Latest / Becker’s Healthcare Podcast / Building AI That Delivers Real Value in Rural Healthcare with Bob Berbeco

Transcript

Building AI That Delivers Real Value in Rural Healthcare with Bob Berbeco · Becker’s Healthcare Podcast

• 0:02
  - Every health system executive right now is being
• 0:04
  - asked to do something that has no useful
• 0:06
  - precedent,
• 0:07
  - make durable technology decisions in an environment that
• 0:10
  - looks meaningfully different every six months.
• 0:13
  - The pace isn't slowing,
• 0:14
  - the vendor landscape isn't getting simpler, and the
• 0:17
  - cost of missteps
• 0:18
  - keeps rising.
• 0:19
  - Becker's eleventh annual IT and Revenue Cycle Conference,
• 0:23
  - The Future of AI and Digital Health, exists
• 0:25
  - for exactly this challenge.
• 0:27
  - Here, you'll find more than 2,500 executive level
• 0:30
  - attendees,
• 0:31
  - 600 plus speakers, and four days of sessions
• 0:34
  - built around the questions leaders are actually wrestling
• 0:36
  - with.
• 0:37
  - How to scale AI responsibly,
• 0:39
  - how to protect increasingly complex systems,
• 0:42
  - how to wring more performance out of the
• 0:44
  - revenue cycle, and how to make tech investments
• 0:46
  - that hold up over time.
• 0:48
  - Join us September fourteenth through the seventeenth at
• 0:51
  - the Hilton Chicago.
• 0:53
  - You can register on our events page at
• 0:55
  - beckershospitalreview.com
• 0:57
  - by clicking on the events tab in the
• 0:59
  - upper right.
• 1:00
  - This is Laura Dierdo with the Becker's Healthcare
• 1:03
  - podcast. I'm thrilled today to be joined by
• 1:05
  - Bob Berbecco,
• 1:06
  - CIO of Mahaska Health in Iowa. Bob, it's
• 1:09
  - a pleasure to have you on the podcast
• 1:10
  - today. Pleasure to be here, Laura. Looking forward
• 1:13
  - to the discussion.
• 1:14
  - Absolutely. Now I'm excited to dig in. I
• 1:17
  - know there's so much going on in health
• 1:18
  - care, and technology is moving so, so quickly.
• 1:21
  - So I was always excited to speak with
• 1:23
  - CIOs like you to learn a little bit
• 1:24
  - more about how you're thinking about this technology
• 1:26
  - and what's next on your docket. But before
• 1:29
  - we dive in, can you tell us a
• 1:30
  - little bit more about yourself and Mahaska Health?
• 1:32
  - Yeah. Absolutely. So
• 1:35
  - I am the CIO here at Mahaska Health.
• 1:38
  - I lead
• 1:39
  - everything
• 1:40
  - when it comes to technology here. So you
• 1:43
  - have IT,
• 1:44
  - keep the lights on type activities.
• 1:46
  - You have data science. You have artificial intelligence,
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  - cybersecurity,
• 1:51
  - and informatics.
• 1:52
  - And where my role sits, you know, historically,
• 1:55
  - the CIO role, even in health care, was
• 1:58
  - very focused on people, lights on, servers,
• 2:00
  - help desk.
• 2:01
  - Nowadays, it's it's morphed into more than that.
• 2:04
  - And so where my role is now is
• 2:07
  - I'm at the intersection
• 2:09
  - of patient care, operational efficiency,
• 2:13
  - operational excellence,
• 2:14
  - and then responsible
• 2:16
  - innovation in terms of delivering to the needs
• 2:18
  - of not only our patients, but our clinicians
• 2:20
  - and our physicians.
• 2:23
  - And, a little bit on Mahaska Health.
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  - We're a rural health care
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  - delivery organization.
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  - We're a critical access hospital here in Hossaloosa,
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  - Iowa.
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  - And,
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  - that
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  - directs
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  - where I look. I look to be practical,
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  - supportable,
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  - and very tied to the workflow value of
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  - what we're trying to get accomplished here. With
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  - rural hospital, there's not a lot of resources,
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  - a lot of money, so you have to
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  - be very focused on what delivers value.
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  - And what really drove drove me to be
• 2:58
  - here and in health care in general is
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  - just the mission. The mission drives me. It's
• 3:03
  - it's very meaningful,
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  - opportunity to have impact on patients, clinicians,
• 3:09
  - and team members. I I truly enjoy it.
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  - I love that. I think it's such a
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  - special place when you're able to, you know,
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  - find that community. Mhmm. And especially in rural
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  - health care is a a uniqueness to it.
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  - So being able to be in that space,
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  - understand what the resources are, what the community
• 3:26
  - needs, and how you can actually,
• 3:28
  - deliver,
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  - those two things are are really critical, and
• 3:32
  - especially right now as technology evolves quickly. And
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  - I know it's not cheap to bring in
• 3:36
  - some of these systems and,
• 3:38
  - different types of functionalities.
• 3:39
  - So from your perspective, what are some of
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  - the most powerful forces that are shaping digital
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  - health and IT,
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  - within the health system, and how do you
• 3:48
  - anticipate they're gonna change in the next year
• 3:50
  - or so?
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  - Yeah. I love it. I love it. So
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  - to set context,
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  - for the organization
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  - here is I I've created a three year
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  - strategic plan that focuses on digital technology
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  - and AI initiatives
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  - based upon based upon the strategic plan of
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  - our organization.
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  - And from that,
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  - we have some tactical plans
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  - that are decomposed from the strategic plan that'll
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  - drive what we're looking to get accomplished over
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  - the next few years. Now sometimes,
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  - you know, you have those strategic plans and
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  - sometimes sometimes,
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  - something comes in from the side.
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  - You look to incorporate it as it does.
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  - I would say, like, the powerful forces shaping
• 4:31
  - what we're looking to get accomplished today
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  - is
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  - how do we reduce clinician burden?
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  - How do we ensure that the data that
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  - we're using and sharing
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  - and working with is
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  - trusted.
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  - When we talk about AI, I'm very focused
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  - on
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  - the AI pieces that are workflow
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  - native
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  - AI. And that's
• 4:56
  - as we embed AI into our processes, whether
• 4:59
  - it's revenue cycle, whether it's clinician,
• 5:03
  - whether it is patient interactions,
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  - there needs to be, trust
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  - and there needs to be value in how
• 5:10
  - that AI is embedded so it's delivering to
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  - those needs.
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  - And,
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  - others,
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  - cybersecurity,
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  - that's a huge one in healthcare. It just
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  - keeps growing and growing and,
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  - you have to you have to be very
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  - focused there.
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  - And
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  - in rural
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  - and it's crossed like that in healthcare everywhere.
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  - But in rural, we have to be very
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  - practical.
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  - The balance of how much it costs versus
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  - the value that we're looking
• 5:38
  - to to use for it.
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  - So on the IT side,
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  - our road map is very centered on,
• 5:45
  - defining enterprise KPIs. What are we looking to
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  - get accomplished?
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  - We have a data governance council and data
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  - catalog.
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  - We're also looking to improve our provider experience
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  - through quick production
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  - and,
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  - modernizing
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  - like, it's interesting.
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  - There's so many different facets. Right? So the
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  - other piece too is as we're doing these
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  - things, we have to modernize our our infrastructure.
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  - We have to make sure that it is
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  - all up to date to be able to
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  - deliver it to the need.
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  - And in in line, continuing to strengthen our
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  - cyber security,
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  - our incident response,
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  - zero trust roadmap.
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  - So
• 6:25
  - getting back to AI,
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  - I'll jump back to AI,
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  - is
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  - we are
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  - moving from we we were doing
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  - experiments,
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  - and now we're being more intentional,
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  - and we're looking to expand on some of
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  - what we were experimenting with. So we're doing
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  - the ambient documentation and visit summaries,
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  - predictive alerts,
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  - ED radiology
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  - triage pilots,
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  - telehealth,
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  - no show predictions,
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  - cost centers denial forecasting,
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  - and then at some point, we'll do predictive
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  - staffing.
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  - And as we do these, like, we're making
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  - sure that
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  - there's human in the loop, you know, we're
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  - modeling these. We're also ensuring that the processes
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  - that the AI is going to be augment
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  - is the processes are mapped out. Processes are
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  - well known. So you can determine how AI
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  - is gonna be embedded.
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  - So I think in the end I I
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  - said a lot.
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  - I I think in the end,
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  - you know, the evolution, we're we're doing a
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  - lot in technology,
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  - but it's a lot of discipline too. So
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  - we're being very disciplined in data,
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  - AI, digital tools,
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  - and and using other technologies that we have
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  - available to us to
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  - improve
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  - clinician time, improve access,
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  - improve the overall experience for our patients,
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  - and then have measurements
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  - around so that we can see the value
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  - that it's bringing to our organization.
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  - That makes a lot of sense, you know,
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  - and and it is really an important journey
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  - for all health care organizations
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  - to be on. I I'm curious from your
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  - perspective and,
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  - you know, being in a rural setting especially,
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  - as you're looking to navigate a lot of
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  - the more techno
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  - technology forward
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  - initiatives, thinking about governance and and thinking about
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  - actually,
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  - you know, deploying them among staff and patients
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  - as well.
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  - How do you see, you know,
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  - really kind of having to craft the argument
• 8:29
  - and then the implementation
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  - in a way that makes sense to put
• 8:33
  - resources towards the technology and then make sure
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  - that it's as valuable as you hoped it
• 8:38
  - would be at the end of the day?
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  - Wow. That's a that's a really, really good
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  - in-depth question.
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  - And and I think
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  - how I look at that is it comes
• 8:49
  - down to having a demand management strategy.
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  - So as you're evaluating
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  - technologies,
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  - as you're weighing
• 8:58
  - what needs to be incorporated into your environment,
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  - you have to have a master strategy around
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  - how you are going to prioritize,
• 9:08
  - how you're gonna embed those,
• 9:10
  - how,
• 9:12
  - as as
• 9:13
  - solutions come forward,
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  - how are you gonna be able to determine
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  - the value of those on the onset?
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  - And then I think you touched on it.
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  - You know, how do you determine the ROI
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  - at the end?
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  - So
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  - so how how I look to do this
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  - here at Mahaska
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  - and other places I worked at is I
• 9:34
  - start with demand management.
• 9:36
  - So demand management
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  - is the method of IT. Demand is everywhere.
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  - You're you're literally in the middle and everything
• 9:44
  - is coming at you. So you make that
• 9:46
  - into a funnel.
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  - And
• 9:49
  - as those ideas are coming your way, the
• 9:52
  - potential solutions
• 9:54
  - or even strategies, you bring those into the
• 9:57
  - funnel, you weigh those,
• 9:59
  - you,
• 10:01
  - look at the
• 10:02
  - strategic roadmap for the organization, determine how those
• 10:05
  - are prioritized there,
• 10:07
  - and then you take them down the path
• 10:09
  - of incorporating them or or getting them to
• 10:11
  - a solution state.
• 10:13
  - The real key though, you mentioned measurement,
• 10:16
  - the key is is as you're doing those
• 10:18
  - things,
• 10:19
  - you need to have what are the methodologies
• 10:22
  - that you are going to use to determine
• 10:24
  - what the ROI is. And it can be
• 10:27
  - green dollars,
• 10:28
  - which are true dollars, like actual money,
• 10:32
  - or it could be blue dollars,
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  - which
• 10:35
  - a lot of a lot of what you
• 10:37
  - do with technology and health care tends to
• 10:39
  - be blue dollar related.
• 10:41
  - So,
• 10:43
  - those could be
• 10:44
  - reducing
• 10:45
  - the amount of time in a workflow, reducing
• 10:48
  - time in interactions to an EMR, those types
• 10:51
  - of things.
• 10:53
  - And
• 10:54
  - each solution,
• 10:56
  - each idea that you have as you take
• 10:58
  - us through the demand management process,
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  - you have to, at that
• 11:03
  - point of framing it,
• 11:06
  - determine
• 11:07
  - what is the value of the direction we're
• 11:09
  - looking to go,
• 11:11
  - and how are we gonna measure it. And
• 11:13
  - then try to decompose that into how do
• 11:16
  - you measure the green value of it, how
• 11:19
  - do you measure the blue doll dollar value
• 11:22
  - of it,
• 11:23
  - and at the end like, where the endpoint
• 11:25
  - is, how are you gonna be able to
• 11:27
  - measure
• 11:28
  - ongoing
• 11:30
  - that you're getting a return on value, return
• 11:33
  - on investment.
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  - And,
• 11:35
  - that is
• 11:37
  - yeah. That was that was a really good
• 11:38
  - question.
• 11:40
  - Well, thanks so much. Yeah. I mean, I
• 11:42
  - I think it's one of those things that,
• 11:45
  - really
• 11:47
  - is a point of conversation for so many
• 11:49
  - CIOs and,
• 11:51
  - c suite leaders for hospitals and health systems
• 11:53
  - in general because,
• 11:55
  - there's not really a standard blueprint right now.
• 11:58
  - It seems like so many leaders are trying
• 12:00
  - to figure things out and match what makes
• 12:03
  - sense for their own organizations, but it's just
• 12:05
  - fascinating to hear about how you're thinking about
• 12:07
  - it. It seems like you've got,
• 12:09
  - you know, a strong and thoughtful plan,
• 12:12
  - in place. And so, you know, in that
• 12:15
  - vein, when you think about the last year
• 12:17
  - or so, can you tell us about a
• 12:19
  - big swing you took,
• 12:20
  - that paid off? What did you do and
• 12:22
  - what were the results?
• 12:24
  - Yeah.
• 12:25
  - Yeah. Okay.
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  - So I would say over the past year,
• 12:29
  - and and it's actually still ongoing.
• 12:32
  - One of the biggest swings that we took,
• 12:34
  - and this actually goes a little bit further
• 12:36
  - than a year,
• 12:38
  - is
• 12:39
  - we so
• 12:41
  - a year and a half ago, you know,
• 12:43
  - AI's got all the buzz.
• 12:45
  - And so AI comes at you from all
• 12:47
  - these different directions. Hey, we could do this,
• 12:49
  - we could do that.
• 12:50
  - And we were evaluating
• 12:52
  - it's like before we we
• 12:54
  - and this is a lesson learned for Ross.
• 12:56
  - It's before
• 12:58
  - we,
• 13:00
  - we didn't really encapsulate what
• 13:04
  - what needs were out there. So we were
• 13:07
  - evaluating AI just based upon the AI that
• 13:10
  - was tossed in our direction, but we didn't
• 13:12
  - really get a good handle operationally on what
• 13:15
  - would we use AI for. So so long
• 13:18
  - story short,
• 13:20
  - one of the big swings we took is
• 13:22
  - we just stepped away from isolated bolt on
• 13:25
  - AI pilots.
• 13:26
  - We had some in in motion.
• 13:28
  - We decided to stop those,
• 13:31
  - and
• 13:31
  - we stepped back to process.
• 13:35
  - So
• 13:36
  - let's replace
• 13:37
  - the approach that we had. We wanna be
• 13:39
  - intentional.
• 13:41
  - We want it to be a governed
• 13:43
  - workflow
• 13:44
  - type approach.
• 13:45
  - We wanna have a process around it. And
• 13:47
  - so we we ended up with a
• 13:50
  - center of excellence that was focused on AI,
• 13:54
  - like a brainstorming group, where a few of
• 13:56
  - us get together and we talk about what
• 13:58
  - are the opportunities that we have in our
• 13:59
  - organization that AI could be good at.
• 14:02
  - And that has helped us a lot. That's
• 14:04
  - the first start. Just start with that need
• 14:06
  - and assess that need. Determine where do you
• 14:09
  - wanna focus.
• 14:10
  - The next one was is and this is
• 14:12
  - the bigger swing.
• 14:14
  - We're building our own AI.
• 14:18
  - So
• 14:19
  - so there's two two places that we're we're
• 14:21
  - gonna focus our efforts. One is Epic is
• 14:23
  - coming out. So Epic is what we use.
• 14:25
  - Epic is coming out with,
• 14:27
  - three big focus areas. One's Penny, one's Emmy,
• 14:31
  - the other one's Art. Those are all focused
• 14:32
  - on different different,
• 14:34
  - functional aspects of AI within their platform.
• 14:38
  - And beyond that, we are piloting our own
• 14:41
  - AI system
• 14:42
  - where we're building it internally.
• 14:44
  - It's,
• 14:46
  - I'm blessed to have someone here on-site that
• 14:48
  - actually has a lot of experience doing these
• 14:50
  - things, so he's building it. And we're gonna
• 14:52
  - focus on things like,
• 14:56
  - mostly insurance,
• 14:58
  - denial reduction,
• 14:59
  - knowledge base,
• 15:01
  - kind of a staff augmentation for our coding
• 15:04
  - people. So not using AI to replace anyone,
• 15:07
  - but using AI to augment knowledge that we
• 15:10
  - have with our coding and the processes that
• 15:12
  - we have within our coding. There's much more
• 15:15
  - to come there. We're still in the process
• 15:16
  - of building it. But that's that's the biggest
• 15:18
  - swing. We've we're building our own thing.
• 15:23
  - That's really impressive. I think, you know, especially
• 15:25
  - when you look at,
• 15:27
  - building AI is not easy, and it takes
• 15:29
  - a skill set, that, you know, didn't exist
• 15:32
  - maybe even five years ago for many hospitals
• 15:34
  - and health systems and trying to bring in,
• 15:37
  - the knowledge and and skills and technology,
• 15:40
  - to to build AI from within. So what
• 15:42
  - has that been like, trying to compile the
• 15:44
  - team, or was it really upscaling who you
• 15:47
  - have?
• 15:48
  - I would say it's it that's another good
• 15:51
  - so
• 15:52
  - I would say it was more upscale.
• 15:54
  - So we have a team. This is what's
• 15:56
  - really cool, and I'm gonna I'm gonna go
• 15:58
  - off topic for a sec second when it
• 16:00
  - comes to organization.
• 16:01
  - Within organization,
• 16:03
  - you have to be mindful of the fact
• 16:05
  - that you have some really talented people within
• 16:07
  - in your organization
• 16:09
  - that may be doing something
• 16:11
  - that is is specialized,
• 16:13
  - but they actually have talents elsewhere.
• 16:17
  - We've learned that here at Mahaska Health. The
• 16:19
  - person who is building
• 16:22
  - our AI system
• 16:23
  - has a clinical
• 16:25
  - is a nurse practitioner.
• 16:27
  - So he has a clinical background.
• 16:30
  - And so you could kinda put him in
• 16:32
  - that box and say, this is only someone
• 16:34
  - who does clinical stuff.
• 16:36
  - So we're, you know, we're gonna keep them
• 16:38
  - in the box. But we noticed the talent
• 16:41
  - and the interest
• 16:43
  - that this person had.
• 16:44
  - So let's go ahead and give them resources.
• 16:47
  - Let's feed that knowledge,
• 16:49
  - feed that interest,
• 16:51
  - feed that passion they have, and we're we're
• 16:53
  - realizing the benefits of it.
• 16:56
  - That's really cool to hear and such a
• 16:58
  - great reminder of the talent that surround you
• 17:00
  - and ways to look from within,
• 17:02
  - and the way to keep growing and building
• 17:04
  - as the organization evolves. And, you know, speaking
• 17:07
  - of that evolution, what do you see as
• 17:09
  - being the most important problem you're trying to
• 17:11
  - solve with AI or technology right now? And
• 17:13
  - will that continue to be the case in
• 17:15
  - the future, do you think?
• 17:17
  - Yeah. I would say that the biggest problem
• 17:19
  - that we're solving with AI right now is
• 17:22
  - how do we make technology more useful
• 17:25
  - and less burdensome
• 17:27
  - for the people who use it,
• 17:29
  - especially in rural health.
• 17:31
  - So
• 17:32
  - my focus right now is we have clinicians,
• 17:35
  - we have physicians,
• 17:36
  - we have staff, we have coding people, we
• 17:38
  - have team members. They're all using the EMR
• 17:41
  - system, and there's a lot of things that
• 17:43
  - they're doing that's very manual.
• 17:45
  - And,
• 17:46
  - I think it goes without saying, but I'll
• 17:48
  - say it, is
• 17:49
  - humans typically aren't very good at repetitive. Like,
• 17:52
  - we we tend to make mistakes.
• 17:54
  - Systems tend to be better at that. So
• 17:57
  - how do we the most important problem we're
• 17:59
  - trying to solve with AI now is reduce
• 18:03
  - the
• 18:04
  - the friction,
• 18:05
  - reduce the amount of time that people are
• 18:08
  - having to take using our systems
• 18:10
  - by making
• 18:12
  - certain things more automated.
• 18:14
  - So where AI systems can embed themselves to
• 18:17
  - be more automated,
• 18:19
  - we will do that.
• 18:20
  - And then where the people
• 18:23
  - can focus their efforts
• 18:25
  - on their cognitive knowledge and apply the the
• 18:28
  - cognitive
• 18:29
  - knowledge set to what they're doing, they can
• 18:32
  - do that. And so, I know human in
• 18:34
  - the loop tends to be something that's talked
• 18:36
  - about and you see it a lot and
• 18:38
  - it's it's out there.
• 18:40
  - And, I mean, we we are looking to
• 18:42
  - apply that. Is,
• 18:43
  - you know, the big fear is AI can
• 18:47
  - I mean, I think the big fear out
• 18:48
  - there is AI is gonna replace everyone's jobs?
• 18:50
  - No. Not necessarily.
• 18:52
  - What we're looking to do here is let's
• 18:54
  - apply AI
• 18:55
  - where it's best in in
• 18:58
  - repetitive actions, in knowledge,
• 19:00
  - and,
• 19:02
  - things that can reduce
• 19:03
  - clicks and reduce interactions within EMI.
• 19:07
  - Or, like, for denials, how do we how
• 19:09
  - do we make that better? How do we
• 19:11
  - do predictions and improve revenue cycle performance?
• 19:15
  - In line with that is we apply people.
• 19:18
  - So people would be there to, you know,
• 19:20
  - whatever the AI system's doing, we're gonna have
• 19:22
  - people who are going to to look it
• 19:25
  - over and then weigh whether that is the
• 19:27
  - action you wanna take.
• 19:29
  - And they can focus their efforts on on
• 19:31
  - those things, where,
• 19:34
  - people can be better. Actually,
• 19:36
  - something
• 19:38
  - simple is is relationships
• 19:40
  - as well. People are have cognitive thought, and
• 19:43
  - people are good at relationships.
• 19:46
  - It makes a lot of sense because that,
• 19:47
  - you know, that
• 19:48
  - is
• 19:49
  - another central question I think a lot of
• 19:51
  - organizations are working through in healthcare and otherwise
• 19:53
  - is, you know, where are the ways that
• 19:55
  - you can deepen relationships and have that human
• 19:58
  - to human interaction and health care being such
• 20:00
  - a human centric business?
• 20:03
  - It it seems like
• 20:04
  - there still is so so much that,
• 20:07
  - the
• 20:08
  - that human relationship needs to be able to
• 20:10
  - do.
• 20:11
  - I agree. I agree. I I think humans,
• 20:14
  - we can be positioned to do
• 20:16
  - more than repetitive and not not to minimize
• 20:20
  - what a machine can do, but
• 20:22
  - if we can leverage
• 20:23
  - the benefits
• 20:24
  - and the advantages and the pros of an
• 20:27
  - AI based system
• 20:28
  - and blend that with the pros
• 20:31
  - of a
• 20:32
  - a human
• 20:34
  - and and reduce the cons, mitigate whatever potential,
• 20:38
  - issues
• 20:39
  - come with both. You know, we we achieve
• 20:42
  - the best of both. And that's that's what
• 20:45
  - we're we're really looking to do as we're
• 20:47
  - employing AI here is, how can we use
• 20:49
  - AI to augment staff knowledge,
• 20:51
  - augment staff process,
• 20:53
  - and and augment their ability to get, you
• 20:56
  - know, be be more efficient with less burden
• 20:58
  - for them.
• 21:00
  - I love that. That that's a really strong
• 21:03
  - philosophy and definitely will be fascinating.
• 21:05
  - I had to see,
• 21:07
  - the spaces where the workforce, especially in health
• 21:09
  - care, continues to evolve.
• 21:11
  - And before we wrap up here, I wanted
• 21:13
  - to ask, what are you most curious about
• 21:16
  - for the future?
• 21:18
  - Yeah. This is just a really good question.
• 21:20
  - And I would say, what I'm most curious
• 21:22
  - about,
• 21:24
  - professionally
• 21:25
  - and personally,
• 21:26
  - is whether AI is ultimately gonna make us
• 21:29
  - more human or tempt us to to outsource
• 21:31
  - too much of what matters
• 21:33
  - to be human.
• 21:35
  - And so the the deeper question for me
• 21:37
  - is
• 21:38
  - how people
• 21:40
  - are gonna adapt
• 21:42
  - once AI becomes part of their lives. Like
• 21:44
  - an ordinary thing. Kinda like the web.
• 21:47
  - Back in the day when we didn't have
• 21:48
  - the web, went to the web, there's dynamic
• 21:51
  - shift and change in in how we interacted.
• 21:55
  - And and I I'm curious how that's gonna
• 21:58
  - be, because that'll be a big shift. And
• 22:01
  - so my hope
• 22:02
  - is that
• 22:04
  - we continue to adapt
• 22:07
  - by becoming better at judgment,
• 22:10
  - curiosity,
• 22:12
  - ethics,
• 22:14
  - and the human connection.
• 22:16
  - Because that's what makes us
• 22:17
  - special, is that is that human connection.
• 22:20
  - And not by surrendering those things.
• 22:23
  - Because the future that I
• 22:26
  - hope to see and wanna help build is
• 22:28
  - where technology
• 22:29
  - strengthens
• 22:31
  - inner human connections
• 22:33
  - and the sense of community
• 22:35
  - rather than displacing it
• 22:37
  - or or losing it.
• 22:40
  - Absolutely. I I think that's such a a
• 22:42
  - powerful sentiment and and certainly one that as
• 22:44
  - we're looking into the future to hold on
• 22:46
  - to where that technology integration happens and Mhmm.
• 22:49
  - How you can really, make the most of
• 22:52
  - the opportunities that you have.
• 22:54
  - Well, thank you so much, Bob, for joining
• 22:55
  - us on the podcast today. This has been
• 22:57
  - such an amazing conversation, and I think really
• 23:00
  - thought provoking and also
• 23:02
  - inspiring to hear about all the things that
• 23:04
  - you're doing at Mahaska Health. Thanks again for
• 23:06
  - your time, and I look forward to connecting
• 23:07
  - with you and catching up in person at
• 23:09
  - our health IT and revenue cycle conference coming
• 23:11
  - up in September. I know you'll be speaking
• 23:13
  - on a panel, so we'll dig deeper into
• 23:15
  - some of these themes there and just,
• 23:17
  - really stay on the forefront of everything that's
• 23:19
  - happening in technology, AI, and health
• 23:22
  - care today. I love it. Thank you, Laura.
• 23:24
  - I really appreciate the opportunity to,
• 23:26
  - have a conversation with you.