RadNet, Inc. (RDNT) Earnings Call Transcript & Summary

Thank you, everyone, for joining us for the last but the best presentation of the day. Joining me is Executive Vice President and Chief Financial Officer, Mark Stolper. Mark, as always, thanks for supporting us, this conference, our leveraged finance conference. Always appreciate it.

Thanks for having me.

I thought I'd just kick it off, just maybe the call -- yesterday, numbers are out. Maybe I thought a quick review of the quarter, talking about kind of some of the advanced imaging, the volumes and so forth and the numbers for the quarter, just the messaging broadly about the quarter. I know it was a good quarter and so forth. So maybe we'll just start there.

Sure. So when we issued guidance in February, we noted that the first quarter was going to be a challenged quarter due to the Southern California fires as well as some severe winter weather conditions on the East Coast, and we quantified what that impact was going to be on the quarter of $22 million of revenue and $15 million of EBITDA. So it wasn't a surprise, I think, to our stakeholders when we came out with our numbers. And when you add back the impact of the weather and the fires, the quarter was in line with people's expectations and in line with our own original budget that we put together back in December when we were projecting out the year. So a lot of positives that we can take from the quarter. Our advanced imaging continues to grow. And as a percentage of the overall volume, procedure volume that we perform, it grew by 126 basis points relative to the first quarter of last year. The big rising star is our PET/CT business, which was up almost 23% relative to last year's first quarter, and that's being driven by some of the newer prostate and brain PET/CT imaging that we're doing. That is a result of some of the newer technologies in the radioisotope industry.

Okay. Great. As it relates to kind of, I'll call it, the core business model, your core 400-plus centers, you talked about the state of the industry right now. I know we've talked at times about and I thought it would be worth sharing with the audience just nature of the freestanding center versus the inpatient model right now? And possibly the opportunities, some of the challenges that the inpatient model is facing and what opportunities that is presenting you on the freestanding side?

Sure. So we've been enjoying every year that the radiology industry grows. The overall pie of diagnostic imaging is being driven by a lot of the trends that you're seeing that's driving health care utilization in general in terms of the growing population and the aging population. Our industry, in particular, is being driven by advances in technology on the equipment side, the contrast materials, radioactive pharmaceuticals, postprocessing, software, AI, and that drives new applications or new clinical indications for ordering the tests that we perform. What's also happening in favor of outpatient imaging is that there's a market share shift taking place in that growing pie. And that's from hospitals into freestanding centers. The commercial insurance companies have recognized that the lower cost sites of care are on the outpatient side, not within the hospitals. In our markets, hospitals typically charge commercial insurance companies anywhere between 200% to 500% the pricing that we charge. So the -- over the last, let's say, half a decade, the commercial insurance companies have become more aggressive in trying to direct that business out of the more expensive hospitals into the freestanding centers. And they're doing it in several ways. One is through plan design by providing financial incentives to the patient to pay lower co-pays or lower office visits or coinsurance if they go into a network of outpatient imaging centers as opposed to hospitals. And then they're also doing it through utilization management or a pre-authorization process that once they pre-authorize the advanced imaging, they'll then be communicating with the patient and then try to direct them into the lower-cost sites of care. So that's clearly been a driver of our same-center performance and our overall volumes where historically, we've grown the business over a long period of time on a same-center procedural volume basis of kind of 2% to 4% growth. And now we're routinely averaging kind of in the mid-single-digits.

And how -- to that end, has the role -- obviously, radiologists -- the shortage radiologists. Is that playing as well into that metric in terms of staffing your model relative to the inpatient side?

Yes. There is certainly a shortage of radiologists. The growth in the overall industry and procedure volume has outpaced the ability for these medical school programs to -- and fellowship programs and internship programs to produce radiologists. And we offer a model that is highly attractive to radiologists in the -- as opposed to the hospital radiologist who does weekend call, night call, deals with emergency situations. The lifestyle that we provide to our radiologists is we allow them to have predictable hours. They don't have any night call or weekend call or emergency patients. We see a lot of pathology. We're doing over 11 million exams per year, and we allow the radiologists to focus on practice areas that they're most capable to read and that they enjoy reading. So we've had a pretty good -- we and our affiliated radiology groups have had a pretty good experience with hiring, attracting talent and retaining talent. The demands of the hospital-based radiologists have been -- have made staffing hospital-based radiology departments very challenging.

Has that played into the opportunity on the JV model side a little bit?

Yes. I think what I was talking about earlier has played into the JV model more so than the staffing issue. Although the staffing issue does in a sense, a lot -- because the hospitals are losing more and more of the ambulatory outpatient work to the freestanding centers, some of the hospitals are saying, "Look, we just want to hold on to this business as long as we can. We're getting such high pricing. It's a profit center for us. Let's keep the business." And others are saying -- and these are hospital and health systems that are coming to us for partnership opportunities saying, "Okay, look, we're clearly on the wrong side of a trend. We're going to lose this trend eventually. Why don't we position ourselves today to participate in the trend as opposed to continue to fight it?" And so we allow a structure where health systems can buy an equity interest at fair market value into existing RadNet centers in their market and then benefit from the growth of the outpatient business. And the quid pro quo from our standpoint, you might ask why would we want that. One is, in a sense, takes the hospital away from competing for that business. And second, the quid pro quo is that we ask them to use their relationships with community-based physicians and try to direct those referrals now into our jointly owned centers. The other thing that the hospitals and the health systems help us with is protecting our reimbursement in the sense that they help us with establishing fair and reasonable long-term outpatient pricing. So it's been a great relationship today. 154 of our 401 locations are held within these joint ventures, representing about 38% of our business.

Thank you for that. Flipping over to the digital health side, which obviously has been -- is pretty exciting. Can you just maybe walk us through, just broadly speaking, the DeepHealth initiative and kind of what your thought process is and where this model is going, the competitive landscape is, what the market opportunity is from a kind of a top-down perspective? And then maybe we can step into some of the recent initiatives.

Sure. So in one way or another, we've been in the radiology software business or the digital health business really since 2010 when we made the decision that we wanted to own our own IT backbone. At the time, we were relying on some outside third-party vendors for some critical solutions that are the lifeblood of managing the data, the reimbursement, the images themselves. And we -- as we were scaling the business, we recognized that those third-party vendors either weren't willing or capable of keeping up with the demands that we had in terms of requirements for the systems and customization. So we got into the business really for our own account. But over the last decade or so, we started getting more and more demand from the rest of the industry to license our solutions. So as of a couple of years ago, we had over 250 customers using our software platform. A few years ago, we decided -- we saw the advent of machine learning and cloud computing, and we realized that it was a big opportunity for us as a business, a big opportunity for the industry and that we wanted to be a major player in radiology software and in particular, in artificial intelligence. We felt that this industry was going to transform because of these solutions. So we started hiring amazing talent from the outside, including some of the top talent out of Philips, companies like Carestream. And we bought several companies who were early on in the development of certain artificial intelligence clinical solutions, the first being a breast cancer mammography solution that was originally called DeepHealth, which is how we got the DeepHealth name. And then we bought 2 companies out of the Netherlands, one focused on lung cancer screening, the other on prostate and brain. And at the same time, we started developing or redeveloping our software platform, our end-to-end solution, both the radiology information system, which is the brains of our operation as well as the back-end image management solution, which historically has been called PACS, our picture archiving and communication system. And we started redeveloping that product into a whole new cloud-native product called DeepHealth OS. And that product was announced to the industry last December at the big radiology show in Chicago called the RSNA. We have started to implement elements of DeepHealth OS within the RadNet environment. We started building a sales and marketing team. We are now selling it to the rest of the industry. We're close to implementing our first or inaugural third-party customer, a company called ONRAD, a big teleradiology operation. And we're making the necessary investments this year in the infrastructure of digital health to support what we think is going to be a big and growing business going forward. The opportunity we're going after is about a $4.5 billion worldwide market in terms of radiology software. And today, when you look at that market, about $0.5 billion of that is in AI solutions, which we think is going to grow exponentially, particularly when reimbursement is ascribed to some of these solutions. And then the other $4 billion is in radiology software, the traditional risk packs and other point solutions. Most -- the vast majority of those solutions today are on-premise software, which our thesis is that these -- that over the next decade, there's going to be a replacement cycle and most everybody is going to move towards cloud-based solutions like the one that we developed.

I mean, if you look at that, what -- is that what that market, $4 billion market looks like today, very fragmented, I take it?

It's highly fragmented. Now there are a bunch of big name companies that sell products into that $4.5 billion marketplace, like some of the big OEMs have software divisions. But there's not one big player. So it's incredibly fragmented, and that's part of the opportunity that we're going after.

And the opportunities I know you've talked about, maybe it's worth discussing, you said that really -- and maybe this ties into this. It's basically exam interpretation and automation of the infrastructure. There's 2 different initiatives within that...

That's right.

The $4 billion.

So the DeepHealth OS software platform, you can think about it as a workflow solution. So these are -- it's a solution that's an end-to-end management solution where that would be used by an outpatient imaging center. So the front-end radiology information system and the back-end image management solution. And this includes patient scheduling, pre-authorization, insurance verification, customer call centers, certain revenue cycle functions. And then the whole image management solution that takes the images off the machines, sends it to an appropriate radiologist workstation, has viewers and visualization software to manipulate the image, does digital storage, digital retrieval and has very advanced compression technology. And so that end-to-end solution is the vast majority of that $4 billion marketplace. And then we're developing the clinical solutions that plug into DeepHealth OS, that are tools that the radiologists use to be more productive, meaning they can read faster and more accurate. And there could be a day sometime in the future where we may look back to 2025 and say, oh, remember the day that we paid very expensive physicians to sit in dark rooms looking at images and dictating reports [indiscernible]. We think that this is going to be highly automated in the future, maybe even replace physicians.

I mean, is there -- is it a fair question to ask, time frame?

I wish I had the answer.

Is that [indiscernible] in 2025?

In health care, we're always surprised at how slow things move and the inertia that takes place. Part of the impediment to the proliferation of some of these AI solutions on the clinical side is the fact that there's very little reimbursement now offered for the use of these clinical tools so that you're -- when you're going to a radiology practice and you're trying to sell them or license them these tools, you have to sell it on the promise of them being more productive and more accurate. And that's a much harder sell than if you can say, well, by the way, there's a billing code that you can bill Medicare and commercial insurance for utilizing it and it could become a profit center for your practice. But we're getting there. We're having very constructive conversations with commercial payers and alternative payers such as some of our capitation contracts as well as self-insured health plans around ascribing a reimbursement to our breast cancer AI. And I think we're pretty optimistic that we'll have something exciting to talk about by year-end.

Okay. Great. The early detect EBCD, can you talk to that? I guess, I won't say the evolution but your reception and where you are with the rollout of that product in particular within the context of the AI platform?

Sure. So the EBCD stands for Enhanced Breast Cancer Detection program. And this is a program that we created and came up with the idea when we were successful in getting our breast cancer AI through the FDA and started talking to payers, including CMS and realizing that the road to reimbursement was going to be a much longer road than we anticipated and that they were looking for data that supports reimbursement. We came up with this idea to go directly to our patients and see if they would pay out of pocket for the use of this technology. And then that way we could collect all this data and statistics around finding more cancers or lowering callback rates. And so, we started this as a pilot in November of 2022. And on the success of that pilot, we've rolled out this program to all of our mammo centers across the United States with the exception of the Houston market, which we've more recently entered into. And it's been a successful program. We're now seeing about a blended adoption rate of about 40% of all of our screening mammography patients electing to pay $40 out of pocket for the initial read to be read by our AI. Our physicians absolutely love it. It's making them more productive, more accurate. It's making them more confident on the initial read. We have a workflow that we've created in our software platform that if the initial reader and the AI have a disagreement, then that gets arbitrated by a second expert reader. The report is held up in the system. It doesn't go out to the patient or the referring physician. So there's a whole process and a whole program around it. We've gotten better and better as we've been running the project in terms of being able to communicate to our patients the effectiveness of the program and the benefits of the program, and we're seeing tremendous results. We're seeing that we're finding more cancers, and we're finding them earlier in the disease process when it's much more treatable. We're showing that we're finding over 20% more cancers than we did before. And we're lowering callback rates significantly, meaning the -- when our physicians see something that looks like pathology in the report, they'll bring back the woman into the center to do a further diagnostic workup with other more advanced tests. And we're seeing a lot fewer false positives because we are more definitive on the front end. So we started presenting this data to the insurance companies, and I think we're really optimistic about that.

Is that -- you're at the front end of that process trying to show the value prop to a payer, if you will [indiscernible] data?

I would say we're closer to the back end with a number of the larger payers that I think we'll see something positive, hopefully, by the end of the year.

Yes. On your most recent acquisition, iCAD, is that kind of in the same, I guess, an extension of that, the breast cancer?

Yes. So for those of you who don't follow us closely, we announced the acquisition of another public company called iCAD. iCAD was an earlier -- an early entrant into the AI space for radiology in breast cancer. And they have a point solution that they've sold to over 1,500 customer locations. And similar to some of the technology that's now embedded in our AI and our smart -- what we call our smart mammography product, which is our AI, plus some of the workflow tools that we have. And we're really excited about this because it gives us a different price point. It's a lower-priced product relative to what we're offering to the industry. It also gives us an entree to those 1,500 customers that we feel we can be successful in introducing some of our other solutions to them, either the DeepHealth OS, our SmartMammo product, our remote scanning technology, which we didn't talk about, it's called TechLive. And they also have some terrific employees that we're excited to bring on, on the development side as well as on the sales and marketing and commercialization teams. These were investments that we had earmarked to make in our own business that now essentially we're getting with the iCAD operation. And we're hoping that the transaction should close sometime in the June, July time frame.

This may sound like an ignorant question. You have a variety of different technologies, a variety of different outcomes and so forth. Is this a little bit of a learning process that you're going through and looking at these different tools and tools, I should say, tools, an aggregation of these acquisitions to bring it together? How do we think about -- [indiscernible] [ actually ] how do we think of it as a single strategy with these?

Yes. No, very good question. So the overarching thesis that we have about diagnostic imaging and the future of diagnostic imaging is that today, most of the imaging that we perform, we're performing on patients who've presented with some type of symptom. They're symptomatic, either with injury or disease, right? They get referred to us for us to help assist diagnose the pathology on behalf of the referring physicians, and then we send it back to the referring physicians and they treat them appropriately. Our thesis is that where we think that diagnostic imaging can have the biggest impact on the delivery of health care in the future is in the areas of large population health screening programs, meaning, screening large patient populations who are healthy in general for some of the most chronic diseases, cancers, metabolic diseases. So we're talking about heart disease, diabetes, the 4 main cancers being breast cancer, lung cancer, prostate cancer, colorectal cancer. And mammography is the perfect example of one of those disease processes that has been incredibly impacted by widespread screening programs. The -- when we're screening women over the age of 40 and today, there's about 42 million or so women each year that come in, in the United States for their annual screening mammography exam, the vast majority of those patients are negative, meaning they don't have cancer. Typically, the ratio is that you see cancer in 5 to 6 women out of every 1,000 screeners that you do, right? But when you look at the statistical improvement in breast cancer morbidity and mortality, it's been a game changer for women. And we think that diagnostic imaging can play a role in a number of other cancers and a number of other chronic diseases. But part of the impediment is there has to be a return on investment for doing widespread screening because widespread screening is expensive. And we think with the technology advances of AI, with lowering the cost of the workflow with some of the tools that we have, we can bring down the cost so that widespread screening can be part of health care in the future.

In the future. That makes a lot of sense. A few minutes here. I don't know if there's any questions in the audience. But certainly, one of the questions, and thank you for that, is you've very sizable cash balance, 1x levered, very well capitalized. I mean, what are your thoughts about deployment of capital, capital allocation strategy? What are the opportunities that will present themselves? And what would you potentially have interest in?

Sure. So we're sitting on a cash balance as of the end of the quarter of about $717 million. Our net leverage is about 1x. So we certainly have a lot of firepower and dry powder to continue to progress our business plan. There's no shortage of opportunities to spend this capital. I mean, we see opportunities both on the traditional core imaging center side of our business, which is the lion's share of our revenue as well as the digital health platform. We do have an active pipeline of acquisitions on the imaging center side. We're looking at expanding our joint venture business significantly this year. I think we'll have something exciting to talk about in the coming quarters, a couple of things that are exciting to talk about in the next couple of quarters. We do see some more investment on the digital health side. There was some M&A opportunities. We think that there's going to be some consolidation in the AI world within the radiology software business as the industry is slow to adopt because of the lack of reimbursement. So we will put this capital -- I'm pretty confident we'll put this capital to work, but it will take some time. Just because we have a lot of capital doesn't mean that we're going to change our criteria by which we value companies and the multiples in which we're willing to pay. But we're excited to be in this position.

Yes. Are there any -- looking at, I'll call it, the core side of the business. Are there larger trades out there to be done, larger transactions potentially to be done? Or is it all relatively small and kind of tuck-in?

Well, it is a highly fragmented business. And if you took the top 5 owners and operators of imaging centers in the United States, including ourselves, maybe we comprise only about 15% of the imaging centers in the U.S. But there are some private equity-backed consolidators. There are some substantial regional players that are physician-owned. All of those we'd have interest in, assuming it makes sense for the seller and it makes sense for us from a return standpoint. So we know all these players. They know us. It's a pretty small group of players out there. And we'll see.

It's a matter of right market, right price.

Right price, right time, right situation for the seller, right situation for us.

And on the technology side, are there larger transactions to be add on that side?

Yes. My sense is on the M&A side, we'll probably end up doing smaller things. We're not going to put a lot of capital. If we're going to put a lot of capital to work, we'd rather do it by backing our own team and building it internally as opposed to going out and buying somebody. The multiples in the AI space and in the technology space are pretty robust and probably could build...

Internally.

Yes, internally.

I think we're -- well, actually, we're over time. I don't -- unless there's any questions in the audience, I think we'll go ahead and wrap up. Nothing there. So thank you, Mark.

Thanks, Larry.

Thanks for joining us.

Thank you.