Latest / Becker’s Healthcare Digital Health + Health IT / Chris Carmody, CTO & Senior Vice President at UPMC

Transcript

Chris Carmody, CTO & Senior Vice President at UPMC · Becker’s Healthcare Digital Health + Health IT

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