Latest / Becker’s Healthcare Podcast / Building a Unified Data Foundation for AI and Healthcare Innovation with Chris Carmody
Transcript
- 0:00- What we wanna do with AI is help
- 0:01- clinicians go from being reactive
- 0:04- to proactive.
- 0:05- At Philips, we can recognize patterns in monitoring
- 0:08- data across populations
- 0:10- and apply those insights to specific patients.
- 0:14- Safe and responsible AI can support sharper insights,
- 0:18- pave the way for faster diagnosis,
- 0:21- and help streamline care.
- 0:23- That can benefit clinicians, it can benefit health
- 0:26- systems. And most importantly, it can benefit patients
- 0:29- and their families.
- 0:33- Phillips.
- 0:34- Hi, everyone. This is Scott King with Becker's
- 0:35- Healthcare. Thank you so much for tuning in
- 0:37- to the Becker's Healthcare podcast series. Joining me
- 0:39- for today's discussion is Chris Carmody, chief information
- 0:42- officer over at UPMC. Chris, thanks so much
- 0:44- for being here today. How are you doing?
- 0:46- I'm doing great, Scott. Thanks. Thanks for having
- 0:48- me. Absolutely. It's great to have you here
- 0:50- at the conference. Before we kinda dive into
- 0:52- our questions, just wondering if you can share
- 0:53- just a little bit about your background, your
- 0:55- career journey with us. Sure. I have been
- 0:57- in health care IT for about thirty years.
- 1:00- The last twenty eight, I've been at UPMC
- 1:02- in many different roles. And and, actually, in
- 1:05- the last couple weeks, I was just, moved
- 1:07- into the CIO role, which I'm very excited
- 1:09- about that opportunity and follow a a great
- 1:12- line,
- 1:13- from a succession perspective.
- 1:15- And,
- 1:16- as part of UPMC,
- 1:18- I'm actually in a position where I can
- 1:20- serve the community where I grew up in
- 1:21- the city of Pittsburgh and the surrounding regions.
- 1:24- So,
- 1:25- I'm very humbled and and motivated by that
- 1:27- opportunity to continue my IT career in this
- 1:30- leadership position. That's awesome. Well, you're helping the
- 1:32- community back home, and and congrats on the
- 1:34- promotion. That's That's wonderful. Good for you. And
- 1:36- then we're gonna dive into these questions here.
- 1:37- I I gotta lean on you for a
- 1:38- lot of big topics in health care right
- 1:40- now. You you know, health systems are receiving
- 1:43- a growing stream of patient data from bedside
- 1:45- monitoring,
- 1:46- ambulatory devices, and and care delivered at home.
- 1:49- Where's that data creating actionable insights for clinicians,
- 1:52- and where does it still create more work
- 1:54- than insight?
- 1:55- That's a that's a great question. I think
- 1:57- it's... There's an evolving answer to it in
- 1:59- terms of how we're dealing with all the
- 2:01- data that's being generated.
- 2:03- We started our electronic journey
- 2:06- decades ago and have generated a tremendous amount
- 2:09- of of data that we've worked towards transforming
- 2:12- an information and and then actionable insights. And
- 2:15- I think that's the key there Yeah. Is
- 2:17- to reduce all the noise and identify the
- 2:20- signals of what an action or what next
- 2:23- steps a clinician needs to take from a
- 2:24- patient care perspective. So when you add in
- 2:27- all the medical devices in addition to all
- 2:29- the different ancillary systems that are plugging into
- 2:32- your your electronic health record system, there's a
- 2:34- lot of information for that clinical care team
- 2:37- to actually
- 2:38- consume and digest and process in a short
- 2:40- amount of time so they're most effective
- 2:43- from a patient care perspective. So
- 2:45- I think
- 2:46- the benefit and the opportunity with artificial intelligence,
- 2:49- whether it be generative or Genentech AI, is
- 2:51- to actually leverage those tools to harness
- 2:53- all that data and summarize that information
- 2:56- into something that's consumable by the clinician that's
- 2:59- complete and accurate and has integrity, which are
- 3:02- so very important when you're talking about these
- 3:04- types of technologies from an AI perspective. But
- 3:07- that... That'll help
- 3:09- make that burden of making sure that all
- 3:12- the information is in one place
- 3:14- and available so the the best possible outcomes
- 3:17- can be achieved from a care perspective. Yeah.
- 3:19- Tuning out to noise, like you said, that's
- 3:20- a good way to put it. Absolutely. And
- 3:22- you kinda walked us into our next topic
- 3:24- here. When clinicians are trying to to reach
- 3:26- a diagnosis,
- 3:27- they often must piece together information from radiology,
- 3:29- cardiology, pathology,
- 3:31- urology, and other systems. Where does that fragmentation
- 3:34- create the most friction in your organization,
- 3:36- and how you bring together data sources and
- 3:38- address this fragmentation
- 3:40- or close those gaps?
- 3:42- We're actually in the midst of solving that
- 3:44- problem from a fundamental perspective.
- 3:47- Just as as late as,
- 3:50- well,
- 3:51- a year ago, we had 10 different electronic
- 3:53- health records,
- 3:55- which are really the core platform for all
- 3:57- that different data to come in from the
- 3:58- ancillary, like radiology,
- 4:00- pathology, lab.
- 4:02- And so when you're seeing patients traverse those
- 4:04- different EHRs, stitching that data back together and
- 4:07- making it available
- 4:08- is a is a challenge. It's it's like
- 4:11- sprinting a marathon from an IT perspective. A
- 4:13- lot of our efforts over the last decade
- 4:15- have been trying to make it a more
- 4:16- seamless experience for clinicians to have all that
- 4:18- data in one place. And we've been really
- 4:21- successful at it, but, again, it's taken a
- 4:22- lot of hard work and effort
- 4:24- to bring all that data together and make
- 4:26- sense of it in one place.
- 4:28- What we've been doing the last few years
- 4:30- is on this journey to a single EHR
- 4:32- platform
- 4:33- to help create that standardization and put all
- 4:35- that data into one place. So we've actually
- 4:37- backloaded
- 4:38- years' worth of data from those other EHR
- 4:40- source
- 4:41- systems. And just so having that that base
- 4:43- foundation and having
- 4:45- the lab, the radiology, and all the other
- 4:46- data sources come into that single spot
- 4:49- is... It took... From our perspective is a
- 4:51- huge win. It's gonna create,
- 4:54- a better experience for the clinician, obviously, from
- 4:57- the patient. The patient actually accesses a lot
- 4:58- of that information from their... Our patient portal,
- 5:01- our myUPMC
- 5:02- system. So it's it's it's it's very exciting
- 5:05- for us. And, again, it positions us from
- 5:08- an opportunistic perspective to actually innovate off of
- 5:10- that and and just drive health care innovation
- 5:13- from there. Yeah. It sounds like a big
- 5:15- relief in terms of efficiency probably for everyone.
- 5:18- Absolutely.
- 5:20- You you mentioned patients. Patients increasingly move
- 5:23- among the hospital outpatient settings and and home.
- 5:26- Where does clinical context most often get lost
- 5:28- during those transitions,
- 5:30- and what would it take to give care
- 5:31- teams more continuous view of the patient?
- 5:34- You you just said it, Scott. It's it's
- 5:36- during that transition when they're going from inpatient
- 5:39- to outpatient or vice versa.
- 5:41- It's making sure the data
- 5:43- travels with the patient that's available, and that's
- 5:45- why we made the,
- 5:47- pretty big investment in time and resources
- 5:50- to put UPMC onto one EHR system, which
- 5:53- makes all that data
- 5:55- seamlessly available in one place for clinicians. So
- 5:58- as a patient traverses our system,
- 6:00- they're able... Their data is able to move
- 6:02- with them. And what our EHR does, which
- 6:05- it's pretty well documented,
- 6:06- we're implementing Epic.
- 6:08- But what Epic does is actually help,
- 6:11- that patient if they would traverse outside of
- 6:13- a UPMC facility for that data to be
- 6:15- shared back and forth, as they traverse their
- 6:18- health care needs.
- 6:19- Yeah. I get to AI now. You know,
- 6:21- we're gonna cover AI in some respect.
- 6:23- With so many AI use cases competing for
- 6:26- attention, how do you distinguish a compelling pilot
- 6:28- from something
- 6:30- ready to become part of everyday care, and
- 6:32- what must be in place to scale it
- 6:34- responsibly?
- 6:36- So I think there's great opportunity with AI,
- 6:39- and I think one of the challenges is
- 6:40- to
- 6:41- actually slow things down in order to accelerate.
- 6:44- Sure. That we have to have the right
- 6:45- processes in place, the right governance to identify,
- 6:47- hey. These are the these are the top
- 6:50- three,
- 6:51- five, 10 problems that we're trying to solve
- 6:53- as an organization
- 6:54- and focus and channel our efforts on making
- 6:57- those successful
- 6:58- so we can build off of that and
- 7:00- and and move things forward and and take
- 7:02- advantage of the opportunity with AI. But it
- 7:04- really does start with that governance piece Right.
- 7:06- And the processes around to support it. And
- 7:09- then the last piece, which is just as
- 7:11- important, is is making sure that the the
- 7:13- users that are having their workflows changed to
- 7:17- make sure that they're trained to understand the
- 7:18- why behind
- 7:20- utilizing that technology and what the benefit is.
- 7:23- Right. Right. The reason you're using it and
- 7:25- and the result you're trying to achieve.
- 7:27- As technology relationships move beyond
- 7:29- one time purchases, what should a partner remain
- 7:32- accountable for
- 7:33- after
- 7:34- go live to make the relationship
- 7:36- genuinely valuable over time?
- 7:38- Accountability is a great term to use with
- 7:40- our technology partners.
- 7:43- What is unfortunately the case
- 7:45- far too often for my liking
- 7:48- is our technology partners come in and
- 7:50- they make the sale, we do the transaction,
- 7:53- and then they disappear.
- 7:55- And what we look for, and I encourage
- 7:57- all health care IT to look for,
- 7:59- are partners that stay engaged, that stay accountable,
- 8:03- and work with you to actually solve the
- 8:05- problems. Because their technology is not the end
- 8:07- all be all, especially when you're acquiring something
- 8:09- out of the gate. You have to integrate
- 8:11- it and make sure it works with the
- 8:13- rest of your technology platforms, let alone integrate
- 8:16- into the workflows for the users of that
- 8:18- technology. But
- 8:20- I I personally think it's a a great
- 8:23- place to be in to... That your technology
- 8:25- partners are always a little uncomfortable.
- 8:27- Anytime they get comfortable, that's a bad sign
- 8:30- that they're being complacent, and we need to
- 8:32- work together and partner and innovate to drive
- 8:34- health care forward. Yeah. Yeah. Absolutely. For our
- 8:37- last question, what's the future of integrated diagnostics
- 8:41- or just diagnostic services, and where do you
- 8:43- see yourself in the next five years?
- 8:46- That's... Those are some big questions.
- 8:48- The five the five year outlook,
- 8:51- I'm I'm an opportunistic
- 8:53- person, and I... I'm... I believe that health
- 8:56- care is only gonna get... Be better,
- 8:58- be more accessible,
- 9:00- have higher quality and better outcomes for our
- 9:02- patients that we serve across
- 9:05- the entire US and beyond because of technology.
- 9:08- And I I hope for... And to me,
- 9:11- a successful technology implementation, whatever that might be,
- 9:13- however we use technology,
- 9:15- really is...
- 9:17- It's at its best when the technology fades
- 9:19- to the background Yeah. When it's not a
- 9:22- distraction for our clinical users and end users
- 9:25- trying to use something, do something when they
- 9:27- should be focusing on the patient. So to
- 9:30- me, that... That's where I hope to be
- 9:31- in five years and how technology will help
- 9:33- us get there. And that, to me, that's
- 9:35- the the the measuring stick on whether we're
- 9:38- successful or not. On the other, like, diagnostic
- 9:41- side, I think there's great opportunity there as
- 9:43- well, but I think we have to
- 9:45- be measured with our approach and adoption
- 9:48- of leveraging things like AI to help perform
- 9:51- some of that
- 9:52- diagnostic work. There's obviously been a lot of
- 9:55- success cases in the imaging space,
- 9:57- and that's a great place to build off
- 9:59- of. But there's also a lot of data,
- 10:00- and, again, we just have to be very
- 10:02- cautious about how we approach that and and
- 10:04- and leverage the technology. We don't wanna just
- 10:06- adopt technology for technology's sake. Right. Again, it
- 10:09- gets back to... Which I believe is all
- 10:11- of our mission, is to provide the best
- 10:13- patient care, to improve patient safety, and ultimately
- 10:15- have those great outcomes that we're that we're
- 10:18- searching for. A 100%. Chris, thanks so much
- 10:20- for joining us on the podcast. It was
- 10:22- a great conversation. I look forward to work
- 10:23- with you again soon. Thanks, Scott. Appreciate being
- 10:25- here. And, again, appreciate everything Becker's HealthCare does
- 10:28- for the industry. Such such a great event,
- 10:30- and I encourage all to join us here
- 10:32- next time. Oh, thanks so much. We appreciate
- 10:33- the support.