Latest / Becker’s Healthcare Podcast / Brian Lancaster, VP/CIO of Information Systems at Children’s Mercy Kansas City

Transcript

Brian Lancaster, VP/CIO of Information Systems at Children’s Mercy Kansas City · Becker’s Healthcare Podcast

• 0:02
  - There's a version of AI in health care
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  - upper right.
• 1:00
  - This is Laura Dierda with the Becker's Healthcare
• 1:02
  - podcast.
• 1:03
  - I'm thrilled today to be joined by Brian
• 1:05
  - Lancaster, vice president and CIO of information systems
• 1:08
  - at Children's Mercy Hospital Kansas City. Brian, it's
• 1:11
  - a pleasure to have you on the podcast
• 1:12
  - today.
• 1:13
  - Yeah. Thanks for having me. Absolutely. Now I'm
• 1:16
  - excited for our conversation because I know we're
• 1:18
  - gonna dig deep into some of the cool
• 1:20
  - things that you're doing at the hospital as
• 1:21
  - well as how you're looking at the future
• 1:23
  - and where AI plays a part in more.
• 1:25
  - But before we dive in, can you tell
• 1:27
  - us a little bit more about yourself as
• 1:29
  - well as Children's Mercy Hospital Kansas City?
• 1:32
  - Yeah. So,
• 1:33
  - so my name is Brian Lancaster. I've been
• 1:36
  - here about four years.
• 1:38
  - Prior to that, I was the CIO at
• 1:39
  - Nebraska Medicine in Omaha, Nebraska.
• 1:42
  - Originally from Kansas City and really excited to
• 1:45
  - be at Children's Mercy because,
• 1:48
  - you know, all three of my kids have
• 1:49
  - had events that crossed
• 1:52
  - them into Children's Mercy and they got wonderful
• 1:55
  - care. And it's always so exciting to provide
• 1:58
  - my services back to the community that has
• 2:00
  - provided such great care to my family. So
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  - I love that kind of connection to purpose.
• 2:07
  - Children's Mercy is based in Kansas City. We
• 2:10
  - have, kind of two primary
• 2:12
  - locations. One is, in Kansas City. One is
• 2:15
  - another acute care facility in Kansas.
• 2:18
  - And then we have,
• 2:20
  - 40 or so clinics all through the region,
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  - in parts of the
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  - state like,
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  - Wichita, Topeka, then also in,
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  - Springfield,
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  - and in other locations as well. So we're
• 2:37
  - kind of a a regional entity across Missouri
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  - and Kansas.
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  - This helpful context and, you know, really cool
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  - that you've got that strong sense of purpose
• 2:47
  - in everything that you're doing, within the organization.
• 2:50
  - Now what are some of the most powerful
• 2:52
  - forces that you're seeing shape the digital health
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  - and IT
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  - at the hospital, and how do you anticipate
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  - they're gonna change in the next year or
• 2:58
  - so?
• 2:59
  - Yeah. So, it's probably gonna change quicker than
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  - a year. It seems like every day,
• 3:05
  - technology is becoming,
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  - quicker and more relevant to the care we
• 3:09
  - provide.
• 3:10
  - But right now, there's, like, three major forces
• 3:12
  - kinda shaping our work. First is a system
• 3:15
  - transformation. So we recently transitioned to Epic as
• 3:18
  - our enterprise patient platform,
• 3:20
  - which is creating a more connected experience for
• 3:22
  - patients, providers,
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  - really setting the foundation for long term innovation.
• 3:28
  - Then this the next is really the rapid
• 3:31
  - expansion of artificial intelligence.
• 3:34
  - So we we've just started moving by
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  - beyond experimentation
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  - into scaled
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  - use with a focus on governance, safety, and
• 3:42
  - then measurable value.
• 3:44
  - Our approach, basically balances innovation with structured oversight
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  - to make sure that anytime we're thinking about
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  - AI is deployed
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  - reasonably
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  - across clinical operational workflows.
• 3:55
  - And then third is is basically increasing complexity
• 3:58
  - across our our technology landscape.
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  - So you think about everything from cybersecurity to
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  - application sprawl,
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  - the associated rising costs,
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  - we really need to have a strategy to
• 4:08
  - simplify, standardize, and automate
• 4:10
  - whatever is possible to reduce friction and improve
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  - reliability,
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  - or in other words, to make it more
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  - secure
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  - and easier. And I think that is where
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  - that consolidation really comes into play. So over
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  - the next year, I expect these forces to
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  - converge.
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  - The organizations that succeed will be the ones
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  - that really have integrated AI into the core
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  - workflows
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  - that ultimately reduce complexity, align that technology investment
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  - tightly to patients and operational outcomes.
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  - I love that. And I think especially when
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  - you're trying to figure out that balance of
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  - innovation and oversight, trying to find ways that
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  - you can move forward and move fast with
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  - the things that are gonna make a big
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  - difference, but also
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  - not putting the organization at risk. And so
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  - how do you, really balance that? What is
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  - the governance process look like for you, and
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  - how do you make sure that the team
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  - is mindful but also feels like they are
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  - able to have enough space to innovate in?
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  - Yeah. So,
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  - to to really strike that balance, it comes
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  - down to a really a clear definition of
• 5:14
  - what we're trying to achieve. So what what
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  - is,
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  - success look like? What is what is good
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  - look like? How do you measure it? And
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  - then once you have that defined,
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  - how do you pilot it to make sure
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  - it it actually addresses
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  - what your goals are? And then after that
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  - pilot,
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  - look to scale it across the organization.
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  - I think that's so important with artificial intelligence
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  - because,
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  - you really need to think about how do
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  - you measure success and how do you make
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  - sure you don't have any kind of false
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  - positives or incorrect
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  - information being automated or suggested?
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  - And and having that North Star of what
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  - value looks like can help sort that through.
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  - That makes a ton of sense and, you
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  - know, really seems like a strong foundation to
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  - then build upon for the future. Now I'm
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  - curious. Could you tell us about a big
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  - swing that you took in the last year
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  - that paid off? What did you do, and
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  - what were the results?
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  - So so one of the biggest investments we've
• 6:11
  - made recently was transitioning our enterprise electronic health
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  - record to Epic.
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  - There's not just a significant organizational
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  - effort,
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  - but it it's also a significant in terms
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  - of the results it's delivering.
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  - And this this gets into kind of a
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  - a broader
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  - goal of how do we can standardize and
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  - consolidate multiple different systems into one platform.
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  - And then from that platform,
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  - can really drive forward automation because the datasets
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  - are clean and available and integrated.
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  - So So post CO live, we're already seeing,
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  - some strong adoption from both patient and clinicians,
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  - with engagement metrics performing at or above kind
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  - of pure benchmarks across the pediatric community.
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  - More
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  - importantly, it created a standardized
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  - standardized foundation for how we deliver care, access
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  - data, and introduce new capabilities
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  - like AI.
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  - The real payoff wasn't just the system itself,
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  - but stability
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  - that we now have on one single connected
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  - platform that makes the patient experience and operational
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  - efficiency
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  - through new new partnerships
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  - or relationships
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  - across
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  - kind of the technical teams
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  - and then the teams providing the care or,
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  - otherwise
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  - leading the organization.
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  - So that those relationships
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  - and how we work together on these types
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  - of initiatives.
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  - That makes a ton of sense. And, you
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  - know, I know it's a huge undertaking
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  - switching and transitioning the EHRs. And so I'm
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  - curious what lessons did you learn along the
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  - way? What were some of the things that,
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  - maybe,
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  - you know, you you
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  - pivoted on or,
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  - advice you'd have, I guess, for other similar
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  - hospitals that are trying to make a jump
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  - between EHRs and, especially as they're,
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  - again, trying to make big investments that will
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  - help them out in the future?
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  - The, in my opinion, both the easiest thing
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  - is the hardest thing, which is the these
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  - types of projects have nothing to do with
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  - the technology itself,
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  - which
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  - basically has everything to do with change management
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  - and the relationships.
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  - So that's somewhat
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  - easy because the technology is pretty straightforward, but
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  - it's impossible for someone like they need to
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  - always solve because it's the relationships,
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  - the partnerships, and change management, which
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  - sometimes gets more complex because it's more nebulous.
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  - So I think one of the lessons learned
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  - is really understand
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  - what level of change happens. And to get
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  - value from the system,
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  - you have to have agreement on levels of
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  - adoption,
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  - levels of workflow.
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  - And for all that to work,
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  - you you need agreement across
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  - the clinical and operational leaders that what what
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  - we're doing, it's a project we're doing together,
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  - and technology
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  - is just enabling
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  - operations
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  - versus being the strategy in of itself. So,
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  - again,
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  - for a from a technology perspective,
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  - that's somewhat harder because it gets into
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  - relationships,
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  - kind of the business side of things, the
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  - clinical side of things, which really needs to
• 9:15
  - have that strong partnership to be successful.
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  - Got it. That makes a lot of sense.
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  - And, you know, it's just,
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  - so so fascinating to see how
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  - different organizations are going about that change management
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  - and setting up teams for success and optimizing
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  - the technology once it's in place.
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  - Now what is, as you're looking into the
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  - future and looking ahead now that you've got,
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  - the EHR transition, you know, underway,
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  - what is the most important problem that you're
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  - trying to solve right now with technology or
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  - AI?
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  - Yeah. So so we really think about this
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  - as kind of a start line. So we
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  - now have gotten to the place where we
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  - can start to focus on these really cool
• 9:55
  - types of technologies and solve these important problems.
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  - And and I think that's really the most
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  - important problem we're we're focused on is reducing
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  - cognitive and administrative burden for clinicians while maintaining
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  - safety and quality.
• 10:09
  - As I I'm sure you can appreciate, clinicians
• 10:11
  - spend a significant amount of time navigating systems,
• 10:14
  - searching for information, and completing documentation.
• 10:17
  - So our goal is to use AI to
• 10:19
  - simplify that experience,
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  - surfacing the right information,
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  - at the right time,
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  - automating routine tasks, and allowing clinicians to really
• 10:27
  - stay focused on the patient.
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  - In other words, kind of reduction of system
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  - time and reduction of pajama time at time
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  - spent after hours documenting care
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  - so they can focus on
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  - patient experience. And then if they're focused and
• 10:43
  - engaged with the patient, that will drive forward,
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  - the quality of care.
• 10:48
  - So at the same time, we're also solving
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  - for trust. So
• 10:53
  - AI and health care must be safe, audible,
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  - aligned with clinical standards.
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  - And that really speaks to our approach with
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  - governed AI and looking at how do we
• 11:04
  - create the internal controls with
• 11:07
  - AI development platforms
• 11:09
  - to have a sandbox,
• 11:11
  - to have an agent factory,
• 11:13
  - to really start to allow us to test
• 11:16
  - build.
• 11:17
  - So it gets into that pilot and scale
• 11:19
  - mantra
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  - because ultimately the goal is not just efficiency.
• 11:23
  - It's really about better care delivered with greater
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  - clarity and confidence,
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  - which all gets back to to have the
• 11:29
  - right datasets. Can you test that these models
• 11:32
  - are working? And then can you catch anything
• 11:34
  - that, might appear to be working initially
• 11:37
  - before you roll it out,
• 11:39
  - at a broad scale and have a larger
• 11:41
  - impact because something wasn't quite right. So really
• 11:44
  - focus on that governance and having the right
• 11:46
  - sandboxes and platforms
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  - to test and build,
• 11:51
  - ourselves.
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  - Absolutely. And I think, you know, when you're
• 11:57
  - looking at that patient experience is so important,
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  - in in making sure you're delivering
• 12:03
  - the on expectations. I I think it's been,
• 12:05
  - really interesting over the last couple of years
• 12:07
  - to see how,
• 12:09
  - those patient expectations have evolved and then bringing
• 12:11
  - in, the frontline and caregivers and folks from
• 12:15
  - throughout the organization interested in making those changes
• 12:18
  - and giving them the tools to be able
• 12:19
  - to do that.
• 12:20
  - I'm I'm curious as you're, you know, developing
• 12:23
  - these different tests,
• 12:25
  - sandboxes and and
• 12:27
  - capabilities and opportunities for the team. Where do
• 12:30
  - you see that that being most valuable or
• 12:32
  - adding the most value? What kind of time
• 12:34
  - do you have to spend just getting used
• 12:35
  - to the tools and and what it looks
• 12:37
  - like, in order to be on the development
• 12:40
  - side for people who aren't usually in IT?
• 12:43
  - How are you really going about that in
• 12:44
  - a way that's gonna,
• 12:46
  - spark that innovation but not also detract too
• 12:49
  - much from core responsibilities?
• 12:52
  - Yeah. So that's that's a great question
• 12:55
  - in maybe a debate, you know, because I
• 12:58
  - I think
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  - at the center of what I do every
• 13:01
  - day is
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  - how do I provide technology to solve the
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  - problems that my organization has or to enable
• 13:07
  - opportunities
• 13:08
  - my organization has. So I I think that's
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  - my kinda core responsibility.
• 13:13
  - And with
• 13:14
  - AI
• 13:15
  - coming about in the last, you know, twelve
• 13:18
  - months, six months,
• 13:20
  - last month, and it keeps getting
• 13:22
  - better and easier to use.
• 13:25
  - I think myself, my team
• 13:27
  - needs to start building with AI.
• 13:31
  - So that becomes paramount
• 13:34
  - to how I can think about solving future
• 13:37
  - problems
• 13:38
  - or enabling opportunities
• 13:40
  - with technologies, really becoming a user of AI
• 13:43
  - myself.
• 13:44
  - And if I and if my team and
• 13:46
  - myself can do that, I think we can
• 13:48
  - best align ourselves to provide
• 13:50
  - the most innovative,
• 13:52
  - transformational
• 13:54
  - platforms,
• 13:56
  - and capabilities
• 13:57
  - by doing just that. So so in essence,
• 14:00
  - the way we're thinking about it
• 14:02
  - is, you know, how do we
• 14:04
  - lean into
• 14:05
  - the tool sets themselves?
• 14:08
  - So then as a problem arises, we can
• 14:10
  - quickly address it. And we've we've already seen
• 14:13
  - some of that,
• 14:14
  - in terms of, you know, we had a
• 14:16
  - issue with faxing during our go live, and
• 14:19
  - we had a small team
• 14:22
  - who were able to quickly use AI based
• 14:24
  - development tools to kinda solve a a problem
• 14:27
  - that was initially pretty
• 14:29
  - pedestrian in terms of just getting a file
• 14:32
  - from
• 14:33
  - this server to that server so it can
• 14:35
  - be appropriately faxed. But then now we are
• 14:37
  - also able to automatically route and then also
• 14:40
  - understand what's in the facts so a human
• 14:43
  - doesn't have to transcribe the facts once it
• 14:45
  - comes in.
• 14:47
  - So I think, again, investing in those types
• 14:50
  - of capabilities allows us to quickly solve a
• 14:52
  - problem
• 14:53
  - and then also enable a future
• 14:56
  - possibility. So, again, the problem solved was getting
• 14:59
  - the facts out, and the future opportunity is
• 15:02
  - making it more efficient by
• 15:04
  - learning what information is in the facts that
• 15:06
  - would be routed and then also transcribed. So
• 15:08
  - those sorts of things,
• 15:10
  - I think, we have to invest in so
• 15:11
  - we can holistically solve those types of problems.
• 15:15
  - That makes a ton of sense, and thank
• 15:16
  - you so much for going through that example.
• 15:18
  - I I think it truly shows, you know,
• 15:21
  - how taking that lens into a wide variety
• 15:24
  - of workflows and processes can make a big
• 15:26
  - difference even on some of the,
• 15:28
  - more mundane things, which is great.
• 15:31
  - For my last question here, I was wanting
• 15:33
  - to know, what are you most cue curious
• 15:35
  - about for the future? I think there's so
• 15:36
  - many different possibilities, but what do you wanna
• 15:39
  - dig deeper into?
• 15:41
  - Yeah. So so I think
• 15:42
  - the technology we're seeing,
• 15:45
  - come about and and also kinda leaning into
• 15:47
  - it as a,
• 15:49
  - you know, person and a team who needs
• 15:51
  - to be using the technology to create solutions
• 15:54
  - and to solve problems.
• 15:56
  - I think it really gives us an opportunity
• 15:58
  - to fundamentally change
• 16:00
  - how
• 16:01
  - patients and and their families
• 16:03
  - are experiencing us and kind of reshape
• 16:06
  - the front door of health care.
• 16:08
  - And and and what I mean by that
• 16:10
  - is historically,
• 16:12
  - access to,
• 16:13
  - care has been through portals, phone calls,
• 16:16
  - that sort of thing. So you go to
• 16:19
  - a a website,
• 16:21
  - you
• 16:21
  - try to,
• 16:23
  - book an appointment or you call someone.
• 16:25
  - But we now have the capabilities to finally
• 16:28
  - change that and and and really to create
• 16:30
  - that experience to be why
• 16:32
  - they come to us in the first place.
• 16:35
  - They come families come to Children's Mercy for
• 16:38
  - our know how, our clinical
• 16:41
  - expertise,
• 16:43
  - and and the best care we can provide
• 16:45
  - to
• 16:45
  - that family across the region.
• 16:49
  - We, with this technology,
• 16:51
  - can create, in essence, a sovereign AI
• 16:53
  - that is
• 16:55
  - our best practices
• 16:56
  - with their history
• 16:57
  - in a walled off version of
• 17:00
  - AI
• 17:01
  - that they can then ask questions of it
• 17:03
  - that then can allow them to guide us,
• 17:06
  - or we can allow
• 17:07
  - the AI to guide them through our services
• 17:10
  - that are appropriate
• 17:12
  - just as
• 17:13
  - a human would guide them through the practice.
• 17:15
  - So that that kind of thought process of
• 17:18
  - how does it reshape the front door of
• 17:20
  - health care
• 17:21
  - in a safe, protected
• 17:23
  - manner
• 17:24
  - is is one of the reasons why I
• 17:26
  - am investing in learning how to build with
• 17:28
  - AI myself and with my teams
• 17:31
  - because we can only do that because we're
• 17:33
  - the only
• 17:34
  - people who have access to our best practices,
• 17:37
  - are trusted,
• 17:38
  - with the patients,
• 17:39
  - and really create a safe and equitable way
• 17:42
  - of of doing that.
• 17:44
  - So I think fundamentally, the question is not
• 17:47
  - whether that will happen, but
• 17:49
  - how do we build it in a way
• 17:50
  - that can be trusted, clinically sound, and aligned
• 17:53
  - to how the care is actually delivered.
• 17:56
  - And if we can do that through a
• 17:57
  - sovereign AI,
• 17:59
  - I think that will be a game changer,
• 18:01
  - not just for technology's sake, but how
• 18:05
  - easy it is to navigate the complexities of
• 18:07
  - pediatric care.
• 18:09
  - So so really curious about how we balance
• 18:11
  - that choice and standardization
• 18:13
  - in the AI ecosystem,
• 18:16
  - and then how we think about all the
• 18:18
  - platforms that are emerging
• 18:19
  - and the organizations we need to decide to
• 18:21
  - standardize
• 18:22
  - with and where and and to also remain
• 18:24
  - flexible so we can drive that innovation forward.
• 18:28
  - So the I think the health systems that
• 18:29
  - get that balance right were the ones who'd
• 18:31
  - be able to move the fastest
• 18:33
  - while still maintaining that safety and trust. So
• 18:36
  - in other words, how do you know when
• 18:37
  - to leverage the tools to build something
• 18:40
  - versus a partner to lean into?
• 18:45
  - It's incredible to think about and, you know,
• 18:47
  - certainly so important to have that right balance
• 18:49
  - and and find the platforms and partners that
• 18:51
  - are gonna be most beneficial for moving this
• 18:54
  - vision forward. Brian, thank you so much for
• 18:56
  - joining us on the podcast today. This has
• 18:57
  - been such a fun conversation, so informative and
• 19:00
  - and thought provoking as well. I look forward
• 19:02
  - to speaking with you again soon, and I
• 19:04
  - know you'll be speaking at our health IT
• 19:06
  - and revenue cycle conference in September. And so
• 19:09
  - it'll be amazing to continue these conversations and
• 19:12
  - just dig a little bit deeper too into
• 19:13
  - some of the examples you provided and,
• 19:16
  - learn more. So I appreciate this time today
• 19:18
  - and look forward to seeing you soon.
• 19:20
  - Yeah. Well, thanks so much for the opportunity.
• 19:21
  - I really appreciate the time and the, thoughtful
• 19:24
  - questions.