Speaker 1: Bloomberg Audio Studios, podcasts, radio news. In the meantime, we
Speaker 1: want to continue with AI. Phillip's eleventh annual Future Health Index.
Speaker 1: It is out now. It examines how AI is already
Speaker 1: changing the way clinicians work, how they deliver care and
Speaker 1: manage pressure across the healthcare system. Now, among its findings,
Speaker 1: how healthcare executives are discovering that AI just isn't about
Speaker 1: cost savings. So let's get into it. Jeff Delulo is
Speaker 1: CEO at Phillips North America. It is the largest regional
Speaker 1: market and division of the Dutch health tech company Giant
Speaker 1: Phillips NV. Those ADRs trade in the US. They're done
Speaker 1: about three percent year to date. As we said, jeffs
Speaker 1: joins us in here in studio. Welcome, Welcome, How are
Speaker 1: you wonderful?
Speaker 2: Thanks for having me.
Speaker 1: Well, it's good to have you here. We do feel
Speaker 1: like we are spending so much time talking about AI.
Speaker 1: It's just coming into every aspect of our world. Tell
Speaker 1: us so about the study that you guys do. It
Speaker 1: is your eleventh annual. What it's all about, who you
Speaker 1: talk to and what are some of the findings.
Speaker 2: Well, thank you for having Carol. I want to set
Speaker 2: the table here very quickly, because what I talk to
Speaker 2: healthcare CEOs on a weekly basis, and the same three
Speaker 2: things always are putting pressure on that system. As you said,
Speaker 2: they're delivering more care longer to people that are living longer,
Speaker 2: and that complex complexity of that care is increasing, so
Speaker 2: that's actually putting stress on the system. They have staff
Speaker 2: shortages which continue to persist and get worse post pandemic,
Speaker 2: and then the cost of delivering that care is actually
Speaker 2: continuing to go up. So all those three things are
Speaker 2: really putting stress on the system. But the opportunity that
Speaker 2: we see is AI in healthcare is becoming quite of age.
Speaker 2: Where a year ago in this study, roughly twenty thousand people,
Speaker 2: two thousand clinicians, eighteen thousand patients, And what we saw
Speaker 2: from year to year is they've gone from experimenting and
Speaker 2: piloting and AI applications to add much more broad adoption
Speaker 2: and impact impact in time back they can spend with patients,
Speaker 2: impact in quality, diagnosis, and impact in well being, And
Speaker 2: they've been very clear about that in the study.
Speaker 3: What do those AI applications in healthcare actually look like
Speaker 3: in practice?
Speaker 2: So I'll give you a simple A simple example that
Speaker 2: everybody can relate to. So the average physician in this
Speaker 2: study said that they're getting five more patients per week
Speaker 2: because of tools that they're deploying in their practice. So
Speaker 2: when I go to my general practitioner, I get maybe
Speaker 2: ten or fifteen minutes if I'm lucky with him for
Speaker 2: and most of that time it's sitting on the keyboard
Speaker 2: asking me questions. Right, what we're seeing is they're getting
Speaker 2: the chance to ambient speak. What they're talking that dialogue,
Speaker 2: it's translating it into the medical record. So what they're
Speaker 2: doing is they're spending time looking you in the eye,
Speaker 2: asking you more questions. That's better for more patients they
Speaker 2: can see because they're spending quality time in the room,
Speaker 2: or maybe even more patients like we're seeing.
Speaker 1: Do doctors feel or medical professionals Jeff feel that we
Speaker 1: are just barely scratching the surface when it comes to
Speaker 1: AI in healthcare.
Speaker 2: Yeah, a prudent approach is good because you want to
Speaker 2: make sure that you have responsible AD deployment. And we're
Speaker 2: hugely as a tech company. We want to make sure
Speaker 2: it's responsible. What I actually think, we're the scraps at
Speaker 2: the table and the feast is yet to come.
Speaker 1: What do you think that feast looks like?
Speaker 2: So take the life of a radiologist. So the average
Speaker 2: radiologist has to work all day, sees patients, maybe do procedures.
Speaker 2: Then they take all these studies, two hundred studies home
Speaker 2: at night and they have to go these go through
Speaker 2: these studies. That's pajama time, right, it's there. It's long
Speaker 2: days for radiologists, which.
Speaker 1: It makes me always nervous as a radiologist who might
Speaker 1: be tired exactly and reading my like.
Speaker 2: I yeah, exactly, So you have the real days. They's stressful,
Speaker 2: and I know.
Speaker 1: There's great doctors out there, so I don't want to diss.
Speaker 2: This, but the system that's meant for them to have balance.
Speaker 2: And so what we're seeing is AI in the in
Speaker 2: the work, in the pathway, the whole. If you if
Speaker 2: you don't think of AI as a bunch of point
Speaker 2: solutions that do discrete things in healthcare, it has to
Speaker 2: fit to the radiologist. It has to fit into their workflow.
Speaker 2: So I can I can scan somebody with great AI
Speaker 2: much faster I get it into their workflow. I can
Speaker 2: determine who the most important person is to look at.
Speaker 2: I can find the slices in their scan that are
Speaker 2: the most important things to look at and even recommend.
Speaker 2: We think it looks like this, you should look right here.
Speaker 2: If you can do that at scale for two hundred
Speaker 2: studies a day, you're improving quality life that radiologist in
Speaker 2: the study, a third of them say they take a
Speaker 2: lot less work home and they're suffering less burnout and
Speaker 2: they're just charged in their in their balance. That also
Speaker 2: adds to quality exactly like you're saying.
Speaker 1: I also feel like the data that is input right, Like,
Speaker 1: there's just more data sets that scans can be compared against,
Speaker 1: whether it's an MRI, right, Like, do you know what
Speaker 1: I'm saying?
Speaker 2: That data coming you can use, but AI can use it,
Speaker 2: right And I'll give you an example.
Speaker 1: That I mean, when they're comparing scans, right, it's something
Speaker 1: that might be overlooked. Again, not dissing anybody professionally, but
Speaker 1: when you've got just hardcold data, that's what they're looking at.
Speaker 2: In the study, it'll say roughly half of the physicians
Speaker 2: that use AI as a as a buddy or as
Speaker 2: a check or actually more confident in the ability to
Speaker 2: make their own diagnosis because of the buddy check and
Speaker 2: a quarter of them are saying that it's a significant
Speaker 2: improvement in there in the result that they deliver. They're
Speaker 2: missing they're not missing medical issues, they're not misidentifying, and
Speaker 2: they're not missing things. And that's from the physicians themselves
Speaker 2: that are saying it's actually helping them have higher quality
Speaker 2: diagnostic which if you're dealing with something like cancer potential,
Speaker 2: this is a big deal.
Speaker 3: How do you kind of, I guess, help the physicians
Speaker 3: who maybe see, you know, an introduction of a new
Speaker 3: technology as just another thing that they have to deal
Speaker 3: with on top of their already busy day, Like do
Speaker 3: you get pushed back from maybe I'm trying to think
Speaker 3: of some of those old school doctors who still you know,
Speaker 3: do everything by hand. They still have paper notes, they
Speaker 3: still have all their files, you know, in a pay
Speaker 3: per form, this is a pretty advanced technology if we
Speaker 3: have to implement.
Speaker 2: I go back to this triple threat, the fact that
Speaker 2: there are not enough people to do the work today
Speaker 2: and they're burning out the ones that are doing it,
Speaker 2: And so we actually find in most of the larger
Speaker 2: health systems there's a huge appetite to embrace this. If
Speaker 2: we're doing the design along the clinical workflow. The challenge
Speaker 2: is we took in the industry typically have thrown technology
Speaker 2: of people and said digest it and the workflow has
Speaker 2: to change. We're not doing that at Phillips. We walk
Speaker 2: alongside our our customers. I work with most of all
Speaker 2: the largest health systems in the US and Canada and
Speaker 2: we're walking alongside them. So when we're designing it, we're
Speaker 2: having them in mind. The beauty of AI driven tooling
Speaker 2: is that it can actually do the work if in
Speaker 2: the process that they're in, we can adapt to do
Speaker 2: the work. That's a lot different than deploying software and
Speaker 2: complex things that you have to learn, screens and all that.
Speaker 2: All that goes away and that's really the promise that's
Speaker 2: not this magic black box thing that's actually happening today
Speaker 2: and some of the leading else's.
Speaker 1: So where do you see it all going? Like what
Speaker 1: are you in terms of generative AI and how what
Speaker 1: role do you see in like I don't know in
Speaker 1: the next three to five years, Like do you have
Speaker 1: a feel of how dramatic the impact is well? I think,
Speaker 1: or what are you hearing from the doctors that you
Speaker 1: talk to.
Speaker 2: I think it's a journey that will be rightly done.
Speaker 2: With some conservativism. Again, the operational aspects of clinical practice
Speaker 2: will have dramatic improvement. That's going to give staff back
Speaker 2: time to be with patients, and you're going to get
Speaker 2: a better workforce, and you may even draw people into
Speaker 2: the practice because they actually have these tools that help
Speaker 2: them be better at what they do and they continue
Speaker 2: to have better balance. The sky's the limit, But we
Speaker 2: want to make sure when it comes to generative AI,
Speaker 2: that were really thoughtful about not getting over our skis
Speaker 2: and allowing hallucinations because trust is the number one thing.
Speaker 2: If we build trust with clinicians and we do it
Speaker 2: in the right way, that embrace and that self check
Speaker 2: process actually improves the quality of the output. I've met
Speaker 2: with a bunch of CEOs here in New York last night. Yeah,
Speaker 2: really really top notch institutions, and they're actually telling us
Speaker 2: in six months the quality of the generative AI algorithms
Speaker 2: that they're building is improving itself at a rate they
Speaker 2: didn't anticipate. So again, I think, do it where there's
Speaker 2: high trust, build that trust with clinicians, design it around
Speaker 2: the workflow, and then you'll really get better adoption. And
Speaker 2: we're seeing that we're seeing year to year, we're seeing
Speaker 2: a massive improvement and adoption of tooling that is giving
Speaker 2: life back to a community that joined the practice to
Speaker 2: serve other people. So it's exciting time.
Speaker 3: Okay, So in maybe three to five years, is the
Speaker 3: artificial intelligence actually going to be making clinical decisions?
Speaker 2: I e.
Speaker 3: You can go as a patient into a doctor's office
Speaker 3: and instead of actually seeing the doctor, there's there's not
Speaker 3: a human involved. Essentially the AI is giving you the
Speaker 3: diagnosis and telling you.
Speaker 2: I think it would be foolhardy to think about what
Speaker 2: could be in three to five years because the rate
Speaker 2: of innovation is so fast. What I can tell you
Speaker 2: is we believe as a technology company that decisions always
Speaker 2: land with the physicians, and so we want to augment
Speaker 2: that physician with as much of the non value add
Speaker 2: work and as much of the diagnostic quality they can
Speaker 2: so that they can make the best decision clinically for
Speaker 2: their patients. And I wouldn't I can't see how that'll
Speaker 2: change in the near future.
Speaker 1: Jeff, What does it mean for the devices that you guys,
Speaker 1: whether it's MRIs or cat scans or sonog like the
Speaker 1: device is the medical equipment? How does it impact you
Speaker 1: guys as a company, and how you have to think about, Yeah,
Speaker 1: well we're borating AI or is it kind of pretty easy?
Speaker 2: It's interesting we've made the step to become more of
Speaker 2: a productivity company than a product company. I mean, that's
Speaker 2: a pretty big leap in this business. We think the
Speaker 2: beauty of orchestrating a workflow for healthcare concerns is where
Speaker 2: we want to be. It's not about the products anymore.
Speaker 2: And so when we think of like our patient monitoring journey,
Speaker 2: we're thinking about how do I have a monitoring, persistent
Speaker 2: monitoring experience across every aspect of where a patient could
Speaker 2: be in a healthcare system, even at home. And so
Speaker 2: we're building these platforms around radiology, around cardiology and cardiovascular intervention,
Speaker 2: and around patient monitoring from home to hospital to home,
Speaker 2: where we give hospitals that rich data and that physiological
Speaker 2: data from patients. And we think of it as the
Speaker 2: software layer or the platform that you can start to
Speaker 2: build these AI algorithms into exactly right, think about the
Speaker 2: apps on your iPhone. Oversimplified, but think about apps on
Speaker 2: your iPhone.
Speaker 1: Right.
Speaker 2: You plug the apps and that do certain things, but
Speaker 2: the platform itself and that's where we've really moved our
Speaker 2: R and D.
Speaker 1: Hey listen, we'd be a remissed you've only got about
Speaker 1: a minute and a half left here, but I got
Speaker 1: to ask you about the macro You see a lot.
Speaker 1: Your company obviously is global charge of the North American unit.
Speaker 1: How would you describe the business environment and the consumer
Speaker 1: side of things?
Speaker 2: Actually pretty strong for both, at least for Phillips. In
Speaker 2: the consumer segments we're in, we're seeing double digit growth
Speaker 2: across the globe, particularly strong here in North America. Consumer
Speaker 2: demand has actually gone up for us, and we've got
Speaker 2: a great portfolio. In the health system side, again, we've
Speaker 2: seen double digit growth last year, where we've consistently outpaced
Speaker 2: the industry for some time. But about the industry itself,
Speaker 2: we see strong demand because of all the things we've
Speaker 2: been talking about. We're pivoting to be less about the
Speaker 2: product and more about productivity. And you think that's going
Speaker 2: to be a game changer for health systems. That's long
Speaker 2: term demand.
Speaker 1: How are you guys using AI at your company?
Speaker 2: So we're deploying everything from our financial systems to my
Speaker 2: commercial operations, to contract management, our services portfolio so that
Speaker 2: we can deploy agents to look at systems health systems
Speaker 2: products that we have in the field to be able
Speaker 2: to do automatic determination of root cause and a correction path.
Speaker 2: We're as committed internally to driving productivity and efficiency so
Speaker 2: that we can grow with our customers at at pace.
Speaker 1: Yeah, it's kind of falling. I know, I know, I
Speaker 1: know your.
Speaker 2: Own dog food.
Speaker 1: That's right, that's exactly Jeff Delulo, he is CEO at
Speaker 1: Phillips North America. Thank you so much. Really appreciate it. Yeah,
Speaker 1: we appreciate it.