This is Laura Dierdahl with the Becker's Healthcare
Podcast. I'm thrilled today to be joined by
doctor Rohit Chandra,
chief digital officer at Cleveland Clinic. Rohit, it's
a pleasure to have you on the podcast
today.
Pleasure to be here.
Fantastic. And, you know, I'm excited to dig
into our conversation because I'm looking forward to
learning a little bit more about some of
the cool things you are doing at Cleveland
Clinic right now. I know you've got a
lot, with AI happening, and it's just really,
you know, important to have that perspective and
where you how you're thinking about the future
too. But before we dive in, can you
introduce yourself and just tell us a little
bit more about what you're doing at Cleveland
Clinic?
Sure.
I'm Rohit Chandra. I'm the chief associate officer
at the clinic. I joined the clinic about
four years ago actually from outside of health
care, so I'm a engineer by training.
And in my role here at the clinic,
I have responsibility
for
our technology footprint at the clinic.
And the way to think a little bit
about it is that technology is an critical
capability
for any industry, but for health care in
particular.
And so from that lens, I have responsibility
for traditional IT,
artificial health records,
data,
analytics,
and increasingly,
AI.
That's fascinating to hear. And, you know, a
a huge job in front of you. And
so I think if we narrow it down
to just the last year or so, can
you tell me a little bit about the
projects or initiatives that had the most impactful
results? What did you do, and how did
you measure those outcomes?
So,
for 2025,
I think,
for us and perhaps for many organizations
like us,
the single most impactful
AI initiative has been the AI Scribe.
And AI Scribe for the audience today, just
to simplify it, is
all of us will often, as patients, go
to a physician for an outpatient appointment. And
let's say it's a twenty or thirty minute
appointment
that we have, let's say, with our primary
care physician or some other physician.
What we don't realize is that after that
encounter,
physicians typically need to spend anywhere from ten
to fifteen minutes writing up their clinical notes
from the encounter.
So primary care doctor today can spend anywhere
from
one and a half to three hours
every day
after their clinic time
writing up their notes from each patient visit.
Now this is essential work. It's really important
for continuity of care, for safety, quality, and
everything else. So this documentation is a good
thing from every aspect. It's just that it's
very time consuming.
So what we,
what technology has increasingly emerged over the last
year or
two is something that I refer to as
an AI scribe.
So this is essentially
you can just on your iPhone, you can
have something that will listen to the provider
patient
conversation.
It will
record it,
transcribe it, and then automatically
generate a draft of the physician notes and
the patient notes.
And what is amazing is the technology has
become so good that it can generate really
high quality notes.
We still have a physician in the loop
to ensure that they're complete and accurate,
but,
it can
substantially
reduce the documentation burden on physicians.
And equally, if not more importantly,
it can
significantly
enhance the
patient provider
interaction
during the encounter.
So today, very often, if you were to
go to your see your doctor, the doctor
is often sitting at the computer sometimes looking
at you, but most of the time looking
at the screen typing up their notes. Well,
guess what? With this technology, they don't have
to do that. They can have their full
attention on the patient,
and, the documentation
happens almost magically.
So I would say looking back to 2025,
this has been
a game changing experience in reducing the documentation
burden,
enhancing the provider experience, enhancing the quality of
the provider patient interaction.
We've been very successful at it. We've had
more than 4,000 physicians adopted, and we've had
millions of encounters that have now been
documented
leveraging AI as opposed
to manually.
So I would say looking back in 2025,
that has been a big success story for
us.
That's great to hear. And I know that,
you know,
documentation technology and
AI scribes,
have a lot of value when it you
it comes to supporting the clinicians and making
sure that they're able to have more of
that human to human interaction.
As you look into the next year, where
do you see some of the big,
priorities as well as headwinds that you're focused
on for 2026?
So we're looking at bringing technology
in both
clinical and nonclinical
domains or operational areas.
I think just building on the Scribe conversation
we just had,
we think that the potential for AI
to build significant that the Scribe is just
the beginning.
We think that there are so many more
powerful capabilities
that can help a physician
in delivery of care. It can be
summarization
summarization of a patient chart before an encounter.
It can be engaging with the patient chart
in a much more conversational and intelligent way.
All of these are capabilities that will significantly
provide assistance to the provider at the level
during a patient encounter. So those are areas
where we are trying to enhance and build
upon
the AI scribe, which we think is just
a starting point.
Other areas are, I'll say, more in the
back office space. We've done good work over
the last year in bringing AI into coding
automation.
That has been pretty helpful for us and
has potential to significantly
accelerate that work for us going forward.
We've also
started to use AI and machine learning in
clinical risk prediction. So we launched something to
do sepsis prediction last year
that was very helpful.
Sepsis, just for our listeners,
is a
a bloodstream infection that is very complex to
detect
but and has very high mortality rates.
And so with AI, we can we built
a system that does early detection of sepsis
and that can significantly
improve our ability to intervene early
in patients that show the onset of sepsis.
When I'm going with this is all of
these are areas
beyond just the AI scribe
where we think we have significant potential to
apply AI powered capabilities
in other aspects of health care developing.
That's helpful to understand and really cool to
think about the technology and and implications on
how it can augment it and boost the
quality of care you're able to deliver and
especially with early detection on something like sepsis,
I know is, life saving.
I'm curious. When you look at bringing in,
more of the technology into the clinical setting,
how do you think about,
governance and monitoring and just making sure that
AI stays on track and is giving you
the results that you need? I know it's
not always just, kind of implementing the technology
and and letting it go, but truly making
sure that over time, it's still performing at
the rate you want it to be performing.
Oh, I think, Laura, you're exactly right, which
is
health care
is complex.
It's
tech and technology is only an
enabler.
It's very important for us to work
super closely and in deep partnership
with the clinical leaders at the clinic to
ensure that this is helping with health care
development.
The second aspect that I think is really
important is,
you know, AI is in its early stages,
so it's important for us as we navigate
these waters to do it as safely and
as responsibly as possible.
And so we always have a human in
the loop so that, you know, the technology
is helping assist.
But, you know, the technology is never perfect.
And so,
we just need to be very thoughtful about
what are the areas that we bring AI
to bear and how do we apply,
apply it in a way that has a
human in the loop so that we can
be safe and responsible.
So that's something that's core to us when
we
look ahead,
in terms of bringing AI and applying it
to other areas that I just touched upon.
That makes a lot of sense, and it's
helpful to understand how you're thinking about those
things as I know it's a such a
fast evolving field.
What do you think the hardest thing you'll
have to do in the coming year will
be?
I think the
main
opportunity
ahead of us
is really
how do we scale up our
ability
to
not just the two or three things that
I mentioned,
but 10 or more different initiatives across the
organization. And expands,
we need to expand our ability to mobilize
ourselves as an organization
to
pick and choose the right problems,
mobilize the technology teams, move the clinical and
operational leaders
to say, what are the problems that we
want to go after? How do we
work with
our technology partners to properly build the right
solutions?
And as I mentioned,
bringing an air in a clinical setting is
hard work.
We need to make sure that we are
not bringing in just technology, but we're doing
this in a way where we cannot just
apply it safely, but, you know, apply it
at scale and stay with it till it
is deployed enterprise wide. So, actually, the change
management is
essential
to do carefully and responsibly. That is actually
as big a lift as the technology.
And looking ahead,
I think it's really twofold.
Let's make sure that we're picking the right
areas to apply it to. And then number
two, to be able to do these efforts
at scale with
that carries the organization and carries health care
forward.
That makes a lot of sense. It's helpful
to think about it in that way. I
mean, I know, you know, building a team,
that can be nimble and,
ready to,
you
know, incorporate technology is
easier said than done in many ways. And
so when you look at the culture at
Cleveland Clinic, I know it's a special place
and certainly has been an innovation leader for
a long time.
What do you do to make sure that
your teams are,
you know, ready to
to go with the AI technology and are,
staying innovative while also staying safe?
So it's a work in progress. I think
that
all of us, as well as folks,
in other industries, are
grappling with how to bring the right technology
and tools into the organization,
how to give ourselves a safe space to
explore, to experiment, to learn.
So I think that,
it's a journey.
A few things that we have done
are we hired a chief AI officer,
eighteen months back from outside the industry,
and we are increasingly building up a team
of folks who have background in technology.
And
the approach that we're taking is
how do we
build
deep relationships and partnerships with clinical and operational
leaders at the clinic
so that we can,
bring a technology first mindset to many of
the important areas within health care. That's the
opportunity that I think is ahead of us.
AI is a very powerful tool,
but in our business,
how do we apply it in a health
care setting is the challenge and the opportunity.
So bringing in fresh talent is a thing.
Picking and choosing problems is a thing. Giving
ourselves a safe space to experiment, to try,
to learn as we go along.
These are all the
ways in which we are
increasingly activating our organization
to be,
to apply AI to health care.
That's helpful to understand and, you know, really
a great approach,
in strategy, it seems like, in order to
be ready for whatever comes next. And, you
know, speaking of that, how do you see
health care changing and shifting and evolving because
of the technology and because of AI as
it's coming more rapidly into the space? Where
are those some of those opportunities that you
see and are excited about for 2026 and
beyond?
So let me actually look at it,
from a, perhaps, a multi year perspective.
I think
that
I approach it both from
a operational as well as a clinical setting
where I think over time,
each of these areas have the potential to
be substantially
transformed using AI.
If you just look at the from an
operational lens,
we are a complex organization
that does more than 30,000
patient encounters a day.
Every patient encounter
requires the coordination
of
an exam room, an operating room, providers,
nurses, physician assistants.
So we have to coordinate the activity
of tens of thousands of
caregivers
and orchestrate
30,000
encounters.
But guess what? For every patient, it's perhaps
the most important
event of the day, and we need it
to go perfectly.
So this is an area where we're using
technology to help do the coordination of all
of these activities
so that they work like clockwork.
We want technology and algorithms to automate
to and to optimize
these encounters.
The benefit over time for the industry is
we should be able to do our activities
more efficiently
at greater scale and give us the ability
and maximize our ability to see as many
patients as we can. So this is an
example of an opportunity over time in an
operational setting.
In
a couple of examples I'll give from a
clinical setting perspective,
we know that,
health care is a very
labor intensive industry,
and our ability to deliver care is actually
limited by our capacity
by providers and nurses.
At the same time, providers and nurses are
overworked,
and there's significant burnout.
So there's an opportunity to say, how can
we bring technology
to substantially
transform and ease
the ability, the efficiency, and the experience of
our caregivers.
And ASRIVE is an example that I just
gave, but,
over time, I think all of these technologies
have significant potential to reduce the
busy work that caregivers go through. This is
good for doctors. It's gonna be good for
nurses, and it is going to be good
for patients because it will expand our ability
to deliver care.
The third area I'll touch on over time
is just improving
patient clinical care and safety.
Having technology
that can, let's just say, do risk prediction
and risk stratification of patients
helps us focus our energy on the patients
who are at highest risk for adverse
symptoms and consequences,
and that helps us focus our clinical energy
on the patients that need it most. So
this will help us actually take better care
of patients. So those are examples
where we think
we can substantially
improve
the quality and the safety of the care
that we deliver to our patients.
So if I step back over time,
if I look at
the macro landscape,
I am a deep believer that AI can
help us make health care safer,
cheaper,
and more scalable.
I love that. Roa, thank you so much
for joining us on the podcast today. This
has been a a really fun and fascinating
conversation, and I look forward to seeing you
as well in April. I know you'll be
speaking at our annual meeting, and doing a
fireside chat, which will be amazing to dig
deeper into many of these themes and and
just the things that you're doing at Cleveland
Clinic. So I appreciate your time today and
look forward to seeing you in a couple
months.
Thank you so much, Lauren.