Latest / Becker’s Healthcare Podcast / Inside Children’s Healthcare of Atlanta’s 2 Million Square Foot Smart Hospital with Jeremy Meller

Transcript

Inside Children’s Healthcare of Atlanta’s 2 Million Square Foot Smart Hospital with Jeremy Meller · Becker’s Healthcare Podcast

• 0:00
  - Welcome to the Becker's Healthcare Podcast. I'm Chris
• 0:02
  - Losa, your host, and I'm thrilled today to
• 0:04
  - be joined by Jeremy Mellor. He's the chief
• 0:06
  - information officer of Children's Healthcare of Atlanta.
• 0:09
  - Jeremy, thank you for joining us today. Oh,
• 0:11
  - so happy to be here, Chris.
• 0:13
  - Fantastic. Well, you're here to discuss the lessons
• 0:15
  - learned since the Arthur M. Blank Hospital opened
• 0:18
  - in September
• 0:19
  - 2024.
• 0:20
  - But before we get into all that, could
• 0:21
  - you please just introduce yourself
• 0:23
  - and give us a little bit about your
• 0:25
  - background?
• 0:26
  - Sure. You bet. I'm, Jeremy Mellor, the chief
• 0:28
  - information officer for Children's Healthcare of Atlanta, like
• 0:30
  - you said.
• 0:32
  - I've been the chief information officer here for
• 0:34
  - a little over six years, and I've been
• 0:36
  - with children
• 0:37
  - for going on fourteen years. And so I've
• 0:39
  - been
• 0:40
  - with us as we move to the entire
• 0:42
  - planning phase of the new hospital, really, which
• 0:44
  - has been, you know, a ten plus year,
• 0:48
  - journey,
• 0:49
  - up into the present day. And, and it's
• 0:51
  - just it's been super exciting.
• 0:54
  - Yeah. Obviously, that was a massive undertaking that
• 0:56
  - you guys had a couple years ago, and
• 0:58
  - I'm glad it went as smoothly as it
• 0:59
  - did. So now that you've been at this,
• 1:01
  - like we said, since about September
• 1:04
  - 2024,
• 1:05
  - what would you say were the main challenges
• 1:07
  - you anticipated when the hospital opened, and how
• 1:09
  - those played out so far?
• 1:11
  - Sure. Yeah. Well, you know, like I said,
• 1:13
  - we started the planning,
• 1:16
  - many years ago. I mean, from just a,
• 1:19
  - you know, facility perspective,
• 1:21
  - we were planning out the real estate. We
• 1:24
  - were buying up properties.
• 1:25
  - We were tearing down old properties and that
• 1:28
  - sort of thing. And, really, we kicked off
• 1:30
  - right when the pandemic started.
• 1:32
  - Really was when we broke ground and we
• 1:34
  - started to raise the building. But even a
• 1:36
  - year or two before that, we were starting
• 1:38
  - to plan, okay, what what does the patient
• 1:41
  - experience need to look like?
• 1:43
  - What are,
• 1:45
  - what are the challenges
• 1:47
  - that are present today that we wanna address?
• 1:50
  - So one of the things we did to,
• 1:52
  - address that was we rented out a 100,000
• 1:54
  - square foot facility, and we created
• 1:57
  - what we called cardboard city. And we, had
• 2:00
  - cardboard layouts,
• 2:02
  - easily movable walls,
• 2:05
  - that we could use to simulate
• 2:08
  - different spaces, whether it be hallways, whether it
• 2:11
  - be trauma rooms, whether it be operating rooms.
• 2:14
  - And that allowed us to then do
• 2:16
  - simulations
• 2:17
  - and rehearsals in that space and say, hey.
• 2:20
  - How does that work?
• 2:21
  - And, I mean, certainly, that leads to all
• 2:23
  - sorts of things. You can see, well, alright.
• 2:26
  - You know, the that wall plug isn't where
• 2:28
  - it needs to be, and that door isn't
• 2:30
  - where it needs to be, and this room
• 2:32
  - isn't big enough to hold the 12 people
• 2:33
  - that need to be here in order to
• 2:35
  - to deal with this kind of trauma or
• 2:37
  - whatever it is.
• 2:39
  - You know? But one of the things it
• 2:40
  - did for me
• 2:41
  - is as I was going through that facility,
• 2:44
  - I was just struck by how much larger
• 2:47
  - this,
• 2:48
  - facility was gonna be than our existing facility.
• 2:50
  - You know, a lot of intensive care units,
• 2:52
  - pediatric intensive care units historically are, for example,
• 2:55
  - open bays. And where we were going with
• 2:58
  - this was we were creating, you know, individual
• 3:00
  - standardized rooms for everybody, which is great from
• 3:03
  - a patient experience perspective. But as you might
• 3:05
  - imagine, that really blows out the size of
• 3:07
  - the facility.
• 3:08
  - We ended up with a 2,000,000 square foot
• 3:10
  - facility,
• 3:12
  - nine 19 stories. And for and, you know,
• 3:16
  - so it it's absolutely
• 3:17
  - ginormous.
• 3:18
  - And
• 3:19
  - what struck me, I guess, was the fact
• 3:21
  - that it was just gonna take
• 3:23
  - longer to do everything. It's gonna take longer
• 3:25
  - to move around.
• 3:27
  - It's gonna take longer to communicate,
• 3:29
  - especially when you have to, you know, move
• 3:31
  - around to communicate.
• 3:33
  - So it really just reinforced
• 3:34
  - for us the fact that technology
• 3:37
  - had to bridge the gap in some of
• 3:39
  - that. It had to allow for easier communication
• 3:43
  - across distances, whether that be mobile technologies, whether
• 3:46
  - that be visual cues and that sort of
• 3:49
  - thing. And that's an example of something we
• 3:51
  - did
• 3:52
  - right from the start to meet where the
• 3:54
  - organization was going and try to help it
• 3:55
  - with technology.
• 3:57
  - The other areas we, considered were patient engagement.
• 4:00
  - We well, you know, honestly, we said, what
• 4:02
  - what are the what are the other biggest
• 4:03
  - challenges? One, I mean, you've got kids who
• 4:06
  - are, you know, coming to the hospital.
• 4:08
  - They're scared.
• 4:09
  - They would really just rather be at home.
• 4:11
  - Right? So how we,
• 4:13
  - engage with patients and keep patients and families
• 4:16
  - informed is really important.
• 4:18
  - Two,
• 4:19
  - we are just we are in data overload.
• 4:21
  - And especially with AI and everything on the
• 4:23
  - scene now, it's more important than ever to,
• 4:27
  - to be able to help clinicians,
• 4:30
  - you know, process massive massive amounts of information
• 4:33
  - and make better, more timely decisions. So we
• 4:36
  - really wanted to support
• 4:38
  - the clinician from the AI and data and
• 4:40
  - just, you know, complex decision making,
• 4:43
  - you know, perspective
• 4:45
  - as well.
• 4:46
  - And so, you know, those were a a
• 4:49
  - few of the and we we really wanted
• 4:50
  - to save steps at the end of the
• 4:52
  - day.
• 4:53
  - And so how can we do things that
• 4:55
  - are gonna
• 4:56
  - help save time? And those were the guide
• 4:59
  - the the really the big three guiding principles
• 5:02
  - that led us to where we made investments
• 5:04
  - across patient engagement. We made a lot of,
• 5:08
  - investment in location awareness and integrated that in
• 5:11
  - with the room technology,
• 5:13
  - a lot of work with, device integration to
• 5:15
  - drive AI.
• 5:17
  - We put cameras in every room,
• 5:19
  - to help with, like, real time monitoring and
• 5:21
  - remote consults and virtual nursing,
• 5:24
  - you know, and we layered AI into into
• 5:26
  - really everything. And so I think that that's,
• 5:29
  - you know, I I think we've had a
• 5:31
  - lot of payback from
• 5:33
  - those investments,
• 5:34
  - you know, and certainly
• 5:36
  - adoption. Anytime you change
• 5:38
  - a process or change the way somebody works,
• 5:40
  - you have to you have to think about
• 5:42
  - the change management and adoption. So that's really
• 5:44
  - what we spend a lot of our time
• 5:46
  - doing.
• 5:47
  - Yeah. The the scale of this hospital is
• 5:49
  - just mind blowing in a lot of ways.
• 5:51
  - And clearly,
• 5:52
  - as you said, you put
• 5:54
  - patient experience at at the top of list
• 5:56
  - and rightfully so, and you ended up with
• 5:58
  - this 2,000,000 square foot facility.
• 6:01
  - And so
• 6:02
  - take us through again just how
• 6:04
  - important it is to
• 6:07
  - use technology to make sure
• 6:09
  - there's less ground, you know, in the in
• 6:11
  - the literal and figurative senses that your staff
• 6:14
  - has to cover
• 6:15
  - and how you went about getting them acclimated
• 6:18
  - to that.
• 6:19
  - Sure. You know, and we took a kind
• 6:20
  - of a foundation from the bottom up approach,
• 6:22
  - and
• 6:23
  - we looked at what the available technologies are.
• 6:26
  - And so I mentioned, for example, location awareness.
• 6:28
  - Well, every
• 6:30
  - one of our,
• 6:31
  - staff members in the hospital, they wear a
• 6:33
  - location badge. We call it a tech badge.
• 6:35
  - And that has a number of purposes. Now
• 6:37
  - one,
• 6:38
  - it can help with,
• 6:40
  - you if you press the buttons on the
• 6:41
  - back, it will silently let security know where
• 6:44
  - you're at. So if you've got a, you
• 6:46
  - know, a staff to rest situation where you've
• 6:48
  - got a patient or a family member,
• 6:51
  - and you're you feel unsafe,
• 6:53
  - that's so it's really a safety device.
• 6:55
  - But we can do so much more with
• 6:57
  - it. Just recently, we did some contract tracing
• 7:00
  - with it. We needed to know who's in
• 7:01
  - the room
• 7:02
  - with a particular patient who had a particular
• 7:05
  - condition.
• 7:06
  - And so it can give us that data.
• 7:08
  - But beyond that,
• 7:10
  - you know, it allows us to integrate in
• 7:12
  - with everything else that we have. And when
• 7:14
  - I talked about, like, being able to save
• 7:16
  - save steps,
• 7:17
  - we have, for example, wall boards outside of
• 7:20
  - every door,
• 7:22
  - every room where if a nurse walks in,
• 7:25
  - you get a halo light of a certain
• 7:27
  - color. If a respiratory therapist walks in, you
• 7:29
  - get a different halo light. If a physician
• 7:31
  - walks in, you get a different color halo
• 7:33
  - light.
• 7:34
  - If there's multiple in there, it'll alternate between
• 7:36
  - halo lights. So you think about that, and
• 7:38
  - that's a visual cue.
• 7:39
  - It isn't uncommon that, a, you know, a
• 7:43
  - nurse or another physician will be like, okay,
• 7:46
  - where did doctor so and so go? Or
• 7:48
  - are they on the floor? And you could
• 7:49
  - just look down the hall and you can
• 7:50
  - see exactly where they're at in a in
• 7:52
  - a in a moment's notice.
• 7:54
  - And and so there's just a lot of
• 7:56
  - use cases like that. When you and you
• 7:57
  - enter in the room, one of our patient
• 7:59
  - engagement,
• 8:00
  - innovations where that we have multiple screens. So
• 8:02
  - we have, you know, of course, one screen
• 8:04
  - is for entertainment and videos and education and
• 8:07
  - another screen that's an electronic whiteboard
• 8:10
  - that certainly shows, you know, who your care
• 8:13
  - team is, what your plan for the day
• 8:15
  - is, etcetera.
• 8:16
  - But it allows,
• 8:18
  - when a clinician walks in the room, it
• 8:20
  - knows that a clinician walked in the room
• 8:21
  - because of that location badge. And it allows
• 8:24
  - them to change it to a clinical view
• 8:25
  - where they can see more detailed clinical stats.
• 8:28
  - They can pull up radiology
• 8:30
  - exams. They can blow them up and draw
• 8:32
  - on them and share them with the patient
• 8:34
  - and family, which is something that, you know,
• 8:36
  - our our providers do
• 8:38
  - quite often. And so it's so this is
• 8:40
  - just an example of how you if when
• 8:43
  - you think about the foundational technology and how
• 8:45
  - you can use in innovative ways, you can
• 8:47
  - do a lot more with it than you
• 8:48
  - thought you could.
• 8:49
  - I love all these details that you're sharing
• 8:51
  - with us, Jeremy. You know? I'm sure our
• 8:53
  - audience is gonna love how they'll be able
• 8:55
  - to adapt these to their own facilities, at
• 8:57
  - least I hope so.
• 8:59
  - So you've listed so many of these wonderful
• 9:01
  - features. Are there anything else that you can
• 9:03
  - think of where you think of, you know
• 9:05
  - what? The the clinicians, you know, any member
• 9:08
  - of the SAS, like, they really love using
• 9:10
  - this, and I'm so glad we added that.
• 9:12
  - Yeah. I mean,
• 9:14
  - it it it didn't, it didn't just stop
• 9:16
  - there, of course. I mean, one of the
• 9:18
  - other really big things that we did was
• 9:20
  - we, we brought robots into the hospital, and
• 9:23
  - these are autonomous delivery robots.
• 9:26
  - We're actually,
• 9:28
  - have one of the world's largest fleet of
• 9:30
  - these,
• 9:31
  - autonomous robots in health care. We have 90
• 9:34
  - robots,
• 9:35
  - in our hospital
• 9:36
  - delivering everything from meds
• 9:39
  - to supplies
• 9:40
  - to patient meals to medical equipment, then it'll
• 9:43
  - haul trash,
• 9:45
  - in dirty linens.
• 9:47
  - And, and so I think that that's had
• 9:49
  - a a really positive effect as well. I
• 9:51
  - mean, these things run like clockwork. So,
• 9:55
  - so timely,
• 9:56
  - and consistent delivery of medications,
• 10:00
  - and meals and supplies,
• 10:03
  - the the better the more we can do
• 10:04
  - with that, the the the less of the
• 10:06
  - the burden that the clinician has to feel
• 10:08
  - around those things. And hopefully, the whole system
• 10:11
  - just works works a little bit better. So
• 10:13
  - I think that was another,
• 10:16
  - pretty big win as well. And then, I
• 10:18
  - had mentioned the cameras.
• 10:20
  - We have, we've been running and it's just
• 10:22
  - been extended a virtual nursing pilot where
• 10:26
  - we can handle admissions and discharges,
• 10:29
  - which are, you know, generally much more standardized,
• 10:33
  - and, and offload that from some of our
• 10:36
  - floor nurses who are really taxed. And on
• 10:38
  - some days, it can be really, really hard.
• 10:40
  - And so that's something that they've found that
• 10:42
  - they really,
• 10:44
  - appreciate a great deal. And and having the
• 10:46
  - cameras
• 10:46
  - and having a a more remote,
• 10:50
  - you know, virtual nurse just allows the process
• 10:53
  - to be just a whole lot more efficient.
• 10:56
  - Jeremy, tell us more about these robots in
• 10:58
  - particular. So how one, how do you think
• 11:01
  - or how have you seen
• 11:02
  - patients reacting to them? I mean, is this
• 11:04
  - something the kids enjoy seeing all these robots,
• 11:06
  - you know, floating around the hospital? I mean,
• 11:08
  - I've I've seen some of these at work
• 11:10
  - in in hotels without bringing your towels and
• 11:12
  - things like that. But, obviously, you have 90
• 11:14
  - throughout this entire facility. That's that's an enormous
• 11:17
  - sleep in my mind.
• 11:18
  - So, yeah, what's been the reaction to to
• 11:20
  - these robots?
• 11:22
  - You bet. Well, I mean, many of the
• 11:24
  - robots are just back of house robots. You
• 11:26
  - would never actually see them. They,
• 11:29
  - we have 12 elevators that are just for
• 11:31
  - our robots.
• 11:32
  - Wow. Okay. And so there's a and there
• 11:35
  - are depots on every floor, and there are
• 11:37
  - hallways, etcetera, that the robots use that are
• 11:40
  - a little bit outside of the patient care
• 11:42
  - areas. And that's where a lot of the
• 11:44
  - bulk supplies move. Where the patients may see
• 11:47
  - the robots are where they're delivering,
• 11:49
  - you know, medications and foods and sometimes,
• 11:53
  - select supplies.
• 11:55
  - And, and those robots are all wrapped in,
• 11:59
  - in, you know, a skin of some sort.
• 12:01
  - They may look like a look like, an
• 12:04
  - ambulance driving along with a couple of kids
• 12:06
  - at the driver's wheel. They may look like,
• 12:09
  - they may have our our dog our dogs
• 12:11
  - on them or whatever else. And so I
• 12:13
  - I think what we found is that the
• 12:14
  - kids are are are amused by the robots.
• 12:19
  - But, I mean, it it's a great question
• 12:21
  - because anytime you're introducing
• 12:23
  - anything new, you have to adapt to it.
• 12:26
  - And,
• 12:27
  - and so there's a fair amount of training
• 12:29
  - just for our staff on, okay, when a
• 12:31
  - robot's coming down the hall, what's it gonna
• 12:33
  - do and what what should you do if
• 12:34
  - a robot is, you know, going some play
• 12:36
  - if you feel like it's going some play
• 12:37
  - or you need it to stop, how do
• 12:39
  - you get it to stop?
• 12:41
  - And, and and those sorts of things as
• 12:43
  - well.
• 12:44
  - I imagine there are a lot of fun
• 12:45
  - things you can do with the robots at
• 12:46
  - Halloween as well. I'm I'm rather Right.
• 12:52
  - Yeah. Thanks thanks for all of this, Jeremy.
• 12:54
  - This is wonderful.
• 12:55
  - Next thing I wanna ask you though,
• 12:57
  - is now that you have been at this
• 12:59
  - for a little over a year and a
• 13:00
  - half as we've said, do you have any
• 13:01
  - advice that you would give to other hospitals,
• 13:04
  - health systems that now you've seen all this
• 13:06
  - cutting edge technology, you've been able to apply
• 13:08
  - it, you know. What what don't you tell
• 13:10
  - someone who who wants to pick your brain
• 13:11
  - about this? Sure. Yeah. I mean
• 13:14
  - and I'm not gonna pretend that we got
• 13:16
  - everything right. I mean, there were some things
• 13:18
  - that we invested in and we thought were
• 13:20
  - gonna be a big deal and weren't a
• 13:22
  - big deal. So Okay. An example of that
• 13:24
  - is,
• 13:25
  - on our mobile clinical phones that all the
• 13:28
  - nurses have, you can, for example, see waveforms,
• 13:32
  - off the monitor in the room, which is
• 13:34
  - a great thing.
• 13:35
  - And we thought that we'd noticed that the
• 13:37
  - utilization of that wasn't exactly what we thought
• 13:40
  - it would be.
• 13:41
  - And we thought, is something wrong? Is something
• 13:43
  - broke? Is this an educational opportunity? Well, you
• 13:46
  - know, it comes to comes to be that,
• 13:49
  - you know, the, the data that came along
• 13:51
  - with it, the text alerts, for example, giving
• 13:54
  - you information about it
• 13:57
  - really pre precluded the need there to have
• 13:59
  - the actual waveform on the phone. Now it
• 14:01
  - does have some utility, but for a lot
• 14:03
  - of people, it didn't. So that's an example
• 14:05
  - of something we thought was gonna be big,
• 14:07
  - which didn't turn out to be big.
• 14:09
  - And so I think you have to, one,
• 14:12
  - acknowledge that there may be some of that.
• 14:14
  - But if you, you know, start with, you
• 14:16
  - know, what are your, you know, grounding and
• 14:18
  - guiding principles? For us, it was saving steps,
• 14:21
  - supporting better decisions, and improving the patient experience.
• 14:24
  - It was those three. And so that was
• 14:26
  - the framework that we thought about what our,
• 14:29
  - needs were gonna be. Then we said, look.
• 14:31
  - Let's again, let's look at the foundation of
• 14:34
  - everything that we have.
• 14:36
  - There's a lot of you know, everyone's talking
• 14:38
  - about AI. But the thing is AI needs
• 14:41
  - data, right, in order for to do anything
• 14:44
  - with,
• 14:45
  - especially in a clinical setting.
• 14:47
  - And,
• 14:48
  - and that data needs to represent reality.
• 14:52
  - And so it's a representation
• 14:54
  - of reality that the computer can use to
• 14:56
  - do things like
• 14:58
  - understand, is this a patient who's deteriorating?
• 15:00
  - Is this a patient maybe who has an
• 15:02
  - infection that we're not recognizing, etcetera?
• 15:05
  - And so and that's a hard it turns
• 15:07
  - out that that's a really hard thing to
• 15:08
  - do.
• 15:09
  - But,
• 15:10
  - but you have to have the foundational
• 15:13
  - things in place. So
• 15:16
  - for us, we thought about having all we
• 15:18
  - have thousands of medical devices with all of
• 15:20
  - this data, whether it be monitors, pumps, etcetera,
• 15:23
  - getting all that data into the system and
• 15:25
  - building it from the ground up so we
• 15:26
  - had all of it. That was one. Two
• 15:29
  - was dislocation data. I mean, just the the
• 15:31
  - amount these are all data points and they're
• 15:33
  - all signals.
• 15:35
  - You know, how much activity there is going
• 15:37
  - around around a patient is actually an indicator
• 15:40
  - that could be used to understand,
• 15:42
  - is this a patient that, you know, really
• 15:44
  - should be, should be, you know, paid attention
• 15:46
  - to?
• 15:47
  - And, and things like camera, even even the
• 15:50
  - the visual. And there's a whole, you know,
• 15:52
  - you know, emerging field around visual AI. And
• 15:55
  - can you use,
• 15:57
  - visual to really understand better whether it's, you
• 16:00
  - know, the the relative motion of the patient
• 16:03
  - today compared to yesterday. And all of those
• 16:05
  - things, it can help you understand what's really
• 16:07
  - going on.
• 16:08
  - So that was another one.
• 16:11
  - Then we
• 16:12
  - another thing I would probably pass on is
• 16:14
  - that
• 16:15
  - now when we opened, we had we had
• 16:17
  - we had staffed, I wanna say, like, a
• 16:19
  - three week technology command center, and we shut
• 16:23
  - that down probably after a week.
• 16:25
  - And we had, I wanna say, about 25%
• 16:29
  - of the
• 16:30
  - issues and incidents that we had expected to
• 16:32
  - have. Like, you know, so we were like,
• 16:33
  - okay, we're gonna plan on this. It turned
• 16:36
  - out that we had about 20% more issues
• 16:38
  - than we have on a standard day,
• 16:40
  - which was just remarkable. And I and I
• 16:42
  - credit the
• 16:44
  - real hard work
• 16:46
  - with preparation
• 16:47
  - and simulations.
• 16:49
  - We had, simulations that we that the clinical
• 16:52
  - teams ran, and then we also ran technology
• 16:55
  - focused, simulations.
• 16:57
  - And we treated them less like training, but
• 16:59
  - more as a means for how we could
• 17:01
  - discover and learn where issues are, where things
• 17:04
  - weren't gonna work, or whatever. And we caught
• 17:06
  - a number of major issues with those simulations.
• 17:09
  - And I really credit that to allowing us
• 17:11
  - to have
• 17:12
  - as smooth of
• 17:14
  - a implementation as we have. And then finally,
• 17:16
  - I would just wrap up by saying,
• 17:18
  - expect to have adoption of lips, like I
• 17:20
  - said.
• 17:21
  - Expect to have challenges.
• 17:23
  - Changing human behavior is just hard.
• 17:26
  - You know, some technology will work better than
• 17:28
  - others. It'll be more important than others, and
• 17:30
  - it will some of that will surprise you.
• 17:32
  - Jeremy, so you mentioned these simulations, and I
• 17:35
  - I imagine a lot of that goes back
• 17:36
  - to the cardboard city that you mentioned.
• 17:38
  - So that's when you went into this whole
• 17:40
  - project, I mean, certainly, you can
• 17:43
  - computers can do a lot of things. You
• 17:44
  - can say, okay.
• 17:45
  - Tell me this. Right? And give it some
• 17:47
  - input, and it can
• 17:50
  - do some simulations on its own.
• 17:52
  - But how how
• 17:54
  - much it should be put into percentage.
• 17:56
  - Like, what what did you learn from the
• 17:58
  - practical simulations at Cardboard City compared to other
• 18:01
  - means?
• 18:03
  - Yeah. I mean, I I it was a
• 18:04
  - learning process the entire way, Chris. I mean,
• 18:06
  - the, you know, it started with just,
• 18:09
  - okay, the Cardboard City from a technology
• 18:12
  - perspective really helped us understand where we would
• 18:14
  - have to interact with staff
• 18:17
  - visually.
• 18:18
  - Where we're gonna have the space to
• 18:20
  - mount the monitors and TVs and screens and,
• 18:24
  - you know, just some of those very tactical
• 18:26
  - physical things? Yeah. As we got into the
• 18:29
  - project and we you know, some of these
• 18:31
  - things were relatively new. You know? When we
• 18:33
  - first started, we were we were wondering, do
• 18:36
  - we need to we need to plan for,
• 18:39
  - self driving cars? We need to have a
• 18:41
  - special self driving car drop off, you know,
• 18:43
  - spot at the hospital because we didn't know
• 18:45
  - how big that would be yet. Right? And
• 18:47
  - some things but on the other hand, we
• 18:49
  - didn't we didn't see AI adopt, you know,
• 18:52
  - you know, happening as fast as it did
• 18:53
  - either.
• 18:54
  - And so you're gonna get those things wrong.
• 18:56
  - Some things move we call it the jagged
• 18:58
  - frontier in IT where, you know, some of
• 19:00
  - the things move faster than you thought and
• 19:01
  - other things just don't.
• 19:03
  - And
• 19:04
  - so, you know, having an iterative process, I
• 19:07
  - think, is what's most important.
• 19:08
  - You're you're, you know, you're you're developing a
• 19:11
  - a theory for what you think is gonna
• 19:13
  - work. You're trying to find some way to
• 19:15
  - test whether or not that will work, whether
• 19:16
  - it's through a simulation or other means, you
• 19:19
  - know, and then you're adjusting.
• 19:21
  - Yeah. Certainly, I'd like to be able to
• 19:22
  - say, yeah. We saw all of this coming.
• 19:25
  - Not quite possible or practical,
• 19:28
  - but you guys you know, you do the
• 19:29
  - best you can. Right? So I I look
• 19:32
  - forward to
• 19:34
  - the next
• 19:35
  - you know, hopefully, we'll be able to talk
• 19:36
  - to you in another year and a half,
• 19:37
  - two years, and you can and give us
• 19:39
  - more,
• 19:40
  - another breakdown of what's happening. So as you
• 19:43
  - look to the
• 19:44
  - whatever time period that is most practical for
• 19:47
  - you down in Atlanta. So what's most exciting
• 19:50
  - to you about where technology is headed and
• 19:53
  - just health care is headed?
• 19:55
  - Well, certainly. And I'm sure everyone is
• 19:57
  - thinking about AI, what its potential is, what
• 20:00
  - its,
• 20:01
  - capacity is to help help us solve access
• 20:04
  - challenges,
• 20:05
  - improve outcomes,
• 20:07
  - you know, find efficiencies and improve the patient
• 20:09
  - experience.
• 20:10
  - But I think that even there, we have
• 20:12
  - to
• 20:13
  - we have to be realistic, and we have
• 20:14
  - to understand where we're at in everything.
• 20:17
  - You know, there was this thing in 1987,
• 20:20
  - called the, the productivity
• 20:23
  - paradox.
• 20:24
  - K. And, you know, PCs had been around
• 20:26
  - for going on ten years,
• 20:28
  - and everyone was wondering where is the productivity
• 20:31
  - gain because they weren't seeing it in the
• 20:33
  - numbers.
• 20:34
  - Now,
• 20:35
  - that eventually came. That came in the nineteen
• 20:38
  - nineties, but what they ended up finding out
• 20:39
  - was that it wasn't until roles changed.
• 20:43
  - It wasn't until you know, I mean, pre
• 20:45
  - computer, they would have, for example, a secretarial
• 20:48
  - pool. And the first thing they did is
• 20:50
  - replace the typewriter with a PC, and it
• 20:52
  - turns out that did absolutely nothing for productivity.
• 20:55
  - Right? It was it was, you know, rethinking
• 20:58
  - the entire thing. We don't need to have
• 21:00
  - secretarial
• 21:01
  - pools, and we don't need to have proofreaders,
• 21:03
  - and we don't need to have some of
• 21:05
  - those things,
• 21:06
  - because,
• 21:07
  - because the technology
• 21:09
  - can can change the entire process. And so
• 21:11
  - I'm sure that there's gonna be a fair
• 21:13
  - amount of that.
• 21:15
  - And coming with that, of course, there's a
• 21:16
  - lot of, you know, concern about the human
• 21:18
  - impact on AI as well as cybersecurity.
• 21:22
  - And I think that we just you know,
• 21:23
  - if we have a human led,
• 21:26
  - approach, I think,
• 21:28
  - you know, if we do it correctly, I
• 21:29
  - think we can hopefully see some real improvements
• 21:31
  - in quality, speed, and patient experience.
• 21:34
  - I think we are all looking forward to
• 21:36
  - that. I'm sure all of your colleagues and
• 21:38
  - peers would echo that as well, Jeremy.
• 21:40
  - Thank you so much for coming on the
• 21:41
  - podcast today and sharing all your candid insights
• 21:44
  - about things that did not work, more importantly,
• 21:46
  - things that did and that you're looking forward
• 21:48
  - to to tackling in the future.
• 21:51
  - Wonderful. Yep. It has been great. Thanks so
• 21:53
  - much, Chris.