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Hello, everyone. This is Jacob Emerson with Becker's
Digital Health and Health IT podcast. Thanks so
much for tuning in to all of the
media opportunities with Becker's Healthcare.
Today, we're thrilled to be joined by a
special guest. Doctor. Rohit Chandra is executive vice
president and chief digital officer at Cleveland Clinic.
Doctor Chandra, thank you so much for taking
the time to be with us on the
podcast today.
Oh, thank you.
So, Rohit, there's a lot we wanna talk
with you about today. But to get us
started more broadly, there's obviously a lot going
on right now all across the healthcare tech
world. So so talk to us a little
bit about from your perspective, the the trends
that you're watching most closely right now that
you think isn't receiving enough attention either in
the media or among your industry colleagues.
What what's top of mind for you right
now and within your role?
I think there's a few different areas that
we're trying hard to pay attention to.
Stepping back. I think the
developments
in AI,
especially over the last couple of years have
been
mind blowing. And I think the potential is
remarkable.
I think a few trends that I think
we're trying hard to keep an eye on
is
this traditional machine learning, which is well understood
and or at least much better understood in
the industry and making sure that we're leveraging
that where it makes sense is important.
And separate that a little bit from generative
AI, which has shown up in the flavor
of chat GPT
that is has
remarkably different potential to help streamline healthcare.
So I think keeping an eye on both
capabilities that are emerging from technology, I think
is important.
The second part I would say is that
within healthcare,
we all get excited by the,
I will say the shiny objects that have
to do with frontline clinical care.
But given that AI
is an imperfect technology that we're still trying
to learn how to deploy and use in
a responsible and safe way,
it's important to not just
look at clinical use cases, but to also
look at
nonclinical use cases where we can learn how
to use it, apply
it in a much safer setting where there
is minimal risk to patient harm.
The
third area that we're trying to keep an
eye on is
just technology is an enabler. It's important to
think in terms of the healthcare problem so
that it is our responsibility to connect the
dots from technology to the change that we
wish to drive within healthcare.
Absolutely. And I wanna follow-up with a really
important point you just made about AI's use
cases beyond just clinical care. As I understand
it at Cleveland Clinic, you're using AI in
a lot of different ways right now, including
accelerating the pace of medical research and
addressing staffing and organizational
challenges.
So Rohit, if you were going to look
back over the last, let's say 6 to
18 months, is there any initiative or accomplishment
that that you're most proud of within this
space? And and can you tell us a
little bit about that?
So we focus on a few different areas
that actually span both clinical and nonclinical.
I give a few a few examples from
perhaps each of those. In clinical care, we've
been working on an effort to do
prediction of the onset
of sepsis.
Now, sepsis is a
bloodstream infection that has a very high mortality
rate,
and and it kills nearly like a 1000
people in the country almost every day.
And with those numbers, it becomes
quite imperative for us to bring everything we
can to bear on treating sepsis.
So that's an area where we're using machine
learning and AI to predict the onset of
sepsis,
to
integrate that with our clinical care protocols
so that we can alert our caregivers
to the onset of sepsis and drive early
intervention.
And that is the best known methodology
to help take care of our patients better.
So that's a clinical use case and I'm
quite encouraged by the data that we have
so far where if we can get roughly
6
times better positive predictive value of patients with
the onset of sepsis
with very few false alarms. And this is
critical
to our caregivers so that their resources can
be deployed on the patients that need it
the most.
That's an example in clinical care.
For caregiver,
there's a second area which really has to
do with work,
staffing
and
caregiver burnout
where we are leveraging
AI powered scribes.
And think of this as physicians and nurses
spend
anywhere from
1 to 3 hours a day
on clinical documentation.
Now this documentation is essential for patient care
and for regulatory reasons,
but it is very time consuming.
And one can imagine that technology that can
automatically listen to a conversation,
transcribe it, summarize it, has the potential to
significantly streamline
the efficiency of the caregivers.
So that's an area where
we're actually working with a few different companies
to test drive their technologies.
And
if you're successful in this effort, we will
have the potential to substantially
streamline the work of our caregivers.
A third area, which is still in the
early stages is actually the other extreme of
the spectrum, which is back office.
And there we're focusing on
the problem of coding.
Now coding is essentially the task of taking
a patient encounter
and the documentation associated with it and generating
billing codes for reimbursement purposes.
It's a necessary part of our business,
but it is also very manual, very cumbersome,
and very costly. I
think
Now if I step back, I think,
the question you asked a little bit was
what are the things that we're most proud
of? I like these initiatives
in that they touch on different areas of
our operations.
The other part I think that's important is
they're a good set of initial steps to
take in bringing AI into the organization.
And they're teaching us the playbook, the methodology
on
how to engage with different partners, how to
bring those technologies in, how to streamline the
process of leveraging those technologies
in a clinical care context or a caregiver
context. And this methodology and playbook is I
think going to be the foundation for our
success going forward.
Wow. Well, those are some really fantastic examples.
I I appreciate you sharing those with us.
And that that last one you mentioned about
back office coding,
you mentioned that was new, Rohit. Where are
you at with that? What's what's the timeline
of that most recent initiative?
So,
we're engaging with a variety of partners.
The timeline, I would say, is we're somewhat,
I'd say, in the early stages of doing
a pilot where we've identified
areas within coding,
just the whole revenue cycle management in the
industry is a complicated space.
There is prior authorization
for a set of encounters. There is the
actual coding and billing exercise, and then there's
a subsequent denials and claims exercise. So revenue
cycle management is a complicated area.
Where we are is
we're pushing on each one of those, but
we're at different stages on each one. So
right now, we're currently more focused on the
middle area, which is converting
the a patient chart to the corresponding billing
codes doing and being able to do that
more automatically and more efficiently
than we do today. And that's an area
where we hope to have results within the
next, I would say, 6 to 12
That's really interesting. And I imagine someone who
will be helping you on a lot of
these initiatives
is your new chief
AI officer,
who you actually just announced today here at
the end of July.
You're one of only a handful of health
systems nationwide that now has a position
like this in place.
So can you talk a little bit about
that? What went into that decision? And,
do do you think that all health systems
should be moving in this direction?
So I'll
I think it's important to step back, and
our thinking on this has evolved over time
as well.
Our beliefs have evolved over the last couple
of years to think that both the developments
in technology and AI
are actually accelerating
And the potential for these technologies to transform
entire industries
is remarkable.
You combine that with the
health care as an industry
that is in substantial
need for this transformation.
So sitting in our shoes, I think there's
a unique opportunity to say healthcare as an
industry really needs technology power transformation and the
emerging technologies have remarkable capabilities.
So that's what prompted us to say, how
do we elevate this to a first class
effort for us?
And that's what led us to say that
if it is an important enough area for
us that has the potential to transform healthcare,
then it needs to be something where we
need to make sure that we have
internal expertise,
not just working with external partners, but we
need to have in house expertise that can
help us navigate
these waters as technology evolves and as healthcare
needs evolve.
I think the related question that you so
that's what went into our decision to say,
hey, let's bring on somebody with AI expertise
into the organization.
I think the second part of your question,
should all systems do the same?
The way I would approach it is I
think it is important for every system to
approach AI with the potential for it to
over time
transform
many of their core operations
ranging from clinical to non clinical. And I
think that positioning themselves to navigate those waters
is important.
Do you need a chief AI officer necessarily?
Those organizational constructs may vary from organization to
organization,
but I would say that there needs to
be a process by which organizations are being
intentional
about the areas that are most important to
them,
intersecting them with the potential for technology and
AI,
and engaging with the health tech ecosystem
with that mindset. I think that's an imperative,
a chief AI officer is obviously interesting construct
to go about it. But I think that
every health system should be thinking in those
terms.
Absolutely. That makes complete sense. I I appreciate
you sharing a little bit about your thoughts
on on that topic,
which I imagine will be a big point
of conversation at our upcoming,
health IT event in Chicago in October, which
I know you'll be a speaker at. So,
one thing I did wanna ask you is
if, and I and I imagine this some
some thoughts you'll be sharing similarly at that
event. But is there any advice that you
would give to evolving leaders serving in similar
roles like yours?
What would you share on this podcast while
you have the ears of of a lot
of health system leaders from across the country?
I
think my learning
over the last couple of years is
it's very important
to be
intentional
about
the problems that we are trying to tackle.
While the evolutions
and sort of the developments in technology and
AI are amazing,
eventually they need to be in service of
a healthcare problem or need.
This becomes all the more important
because
technology is just an enabler.
The adoption of technology, the adoption of AI,
the culture, the process, the people, the change
management required to actually drive
change and change in outcomes and the transformation
in healthcare is not easy.
So it's important not to underestimate that adoption
of AI
that it makes sense is not easy. So
it's important to start with a very intentional
mindset that says, hey, these are our key
problems.
This is where technology fits in. And if
we have technology that works, this is how
we're gonna drive the change management, the adoption,
and the process changes that need to go
in
into,
actually helping transform healthcare.
Just as an example, if you look at
the sepsis example that I use where I
said, hey, we're using AI for the prediction
of the onset of sepsis.
That's only part of the story.
Those
technology powered alerts
need to be baked into the clinical workflows
that are used by nurses and are used
by doctors so that they adopt them, they
take action based on them and it drives
the right interventions.
So the process change cannot be underestimated.
So I think those are the 2 aspects,
which is be very intentional about the problem
areas that you're trying to go after and
be very mindful that it's not just about
technology. The change management is a significant lift.
Mhmm. Well, it's it's great and timely advice.
So appreciate you sharing that. Anything else we're
missing? Rohit, any any final thoughts you'd like
to share?
I think the main thing is that,
like the developments in technology are fascinating.
It becomes tricky on how to navigate them.
All of the things that I alluded to,
which is, are you intentional about the problems?
Are you intentional about
the change management? All of this is hard
work. I think at the same time,
the part that fascinates and excites me is
the potential for these technologies
is amazing. One can imagine a future where
the
amazing amount of inefficient back office paperwork that
we do is mostly automated
with
technology, AI, and generative
AI. One can imagine clinical care that is
increasingly powered by a highly intelligent agent.
I don't know the path to get from
here to there and I don't know how
long it will take, but I am convinced
that if you navigate these waters well,
this technology has amazing potential
to transform healthcare and make it
more accessible,
safer,
more scalable, and available to many more patients.
So I'm very intrigued by the potential
and that's a journey that I think they're
all on.
Fantastic. It's exciting stuff. So, doctor Chandra, thank
you for taking the time to sit down
with us and for sharing your insights with
our listeners.
You're welcome, Jacob.
If you'd like to listen to more podcasts
from Becker's Healthcare, you can visit beckershospitalreview.com.