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Hello, and welcome to the Becker's Health Care
podcast recorded at the 9th annual health IT
and digital health with RCM conference in Chicago.
I'm joined today by Chris Carmody, chief technology
officer at UPMC.
Chris, to get us started today, will you
please share a bit about yourself, your background,
and your role at your organization?
Sure. I've, been with UPMC for over 26
years. I've done pretty much everything in IT
you can imagine.
But the easiest way to describe my role
today
is I
am responsible for everything except for our payer
applications
and our oncology EHR.
But everything from cybersecurity
to our currently ten EHRs,
to our epic,
single EHR implementation that we're going through right
now.
Among everything else you can imagine, infrastructure,
just everything kinda falls under, my responsibilities. But
I have a great team that I work
with closely,
to make sure that things work well at
UTMC.
Awesome. Well
well, in your role, obviously, you're aware, you
know, AI adoption is exploding in health care.
In your view, you know, what's the most
significant or promising application of this technology right
now, and how is this informing your organization's,
innovation strategy?
They're you're right. AI is exploding. I think
it's a tremendous opportunity for health care. A
couple areas that we're really focused on right
now have to deal with
efficiency opportunities. So
great example is the Ambient AI that our
physicians
in fact, over 1700 currently use Ambient AI
in their interactions with patients to help with
the clinical documentation.
So it's really about that efficiency to get
them away from turning away from the computer
and typing things in or even dictating after
they have that patient encounter
to engaging with a patient, having a a
better experience, and, again, getting them out of
the documentation business. They still have to review
things and then and, you know, accept it
into the electronic health record, but,
we're seeing great positive feedback with that. We've
used AI,
from a data acquisition
and aggregation perspective. So from a clinical analytics,
so we look at predictive modeling
and and trying to,
achieve our goals around higher quality and more
precision medicine for patients.
We use these predictive models that are informed
on all this data that we've generated over,
honestly, over 2 decades,
with electronic health records and other sources
to predict out different models for,
readmission
and even presurgical,
preventative actions that we can take with patients
before they go through a surgical process to
help improve the quality and outcomes. And then
lastly, I think you see a lot of
this from a diagnostic perspective around
images. A lot of things like auto contouring,
things that are saving time and very accurate
at this point in time. But I think
our challenge still ahead is, again, training the
the generative AIMO models and how that fits
into
the delivery of care and and and, again,
creating the efficiencies, but improving the quality and
and the outcomes for our patients. Mhmm.
So
on a daily basis, health care leaders are
managing greater volumes of data, you know, on
more devices and in a growing number of
care settings and growing number of populations.
In this complex environment, what clinical data integration
tools or practices are you seeing drive improvements
in patient outcomes and operations? And can you
share an example or 2? Yeah. I I
getting back to the use of AI,
we actually have used a tool
for the last few years.
I don't know if you want me to
name vendors, but I'll stay away from it
from now. But Mhmm. It's a it's an
AI machine learning tool that actually
takes the unstructured data. So, you know, it's
very easy to take a structured field and
make sense of it. Think about if you're
unfamiliar with the one an electronic health record
looks like. Think of it, like, as a
cell, like, in in Excel or
Access or something like that to where it's
it's structured. You can, you know, mail, theme,
or whatever,
versus the the unstructured data where there's a
lot of rich content that wasn't always readily
accessible in the EHRs
in helping inform those models. So we use
AI to extract out things like symptoms and
social determinants of health, which weren't in EHRs
10 years ago or 5 years ago or
maybe even 3 years ago to help get
that data and and inform the models in
terms of our predictive,
analytics that we've created
around our ecosystem of delivering health care. So
it's been it's been wily,
helpful for us to actually do something productive
with that data other than just creating an
electronic record of something that used to be
on paper. Mhmm. Mhmm.
So, you know, you talked about things that
weren't possible 5, 10 years ago.
You know, what do you think might be
possible in in 5 to 10 years that's
not possible at all today? Well, I think
AI is gonna be
a a big driver towards that. But, again,
I'm a technologist at heart. I'm very excited
about quantum computing and what that can do
in terms of solving some very complex problems.
Hopefully, down the road, it'll actually help, you
know, cure diseases,
and help drive that that discovery.
So I'm I'm I'm very excited what that
might mean 5 or maybe maybe it's closer
to 10 years from now, that intersection of
all this data we're we're generating,
the focus on health care, not just within
the four walls of a hospital or physician
office, but how we're reaching in and and
and being present for the patient wherever they
may be.
Obviously, all the wearable devices that that we
have today, which Mhmm.
Isn't really well adopted in terms of ingesting
that into our records, but I I think
there's an opportunity to improve that as well.
When you see this sort of intersection
up ahead on the horizon of all this
coming together,
I just think the sky's the limit as
we look into the future or what's what's
possible from a health care perspective. Right. And
and I I often hear it described too
as similar, like, when the iPhone hit the
market, you know, you couldn't even imagine some
of the things we're doing with it today.
And that's gonna be kinda the same way
we look at, like, like, say, for example,
AI and health care and its uses in
the future. A lot of them don't even
have any idea yet. Absolutely. And I and
I think, obviously,
we'll we'll figure out the future down the
road, but I at least within the next
couple years, I think AI is gonna get
better. It's gonna become more accurate. We'll have
less hallucinations.
We'll figure out better ways to govern the
use of it,
to where not just our patients or, in
our case, at UPMC, our our health plan
members feel comfortable interacting with a Mhmm. A
generative AI type of technology, but our physicians,
our nurses, our technicians that how that can
help better enable them doing their job. Again,
all geared towards the outcome of higher quality
of care in a more efficient and effective
way.
Perfect.
Well, how can health care leaders and organizations,
better support IT and clinical teams as they
carry out innovation efforts? And, you know, what
are some of the common pitfalls you see
here? I think
probably the biggest thing has nothing to do
with technology. It has everything to do with
change. And how how do we, as leaders,
put our organization in a position that our
our our users, the people actually using the
technology, again, doctors, nurses, technicians,
operational folks, revenue cycle,
how can how can they adopt and change
how they did things in the past? So
as we see that improvement, that's a that's
tough to get human beings to change how
they did things in the past. So we're
successful with that. Again, sky's the limit to
what what's possible in leveraging technology and actually
getting the most out of the investment because
technology is not cheap. AI is definitely not
cheap. Mhmm. So we need to be effective
in how we manage that change and how
do we get it institutionalized
into our organizations.
Mhmm. Mhmm.
And what would you say your top piece
of advice for health care leaders as they
prepare for further advancements in technology and greater
demands for care? That's a great question.
A lot of it is
participating in events like Becker's, where you get
to hear from different technology companies. You get
to talk to your peers across the industry.
You get to hear their problems and how
they're potentially solving them. You might have very
similar ones that, you know, you can basically
beg,
beg, borrow, and steal their ideas, which isn't
a bad thing. But,
you know, an aspect of that is listening,
you know, talking, engaging with your your clinicians,
with with the folks that are utilizing the
technology and trying to help come together and
figure out what that right solution is from
a technology perspective versus, hey. We're IT, and
you're gonna use this. We're gonna force this
upon you. It's that's not a successful way
to especially in health care to get that
level of adoption and the outcomes that we're
striving for. So we have to be in
this together. Mhmm. So a lot of that,
again, is building relationships that's listening to our
customers
and then working with them to Mhmm. Again,
deal with that change management
aspect and and accepting and adopting the technology.
So we actually fulfill what we think will
happen with a new technology.
Well, Chris, I really appreciate this conversation today.
Just wanna know, do you have any final
thoughts you'd like to leave with our listeners?
No. Just, again,
it starts out to be a a great
conference again at Becker's, and looking forward to
the rest of the rest of the time
here and looking forward to to learn a
lot more about what others are doing and
what some of these technology partners are up
to. Well, thank you so much for joining
us today, and I hope you have a
great rest of your day. Thank you.