Latest / Becker’s Healthcare Podcast / Jochen Reiser, MD PhD, President and CEO, UTMB

Transcript

Jochen Reiser, MD PhD, President and CEO, UTMB · Becker’s Healthcare Podcast

0:02
R one is the leader in health care
0:03
revenue management, helping providers achieve new levels of
0:06
performance through smart orchestration.
0:09
With more than twenty years of experience, r
0:11
one partners with 1,000 providers,
0:13
including 95 of the top 100 US health
0:16
systems and handles over 270,000,000
0:19
payer transactions annually. If you want to learn
0:21
more about how you can transform your revenue
0:23
cycle operations, visit us at wwwr1rcm.com.
0:31
Hello, and welcome to the Becker's Healthcare podcast.
0:34
My name is Will Riley from r one.
0:37
I am joined today by doctor Jochen Reiser.
0:41
Jochen is the president and CEO of UTMB.
0:46
Welcome to the podcast, Jochen.
0:48
Always a pleasure to be here. Thank you,
0:50
Will. Thank you. So start us off. Tell
0:52
us a little bit about yourself. Tell us
0:54
a bit about UTMB and some of the
0:56
work that you do.
0:58
Wonderful. I grew up in rural Germany in
1:01
the Black Forest.
1:02
And as part of my education as an
1:05
MD PhD at the University of Heidelberg, I
1:08
was granted a stipend to do research
1:11
in New York
1:12
and never left The US.
1:14
And,
1:16
but while I was doing my, residency in
1:18
internal medicine in at Albert Einstein
1:21
Montefiore,
1:22
in New York.
1:24
I also then moved on to become a
1:25
nephrologist at Harvard Medical School, Mass General Hospital,
1:28
and Brigham Hospital,
1:30
went to University of Miami,
1:33
as a faculty member,
1:34
and chief of nephrology,
1:36
learned a lot about innovation
1:38
at that time, and then moved to Rush
1:40
University Medical Center. And from there after, a
1:43
little bit over a decade,
1:45
to University of Texas medical branch
1:47
in 02/2023.
1:50
UTMB
1:50
is a legacy institution in Texas. It's the
1:54
oldest
1:55
health care
1:56
institution
1:57
with,
1:58
the oldest medical school, the oldest nursing school,
2:01
and some really great missions that we cover.
2:03
For example, 82% of prison health care in
2:06
the state of Texas,
2:08
six hospitals, 100 clinics,
2:10
big pharmacy enterprise,
2:12
and,
2:13
also,
2:14
quite an interesting mission around aerospace medicine
2:18
and, of course, the national laboratory. Only two
2:21
labs in The United States are
2:23
biosafety level four. We are the larger one,
2:27
and we are leading that as well. So
2:29
very interesting place with,
2:31
a lot of, excitement for the future.
2:34
Fantastic. And a great place to talk about
2:37
innovation,
2:39
and advancing
2:40
the role of technology in health care, I
2:41
think, which is where I'd like to start.
2:44
Yeah. In fact, well, you hit the nail
2:47
on the head. I,
2:49
was always
2:51
quite a fan of innovation. And by innovation,
2:54
I mean innovation around biotech,
2:57
but also health tech,
2:58
technology around AI, educational
3:01
technologies.
3:03
And we officially made,
3:05
innovation the fourth pillar of UTMB. So when
3:08
we talk about our mission today,
3:10
we have education, research, clinical care delivery, and
3:13
innovation.
3:14
Okay. Opened an innovation center in 2023
3:18
and have, a few start up companies now
3:20
and
3:21
have also changed how we organize
3:24
and govern innovation
3:26
at UTMB and also made it part
3:29
of some of our curriculums
3:30
curricula.
3:32
So an exciting topic,
3:33
to talk about. Okay. Good. Excellent. Well, I'd
3:36
like to dig in on on a lot
3:37
of that.
3:38
Firstly,
3:39
it it
3:41
you can tell me if I'm wrong, but
3:43
it it it seems to me that health
3:45
care
3:46
providers have often been very cautious when it
3:48
comes to technology and innovation.
3:51
But
3:52
we might be seeing that change with the
3:55
adoption of AI and some more modern contemporary
3:58
technologies.
3:59
I'm curious as to whether you see that
4:01
happening,
4:02
whether you see this shift in approach to
4:04
innovation because of AI.
4:07
I think you
4:09
formulate
4:10
that very well.
4:12
Typically,
4:13
innovation around biotech is a long term commitment.
4:17
You need to have a lot of
4:19
misses to have one or two hits,
4:21
and that was seemingly not the right place
4:24
for universities
4:26
and health systems because
4:28
we had to struggle with finances
4:30
anyway to begin with with small margins,
4:33
on your largest,
4:35
income stream, which is health care delivery.
4:38
But with
4:39
AI and
4:41
health tech,
4:42
this seems to be not quite the case
4:44
because the needs are so vast
4:47
that it's almost clear that technologies that are
4:50
good and,
4:52
rooted in in sound,
4:54
science will ultimately and probably a lot faster
4:57
make them to the market.
4:59
You're also avoiding
5:00
potentially long clinical trials that you do have
5:03
in biotech.
5:04
It's much more actionable.
5:05
Mhmm. And, also, you can utilize those tools
5:10
in pilot programs already
5:12
at the inception and creation phase.
5:15
So it's a much better suited
5:17
innovation
5:19
tool at the university. So we see a
5:22
lot more of it, and not just at
5:24
UTMB,
5:25
but, also at other places. But we are
5:27
proud to say that at UTMB,
5:30
we are very,
5:31
technologically advanced around AI and have probably more
5:35
programs running today
5:36
than most other places will have. And you
5:39
talked about there about research, but it seems
5:41
that that this,
5:44
benefit of AI flows down the food chain
5:46
too when it comes to the provision of
5:48
clinical care in a health care setting, when
5:51
it comes to the administration
5:53
of health care as well.
5:55
Yes. And so we have ambient listening like,
5:58
many others have talked about here at the
6:00
meeting,
6:01
and some have it in small
6:03
pilot components of, of the health system. We
6:05
already have it,
6:07
rolled out
6:08
for for our entire faculty.
6:10
So it's a routine
6:12
component of, care at UTMB,
6:14
which, as you know,
6:16
focuses the interaction
6:18
back to the doctor and the patient, which
6:21
we wanna have it.
6:23
It takes the pressure off of documentation. It's
6:25
been really a a big differentiator in terms
6:27
of happiness
6:29
for the patient, but also for the provider.
6:32
But you're right. When you look at,
6:34
revenue cycle, when you look at, billing, when
6:37
you look at compliance,
6:38
those are all areas, contracting,
6:41
where you can utilize
6:42
AI.
6:43
And in our innovation domain, we're working together
6:46
with many partners
6:48
to develop customized,
6:51
programs
6:52
for health systems that we then pilot
6:55
at UTMB,
6:57
but ultimately also can spin out or be
6:59
part of a larger
7:01
company effort and hopefully get an alternative,
7:04
revenue stream with that as those technology become
7:07
mature.
7:08
Yeah. So let's talk about that. You've mentioned
7:11
partners and and and and innovation and and
7:13
new revenue streams.
7:14
So in health care innovation,
7:17
you I think you hear about two archetypes.
7:20
Right?
7:21
Incumbents,
7:23
large,
7:23
right, established health systems, established payers, established
7:27
technology platforms. Right? They have the data, the
7:31
infrastructure,
7:32
control the system.
7:33
And insurgents,
7:35
let's say, right, newer entrants, people who are
7:37
coming in with more of a disruptive agenda
7:39
Yes. Trying to change things. How does innovation
7:43
play out around
7:44
AI with those two
7:46
participants in mind, and where do you sit
7:49
in in that as UTMB?
7:52
Well, I would say what has not changed
7:54
is that the data
7:57
that health systems have Mhmm. Is the main
8:00
capital
8:01
for the innovation.
8:03
So whether the data is absolutely vast
8:06
or whether it's,
8:08
meaningful in terms of region,
8:11
or diversity of data,
8:13
that doesn't matter that much. But it's making
8:15
that data available safely
8:18
and to really work with it what's making
8:21
the difference.
8:22
And I would say that,
8:23
Texas is generally seen as a place where
8:26
innovations are done,
8:28
typically well. So we've had no issues with
8:31
attracting partners.
8:33
But what has changed at UTMB is how
8:35
we work with our own datasets with partners
8:39
and making that data available
8:41
for others to use safely and, obviously, with
8:43
a lot of oversight and rules. Mhmm. But
8:46
in a way that we can create these
8:48
novel tools
8:50
in our markets and then begin to employ
8:52
them and see how they work as we
8:54
are refining them.
8:56
So data is a massive advantage
8:59
for an incumbent who can then facilitate that
9:02
innovation
9:03
network and process, essentially. Yes. And so our
9:06
access center, for example, is now really a
9:09
combination
9:10
of actual intelligence
9:12
and artificial intelligence. Yeah. So AI square, I
9:16
sometimes call it,
9:17
where we have AI
9:20
supported components in there, but then we have,
9:24
escalated nursing branches,
9:26
and real life operators that come to augment
9:30
the AI component and vice versa.
9:32
And that is very relevant to our own
9:34
markets because we wanna we wanna expand access
9:37
to our health system,
9:39
but it's also a great real life working
9:42
space for a technology company. And and there
9:45
are many who are looking for that type
9:47
of partnership. So I think that AI is
9:50
providing
9:51
finally the type of partnership between industry and
9:54
academia that we always wanted
9:57
but never could do
9:59
because prior innovation, like biotech,
10:02
was so much driven
10:04
by the,
10:05
pharmaceutical industry,
10:07
by the investors that are giving the money,
10:10
and rather little
10:12
on the university
10:13
side. In AI, it's different. We are equal
10:16
partner, if not leading partner in this,
10:20
newly established
10:21
friendship,
10:22
as we're innovating.
10:24
So new new friendships and new collaborations
10:27
maybe require new
10:29
governance
10:30
models and governance approaches. I'm curious about that
10:33
too. You've talked about having the this data
10:36
advantage and putting data to work, but, obviously,
10:39
doing it in a way that is,
10:41
compliant and safe and and and so on.
10:43
Can you talk about how you've built a
10:45
governance framework to support the innovation?
10:48
Governance framework for AI is complex. It needs
10:52
to have, obviously, a lot of technical oversight.
10:54
Yeah. It needs to have security oversight. It
10:57
needs to have legal oversight, ethical oversight,
11:01
and also compliance. So all the components need
11:04
to be there. So we have an AI
11:06
council
11:07
Okay. That is typically the governing board of
11:10
everything around AI we do.
11:12
And and that is very helpful to me
11:14
because I know at any given time what
11:16
are all the projects that we're working on
11:18
because I can go to that council. We
11:21
also have a newly established center for artificial
11:24
intelligence
11:25
where we obviously have the work groups that
11:27
work together with our industry partners on the
11:29
projects, but are also giving me an inventory
11:33
and giving me a state of the art,
11:35
of our current affairs.
11:37
I would say that it's unrealistic
11:39
to believe that one can establish such an
11:42
oversight
11:43
even in a month or so. It's an
11:46
evolving
11:47
organ that gets better and better over time.
11:50
And we have to be careful that we
11:51
don't take on too many projects
11:53
before the governing body is actually mature enough
11:56
to handle it all. And I think at
11:58
UTMB, we are confident we have that maturing
12:01
governing body
12:03
ready to go for quite a while now,
12:05
and that's why we are seeing a lot
12:07
of projects coming through, being evaluated,
12:10
and some, not all of them, are moving
12:12
forward to a real creation or implementation stage.
12:16
Can you tell us a bit more about
12:17
a couple of ones that are exciting to
12:19
you or maybe some of the startups that
12:21
you're Yeah. You're spawning? So well, great. I
12:24
keep it I keep it all general. But
12:26
Yeah. One is around education, for example.
12:29
We have an AI tool that,
12:31
screens
12:32
a large language model that goes through all
12:35
of our patient inventory and picks out cases
12:39
that are of particular educational value.
12:41
So there might be a patient, I'm just
12:43
making this up,
12:45
that comes in for shoulder repair
12:47
but has a rare genetic underpinning issue,
12:51
but that's not active right now. So that
12:52
case will get lost under normal circumstances for
12:55
the students to learn about.
12:57
But the large language model will flag those
13:00
cases and say, hey. Bring the students to
13:02
this case
13:03
and make them talk with that patient or
13:05
with the work team about this particular case.
13:08
So we're using that.
13:10
That goes into customized education.
13:13
So we are learning
13:14
how students
13:17
prefer they get their content,
13:20
managed.
13:21
And some some of our students might do
13:23
better with virtual content. The other one's more
13:26
with hands on. Some might have some issues
13:28
with three-dimensional
13:30
thinking. And so our,
13:32
AI tools will help those students to get
13:35
their preferential
13:36
mode of learning
13:38
delivered to them so they can best fulfill
13:41
the task of getting to the next level.
13:43
That's very exciting. I think this is like
13:45
redefining
13:46
how we are teaching as a university, not
13:48
just content delivery, the way of how we
13:51
deliver content.
13:53
And I think that's, something I am particularly
13:55
excited about because our universities, and that's not
13:58
just UTMB,
14:00
need to be
14:01
really rethinking
14:03
relevance
14:04
for university.
14:05
Only if we stay relevant and people wanna
14:08
come to university to get their content.
14:11
We are going to survive as a university.
14:13
Otherwise, we just have everybody learning online from
14:17
some platform
14:18
and then go and do a test somewhere.
14:20
That's not where we want our universities to
14:22
ultimately go. Mhmm. We wanna continue to create
14:25
the best, most advanced learning environment, and that's
14:28
why I'm very excited for the use of
14:30
AI.
14:31
As consumers and patients get better equipped with
14:34
data about themselves and access to tools that
14:38
are very powerful but very cheap and easy
14:40
to use, do you see that risk as
14:43
well from the
14:44
delivery of health care? You're talking about it
14:46
from a academic perspective, but actually
14:49
patients really empowered to
14:51
to know what to do from a health
14:53
care perspective.
14:55
I I think it would be
14:58
not truthful to say that
15:00
every patient is more educated today literally than
15:03
perhaps ten, fifteen, twenty years ago. But there's
15:05
also a lot of education that's not quite,
15:08
correct.
15:09
And so we will always need the expert.
15:12
Right? But, the good news are that in
15:15
today's needs,
15:17
in terms of health care delivery, we have
15:19
too few doctors, too few nurses,
15:21
too few health care workers.
15:23
So by adding on, artificial capacity
15:26
and artificial intelligence to help us manage that,
15:29
we're not competing with each other. If anything,
15:32
we need more on both sides. And together,
15:34
it will be better health care delivery.
15:37
I would never want anybody
15:39
to just rely on a computer
15:42
telling him or her what it is they
15:44
are dealing with and what it is that
15:46
they should or should not be doing. I
15:48
want them in conjunction
15:49
with the human brain. Artificial intelligence
15:52
and actual intelligence
15:54
in perfect harmony together. I think that's the
15:56
future. Yeah. Okay. Okay. Fantastic.
15:59
Thank you very much. Is there anything else
16:00
that you wanted to add that we haven't
16:02
that we haven't covered? It's been really interesting.
16:04
Well, Will, you know, I was here last
16:06
year, and and and within one year, so
16:08
much has happened. Yeah. Yeah. I'm just so
16:10
excited to be being different. Because it different.
16:13
Mhmm. It feels like we are not just
16:15
talking about AI. We're doing it. We actually
16:17
have some experience reports. Mhmm. And we're starting
16:20
to really
16:21
gel with that
16:23
new topic of that cognitive revolution we are
16:26
living through right now. So let's see what
16:28
we are talking about next year. Thank you
16:29
very much. Thank you so much, Joaquin. Thank
16:32
you.