it over the years at different points, but a lot of the technology between the processing capabilities, some of the power capabilities are there.
You know, there's folks in the industry that are working with something called Cadmium Zinc Telluride. It's been around for a while. We use it in our NucMed products. It can do a fine job to be able to increase spatial resolution. And what you're trying to do here in a CT scanner is, can you get finer detail on edges of fixed things? So if you think about even in cardiac imaging or other areas, that finer detail can help you diagnose something earlier. It can do a lot of different capabilities that way. You want to be able to reduce dose, and it holds the promise of reducing radiation dose.
But the third is probably the most profound, which is this idea of seeing in the same level of tissue, different levels of readout or energy, which gives you the capability to understand what's happening, how it's functioning. So when you hear the term functional imaging versus spatial definition, I think the real promise is there. And so, you know, some of our competition have some versions that are out now on Cadmium Zinc Telluride. We went after a different version of technology on what's called deep silicon. And the reason that we went that route is we believe its characteristics for these energy separation buckets is significantly higher. Why is that important? I just kind of give you an example.
Like in cardiac imaging, what's great about where cardiac imaging is happening in CT today is, you know, anybody that is suspect of having potential issues in their family or other things, getting a cardiac CTA is non-invasive and can be a really, really high-quality exam. In the future, in a photon counting world, not only will the detail be better, so the accuracy of is that stenosis where it's at on these distal levels of the vessels? But as you can today see soft plaque, meaning you can tell if there is plaque building up outside the vessel. You have the possibility of actually characterizing it, which means, should you use a stent? Should you use some other diverter? Should you actually go on a pharmacological? And being able to ascertain that data because of more functional is what the real promise is.
So we've gone that route, which means it's gonna take us a little bit longer to get there, but we think the clinical benefits will be wider. The second part to that is, you know, the idea of the way CT has evolved over time, the top technologies typically cascade down. But to do that, you have to almost have a 10x reduction in cost... to be able to flow to those lower ends. We think the electronics and the Deep Silicon has the potential to actually have that type of a cost reduction, to have full scale across the fleet. CZT, I think it's tougher because it is an element that has a price, that has a value that doesn't change that much, unlike electronics. Now, there are ways to reconfigure, but I'm talking about keeping the same level of fidelity and scaling it down.
We believe the platform that we're working on has a greater opportunity to do so. So again, better energy separation, which means more functional capability, and we ultimately think a better opportunity to scale across the whole line. So, it'll be a fun horse race. There's a lot going on in the space. It's a great modality. There's plenty of room for everyone, and I think it's only gonna be a win for patients worldwide on how this evolves.
Very cool area.
Yeah.
A less cool area, or one that's just like, you know, difficult to talk about on some level is China. And obviously, you know, Jay, at dinner last night, you heard the frequency with which it came up. People were kind of tied themselves in a knot, getting a little bit anxious around the anti-corruption measures and things like that. I guess, you know, what are you seeing today? How do you think about the, you know, the impact? Do you think there is one? Any commentary around that region?
Do you want to start?
Yeah, sure. Sure, I'll start and then maybe turn it over to Pete to add to the answer. I do think it's important to take a step back, because China is an important market for us. It represents about 15% of our sales. We've been manufacturing in China for over 30 years. We've been there for meaningfully longer than that. We recently announced a partnership with a company called Sinopharm, to access the non-premium segment in certain geographies in China that we were previously not present. So we're very excited about China. Now, over the years, there have been a number of things that we've had to navigate. VBP, you know, that's an area that we've seen in our pharmaceutical diagnostics business. We were successful in 2020 and 2021.
As it relates to Made in China initiatives, to some extent, we're less exposed to that, given the strong presence that we have in many of those markets already. Frankly, many of the imaging sales that we make are under tender, so there are already a competitive process around that. The latest, and this is a second iteration, because frankly, there was a similar impact in the 2013-2015 timeframe, is this idea of anti-corruption. What I would say is, as a healthcare company, it's operating on a multinational basis, the quality of the compliance environment is an essential area of our focus, and ultimately, it has to be a differentiator for us.
So we are incredibly focused on compliance, be it in China, be it in the United Kingdom or the United States. And so this idea of raising the bar on compliance, we're okay with that. Now, there have been some short-term impacts in terms of physician concern. There have been some short-term impacts on delayed tenders. And what I can say at this point, we've seen a limited, what we would characterize as short-term impact on our business. We're watching it very carefully, and frankly, these things can change. But I think as we sit here today, you know, we're okay to navigate through the impacts that we've seen through this particular initiative, and we'll have to watch the duration of it, how it evolves over time. We'll watch all of that very carefully and update things as we go.
Pete, I don't know if you would add anything to that.
You know, I think you covered it well. I mean, I think in short, you know, we think China is gonna be one of the largest healthcare markets in the world, right? It's a matter of time. There's a major focus to provide broader care to the general population. That's where part of the stimulus funds went into. You know, I think our take is, obviously, as these things work through the system, you know, this market doesn't change. I think there's a significant amount of growth potential. It's why we did the joint venture. It's why we have an in China, for China strategy, meaning local sourcing and manufacturing, and I think it's gonna continue to be a strong growth driver into the future.
There's always kind of, you know, bumps here and there in the midterm, but I think, I think over the long run, and particularly, well, medium to long term, we see a lot of positive momentum in China.
And maybe turning to ultrasound, kind of a two-parter. On the product side, you know, you obviously mentioned the miniaturization, the ease of use. You can get automated output. There's been some attempts from much smaller peers in the past to do that, and they've typically struggled. In my head, I'm thinking of, like, not that much smaller, like Lumify, or there was Butterfly and things.
Yeah.
Curious, like, how you see your vision of that category going forward, because that could be a big white space. And sort of separate but connected is, you know, very dominant position, ultrasound overall, some of the best margins as part of the group. How do you feel about the sustainability of margins and, you know, that side within that category?
So I'll start with the sustainability. I think ultrasound for us, we're the number one position, women's health, cardiology, we have a very strong position, general, and we're growing this point of care or handheld. It is our business that's done the best job platforming and leveraging capabilities, having every 18-month innovation cycles, which has enabled price, in many ways, something that we look to mimic across the board. We're seeing more and more ubiquitous adoption of ultrasound. So like we bought BK, it is a critical device in neurosurgery to determine, did you get the whole tumor or not? Something that doesn't exist in another tool real-time within the procedure. I think we're just gonna see much more early screening. So you brought up the point, I carried it in my pocket here with me, is the Vscan Air.
So this is our, you know, cordless, tetherless, handheld. We just came out with a cardiac version of it two weeks ago. But this has more capabilities than the best system we made eight years ago... And, and this product then is all cloud-based, right? It works with your phone, where you actually see the images on that or an iPad. But and we also have recently invested heavily in AI capabilities. One of the challenges with ultrasound, it's still much of an art to a science, and that's why you have a sonographer that has multiple years of experience. We're big believers with AI, that we can actually have tools and capabilities that anybody in this audience will be able to learn how to do basic sonography. If that's true, what does that actually mean?
It means that somebody that normally goes to collect blood at someone's house in an underprivileged neighborhood, knows that they have peripheral artery disease, could actually do a lower scan to see how that block is. Or they could be checked to see if they have fluid, maybe they're actually having some congestive heart issues, and is there something at TAVR you could scan, that gets sent over and has an overread someplace, a minute clinic. But the big one, Patrick, I think, and you get into this, is that in the future, every primary care physician, internal medicine, when you go see them, is gonna have a handheld. They're not just gonna be having the stethoscope and say, "Breathe," they're gonna be able to do a much more sophisticated capability.
And so when you think about what that's great for all of us, finding disease earlier, be able to intervene and make decisions so you don't have to go to subsequent doctors. The overread and capabilities that will bring back to radiology, and then with the integration of the data and the AI along the way, not only to enable workflow, but to actually rule things in or rule out, we just believe is gonna be a tremendous opportunity. So you're gonna hear a whole lot more about this from us. We have interest in foundations that wanna say, if you're thinking about taking care of underprivileged groups of folks in Africa or other areas, you know, handheld ultrasound, travels well, handles well. So there's a lot of interesting directions on that, but I think AI, cloud computing, miniaturization, it's the three.
That's what's really enabling this now. We haven't had all three converging at once. It is happening now.
The margins, sort of the long-term margin outlook, it's a very profitable business.
As we move more and more to, in this case, say, as a subscription base, where you're paying a monthly fee, you get the device, you have these other applications. Obviously, the software margins are significantly higher than the hardware, but the convenience and also the recurring revenue component, which we plan to grow over time, is also an interesting part of the strategy.
You know, for both of you, you know, you've done a bunch of these meetings, you've done, you know, dinners and events and things like that. Are there any, like, areas you're surprised that you don't get asked about a little bit more? Or alternatively, where there's just a lot of external focus, but there's not a lot of internal focus, or somewhere internally where there's a lot of focus, but you just don't get asked about it. You know, that disconnect between your day-to-day lives and, like, what you get asked about.
Yeah. I'll let you start.
Sure. I would say that this idea of care pathways is something that we are intensely focused on. The idea of taking the product lines that we have, identifying a deep disease state, and putting on top of that data and digital to support better outcomes and enhance hospital operations, it's an immense area of focus. And really, the area that we get asked about is Alzheimer's, just because it's so prominent and we're playing such a significant role in that early on. But I think the proxies, and Pete's alluded to this in his opening remarks, the proxies to other care areas, gets us very exciting-so excited. So I think we have a tremendous role to play in that. The other thing I would say is, you know, I really do think this is a great cash flowing business over time.
And so I think that has some unique properties in terms of how we can deploy capital over time and really build this engine of business development, and capital deployment. So we're quite excited about that, too. I don't know-
I would just say the other areas, because in the med tech world, we're so device centric, that there's less questions about artificial intelligence and really how we change that. Look, our long-term vision, and I'll talk a little bit about, you know, our digital group that we've got, is that what you're gonna have and, you know, in the coming decade, is a clinician that can sit down with one pane of glass in front of them, see all of the tests that you've actually had, so for a particular disease. It's why we talk about care pathways that way, from that period. Today, it's very difficult to do.
And not only have an AI algorithm that looks on just a mammogram or a chest X-ray, but an AI algorithm that can look at pathology, look at the imaging, look at your genomics profile, and actually help a physician simulate that and say, "You ought to consider X or Y." Maybe not give you the full answer, but direct you that way. But that type of multimodal data that can be converted into insights with AI, we think we're unbelievably well positioned to go after. And so, you know, the structure that we built, typical CTOs in this world are engineering or electric guys. We perfectly indexed heavy on having someone that's deep in AI and digital. And so Taha comes to us, from Amazon after seven years being head of MI, AI and ML. And, but he's interesting background.
He's an interventional cardiologist who practiced for many years and also a deep stats guy, actually worked with the FDA on this. Why that's so important is, you know, helping the agency also think about how we evolve active learning models, having the ability to know what good looks like on large computational models in this space, and how to integrate cloud computing with that. I would say, you know, later this year, at the big radiological show, we'll show more of those items. But I would say in the next 18months-24 months, keep an eye on us and what we're doing on AI and, and cloud-based computing, because I think, you'll see some pretty interesting stuff coming, coming out of GE HealthCare.
RSNA is always a fun conference. I think with that, we're perfectly out of time. Pete, Jay, thank you so much.
Great.
Really appreciate it.
Thank you.