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This is Gracelyn Keller with the Becker's Healthcare
Podcast, and we are live at the 9th
Annual Health IT Digital Health and RCM Conference.
I'm currently joined by Kung Win, who is
the assistant executive medical director and care transformation
at Kaiser Permanente. So thanks so much for
being here today, and would love to get
us started by having you introduce yourself and
telling us a little bit more about your
role and background.
Great. Thank you very much, and happy to
be here. It sounds like a very, it
is has been a very exciting event. So
my name is, doctor Kang Nguyen. First and
foremost, a very proud family physician.
I'm a part of the Kaiser Permanente,
group.
Kaiser Permanente is actually made up of multiple
entities.
First and foremost, it is an insurance plan.
So that's the Kaiser Foundation health plan, and
that is national.
There's also Kaiser Foundation Hospitals that manages our
multitude of hospitals throughout the country.
And then the third entity is really the
Permanente medical groups. So that's the group of
doctors that that are independent.
And my group is the Southern California Permanente
Medical Group in Southern California.
They're actually in that, area. I have the
role and responsibility of being the care transformation
leader
over operations and technology in Southern California.
I'm also the founder and the current medical
director for Southern California's Virtual Medical Center that
helps assist in synchronous and asynchronous care.
And more recently, I'm, been appointed to be
the chief chief medical officer for care navigation
for the Permanente Foundation oversee, helping all of
our medical groups work with the Kaiser health
plan.
Wonderful. Well, thank you for taking the time
to be here. And let's begin our conversation
with AI adoption. As you know, this is
exploding in health care. So in your view,
what is the most significant or promising application
of AI right now, and how is this
informing your organization's innovation strategy?
Yeah. That seems to be the question of
the day, if not the year, is where
is AI kinda
going? You know, I think there's, 2 ways
to look at it. There's the short term
view and there's a long term view. As
part of the health care being in health
care, obviously,
what we wanna do is have artificial intelligence
really help us out with
prevention of illness
and also help us out with prediction. So
prevention and prediction. And then we also want,
artificial intelligence to help assist our doctors and
our clinicians
with immediate care delivery.
These things are actually,
really, in my mind, more futuristic looking
because we we what we have to do
is really prepare our current datasets to be
able to have some of the algorithms
consume that.
So, you know, we Kaiser has been kind
of the early adopter for the electronic medical
record,
for more than 20 years now. And as
a result, we have a lot of data
that will help us out with that. But
that data has been largely unstructured.
Artificial intelligence is a is a fancy software
that needs to ingest that data.
So for the future for this, we have
to basically, effectively organize our data and then
build new datasets that are more curated so
that we can actually take advantage of AI.
So that's more for the future. The immediate
role of artificial intelligence, I believe, is really
in augmenting,
clinicians. So things that will, release the,
burden of care delivery. So one of the
biggest things we've done is to roll out,
ambient listening,
for the doctors. And what that is is
it's a scribe technology that will literally take
notes,
summarize it for the clinicians.
And in Kaiser Permanente, we've actually deployed it
now to over 14,000
doctors. So the largest deployment.
That's one example. Another example in terms of
augmenting is using natural language processing
to help classify patient emails.
And when we classify the patient emails
according to what they typed, we can better
direct that, for better care.
We're also using some early predictive models for
things like mammography screening, for high risk patients
as well as looking into imaging,
to look for cardiovascular disease, for example, imaging
in the back of the eye.
And chips and gears just slightly to data.
Currently, health care leaders are managing greater volumes
of data and more devices on a growing
number of care settings and populations.
And this is a very complex environment that
we find ourselves in. So what clinical data
integration tools or practices are you seeing drive
improvements in patient outcomes?
Yeah. You know, that's, it's funny because that
topic is coming up right now. But the
truth in reality is we actually have been
collecting data for a very long time in
health care. If you think about home cardiac
devices and cardiac monitors, they've been collecting
information forever,
and alerting, clinicians and doctors to,
things like, dangerous, arrhythmias and so forth. So
that's been going on for a while. I
think that the number of things that we
can do now is is gonna increase.
So what's really gonna have to happen is
our ability to synthesize the data and to
summarize it. So at Kaiser Permanente, we are
looking at things like, continuous glucose monitoring for
diabetics
and really being able to, put that into,
graphs and algorithms
that are able to alert us to changes
in therapy in the in the therapy of
the patient.
And we're also looking at home based monitoring
for things like o two sats
and weight based care. So that's that's all
the things we have, that are coming. The
real crux of data is basically what to
do with it. And so behind that really
is the, is a need to really, really
really to organize operations to be able to
consume all this data.
And as we talk about this great volume
of data, AI adoption, all of these technological
innovations,
our burdens on our a IT staffs are
becoming increasingly
great.
So I'd love to hear how you think
health care organizations can better support both our
IT and our clinical teams as we're carrying
out innovation efforts, and if you've seen any
common pitfalls in this area.
Yeah. It's a it's, it's, it's becoming a
a big question. You know, there are a
lot of things that are coming out. We
call them bright shiny objects,
from IT and, from devices and products that
people are seeing. And the real question we
have to ask ourselves is is really,
what problem are we trying to solve?
And I think that in health care, that
is a really, big challenge to really to
start off with that. Like, you know, what
are we actually trying to solve with these
tools? I think that actually will help out
our IT colleagues a lot because then they
will begin to know what to focus in
on. There's another, kind of phenomenon that's emerging,
and that is the the phenomenon of technology,
becoming,
more capable
and available than what we can possibly consume.
So there are 2 concepts that we're looking
into, and that is basically,
technology being a push and, operations and business
being a pull.
So those have to start to harmonize.
A lot of times, in when we start
to think about delivery of care, there are
things that we've done for a very long
time.
And we don't really go back to see
if we can do them better. It's just
the way we've always done it.
So having technologies
that have capabilities that are new, the bright
shining object, is good if we introduce them
in a way to to say, is there
a way to make your operations more efficient
than you would have ever thought?
So viewing these, these technologies is actually very,
very helpful. Ambi and Scribe is a good
example of that. I can tell you countless
doctors
who saw this technology and said I would
never use this.
But the moment they started using it, the
adoption goes through the roof. I I literally
have not met a single person yet who
hasn't said that they couldn't use ambient listening
in some capacity.
At the same time, the business pool has
to be we have to be able to,
on the operational side, really clearly define what
we need so that we can go ahead
and tell the technology. So you have to
reconcile these two forces. 1 is a technology
which we don't necessarily know what we're gonna
use it for
and finding ways that it can be used
better. It it can help us better. And
then really being able to define the operational
needs so that the technologist
can build it for us.
And as we wrap our conversation up, what
is your top piece of advice for health
care leaders as they prepare for further advancements
in technology and greater demands for care?
You know, keeping your, your mind open to
what technology can do,
the biggest barrier will be around,
adoption in my mind.
You know, by nature, health care is a
very conservative field. But at the same time,
there are certain risks that I think we
need to take with technologies
as long as there's some backup plan. So
that would be my biggest advice is being
willing to take a chance, but also being
able to develop the operations to catch the
system if there's something that's wrong and being
able to iterate and move faster.
Absolutely. Well, doctor Nguyen, thanks so much for
joining me today on the Becker's Healthcare podcast.
Again, we are live at the 9th annual
Health IT Digital Health and RCM conference. Thank
you so
much.