← Becker’s Healthcare Podcast
Becker’s Healthcare Podcast
Scaling AI and Transforming Care Delivery at Cleveland Clinic with Dr. Rohit Chandra
00:17:41
Loading summary
Transcript18 lines
- [00:00]
A
This is Laura Darda with the Beckers Healthcare podcast. I'm thrilled today to be joined by Dr. Rohit Chandra, Chief Digital Officer at Cleveland Clinic. Rohit, it's a pleasure to have you on the podcast today.
- [00:11]
B
A pleasure to be here.
- [00:12]
A
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 how you're thinking about the future too. But before we dive in, can you introduce yourself and just talk us a little bit more about what you're doing at Cleveland Clinic?
- [00:35]
B
Sure. I'm Rohit Chandra. I'm the Chief Decision Officer at the clinic. I joined the clinic about four years ago, actually from outside of healthcare. 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 healthcare in particular. And so from that lens and responsibility for traditional it, health records, data analytics and increasingly AI, that's fascinating to hear
- [01:20]
A
and you know, 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 press projects or initiatives that had the most impactful results? What did you do and how did you measure those outcomes?
- [01:33]
B
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 20 or 30 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 10 to 15 minutes writing up their clinical notes from the encounter. Primary care doctor today can spend anywhere from one and a half to three hours every day after the 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. This documentation is a good thing from every aspect. It's just that it's very time consuming. So 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 nodes and the patient nodes. And what is amazing is the technology has become so good that it can generate really high quality nodes. 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 adopt it and we've had millions of encounters that have now been documented leveraging AI as opposed to manually. So I would say looking back on 2025, that has been a big success story for us.
- [04:44]
A
That's great to hear. And I know that documentation technology and AI scribes have a lot of value when 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 prior as well as headwinds that you're focused on for 2026?
- [05:09]
B
So we're looking at bringing technology in both clinical and non clinical 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 elbow 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 there's potential to significantly accelerate that work for us going forward. We've also started to use AI and machine learning in clinical risk predictions. We launched something to do sepsis prediction last year that was very helpful. Sepsis, just for our listeners, is a bloodstream infection that is very complex to detect and has very high mortality rates. And so with AI, we built a system that does early detection of sepsis and that can significantly improve our ability to intervene early and in patients that show the onset of sepsis. Where I'm going with this is all of these are areas beyond just the AI scry where we think we have significant potential to apply AI powered capabilities in other aspects of healthcare delivery.
- [07:16]
A
That's helpful to understand and really cool to think about the technology 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 the 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 letting it go, but truly making sure that over time it's still performing at the rate you want it to be performing.
- [07:55]
B
I think, Laura, you're exactly right, which is healthcare is complex 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 healthcare development. The second aspect that I think is really important is 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. We always have a human in the loop so that the technology is helping assist. But the technology is never perfect. We just need to be very thoughtful about what are the areas that we bring AI to bear and how do we apply applied 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.
- [09:08]
A
That makes a lot of sense and is helpful to understand how you're thinking about those things as I know it's such a fast evolving field. What do you think the hardest thing you'll have to do in the coming year will be?
- [09:20]
B
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, mobilize 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 thoughtfully build the right solutions? And as I mentioned, bringing them there 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 can not 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. Make sure that we are picking the right areas to apply it to. And then number two, to be able to do these efforts at scale that carries the organization and carries healthcare forward,
- [10:55]
A
that makes a lot of sense. It's helpful to think about it in that way. I mean, I know building a team that can be nimble and ready to 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 sponsor, 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.
- [11:33]
B
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 18 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 healthcare. 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 healthcare 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 healthcare.
- [13:09]
A
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 healthcare 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 Bey?
- [13:34]
B
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 healthcare can very labor intensive industry and our ability to deliver care is actually limited by our capacity by providers and nurses. At the same 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 AI Scribe 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 going to 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 healthcare safer, cheaper and more scalable.
- [17:13]
A
I love that. Rohit, thank you so much for joining us on the podcast today. This has been 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 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.
- [17:35]
B
Thank you so much, Laura.