Hi, everyone. This is Lucas Voss with Becker's
Healthcare. Thanks so much for tuning in to
the Becker's Healthcare podcast series.
Today, we're talking about enterprise imaging in the
cloud, and I have the perfect guest for
today's episode to discuss this topic. Eitan Eshner,
regional category leader of radiology informatics and integrated
diagnostics at Philips North America. Eitan, great to
have you. Hey, Lucas. Thank you so much.
It's great to be here. Thanks for the
invite.
Absolutely. Excited to talk about this. Very, very
topical and very on time right now. I
wanna start off with introductions here really quickly.
If you just wanna tell us a little
bit about yourself and and your work in
health care.
Yeah. Absolutely. So,
you know, I have been
working in health care for getting close to
twenty years now. I think I'm at 18.
I spent the first year and change of
my time working on EMR deployments, primarily meditech,
but the remainder of that time about
sixteen ish years at this point in the
medical imaging space, working primarily on packs
and VNA and generally enterprise imaging system deployments.
And that experience has very fortunately given me
the opportunity to travel all over the globe.
I spent three years working in China,
on imaging deployments.
I spent seven years working in Singapore on
the same.
And now I've been back in The United
States since 02/2017,
working with Philips here to, you know, continue
the enterprise imaging journey in the cloud and
otherwise in North America.
Well, it's great to have you. Thanks for
bringing your almost two decades of experience
to the podcast. It's great to have you.
And I know there's a lot of conversations
around the cloud, so to speak, or the
topic of cloud. Right?
What are the three primary reasons right now
customers should consider moving to the cloud and
even think about it?
Yeah. I I think there's
a a number of different reasons, and a
lot of them align to what is the
actual value of the cloud in the first
place.
But but first and foremost, I think it
it's
appropriate and notable
that pretty much every vendor in the imaging
space is shifting to the cloud as a
primary focal point of their ongoing strategy.
So I think in some ways,
although that maybe is not a good enough
reason in of itself, it sort of necessitates
the evaluation
by customers
as to whether or not from an enterprise
imaging space anyway, they will,
take the leap and move into the cloud
since that is now where
most of the major players
within the industry are
focusing their investment energy and see the future
of health care really playing out in the
imaging space and otherwise. So so first of
all, that's just an industry direction. Right?
But be beyond that, you know, the cloud
clearly provides
certain
very tangible value propositions, and I think they're
pretty well known at this point, but I'll
talk through them anyway.
So first of all, durability and scalability
are one of the major
advantages
of the cloud.
Of course, that needs to be considered in
the context of any application that's moving. But
generally speaking,
the cloud offers technologies
to
really scale out
imaging platforms or other health care,
solutions,
and also
provides a base platform of technology
that enables,
you know, a more durable and available
solution that,
is likely to better serve the customer,
in regards to ongoing clinical operations.
So so that that's one
really important key component, just the durability and
scalability that the cloud offers as a foundational
technology layer.
The next bit is security.
Unfortunately, I think we're all
relatively
familiar with the
increasing
frequency
and,
also
damaging nature of cybersecurity
attacks,
as well as the, I guess, increased sophistication
of those same attacks
and that health care institutions,
providers themselves have actually been considered
a prime target because of the urgency of
restoring up your operations, the,
value of the data, the penalties associated with
losing control of that data. And
we
have, obviously, as an industry, come a long
way, and there are many customers
that do an excellent job within their own
IT infrastructure and landscape, securing the applications and
their data. And, of course, it's top of
mind now. But
even for those most gifted, most invested, most
forward thinking customers,
providing the same
security controls and technology
at the same scale and cost and efficacy
that the hypervisors are able to provide it
is no small thing. It was fundamentally impossible
for most customers to get there. Yeah. Yeah.
And that that's not to say that
just by moving your systems to the cloud,
you get security. You know, an irresponsible cloud
deployment is just as bad as an on
premise
deployment that is not secured. Nonetheless,
the tools are there, and they're affordable and
sort of democratized
for a wide
range of customers and competencies to adopt.
And and so it is just, I think,
generally
a better place to secure your data,
and and, you know, run your IT stack
as it pertains to the security question.
The final one, which is probably the most
interesting one,
is
the
opportunity
to innovate and deliver better clinical care in
the long run. And I I think that's
for many health care applications, including in the
imaging space, sort of
at the first stages now. Right? It's not
again that you move to the cloud and
all of a sudden you've innovated and you've
gotten all these new clinical care functionalities and
you've really changed the way you deliver health
care immediately.
But there are obviously
emergent
technologies
and opportunities also for sharing data, you know,
across borders between customer sites, you know, even
for a patient with their their families and
other physicians that the cloud offers
that probably over a long enough time horizon
will truly
impact the way that care is delivered.
And
translating all of those technologies back to on
premise deployments, while it may not be impossible,
like, you know, the obvious one here is
AI, it's not impossible.
I think most of us know at this
point that
artificial intelligence sort of lives in the cloud.
Right? You're talking about huge infrastructure and compute
requirements. You're talking about potentially
hundreds of different applications that have,
you know, their own foundational models associated with
them and that delivering that sort of infrastructure
and technology locally on premise for, again, most
IT organizations is not possible. And even for
the ones where it might be possible is
certainly not desirable
just because of what it means from an
overhead perspective for hardware and management and licensing
and so on and so forth. So I
I think those are the reasons that, again,
durability, scalability, security, and the the opportunity for
clinical innovation and to change the way we
deliver health care in The United States anyway,
really globally,
are the the main
considerations that customers should be looking at.
And then I love that you prefaced this
by saying, you know, this is seems pretty
obvious. Right? We've talked about the cloud for
for quite some time. People should know some
of these factors that you've mentioned because they
are so important, like cybersecurity,
like the clinical implications of it, which are
so key. But the fact is that a
lot of folks don't. Right? A lot of
folks are not where they need to be
from from a knowledge perspective and and really
knowing how to operationalize some of this technology.
What are some of the ways that health
care providers can best leverage some of this
cloud store data that that's there
to really then enhance specifically
enterprise imaging applications?
Yeah. You know, there's, again, a a number
of ways that
you can approach sort of the opportunity with
the data and what the cloud can eventually
offer beyond their building scalability, but now getting
into more of the innovation and insights perspective.
And, you know, I'll I'll say to start
off with that, we've entered over, really, just
the last two years, very interesting
period where,
you know, I I think we've been going
through, especially in enterprise imaging, and I guess
you could say also in the EMR space,
What I would just call is primarily digitization.
Right? The EMRs came about,
hacks came about,
other imaging disciplines followed, but we've we've mostly
digitized data up to this point.
And a lot of the reason for that
was this idea that we would unlock the
data, that we would drive
insights,
and that we would really, again, enable
a better understanding
of how we can treat
complex cases and improve health care and reduce
costs and all of these things that was
the promise of digitization,
that actually turned out to be rather difficult
to approach. Right? I mean, we we not
to say there are no insights as a
result of EMRs and and packs and all
these things, but I don't think anybody
got as far as we would have liked
it to. But just now, in the last
two years, with really generative AI coming onto
the scene, you now have this
opportunity for the first time in history, I
would say, to really put, like, intelligence or
reasoning to disk and do more with the
data than we've ever been able to do
through standard data analytics opportunities.
And so, you know,
that is, I would say, the sort of,
like, golden opportunity that exists out there now
is
how can I take all of my data?
And it's not really just about imaging or
about just radiology. It might be cross functional
across multiple ologies in the imaging space and
also probably combines
medications data and, you know, clinical indications and
reasons for orders to be done and basically
a wealth of information that can come from
any number of different sources,
and then have
these AI models
basically process more data than we mere humans
are fundamentally capable of managing and thinking through
ourselves.
And and then that really creates an amazing
opportunity for, again, that sort of clinical
advancement
in in the way that we we treat
patients and manage costs in The United States,
at least,
where
you can start to drive
more automation and better decision making with larger
sets of data because of really the capabilities
of the combination of the cloud and AI
that enable you to understand more about, you
know, what is the next best steps, how
can I drive
a Gentic follow-up for an imaging case, and
so on and so forth? And I think
that's really where
the combination of the cloud and, you know,
large language models, multimodal models will will eventually
take us and and where a lot of
the investment research focus is across the industry
today.
Yeah. Absolutely.
You mentioned something very important in your in
your previous answer here around cyber security. Right?
You can there is promise when it comes
to cloud
storage, etcetera, in terms of providing more safety,
but it has to be done right. It
has to be something that is that is
thought through that the implication, the application
is
is thoughtfully done and successfully done.
I'm wondering what some of the key challenges
you're seeing are that that health care institutions,
health care IT teams
encounter when they're migrating
enterprise imaging systems to the cloud. Right? What
are some of those things that you're seeing
that that are challenges? And then also, what's
helping address them right now?
Yeah. I I think there's,
again, a number of different
challenges that are being seen, but the the
most
common ones from an from an IT perspective
anyway in terms of adoption are, you know,
first of all, resourcing.
We talk a lot, especially medical imaging, about
the shortage of diagnosticians, whether it be radiologists
or digital pathologists.
We talk about
technologists
and, you know, this
really quite incredible
gap in availability that there are for actually
performing image acquisition within radiology department today across
the country. But we don't talk as much
about IT organizations and their ability to find
the right skilled resources. And, of course, it
depends a bit on geography and also policy
in terms of who you're willing to hire
and where you allow them to be.
But, you know, in
from the perspective of a, you know, seasoned
health care technology professionals, the cloud is relatively
new. And health care IT is not probably
well known for being an early adopter of
new technologies for for good reasons.
And that may be changing slightly now, but
actually recruiting knowledgeable technology resources in all geographies
over the country is is not so easy.
So that that's one major challenge. I think
the good news there is obviously that a
lot of
the industry,
at least in medical imaging, and I think
just generally so, is positioning itself to address
that challenge in terms of providing,
software as a service based solutions that really
mask the technology burden for the customer.
So, you know, and for Philips, for example,
the opportunity for us to host and manage
our own, you know, homegrown and developed solutions
really means that the customer doesn't carry that
IT burden. And that is, from our perspective,
our core competency. Right? We know these solutions
better than our customers do.
We built them, so that should be the
way. And so we are able to provide
them to the customer,
you know, in a way that provides them
with the best and highest quality service with,
you know, frequent updates and all these additional
service entitlements that are very costly to achieve
as an independent customer. And and and we're
able to do so,
hopefully, at a, you know, in a financial
model that scales across our wide range of
customers
that provides a better total cost of ownership
to every customer because it's sort of being
shared as a service entitlement across the install
base.
But that that does bring me actually to
the second of the major challenges, and I
see this all the time in conversations with
customers is cost justification and return on investment.
It's hugely challenging in the cloud environment.
A lot of customers, again,
look at, you know, should I self host
my solutions? What does it mean from a
compute
perspective, from a storage perspective, from a data,
movement perspective, ingress and egress?
And, obviously, every solution has different patterns and
even, you know, different clinical
disciplines have different patterns of access,
in terms of how often the data is
accessed and is reviewed and how much of
us will go in and out of a
cloud based solution.
And so as a
customer evaluating your existing IT landscape, it can
be very challenging to really understand what are
the metered costs of the cloud solution going
to be. Right? It's very different cloud economics
from what most
solutions in the health care space have been
sold at as in the past, meaning
most of the time solutions are sold almost
as a break fix SMA. I buy software
from you. I provision my own infrastructure. I
can write down on a piece of paper
all the servers and switches and, you know,
cables and storage that are required, and I
can roll that into a cost. And then
there'll be a maintenance fee, and that's my
cost. It's very easy to put down on
paper.
The cloud with its sort of dynamic,
you pay for what you use
metering model is
much more complex to estimate to to derive
an actual cost of ownership for, which, again,
is another benefit of a software as a
service model for customers who are willing to
entertain that. The the vendors are usually in
that model,
again, taking over the risk of the operational
run cost of the environment. We are making
the assumptions based on our software. And what
we know about it in common customer usage
patterns
and, of course, you know, information that we
get from a customer during,
you know, discussions prior to proceeding with a
project so that we can appropriately estimate those
costs and actually take the ownership and risk
if we get it wrong.
So, anyway, that that's that's another piece of
the puzzle, the cost justification
and return on investment.
And I should probably say that oftentimes,
the discussion leads itself in my experience to,
oh, this is a lot more than I'm
paying now to Philips or any other vendor.
And, of course, that's true.
The cloud
from a current spend to future spend perspective
may look more from a single vendor perspective,
but you have to look at the full
picture as part of the justification. Are you
going to offset data center costs?
Will you be able to repurpose resources that
are actually running your data center? Is there
a real state investment there?
You know, will you reduce your spend on
securing your applications on premise?
And so creating
a ROI or cost justification model that's more
holistic across many different solutions
and considers all of the actual service entitlements
you would get from a vendor if you're
going down a SaaS
path is is something that
I think takes some educating and isn't maybe
the most familiar
for everyone in the IT space today.
That's where the partnership piece comes in that
you mentioned. It's so important to have that
partner to be able to make some of
these decisions and have those conversations.
Hey, Tom. We colored so many different things
here today in our conversation. You truly brought
the two decades of experience to our podcast,
and I wanna just thank you for for
your time and insights today. It's great to
have you. Thank you so much, Luis. I
really appreciate you joining. Had a lot of
fun. Yeah. Absolutely. And we also want to
thank our podcast sponsor, Philips. You can tune
in to more podcasts from Becker's Healthcare by
visiting our podcast page at beckershospitalreview.com.