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00:00We do feel like we are spending so much time talking about AI. It's just coming into every
00:04aspect of our world. Tell us, though, about the study that you guys do. It is your 11th annual.
00:09What it's all about, who you talk to, and what are some of the findings?
00:13Thank you for having me, Carol. I want to set the table here very quickly because I talk to
00:17healthcare CEOs on a weekly basis, and the same three things always are putting pressure on that
00:22system, as you said. They're delivering more care longer to people that are living longer,
00:27and the complexity of that care is increasing. That's actually putting stress on the system.
00:31They have staff shortages, which continue to persist and get worse post-pandemic.
00:35Then the cost of delivering that care is actually continuing to go up. All those three things are
00:40really putting stress on the system, but the opportunity that we see is AI in healthcare
00:45is becoming quite of age, where a year ago in the study, roughly 20,000 people, 2,000 clinicians,
00:5118,000 patients. What we saw from year to year is they've gone from experimenting and
00:57piloting an AI applications to much more broad adoption and impact. Impact in time back they
01:04can spend with patients, impact in quality diagnosis, and impact in well-being, and they've
01:10been very clear about that in the study.
01:12What do those AI applications in healthcare actually look like in practice?
01:17So I'll give you a simple example that everybody can relate to. So the average physician in this
01:25study said that they're getting five more patients per week because of tools that they're deploying in
01:30their practice. So when I go to my general practitioner, I get maybe 10 or 15 minutes if
01:35I'm lucky with him. And most of that time, it's sitting on the keyboard asking me questions,
01:39right? What we're seeing is they're getting a chance to ambient speak what they're talking,
01:43that dialogue. It's translating it into the medical record. So what they're doing is they're
01:47spending time looking you in the eye, asking you more questions. That's better for more patients
01:52they can see because they're spending quality time in the room or maybe even more patients like we're
01:58seeing. Do doctors feel or medical professionals, Jeff, feel that we are just barely scratching the
02:03surface when it comes to AI in healthcare? Yeah, a prudent approach is good because you want to make
02:09sure that you have responsible AI deployment. And we're hugely, as a tech company, we want to make sure
02:13it's responsible. But I actually think we're the scraps at the table and the feast is yet to come.
02:17What do you think that feast looks like? So taking the life of a radiologist. So the average
02:21radiologist has to work all day, sees patients, maybe do procedures. Then they take all these
02:26studies, 200 studies home at night, and they have to go through these studies. That's pajama time,
02:30right? That's long days for radiologists. Which makes me always nervous as a radiologist who might be
02:35tired. Exactly. And reading my... Exactly. So you have these long days, they're stressful.
02:41And I know there's great doctors out there, so I don't want to diss this.
02:43No, but the system is not meant for them to have balance. And so what we're seeing is AI in
02:47the
02:48work and the pathway, the whole... If you don't think of AI as a bunch of point solutions that do
02:52discrete things, in healthcare, it has to fit to the radiologist. It has to fit into their workflow.
02:58So I can scan somebody with great AI much faster. I get it into their workflow. I can determine who
03:03the
03:03most important person is to look at. I can find the slices in their scan that are the most important
03:08things to look at and even recommend, we think it looks like this. You should look right here.
03:12If you can do that at scale for 200 studies a day, you're dramatically improving quality of life.
03:16That radiologist in the study, a third of them say they take a lot less work home and they're
03:20suffering less burnout and they're just charged in their balance. That also adds to quality exactly
03:25like you're saying. I also feel like the data that is input, right? Like there's just more data
03:35sets that scans can be compared against, whether it's an MRI, right? Like, do you know what I'm
03:40saying? That we have way more data than anybody can use, but AI can use it. Right. And I'll give
03:46you an example. But I mean when they're comparing scans, right? That's something that might be
03:49overlooked. Again, not dissing anybody professionally, but when you've got just hard, cold data, that's
03:56what they're looking at. In the study, it'll say roughly half of the physicians that use AI as a
04:01buddy or as a check or actually more confident in the ability to make their own diagnosis because
04:06of the buddy check. And a quarter of them are saying that it's a significant improvement in
04:10the result that they deliver. They're not missing medical issues. They're not misidentifying and
04:17they're not missing things. And that's from the physicians themselves that are saying it's
04:20actually helping them have higher quality diagnostic, which if you're dealing with something like
04:24cancer potential, this is a big deal.
04:27How do you kind of, I guess, help the physicians who maybe see, you know, an introduction of a new
04:33technology as just another thing that they have to deal with on top of their already busy day?
04:40Like, do you get pushback from maybe, I'm trying to think of some of those old school doctors who
04:44still, you know, do everything by hand. They still have paper notes. They still have all their files,
04:49you know, in a paper form. This is a pretty advanced technology to have to implement.
04:53I go back to this triple threat, the fact that there are not enough people to do the work
04:56today and they're burning out the ones that are doing it. And so we actually find in most of the
05:00larger health systems, there's a huge appetite to embrace this. If we're doing the design along
05:05the clinical workflow, the challenge is we took in the industry, typically thrown technology at
05:10people and said, digest it. And the workflow has to change. We're not doing that at Phillips. We walk
05:14alongside our customers. I'm, I work with most of the, all the largest health systems in the U S and
05:20Canada, and we're walking alongside them. So when we're designing it, we're having them in mind,
05:24the beauty of AI driven tooling is that it can actually do the work. Uh, if in the process that
05:30they're in, we can, we can adapt to do the work. That's a lot different than deploying software and
05:34complex things that you have to learn screens and all that, all that goes away. And that's,
05:38that's really the promise. That's not this magic black box thing that's actually happening today.
05:42And some of the leading else's. So where do you see it all going? Like what do you,
05:45in terms of generative AI and how, what role do you see in like, I don't know, in the next
05:51three to
05:52five years, like, do you have a feel of, of how dramatic the impact is? Well, I think,
05:56or what are you hearing from the doctors that you talked to? I think it's, it's a journey that will
06:01be rightly done with some conservatism. Again, the operational aspects of, of clinical practice
06:07will have dramatic improvement. That's going to give staff back time to be with patients and you're
06:12going to get a better workforce. And you may even draw people into the practice because they have
06:16actually have these tools that help them be better at what they do. And they continue to have better
06:21balance. The sky's the limit. But we, we want to make sure when it comes to generative AI, that we're
06:27really thoughtful about not getting over our skis and allowing hallucinations because trust is the
06:33number one thing. If we build trust with clinicians and we do it in the right way, that embrace and
06:37that
06:37self-check process actually improves the quality of the output. I've met with a bunch of CEOs here in New
06:42York last night. Yeah. Really, really top-notch institutions. And they're actually telling us
06:46in six months, the quality of the generative AI algorithms that they're building is, is improving
06:52itself at a rate they didn't anticipate. So again, I think do it where there's high trust,
06:57build that trust with clinicians, design it around the workflow, and then you'll really get better
07:02adoption. And we're seeing that we're seeing year to year. We're seeing a massive improvement in
07:05adoption of tooling that is giving life back to a community that joined the practice to serve other
07:11people. Right. So it's exciting time. Okay. So in maybe three to five years,
07:16is the artificial intelligence actually going to be making clinical decisions? IE, you can go as a
07:22patient into a doctor's office and instead of actually seeing the doctor, there's, there's not
07:28a human involved. Essentially the AI is giving you the diagnosis and telling you. I think it would be
07:33foolhardy to think about what could be in three to five years because the rate of innovation is so fast.
07:38What I can tell you is we believe as a technology company, that decisions always land with the
07:43physicians. And so we want to augment that physician with as much of the non-value add work and as
07:47much
07:47of the diagnostic quality they can so that they can make the best decision clinically for their
07:52patients. And I wouldn't, I can't see how that'll change in the near future.
07:56Jeff, what does it mean for the devices that you guys, whether it's MRIs or CAT scans or sonogram,
08:02like the devices, the medical equipment, how does it impact you guys as a company and how you have to
08:08incorporating AI or is it kind of pretty easy?
08:11It's interesting. We've made the step to become more of a productivity company than a product
08:16company. I mean, it's a pretty big leap in this business. We think the beauty of orchestrating
08:20a workflow for, for healthcare concerns is where we want to be. It's not about the products anymore.
08:25And so when we think of like our patient monitoring journey, we're thinking about how do I have
08:29a monitoring, persistent monitoring experience across every aspect of where a patient could be in a
08:34healthcare system, even at home. And so we're building these platforms around radiology,
08:39around cardiology and cardiovascular intervention, and around patient monitoring from home to hospital
08:44to home, where we give hospitals that rich data and that, that physiological data from patients.
08:49And we think of it as the software layer or the platform that you can start to build these AI
08:54algorithms into.
08:56Exactly right. Think about the apps on your iPhone, oversimplified, but think about apps on your
09:01iPhone, right? You, you plug the apps in to do certain things, but the platform itself. And
09:05that's, that's where we've really moved our R and D.
09:07Hey, listen, we'd be remiss. We've only got about a minute and a half left here,
09:10but I got to ask you about the macro. You see a lot, your company obviously is global. You're in
09:15charge of the North American unit. How would you describe the business environment and the
09:20consumer side of things?
09:22Actually pretty strong for both, at least for Phillips and the, in the consumer segments we're in,
09:26we're seeing double digit growth across the globe, particularly strong here in North America,
09:31consumer demand has actually gone up for us and we've got a great portfolio in the, in the health
09:36system side. Again, we've seen double digit growth last year where we've consistently outpaced the
09:42industry for some time, but about the industry itself, we see strong demand because of all the
09:47things we've been talking about. We're pivoting to be less about the product and more about
09:50productivity. And I think that's going to be a game changer for health systems. That's long-term
09:53demand.
09:54What, how are you guys using AI at your company?
09:56So we're deploying at everything from our financial systems to my commercial operations,
10:00to contract management, our services portfolio, so that we can deploy agents to look at systems,
10:06health systems, products that we have in the field, to be able to do automatic determination of
10:10like a root cause and a, and a, and a, and a correction path. We're, we're as committed internally
10:15to driving productivity and, and efficiency so that we can grow with our customers at, at, at pace.
10:23Yeah. It's kind of fast.
10:24We're all in.
10:24I know.
10:25You got to practice what you preach.
10:25I know.
10:25I know.
10:26You got to eat our own dog food. That's right.
10:28That's exactly.
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