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This is Laura Dierdahl with the Becker's Healthcare

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Podcast. I'm thrilled today to be joined by

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doctor Rohit Chandra,

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chief digital officer at Cleveland Clinic. Rohit, it's

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a pleasure to have you on the podcast

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today.

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Pleasure to be here.

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Fantastic. And, you know, I'm excited to dig

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into our conversation because I'm looking forward to

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learning a little bit more about some of

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the cool things you are doing at Cleveland

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Clinic right now. I know you've got a

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lot, with AI happening, and it's just really,

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you know, important to have that perspective and

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where you how you're thinking about the future

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too. But before we dive in, can you

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introduce yourself and just tell us a little

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bit more about what you're doing at Cleveland

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Clinic?

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Sure.

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I'm Rohit Chandra. I'm the chief associate officer

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at the clinic. I joined the clinic about

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four years ago actually from outside of health

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care, so I'm a engineer by training.

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And in my role here at the clinic,

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I have responsibility

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for

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our technology footprint at the clinic.

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And the way to think a little bit

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about it is that technology is an critical

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capability

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for any industry, but for health care in

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particular.

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And so from that lens, I have responsibility

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for traditional IT,

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artificial health records,

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data,

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analytics,

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and increasingly,

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AI.

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That's fascinating to hear. And, you know, a

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a huge job in front of you. And

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so I think if we narrow it down

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to just the last year or so, can

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you tell me a little bit about the

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projects or initiatives that had the most impactful

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results? What did you do, and how did

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you measure those outcomes?

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So,

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for 2025,

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I think,

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for us and perhaps for many organizations

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like us,

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the single most impactful

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AI initiative has been the AI Scribe.

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And AI Scribe for the audience today, just

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to simplify it, is

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all of us will often, as patients, go

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to a physician for an outpatient appointment. And

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let's say it's a twenty or thirty minute

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appointment

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that we have, let's say, with our primary

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care physician or some other physician.

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What we don't realize is that after that

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encounter,

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physicians typically need to spend anywhere from ten

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to fifteen minutes writing up their clinical notes

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from the encounter.

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So primary care doctor today can spend anywhere

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from

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one and a half to three hours

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every day

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after their clinic time

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writing up their notes from each patient visit.

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Now this is essential work. It's really important

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for continuity of care, for safety, quality, and

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everything else. So this documentation is a good

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thing from every aspect. It's just that it's

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very time consuming.

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So what we,

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what technology has increasingly emerged over the last

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year or

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two is something that I refer to as

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an AI scribe.

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So this is essentially

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you can just on your iPhone, you can

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have something that will listen to the provider

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patient

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conversation.

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It will

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record it,

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transcribe it, and then automatically

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generate a draft of the physician notes and

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the patient notes.

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And what is amazing is the technology has

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become so good that it can generate really

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high quality notes.

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We still have a physician in the loop

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to ensure that they're complete and accurate,

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but,

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it can

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substantially

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reduce the documentation burden on physicians.

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And equally, if not more importantly,

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it can

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significantly

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enhance the

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patient provider

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interaction

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during the encounter.

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So today, very often, if you were to

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go to your see your doctor, the doctor

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is often sitting at the computer sometimes looking

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at you, but most of the time looking

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at the screen typing up their notes. Well,

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guess what? With this technology, they don't have

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to do that. They can have their full

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attention on the patient,

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and, the documentation

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happens almost magically.

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So I would say looking back to 2025,

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this has been

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a game changing experience in reducing the documentation

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burden,

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enhancing the provider experience, enhancing the quality of

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the provider patient interaction.

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We've been very successful at it. We've had

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more than 4,000 physicians adopted, and we've had

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millions of encounters that have now been

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documented

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leveraging AI as opposed

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to manually.

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So I would say looking back in 2025,

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that has been a big success story for

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us.

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That's great to hear. And I know that,

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you know,

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documentation technology and

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AI scribes,

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have a lot of value when it you

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it comes to supporting the clinicians and making

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sure that they're able to have more of

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that human to human interaction.

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As you look into the next year, where

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do you see some of the big,

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priorities as well as headwinds that you're focused

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on for 2026?

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So we're looking at bringing technology

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in both

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clinical and nonclinical

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domains or operational areas.

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I think just building on the Scribe conversation

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we just had,

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we think that the potential for AI

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to build significant that the Scribe is just

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the beginning.

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We think that there are so many more

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powerful capabilities

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that can help a physician

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in delivery of care. It can be

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summarization

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summarization of a patient chart before an encounter.

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It can be engaging with the patient chart

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in a much more conversational and intelligent way.

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All of these are capabilities that will significantly

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provide assistance to the provider at the level

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during a patient encounter. So those are areas

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where we are trying to enhance and build

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upon

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the AI scribe, which we think is just

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a starting point.

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Other areas are, I'll say, more in the

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back office space. We've done good work over

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the last year in bringing AI into coding

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automation.

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That has been pretty helpful for us and

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has potential to significantly

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accelerate that work for us going forward.

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We've also

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started to use AI and machine learning in

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clinical risk prediction. So we launched something to

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do sepsis prediction last year

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that was very helpful.

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Sepsis, just for our listeners,

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is a

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a bloodstream infection that is very complex to

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detect

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but and has very high mortality rates.

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And so with AI, we can we built

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a system that does early detection of sepsis

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and that can significantly

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improve our ability to intervene early

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in patients that show the onset of sepsis.

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When I'm going with this is all of

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these are areas

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beyond just the AI scribe

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where we think we have significant potential to

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apply AI powered capabilities

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in other aspects of health care developing.

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That's helpful to understand and really cool to

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think about the technology and and implications on

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how it can augment it and boost the

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quality of care you're able to deliver and

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especially with early detection on something like sepsis,

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I know is, life saving.

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I'm curious. When you look at bringing in,

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more of the technology into the clinical setting,

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how do you think about,

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governance and monitoring and just making sure that

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AI stays on track and is giving you

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the results that you need? I know it's

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not always just, kind of implementing the technology

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and and letting it go, but truly making

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sure that over time, it's still performing at

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the rate you want it to be performing.

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Oh, I think, Laura, you're exactly right, which

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is

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health care

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is complex.

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It's

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tech and technology is only an

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enabler.

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It's very important for us to work

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super closely and in deep partnership

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with the clinical leaders at the clinic to

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ensure that this is helping with health care

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development.

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The second aspect that I think is really

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important is,

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you know, AI is in its early stages,

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so it's important for us as we navigate

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these waters to do it as safely and

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as responsibly as possible.

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And so we always have a human in

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the loop so that, you know, the technology

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is helping assist.

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But, you know, the technology is never perfect.

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And so,

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we just need to be very thoughtful about

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what are the areas that we bring AI

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to bear and how do we apply,

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apply it in a way that has a

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human in the loop so that we can

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be safe and responsible.

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So that's something that's core to us when

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we

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look ahead,

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in terms of bringing AI and applying it

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to other areas that I just touched upon.

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That makes a lot of sense, and it's

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helpful to understand how you're thinking about those

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things as I know it's a such a

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fast evolving field.

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What do you think the hardest thing you'll

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have to do in the coming year will

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be?

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I think the

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main

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opportunity

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ahead of us

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is really

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how do we scale up our

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ability

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to

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not just the two or three things that

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I mentioned,

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but 10 or more different initiatives across the

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organization. And expands,

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we need to expand our ability to mobilize

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ourselves as an organization

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to

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pick and choose the right problems,

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mobilize the technology teams, move the clinical and

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operational leaders

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to say, what are the problems that we

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want to go after? How do we

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work with

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our technology partners to properly build the right

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solutions?

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And as I mentioned,

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bringing an air in a clinical setting is

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hard work.

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We need to make sure that we are

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not bringing in just technology, but we're doing

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this in a way where we cannot just

286
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apply it safely, but, you know, apply it

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at scale and stay with it till it

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is deployed enterprise wide. So, actually, the change

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management is

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essential

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to do carefully and responsibly. That is actually

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as big a lift as the technology.

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And looking ahead,

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I think it's really twofold.

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Let's make sure that we're picking the right

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areas to apply it to. And then number

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two, to be able to do these efforts

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at scale with

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that carries the organization and carries health care

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forward.

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That makes a lot of sense. It's helpful

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00:10:57,024 --> 00:10:58,544
to think about it in that way. I

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mean, I know, you know, building a team,

304
00:11:01,585 --> 00:11:03,205
that can be nimble and,

305
00:11:03,585 --> 00:11:04,404
ready to,

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00:11:05,264 --> 00:11:05,764
you

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00:11:06,304 --> 00:11:08,485
know, incorporate technology is

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easier said than done in many ways. And

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so when you look at the culture at

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Cleveland Clinic, I know it's a special place

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and certainly has been an innovation leader for

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a long time.

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What do you do to make sure that

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your teams are,

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you know, ready to

316
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to go with the AI technology and are,

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staying innovative while also staying safe?

318
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So it's a work in progress. I think

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that

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all of us, as well as folks,

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00:11:40,160 --> 00:11:41,779
in other industries, are

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00:11:42,320 --> 00:11:44,899
grappling with how to bring the right technology

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and tools into the organization,

324
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how to give ourselves a safe space to

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explore, to experiment, to learn.

326
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So I think that,

327
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it's a journey.

328
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A few things that we have done

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are we hired a chief AI officer,

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eighteen months back from outside the industry,

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and we are increasingly building up a team

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00:12:10,929 --> 00:12:13,190
of folks who have background in technology.

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And

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the approach that we're taking is

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how do we

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build

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deep relationships and partnerships with clinical and operational

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leaders at the clinic

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so that we can,

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bring a technology first mindset to many of

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the important areas within health care. That's the

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opportunity that I think is ahead of us.

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AI is a very powerful tool,

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but in our business,

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00:12:41,759 --> 00:12:44,000
how do we apply it in a health

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00:12:44,000 --> 00:12:46,660
care setting is the challenge and the opportunity.

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So bringing in fresh talent is a thing.

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Picking and choosing problems is a thing. Giving

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ourselves a safe space to experiment, to try,

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to learn as we go along.

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These are all the

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ways in which we are

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increasingly activating our organization

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to be,

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to apply AI to health care.

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That's helpful to understand and, you know, really

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00:13:11,960 --> 00:13:12,779
a great approach,

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00:13:13,480 --> 00:13:15,815
in strategy, it seems like, in order to

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be ready for whatever comes next. And, you

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00:13:18,134 --> 00:13:20,295
know, speaking of that, how do you see

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00:13:20,295 --> 00:13:22,535
health care changing and shifting and evolving because

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of the technology and because of AI as

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00:13:24,934 --> 00:13:27,335
it's coming more rapidly into the space? Where

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are those some of those opportunities that you

365
00:13:29,440 --> 00:13:32,080
see and are excited about for 2026 and

366
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beyond?

367
00:13:33,920 --> 00:13:36,100
So let me actually look at it,

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from a, perhaps, a multi year perspective.

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I think

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that

371
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I approach it both from

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a operational as well as a clinical setting

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where I think over time,

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each of these areas have the potential to

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be substantially

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00:13:58,110 --> 00:13:59,570
transformed using AI.

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00:14:00,509 --> 00:14:03,070
If you just look at the from an

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00:14:03,070 --> 00:14:04,210
operational lens,

379
00:14:04,990 --> 00:14:06,450
we are a complex organization

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00:14:06,910 --> 00:14:09,584
that does more than 30,000

381
00:14:09,584 --> 00:14:11,445
patient encounters a day.

382
00:14:12,304 --> 00:14:13,684
Every patient encounter

383
00:14:14,144 --> 00:14:15,605
requires the coordination

384
00:14:16,225 --> 00:14:16,725
of

385
00:14:17,184 --> 00:14:20,084
an exam room, an operating room, providers,

386
00:14:20,464 --> 00:14:22,245
nurses, physician assistants.

387
00:14:22,769 --> 00:14:24,950
So we have to coordinate the activity

388
00:14:25,570 --> 00:14:27,350
of tens of thousands of

389
00:14:27,809 --> 00:14:28,309
caregivers

390
00:14:29,090 --> 00:14:29,990
and orchestrate

391
00:14:30,450 --> 00:14:31,269
30,000

392
00:14:31,490 --> 00:14:31,990
encounters.

393
00:14:32,850 --> 00:14:35,970
But guess what? For every patient, it's perhaps

394
00:14:35,970 --> 00:14:37,110
the most important

395
00:14:37,764 --> 00:14:39,684
event of the day, and we need it

396
00:14:39,684 --> 00:14:40,504
to go perfectly.

397
00:14:41,445 --> 00:14:43,445
So this is an area where we're using

398
00:14:43,445 --> 00:14:46,164
technology to help do the coordination of all

399
00:14:46,164 --> 00:14:47,225
of these activities

400
00:14:47,605 --> 00:14:49,464
so that they work like clockwork.

401
00:14:50,019 --> 00:14:52,919
We want technology and algorithms to automate

402
00:14:53,539 --> 00:14:54,679
to and to optimize

403
00:14:55,220 --> 00:14:56,039
these encounters.

404
00:14:56,740 --> 00:14:59,539
The benefit over time for the industry is

405
00:14:59,539 --> 00:15:01,399
we should be able to do our activities

406
00:15:01,860 --> 00:15:02,519
more efficiently

407
00:15:03,274 --> 00:15:05,535
at greater scale and give us the ability

408
00:15:05,754 --> 00:15:08,475
and maximize our ability to see as many

409
00:15:08,475 --> 00:15:10,715
patients as we can. So this is an

410
00:15:10,715 --> 00:15:13,355
example of an opportunity over time in an

411
00:15:13,355 --> 00:15:14,575
operational setting.

412
00:15:16,100 --> 00:15:16,600
In

413
00:15:17,220 --> 00:15:19,220
a couple of examples I'll give from a

414
00:15:19,220 --> 00:15:20,600
clinical setting perspective,

415
00:15:21,460 --> 00:15:22,340
we know that,

416
00:15:22,899 --> 00:15:24,120
health care is a very

417
00:15:24,580 --> 00:15:25,960
labor intensive industry,

418
00:15:26,500 --> 00:15:29,300
and our ability to deliver care is actually

419
00:15:29,300 --> 00:15:31,000
limited by our capacity

420
00:15:31,495 --> 00:15:32,875
by providers and nurses.

421
00:15:33,735 --> 00:15:36,455
At the same time, providers and nurses are

422
00:15:36,455 --> 00:15:36,955
overworked,

423
00:15:37,815 --> 00:15:39,754
and there's significant burnout.

424
00:15:40,215 --> 00:15:42,215
So there's an opportunity to say, how can

425
00:15:42,215 --> 00:15:43,195
we bring technology

426
00:15:43,654 --> 00:15:44,235
to substantially

427
00:15:45,095 --> 00:15:46,715
transform and ease

428
00:15:47,230 --> 00:15:50,110
the ability, the efficiency, and the experience of

429
00:15:50,110 --> 00:15:50,929
our caregivers.

430
00:15:51,389 --> 00:15:53,710
And ASRIVE is an example that I just

431
00:15:53,710 --> 00:15:54,690
gave, but,

432
00:15:55,149 --> 00:15:57,889
over time, I think all of these technologies

433
00:15:58,029 --> 00:16:00,929
have significant potential to reduce the

434
00:16:02,264 --> 00:16:05,144
busy work that caregivers go through. This is

435
00:16:05,144 --> 00:16:07,704
good for doctors. It's gonna be good for

436
00:16:07,704 --> 00:16:09,625
nurses, and it is going to be good

437
00:16:09,625 --> 00:16:12,184
for patients because it will expand our ability

438
00:16:12,184 --> 00:16:13,324
to deliver care.

439
00:16:14,210 --> 00:16:16,549
The third area I'll touch on over time

440
00:16:16,610 --> 00:16:17,990
is just improving

441
00:16:18,610 --> 00:16:20,710
patient clinical care and safety.

442
00:16:21,649 --> 00:16:22,629
Having technology

443
00:16:24,049 --> 00:16:27,269
that can, let's just say, do risk prediction

444
00:16:27,330 --> 00:16:29,350
and risk stratification of patients

445
00:16:30,084 --> 00:16:32,904
helps us focus our energy on the patients

446
00:16:32,964 --> 00:16:36,184
who are at highest risk for adverse

447
00:16:36,804 --> 00:16:37,945
symptoms and consequences,

448
00:16:38,325 --> 00:16:41,304
and that helps us focus our clinical energy

449
00:16:41,684 --> 00:16:44,009
on the patients that need it most. So

450
00:16:44,009 --> 00:16:46,649
this will help us actually take better care

451
00:16:46,649 --> 00:16:48,269
of patients. So those are examples

452
00:16:48,889 --> 00:16:49,790
where we think

453
00:16:50,649 --> 00:16:51,629
we can substantially

454
00:16:52,170 --> 00:16:52,670
improve

455
00:16:53,050 --> 00:16:55,290
the quality and the safety of the care

456
00:16:55,290 --> 00:16:56,830
that we deliver to our patients.

457
00:16:57,365 --> 00:16:59,304
So if I step back over time,

458
00:16:59,764 --> 00:17:00,664
if I look at

459
00:17:01,044 --> 00:17:02,424
the macro landscape,

460
00:17:03,444 --> 00:17:06,404
I am a deep believer that AI can

461
00:17:06,404 --> 00:17:07,944
help us make health care safer,

462
00:17:09,845 --> 00:17:10,345
cheaper,

463
00:17:10,644 --> 00:17:11,704
and more scalable.

464
00:17:13,059 --> 00:17:14,820
I love that. Roa, thank you so much

465
00:17:14,820 --> 00:17:16,500
for joining us on the podcast today. This

466
00:17:16,500 --> 00:17:18,440
has been a a really fun and fascinating

467
00:17:18,660 --> 00:17:20,900
conversation, and I look forward to seeing you

468
00:17:20,900 --> 00:17:22,420
as well in April. I know you'll be

469
00:17:22,420 --> 00:17:24,580
speaking at our annual meeting, and doing a

470
00:17:24,580 --> 00:17:27,295
fireside chat, which will be amazing to dig

471
00:17:27,295 --> 00:17:29,215
deeper into many of these themes and and

472
00:17:29,215 --> 00:17:30,735
just the things that you're doing at Cleveland

473
00:17:30,735 --> 00:17:32,735
Clinic. So I appreciate your time today and

474
00:17:32,735 --> 00:17:34,095
look forward to seeing you in a couple

475
00:17:34,095 --> 00:17:34,595
months.

476
00:17:35,215 --> 00:17:36,515
Thank you so much, Lauren.