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This is Laura Dierda with the Becker's Healthcare
podcast. I'm thrilled today to be joined by
doctor Clara Lynn, vice president of digital health
and informatics as well as chief medical information
officer at Seattle Children's. Doctor Lynn, it's a
pleasure to have you on the podcast today.
Hi, Laura. Thank you so much. Glad to
be back.
Absolutely. And, you know, it's always so fascinating
to talk with you because Seattle Children's really
is doing some innovative things and, is on
the forefront of a lot of what's happening
with digital technologies, AI, and health care and
more. And I know you recently partnered with
Google on some technology developments as well, so
I'm excited to learn more about that. But
before we dig in, for those who
may be newer to the podcast, can you
tell us a little bit more about yourself
and Seattle Children's? What makes it unique?
Yeah.
Seattle Children's is a coronary
referral hospital in the Pacific Northwest.
One of the things that we're super proud
of of among other things is that we
are ranked as one of the top 10
children's hospitals in the country by US News
and World Report, and we are unique in
that we serve a very large region. We
cover the Washington State, Alaska, Montana, and Idaho
region,
as the referrals center for kids in this
area, and we're also the only freestanding children's
hospital in in the state.
Well, that's fantastic. And, you know, could you,
dive in and tell us a little bit
about the accomplishment that you're most proud of
from the last year?
Yeah. I think,
we've done so many cool things. We really
try to keep Seattle Children's as a leader
in innovation, particularly when it comes to pediatric
health care and be an advocate for for
kids when it comes to,
the the national and and global trend of
developing
and innovative technology.
But that being said, if we go back
to sort of the bread and butter, the
really basic stuff, some of the things that
we're super proud of are, of course, our
quality of care,
the fact that we are we've been
ranked and certified by US News World Report
as one of the top 10 children's hospitals
as I mentioned earlier. But, also,
we did our class survey for the first
time in three years in 2024.
The last time that we did it was
in 2021
right after we implemented
a new EHR in the middle of a
pandemic.
And then this is the first time since
we've come out of that sort of stabilization
phase and moving into more of an optimization
and innovation phase.
This is the first time we've done a
class survey, and we're so proud that our
both our physician and our nursing
EHR satisfaction score went up significantly.
My role as the chief medical information officer
is of course with our providers and making
sure that,
that the experience with health IT in general
is a good one. And the physician and
provider
class,
EHR satisfaction score went up by 30 points
in the three years, and that's just something
that that we're so proud of. I mean,
there is so much AI, so much cool
stuff out there, but really the bread and
butter things to make it
a good environment for our clinicians to work
in, to make it not a,
cumbersome some experience for them to provide care
to to the kids in the region. That's
really what my job is, and, really excited
to see that that outcome.
That's great to hear. And, you know, when
you look at those changes you've made and
the transformation that brought you to this point,
where you're seeing such an increase in clinician
satisfaction,
what what did you do? What can you
attribute to some of those things? Is it
just the advanced technology, or are there other
ways that you have really been able to
connect with the,
clinical leaders in in team and,
improve that satisfaction that that you have with
the EHR?
Yeah. I think it's it's a little bit
of both.
AI and innovation
is definitely top of our mind. It's top
of everyone's mind. But really the basic stuff
the going back to the basics the bread
and butter stuff is also really really important
making sure that our EHR
is optimized in from an informatics perspective,
from a usability perspective, from just a supporting
and designing workflows that make sense. I think
all of those things helping helping every role
practice at the top of their license, helping
supporting our physicians and our providers to do
what they're trained to do to help,
provide the best quality of care. I think
all going back to the basics is what
we really focused the last three years,
on doing,
and, and it's really paying off in in
that in that survey result.
That's helpful to know. And and really, definitely
centering to have an understanding of just, you
know, getting back to those basics and understanding
what is gonna be most helpful and beneficial
for the clinicians and bringing that forward. I'm
curious. Where do you see some of the
growth opportunities for your team in the next
twelve months or so?
Yeah. I think the from a from a
health IT perspective,
like everybody
else, the biggest growth opportunity is, of course,
artificial intelligence and what it can offer,
and not just the the the potential that
it can bring to the care that we
deliver and the experience of our our,
workforce, but it's also
in terms of how we can
help our internal workforce skill set grow when
it comes to artificial intelligence. And we're not
just talking about the IT teams growing and
not just talking about giving, you know, cool
generative AI to our our every, you know,
employee to to write emails or make PowerPoints.
That that is great. But I think what
another really big opportunity here is we can
help our workforce become more comfortable
in using artificial intelligence, and they can have
the tool built and the framework that they
need in order to, and kind of a
mental model that they that we can provide
them to evaluate
AI technology when they're interacting with it on
a day to day basis. So evaluating it
critically. Am I using it right? Is this
tool fishy?
You know, do I feel like there's a
concern here? How do I do how how
do I use this particular tool on my
desktop, you know, responsibly? I think those are
that's that's where I think we need as
an organization and as an industry need to
grow in is to start to disseminate this
type of,
this mental model, this framework to help them
critically evaluate these technologies,
on a regular basis.
Got it. And that and it's fascinating to
hear it. And really cool,
to see some of those the AI technology
come into
the day to day use spaces,
and understanding what the workforce needs, supporting them
the right way, but then also of scaling
them into a a place where it,
really becomes most valuable and useful. I'm wondering
too, could you tell us a little bit
about some of the things that you've been
working on with Google and,
just, you know, early what that experience has
been like and and the outcomes?
Yeah. So that was a that was a
really cool experience. So,
about a year ago when,
artificial intelligence and particularly generative AI
became sort of the talk of the town,
Seattle Children's, like everyone else, started to think
about sort of where our use cases are,
where our needs are. So we're not we're
not really going out there to look for
technology and then trying to retrofit it into
our environment. We're really starting with what the
frontline users are asking for and what their
where their needs are. And so,
we
we came up with a list of use
cases that we thought would be,
would be very beneficial to the organization from
an operational efficiency standpoint, from an improving the
quality of the care perspective.
And this particular one that we developed with
in partnership with Google,
ended up being sort of a proof of
concept for us, an early use case that
we wanted to see if it's possible in
a in a sort of fail fast model.
Can we get this technology
using Google Gemini,
to to a state where we think it's
clinically acceptable and from a workflow's perspective,
that is usable and from a technology standpoint
that is scalable.
And so we can of the four or
five, use cases that we ended up coming
up with, we you know, for each of
the use case, we partner with a different
different
team outside of Seattle Children's, and this particular
one was with Google.
And, what we've done is I I need
to take us back a little bit further.
So in 2010,
our,
Seattle Children's created this group called the clinical
effectiveness program, which is under our center of
quality.
And what the clinical effectiveness program does is
that it looks at all of the medical
literature out there. There's millions upon millions. Right?
The medical literature doubles every 70 something days
these days. And the clinical effectiveness team sort
of gathers the most up to date information
and the guidelines that are out there for
each and every disease across the 70 diseases
or conditions that that we have on our
catalog. And for each one of these condition,
they develop
a guideline, a pathway
that we think is the standard provides the
best of care in a standardized fashion. And
so now that we have these 70 something
conditions
sort of created and
provided a guideline and a pathway to to
our clinicians, we can standardize the best of
care for every kid regardless of which provider
you see at Seattle Children's. And so that's
kind of the basis that the shoulders of
the giants that we're standing on. So this
particular tool that we created with Google called
Pathway Assistant
sort of is an evolution to that. So
we took these thousands of pages of really
great content
developed by the clinical effectiveness team under our
center of quality,
and we layered basically Google Gemini on top
of it. And it's not also just the
straight of Gemini that we can see on
online, but it's really a Gemini that's been
fine tuned specifically to these,
these pathways that we see our children's has
developed. So it's only referring to these pathways.
We did it purely through prompt and fine
tuning of Gemini.
And, right out the box, it had a
decent
accuracy, but not good enough for clinical use.
And we kept tuning fine tuning and prompting
and changing, you know, the the prompts and
and making sure that that Gemini understands what
we were trying to get out of it.
And the end product is a conversational
chatbot that can ask you questions if your
prompt is not specific enough, and then it
gives you an answer back. So I can
ask prompt the the chatbot, for example, the
pathway assistant, for example. Hey. I have a
four year old in front of me in
the emergency room with an asthma exacerbation.
What should I do next? The chatbot will
basically ask you questions about the patient. And
then in the end, it doesn't tell you
what you should do next even though that
was the question I asked as a physician.
But what it will do is it will
collate all of that evidence based information
from the pathways that we've created
over the last fifteen years,
by these, you know, dozens of medical experts
here at Seattle Children's. And then they present
that information to the request or to the
to the person that's chatting with and says,
this is here all that information.
Here is the page of guideline that where
I'm referencing from, and here's what we the
guideline suggests your next step of evaluation should
be. And so the human ultimately is still
the one that's making the decision,
and ultimately deciding if this is the information
that is most appropriate for the patient in
front of them. But we using pathway assistant
effectively shrunk the information searching time to just
seconds for for the clinician.
Wow. That's fascinating. You know? And really amazing
what you're able to do bringing all that
information,
in in data and,
pathways together to then, you know, in the
moment, find what will be a recommendation,
that is personalized to the patient. That's really
cool. And and seems like it has a
lot of benefits for clinicians as well as
patients in the future.
Oh, yeah. We're we're really excited. And and
one of the things that that we use
this also as a proof of concept to
see, can generative AI and large language models
cat catalog internal documents like this in that
sort of a breadth. And also, it wasn't
just text because we also fit part of
the a lot of the guidelines are flowcharts
and and spreadsheets and images and, you know,
references and and things like that. And so
it was really,
a multimodal ingestion into the large language model.
And so this was the proof of concept
that we needed to show that, you know,
it can
technologies like this can accommodate
our needs,
beyond sort of the the the the pathway
what what the pathway assistant itself can do.
It's fascinating to hear. Thank you so much
for sharing with us that,
the technology and the innovation journey you've been
on. I I think it meet makes for
a lot of huge opportunities in the future.
We'll just keep an eye on how things
continue to evolve and grow.
I'm curious. You know, we talked a lot
about some of the cool things that are
happening, but what are the challenges that you're
anticipating, especially with technology and AI as well?
Yeah. So I've been thinking about that a
lot lately.
I mentioned earlier that we selected
a small handful, three or four,
AI solutions that we developed ourselves,
starting over the last year with with different,
different teams and different people that we collaborated
with.
This was just one of one of the
three or four that we developed. But then
at the same time, the organization
hasn't slowed down. Right? Like and and the
industry didn't slow down. And so so the
industry is booming, including our own EHR our
EHR epic. You know, they're developing a ton
of AI AI solutions. And then out there,
there's also a lot more off the shelf
products that a lot of our teams are
evaluating and trying to incorporate into their workflows
and into into the organization.
So this is only a growing technology, and
it's growing quite rapidly. So the biggest challenge
is how do we support the technology
from an infrastructure standpoint
all the way up to governance.
How do we make sure that we are
evaluating,
you know, implementing,
scaling,
and then maintaining
that growing portfolio,
whether it's something that's purchased or licensed off
the shelf, or something that we've developed,
upfront. And so so that is what I've
been thinking about a lot and really trying
to figure out because I think that ultimately
will be the challenge, not just for Seattle
Children's, but everybody out there in health care
IT,
that is seeing sort of a rapid expansion
of their their AI portfolio right now.
That's such a great point. And I I
think that is a lot of organizations that
are are really truly seeing the
broad leaps in their AI technologies and portfolios
or or pilots that they're working on. And
then as you mentioned, just trying to figure
out, you know, what's gonna make the most
sense and, and keep that a growing portfolio
under control is,
easier said than done, I think. Yeah. For
sure. Fantastic. Well, before we wrap up here,
could you talk a little bit about the
future? What is the number one thing that
you're doing right now to set Seattle Children's
up for long term success?
I think that's exactly it. Is is how
do I how do we, at Seattle Children's,
set up an ecosystem
so that we can accommodate this rapidly
evolving field? Because we don't one is that
we don't know
we don't know where this is all going
right now. It's such a fast moving train.
It's super exciting.
Everybody's on board. Most people are on board.
But how do we how do we support
that? Right? And so what I'm hoping to
do now is to sort of set the
organization up, not just from a people and
skill set perspective,
but also getting,
like I said mentioned earlier, getting the workforce
to a point where they can evaluate
critically their experience with artificial intelligence
on a day to day click by click
basis
so that, so that they know,
hey, that just seems fishy or, hey, that's
a great opportunity for me. So, you know,
that that to me is is a really
critical
step in in democratizing,
I guess, this technology to to every every
area of the workforce. Because I I think
it's only a matter of time that we're
gonna start to see AI incorporated in everything
that we use.
So I think that that is in and
that is, sort of what we're what we're
working on next is how do we set
up our workforce, both structured teams and also
this AI literacy
to to prepare us for the future.
Absolutely. That it is amazing to hear. Doctor
Lin, thank you so much for joining us
on the podcast today. This has been a
really fantastic conversation, and I look forward to
connecting with you again soon.
Thank you so much, Laura.