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This is Laura Dirdle with the Becker's Healthcare
podcast. I'm thrilled today to be joined by
doctor Chen Kai Kao, chief medical information officer
at UChicago Medicine. Kai, it's a pleasure to
have you on the podcast today.
Thank you so much, Laura. It was nice
meeting you, you know, virtually.
So thanks for having me.
Absolutely. Absolutely. Well, I I'm excited for our
conversation because I know you're doing some really
cool things at UChicago Medicine, and certainly, we'll
look forward to learning more about those, when
you speak at our health IT digital health
revenue cycle event later this year. But
for our conversation here, before we begin, I
was wondering, could you tell us a little
bit more about UChicago Medicine and what makes
it unique?
Of course. So the University of Chicago Medicine
health system is, you know, in Illinois, obviously,
centered in the Hyde Park area in Chicago,
but we also have
satellite hospitals at
Southwest
Suburbs and also Northwest Indiana.
We are a five hospital system,
about 1,300 beds,
and spread again across
the State
of Illinois and Indiana.
I think I would say one thing unique
in our institution is,
like many others, we are very committed to
patient care, but we do serve a relatively
underserved
population here. So there was one New York
Times article citing
the expectancy
in the zip codes that we serve
nearby
was thirty years less than the zip codes
in Downtown Chicago. So you speak to a
lot
of the resource differences,
the digital literacy, digital equity differences
and just all in all,
I think
signified
the the challenges we we should face when
we, you know, try to serve this community.
Got it. That's helpful to know. And, you
know, really an important population you serve as
you mentioned,
those who may not have access to care
otherwise, especially, and then,
truly, just a great academic health system,
resource for the Hyde Park community.
Now I'm curious. When you look back in
the last year or so, what are the
accomplishments that you're most proud of?
Yeah.
I think over the years, we we have,
you know, have I think done a few
things I think, you know, we feel very
proud of.
In my portfolio, I would say one thing
that's relevant
to what I just mentioned about serving the
community, you
know, in our area will be a hospital
home program.
So it's
it's basically a program providing acute hospital level
care in the patient's home.
And we supply, obviously,
you know, staff and resources like medications,
meals, etcetera to the patient's home. We can
do imaging and
EKGs and other studies at home as well.
And but like I mentioned, I think the
geography that we serve posed a lot of
challenges both from the patient's readiness to receive
the type of services
and also the recruitment for nurses who is
willing to travel into these areas. But we've
been fortunate to have a very strong team
where
we are really eager
to serve our patients. We
reach out to them passionately
and introducing the program. And I'm proud to
say that all the patients go through the
program is very happy with the program. They
really feel like this allowed them to be
able to recover in their own home, you
know, while, you know, really just enjoy the,
you know, all the benefit being being at
home, surrounded by, you know, your, loved ones
and also be able to do the stuff
they usually do. You know, watch the TV
show you always watch, read the books they
usually do while you're receiving all the care
that's equivalent to the inpatient level care. And
we are seeing, you know, so huge patient
satisfaction,
a lower readmission rate,
and that's just, you know, overall very fulfilling.
There's also a couple of other informatics related
projects,
that we implemented.
One thing we'll highlight is called auto diagnosis.
This is a project actually spearheaded by one
of our physician
builder, Doctor. Medcel Ocelli, really sort of building
these
auto diagnosis within the node templates to help
reduce physician documentation burden. I mean, as we
all get recognized,
the documentation is a huge
burden for the physician, not necessarily what we
signed up for medical school for,
but obviously it's
an important task that we have to do
every day.
So the the project is basically allowing us
to be able to help physician capture a
company made diagnosis
directly within their note templates
and in the meantime reducing the core inquiries
that people will be getting down the road.
So it really helped reduce the burden and
actually helped to make our notes better.
So we since they have published
the work, we actually soon to have,
additional publications on this work coming up as
well.
We have shared that in a couple of
different epic conferences,
and actually was highlighted, I think, in one
of the Becker newsletter before. And we have
been working with some of the other institution
who are interested in implementing the same,
same sort of technology in their
system as well.
Last but not least,
so clinical decision support is a big chunk
of my portfolio. So we've been using decision
support to help capture
some of the stewardship
requirements. So for example, last year there was
a major blood culture shortage
nationwide. So we're able to use DGN support
to help reduce
the blood culture bottle usage very significantly.
And now we are spending to do more
for daily labs and any other things to
reduce these unnecessary labs, which will be important
to solve to reduce the cost for the
hospital.
Also in the meantime,
it's also reducing unnecessary blood draws or reduced
ultraglionic anemia and obviously patient experience
will be better without these additional plastics as
well.
So these are things I would just you
know, maybe call out particularly, but there's really
a lot going on,
right now.
That's great to hear. And, you know, really
cool to,
have the ability to leverage technology in ways
that have a meaningful impact on patient care
as well as the workflows on the clinical
side. I I know reducing the burden on,
clinicians, doctors, and nurses especially,
is truly a mission for so many organizations
overall.
So that those are both great examples to
hear about. I'm curious, looking ahead over the
next twelve months or so, where do you
see some of the big biggest growth opportunities
for you and your teams?
Yeah. So, with the joint partnership with,
IT, marketing and informatics and data analytics,
we formed what we call the Center for
Digital Transformation.
This is a center
we established
and to really help us
adapt to the a lot of the new
trend
in the healthcare right now. So obviously lots
of work about digital transformation about how we
actually deploy this digital
health and AI technology
in the clinical care and really improve both
the provider patient experience
and improve the efficiency of the health system.
So there's been a lot of initiatives sort
of under the umbrella for this,
what we call the CDP,
Center for Digital Transformation.
And we're also looking at how do we
review the roadmap
of the digital tools we are thinking about
that can help bridge the gap and the
pinpoint that we have in the system. We
are looking at establishing
AI governance for the increasing
number of AI usage, right, almost in every
industry. We're also looking at how we do
a better job in terms of intaking some
of these solutions.
There's always
lots of DG Health startups out there and
they probably download a number in the last
few years. So how do we making sure
we have a process where we can
broadly taking those in and in the meantime
be able to evaluate them fairly and
really factor into
decisions about what's the best
really to help solve the problems that we
have in our health systems, what's the best
model to work with the vendor to co
develop
some of these products, because there there's a
lot of new technology and none of them
are mature yet. In the meantime, we also
have
some homegrown resources that we can build things
as well. So thinking about how we build,
when do we build, when do we buy
is also the other thing we want to
sort of factor into this new process of
that innovation intake.
So that's I think that's a really exciting
opportunity for our team to think about how
we can help institution prioritize these opportunities
and really help bridge the gap and make
a true impact, on clinical care.
I love that. I I think it's so
critical, as you mentioned, to have, you know,
the right evaluation process to bring in technologies
because there are so much exciting things out
there and new
possibilities, especially with AI,
and automation. But, you know, not everything is
gonna be beneficial. And so being able to
stay on track and really understand,
what makes the most sense
is so important.
I'm curious. You mentioned, you know, getting some
of the the governance processes in place,
especially for AI use. Could you talk a
little bit more about that and what those
conversations have been like at UChicago Medicine?
Yeah. So that's a great question regarding the
AI governance. So maybe to start with, you
know, thinking about why we need that. So,
right, there's a lot of AI companies out
there. And almost like when I go to
a conference, it's like almost every company have
AI tagged in their sort of product description.
It's almost as if this is something that's
universally used right now.
But
when we look at these AI solutions, first
is, is it really addressing a critical problem
that we have? And so secondly,
is that problem really need to be solved
by AI? So that will be an important
piece that we need to tease out when
we think about the intake, think about
evaluating these solutions. But after we sort of
decide, all right, there is a true pain
point and problem we're trying to solve And
we do need a solution in a place.
And AI seem to be a potentially a
good
solution to solve the problem. We still would
like to take a very thoughtful process in
terms of validating is AI really delivering what
it's supposed to do. So accuracy, completeness, right,
all these type of evaluation about
the effectiveness of AI. There's also a lot
of risk assessments,
especially nowadays with a lot of cyber
security risk.
So making sure we are reviewing this AI
in a fair way to adjust assist their
to assess their risk level
based on whether the use of AI is
susceptible, not susceptible and high risk versus low
risk.
And also in the meantime making sure they
meet our security, privacy and
asset standards are sort of an important piece
in the intake of process as well. And
last but not least, let's say something really
works well
in past all the risk assessments that we
do, we still want to have a process
to continue to monitor this AI moving forward
to making sure they still perform
as the same way we thought it would
be in the beginning.
Health system is constantly changing. So all these
changes regardless of spending the new units, building
a new hospital,
adding additional outpatient site, we all potentially can
change
how AI model works. We want to be
able to have some light of sight into
that too. So these are the things we
thought about having a strong AI governance. And
again,
the people who will be overseeing the AI
governance will be multidisciplinary.
So know, people with, you know, data science,
you know, analytics backgrounds, informatics, ITs,
and, you know, on security, privacy, and other
stakeholders will also be involved as well.
Got it. That's helpful to to know. Thank
you so much for digging a little bit
deeper in there. Now it really seems like
a lot of opportunities out there, a lot
of cool things that are happening, but I
can imagine there are challenges as well. What
are some of those challenges or roadblocks that
you're anticipating
in the
coming year or so?
Yeah. We are taking a very thoughtful way
when we deploy this technology.
So,
you know, first, like we talk about, the
patient community that we serve. Right? It's not
exactly the most digitally,
savvy population.
So making sure every time we roll out
something,
we'll
always have the digital equity
things in mind that we want to make
sure the things we deploy are benefiting
all the patient population,
maybe not all through the same venue, but
always making sure there's a way to engage,
making sure there's a way to help them
navigate
and benefit from all the new solution we
deploy throughout the health systems. So I think
that
all the work around digital equity
and try to
overcome all the challenges
from digital device, something I think we have
seen since the pandemic and also something we're
still compelled to continue to improve
through our processes.
And now with AI, right, there's even more
thing to think about around
the around like the biases,
based on different gender, race, populations,
etcetera, like how does AI use
being properly governed
to making sure that we are free of
these biases
or ethical concerns? It will be the other
challenge we need to constantly test out and
just be mindful of in our processes.
So I would say I wouldn't say that's
necessarily a challenge. Instead, I think these are
all good questions that we have been solving
over the years before you even have this
technology.
But really with all the tools in mind,
how can we even use this tool in
the right way to actually mitigate some of
these gaps and make things better, not the
other way around? It's just something we need
to constantly be careful about and margin when
we march forward.
Got it. That's helpful to know. And and
certainly,
as you can imagine oh, I know a
lot of goes into trying to figure out
those AI models and, how you can do
that in an equitable way,
especially given how quickly the technology is evolving
and changing.
Yeah. Exactly. I mean, it's it's,
rapid moving world right now. So,
it's, again, both
a challenge, but in the meantime, any excitement.
I feel actually very fortunate to,
live in this era where it's witnessed, like,
all the Internet growth and now AI growth,
and it's just gonna change a lot of
things, which is super exciting.
Absolutely. That's fantastic to hear. It is a
great time to be in health care for
sure. Now I'm curious from your perspective, given
some of the, big,
things that we're excited about as well as,
you know, challenges that we just mentioned,
What is the number one thing that you're
doing right now to set UChicago Medicine up
for long term success?
Yeah. I will talk about one project I'm
working on that's actually related to what we
talk about. So we talk a lot about
the use of AI is growing and there's
more companies, there's more use cases here and
there that's coming up as we speak. And
we also talk about I mean, there's a
lot of saying around people with the AI
may replace
the people who don't know how to use
AI. And maybe in the future, there will
be, you know, even more, AI and automation,
right, in in the work. So I think,
absolutely, what we want to do is making
sure we elevate the AI literacy in our
institution. Right? We want to train people to
know how to make the best use of
AI.
AI is not perfect. So training them to
understand
what's the posting counts, what's the limitation, what
does it mean by AI hallucinates.
And but in the meantime with all of
that, being able to use leveraging AI as
most most likely your inexperienced intern. Someone is
on your team. It's almost like your digital
worker, but who is inexperienced, who is new
to the team. So how do you train
the AI to actually work with you to
actually get things done more efficiently?
That that will be sort of the goal.
We we hoping that we,
convey to our sort of colleagues. So one
thing I'm working on is actually building
up
generative AI platform that will be HIPAA compliant
and secure
for internal use, which will allow us, meaning
our staff
and health care provider being able to upload
certain
information about PHEIs
and be able to use that to
do things, for example, like
drafting some of the messages that we are
about to send out in different formats, in
different languages, in different
type of literacy level, which allowed them to
help improve some of this patient communication.
Or for example, we are developing some of
the modules to help drafting denial letters of
appeals
or for example answering some questions based on
our policies and procedures.
So while we are standing that platform up
hopefully in the next
few months, it's really coming up soon,
we also want to pair that with
staff communication,
education about how you should use AI, right?
How to prompt,
what's the AI governance we've been talking about
so far? And when you have questions, where
do you reach out? And how do you
use the tool better to your
for your purposes to to boost your efficiency
in every area. So that's something I think
really exciting, and I think I'm gonna spend
quite some time really to help stand it
up and thinking about creating different use cases
and,
and training people to to make use of
it. But what we do, I think it's
gonna be really,
improving a lot of efficiency issues that we
have and really allowing people to really do
things that are probably a license. Right? It's
like you let AI to do a lot
of these repetitive
or something that's, you know, less,
less challenging
per se in terms of the complexity or
originality.
But, you know, reserving all your energy on
something that really requires all these, you know,
things,
and the AI just help you out to
save time. So, that's something I think really
exciting, that I'm really working on right now
that I think really would set our institution,
at a really good start
as we continue to, spend and,
deploy additional AI solutions.
That makes a lot of sense. You know,
it's really, helpful to understand from a leadership
context and perspective,
how you're thinking about these things and really,
really putting yourself in a strong position to
continue to,
advance this technology and bring it forward in
a meaningful way. Kai, thank you so much
for joining us on the podcast today. This
has been such a fun conversation, and I
look forward to connecting with you again soon.
Thank you so much, Laura. And likewise here,
meeting you, and, have a good day.