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This is Laura Dierda with the Becker's Healthcare
podcast. I'm thrilled today to be joined by
Omkar Kulkarni,
vice president and chief transformation officer as well
as chief innovation officer at Children's Hospital Los
Angeles. Omkar, it's a pleasure to have you
on the podcast today. Thank you for having
me.
Now I'm excited for our discussion. I know
we'll be digging into some of the cool
things you've done in the last year or
so as well as your perspective on the
future. But before we dive in, could you
tell us a little bit more about Children's
Hospital Los Angeles and what makes it unique?
Absolutely.
Children's Hospital Los Angeles is an amazing organization.
We are, the largest,
children's hospital,
out here on the West,
in California,
and, we are top 10 children's hospital.
We provide multidisciplinary
care,
in,
in in various subspecialties
across pediatrics.
What's incredible to me about Children's Hospital Los
Angeles is we are not only an exceptional
organization for
health
care delivery. Our clinical care is some of
the best in the country.
And, also, we are a safety net hospital.
So,
we are unique in that sense in that
we take care of the safety net in
terms of the children of Los Angeles and
broader Southern California,
meaning we will,
take care of patients
regardless of of their insurance and their ability
to pay.
And that is incredibly important to me and
and every one of the the thousands of
people who work here.
It is part of our mission. It is
part of kinda who we are, and it
makes it a fun place to work and
and a rewarding place to work. I'll tell
you that.
Absolutely. That's amazing to hear. You know? And,
certainly, what a great mission to serve children
and promote health within the community.
Now from your perspective and looking back on
the last year or so, what are the
accomplishments that you're most proud of?
So we have really jumped
two feet in into
the world of artificial intelligence.
We we've done many, many things,
not just AI, but one of the things
I'm really proud of is our approach towards,
evaluating
and then prioritizing
and then,
you know, implementing the piloting and implementing
AI solutions here at the Children's Hospital.
I say that because there's been in the
industry and you know this, there's been so
many,
incredible new technologies that have been introduced in
just the last, you know, year or two.
And it can be hard for a hospital
or a health system to,
you know, make sense of all that,
information and all that, you know, sometimes noise
coming in as it relates to all these
different amazing companies and their technologies.
And we've done a great job,
you know, starting with the problems
that we're trying to solve, always problems first
and
using that as our guide to help us
figure out how best we can solve the
solution. So instead of being kind of about
the technology, we are we've always been this
way with from with regards to innovation,
but especially with regards to AI. We've been
incredibly disciplined about being problem first.
And as a result,
we've come up with some great,
deployments
of technologies
that leverage AI and are making an impact.
I love that. I I think it's, really
cool to
to know that you're looking at AI. I
know that's something that so many different hospitals
and health systems are trying to make sense
of and and really figure out where the
value is going to be. So, you know,
when you look at, the biggest problems or
challenges that AI is taking on, how do
you measure its success? How are you really
incorporating that into workflows and taking that from
a pilot into more of a a scalable
operation or initiative?
They're really good really, really good question. Right?
So every single one of our projects that
we do in innovation,
especially those that leverage artificial intelligence,
we are carefully looking at,
you know, pre and post data. Pre data
meaning what is what is the metric that's
going to evaluate the
the efficacy of a specific process?
You know, how effective is it before you
introduce the technology
and then carefully evaluating, you know, post
AI deployment.
How is that how is that process been
improved?
Often it is a productivity measure. Often it's
a financial measure, clinical measure as we think
about
different ways in which the AI can be
used, but being really concrete about what the
baseline data is and what the improvement is.
I know that sounds simple. It's basic kinda
innovation one zero one, but it's been a
really key part of
of the process for us. We've also introduced
in all of our AI projects this kind
of phase zero
in which we are
validating
and testing the models,
using our own data before it actually goes
live to patients or staff depending on the
use case. So we are evaluating
these technologies,
leveraging retrospective data,
you know, in a really
in a really
controlled manner to really make sure we're comfortable
with the output of the product before we
make it available to
end users who will ultimately be using it.
So that that approach of kind of incorporating
this kind of pre pilot phase zero, whatever
you wanna call it, is really helpful to
help us really understand,
and and make sure these the tools are
are really delivering on what what the promise
is before we introduce them to to real
workflows.
That's really helpful context to understand. Thank you
so much for digging a little bit deeper
in there for us. Now when you look
into the future, where are you thinking about
the biggest opportunities for growth and development,
for your team?
So there's a few areas that are interesting.
Right? So I think,
within
within the space of
one of the most exciting things about artificial
intelligence, let's start there. And I can answer
broadly about things that are, you know, technology
in general. But with regards to AI, one
of the things that appeals to me the
most
is there are many ways that you know,
organizations
and hospitals
specifically like ours
could build our own AI solutions
in a safe and and, you know, efficacious
way
without expanding a ton of resources. Right? That
may not have been possible a decade ago
as we thought about other technologies that you've
been the hospital wanna build. But with AI,
there's a lot of opportunities for us to
build
small, simple
tools. You know, nothing that's gonna commercialize and
be massive, but something that solves a real
problem for us here, either clinically or administratively
or in our research enterprise or our teaching
enterprise,
something that solves a problem that we can
build in house and perhaps
even get to a place in the next
few years where, you know, people who aren't
kind of computer scientists could even
stand up simple solutions that could either work
for their own workflows or for their team
or department. So this whole world of,
you know,
build within AI
is really interesting for us as we think
about solutions that we can build in house,
in partnership with some of our key stakeholders.
But then the broader piece, I think,
for me is
I think we're getting to a place where
where a lot of this technology, a lot
of which is enabled by AI,
is enabling us to
optimize the the output of our,
of our workforce,
which is so crucial. Right? So by that,
it could be that we're improving productivity as
some of our administrative team members.
We could be making we could be helping
our clinicians,
make better, you know, even even better
decisions based on intelligence and and data.
We we could be enabling for care to
be delivered faster
or or improving access so that more people
can access the the clinical care they require.
So I'm just really excited about that element
of where we're headed.
It's not all gonna be AI. Some of
it it can be in it can involve
a variety of different technology modalities, but I
think we're getting to a place. We've been
on this road for a while, but we're
getting to a place where, you know, the
demands of our kind of primary service areas
individually are our population essentially.
The health care demands of our populations
just continue to exceed what our workforce can
deliver, which is relating to all these access
issues, but it's also relating to workforce issues
relates to burnout and it relates to experience.
And I'm really hopeful that we can design
and prioritize solutions
with technology and AI specifically in the next,
you know, few years, if not sooner, they
can really they can really make an impact
on both those things. Let's increase patient access.
Let's give patients answers,
good high quality answers to what they're looking
for, you know, sooner,
and let's enable our clinicians
to, you know,
have assistance and help so they can really
focus on what they got into medicine for,
which is to to help save lives and
to help treat people.
And, you know, and and at the same
token, let's help our health systems,
you know, do the administrative work required to,
you know, keep our doors open. So I
I think there's this trifecta that's that's
really close, and we're we're getting close to
kind of figuring it out.
That is amazing to hear. And what
a cool future that you have painted for
us in terms of being able to utilize
and leverage AI better in a more specific
basis and and having the teams and expertise
available, as well as the technology
to really improve health care and the outcomes
of of patients and populations across the country.
I'm curious when you look at that and
and knowing that the technology is coming, how
do you, really build your teams or educate
your current, workforce to make sure that they're
ready for that, for that future and for
a time when, you know, AI can be
used in such a a more sophisticated way?
So really, it's a it's a really important
part of the innovation process, which is kind
of tilling the earth in a sense. Right?
Getting the the soil ready for the future.
The soil and as you describe it in
this analogy would basically be our workforce and
and included in that is not just our
workforce, but our patients and families. Right? How
do we enable people to to get comfortable
with this? So a lot of it is
exposure. So exposing them, exposing our our our
staff, our clinicians to what's happening in the
industry. Like, what are other examples of children's
hospitals who have proven
value using certain new innovative technologies, whether it's
AI or digital health or virtual care? What
are examples? What are papers? What are studies
that have been done?
Building that evidence base is really crucial. That's
how medicine is you know, that's
how medicine is really
medicine in general has advanced over, you know,
hundreds of years, which is someone discovers something
new, they generate evidence around it, and they
disseminate that to their peers, and that then
builds and moves everybody forward. It's not it's
not all that different as we think about,
you know, technology adoption. If we that's what
I do. Right? We we try to find
and surface,
including through your own organization and all the
great work that you you surface. Right? There's
a great,
you know, Becker's article about this that someone
else is doing, sending it to different people
who I imagine are gonna be part of
that, you know, team that's gonna help us
do it in the future at our hospital
that those little elements of exposure are key.
The other is really picking the right problems.
Right? So we wanna make sure that we're
picking the problems that are gonna be most
impactful.
And as we do so, making sure that
the people who we are going to include
in the process or people like you described
who are ready for that change.
And so, you know, that is helpful. We've
got an amazing, our chief data officer,
has chief enterprise data officer has has a,
you know, an analytics program
that he has, got people across the organization
kind of doing. So there's some actual hard
skills that we've got,
people learning as it relates to intelligence, data,
analytics, AI.
So there there's there's both, you know, didactic
learning, exposure,
and then just change management that are, I
think, all key to getting that workforce and
community ready for the changes that are ahead.
Got it. That's, amazing to hear. And, you
know, I I really love that analogy as
you talked about, you know, building the soil
and getting it ready for the future. And,
certainly, it takes a lot of time, effort,
energy on the technology as well as the
people side, but truly, truly,
with great outcomes,
as the potential rewards. So that's awesome to
hear. I know we've talked a lot about
some of the opportunities and the cool things
that could come,
from the technology side of health care, especially
AI, but I'm curious from your perspective,
what are some of the challenges you have
your eye on as well? What do you
see as being, potential headwinds or things you'll
have to overcome in the future to to
reach this ideal state?
So I think
what's exciting is the technology is being developed
so quickly. The challenge is that
unless you have really
high performing,
consistent
and somewhat sometimes standardized processes,
across your organizations,
if you don't have those in place,
putting
a
a nice, exciting new technology on top of
the current state is just not going to
it's not going to be great. It's not
going to work well. It's really complicated to
do. And especially as we think about the
new technologies coming out now, they really rely
on having
strong core operational processes.
And so as we think about it, I
mean, we all we all in our organizations
have varying,
you know, levels of
process,
you know, cleanup to do. But that's a
key part of, I think, the success is
making sure
that that the the processes
that that, you know, they're underneath all these
exciting new technologies
that they're
as highly
functional as they can be. So that when
you layer on the technology,
you are you're doing so in a way
that is optimizing the value of that technology.
So that's one. The other
is and it goes to your previous question.
I still think there is
a sizable
change management element that we need to navigate.
And it's not just around do we trust
AI? But I think people generally any technology
it changing from their current workflow to a
new workflow,
unless it's really not, you know, noticeable change.
Change for people, especially in our industry, is
not easy. And and we need to really
think about, you know, some of the core
core basics of change management as we think
about,
how we're going to, you know,
get the maximum value out of these innovations.
That is absolutely crucial and definitely being able
to double click and and zero in on
those spaces where there could be
additional challenges or or ways that, success could
be hindered. It makes a lot of sense
and then truly moving forward in an optimized
fashion. Before we wrap up here, I'm curious.
What is the number one thing that you're
doing right now to set up Children's Hospital
Los Angeles for long term success?
I think one thing, and and it can't
it's not a me. It's a we. Right?
This is not there's no
there's no unique thing that I do. I
I I help lead, but there's a team
that does this.
We we've we've established, I think, a really
great process around technology
evaluation.
And it's not just looking at kind of
vendors and solutions that are out there, but
what we do
is we kind of understand the current process,
determine,
you know, is that process in a place
where we feel like it's ready for for
innovation?
And if it is,
you know, what are the core problems that
we're trying to solve? And then we, you
know, we
work with stakeholders to figure out what are
within those problems, what are the most important
problems and what are the ones that are
gonna result in an ROI. And then we
go find innovative technologies that solve those problems
and building that robust,
you know, toolkit
pathway around,
you know, identifying innovation solutions, I think is
a really key
important discipline, especially as I said at the
very beginning of this conversation.
There's so many amazing solutions out there that
it can be really easy to get distracted
by, you know, the the next kind of
great thing that you get pitched.
And so having the discipline around looking at
the process, looking at readiness, looking at problem,
you know, prioritization,
it's really key as we think about the
the ultimate goal, which is
picking a handful of projects that we think
are gonna deliver the maximum value across our
organization with the maximum amount of adoption.
So I think we've been able to put
that process out there, and I think that
process
is really gonna help us.
It is it is already helping us, but
I think it will help us in the
future continue to make disciplined decisions as it
relates to innovation.
I love that. Omkar, thank you so much
for joining us in the podcast today. This
has been a really fantastic discussion, and I
look forward to connecting with you again soon.
Thank you for having me.