Month: November 2025

Virtual-First Care Starts with Making Technology Effortless

Season 6: Episode #188

Podcast with Chris Gallagher, M.D., Founder and Chief Strategy Officer, Access TeleCare

Virtual-First Care Starts with Making Technology Effortless

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In this episode, Dr. Chris Gallagher, Founder and Chief Strategy Officer at Access TeleCare, shares valuable insights on the evolution of AI, how virtual care is reshaping access, staffing, and costs across health systems, and why making technology effortless is the key to driving a successful virtual-first care strategy.

Chris recounts the pioneering achievement of building the first virtual ICU in Texas in 2013, which quickly proved life-saving and marked a turning point in virtual health adoption. He discusses how they are addressing physician distribution issues by augmenting in-person staff, shifting its focus from predominantly rural to 70% urban facilities by offering essential 24/7 virtual specialists to care teams. Chris stresses that solutions must be effortless for clinicians, “Fisher Price easy,” so adoption becomes self-perpetuating.

Chris highlights AI’s immense potential to improve efficiency, enhance physician experience, and expedite patient care, especially through automation and a future “virtual-first” healthcare strategy. Take a listen.

Video Podcast and Extracts

About Our Guest

Chris Gallagher, M.D. is the Founder and Chief Strategy Officer of Access TeleCare. As a cardiologist in rural Texas hospitals, Dr. Gallagher noticed that timely care was one of the most important variables in a favorable patient outcome. However, this was not happening consistently across hospitals.

So, he started looking for a virtual solution that could ensure the delivery of high-quality, timely care. When he didn’t find it, he built it.

As founder of Access TeleCare, the nation’s largest high-acuity telemedicine provider, Dr. Gallagher brought his experience in internal medicine and cardiology to pave the way for tech-enabled clinical networks. Today, Access TeleCare is the standard bearer of excellence in telemedicine, a 2024 Top Remote Workplace, operating virtual care programs in all 50 states across 8 medical specialties, with a virtual catchment area of over 216 million Americans (across 15,000+ zip codes) representing roughly 65% of the U.S. population.

In his role as chief strategy officer, Dr. Gallagher drives innovation, identifies strategic partnerships, and plans for the company’s strategic growth.

Dr. Gallagher trained at UT Southwestern for his Internal Medicine Residency and Cardiology Fellowship and earned his Doctor of Medicine from Texas Tech University School of Medicine. He is a fellow in the American College of Cardiology and a member of the American Association of Cardiovascular and Pulmonary Rehabilitation, the American Medical Association, and the Texas Medical Association.


Charles: I am Chuck Christian. I’m the Vice President of Technology and CTO for Franciscan Health. Franciscan is a 12 or 13 hospital system, depending on how you count them. We cover a swath of the Midwest from just south of Indianapolis all the way to Chicago, basically following the I-65 corridor.

We have between 350 and 400 locations, including physician practices, imaging centers, lab draws, urgent cares, and oncology centers. It’s a pretty large organization. We have about 29,000 team members, both employees and contractors, at Franciscan Health.

We are truly mission focused. We are a Catholic healthcare system with a big C. We are owned by the Sisters of St. Francis of Perpetual Adoration. That means there are two sisters in the chapel praying for whatever they deem important and anything we ask them to pray for, 24 hours a day, seven days a week, 365 days a year. That’s where the “perpetual adoration” comes in.

We are a mission-driven organization. I believe in that. A lot of our hospitals are smaller and in underserved places, and we take care of that patient population. I think we’re really good at it.

I’ve known this organization almost 40 years. The CIO previous to Charles, who is our current COO, was a good friend of mine. I was CIO of a hospital in Southern Indiana for 24 years, and Bill and I ran a similar software stack. I watched Bill and learned a lot from him as far as how he ran this large organization.

I’ve been here for six years. I joined in April of 2019, so in dog years that’s like 35 years or more. We are very busy. I’m very blessed to have an outstanding team that manages all this, and I get to stand in awe and watch everything we accomplish every day.

Rohit: That’s fabulous. Thank you, Chuck for that intro.

Ritu: My name is Ritu Roy, and I’m the Managing Partner here at Damo and BigRio, and also the co-host of The Big Unlock podcast with Rohit. Thank you for being our guest today, Chuck. We are looking forward to an engaging and insightful conversation. With that, we can dive right in and get started.

Charles: Thank you.

Rohit: Hi Chuck. I’m Rohit Mahajan. I’m the Managing Partner and CEO at BigRio and Damo Consulting. It’s great to have you on the podcast. Like Ritu said, we’re looking forward to an engaging discussion. I’d like to start with the first thought on my mind. You’re in a mission-driven organization, and you’ve been a healthcare leader for many years. What started you on this journey? Tell us how you got started in healthcare, what attracted you, and what you’re passionate about.

Charles: Well, it depends on how far back you want to go. I’m an X-ray tech, radiologic technologist if you want to use the term. The first 14 years of my career were in radiology.

I stepped out of high school on June sixth in 1971, and on June seventh I stepped into the hospital, and I haven’t left since. Interesting enough, I did a lot of things in the radiology department and became part of the management team of that department. I guess if the chief tech had not been just a few years older than me, I’d still be there, because that was the role I wanted. But Roy just retired a few years ago, and I wasn’t going to wait that long.

I’m a geek, I’m a nerd. I was a nerd in high school. It wasn’t cool to be a nerd in high school back then, but it’s cool to be a nerd now. I did a lot of programming classes on the old System Threes with punch cards. Then I learned how to code for Z80 processors.

When we started automating hospitals back in the mid-eighties, I got chosen to run the ambulatory implementation of order management after we had put in patient management. I realized I liked it, and I knew that was where healthcare was going. Radiology has been a high-tech department in hospitals for a long time. I was trying to automate the patient record in radiology, but it was so expensive I couldn’t get any funding for it.

So I jumped ship and moved over to the vendors for about five years. Eventually I was asked to move to either an implementation manager role or the director of an outsourced IT department in southern Indiana. I did that. I had four daughters at the time, and it was the right thing to do because it was a great place to raise my girls.

I spent 24 years there. It was during the time the role of a healthcare CIO was defined. When I left that job, I was Vice President and CIO. I moved to Georgia to a health system there as Vice President and Chief Information Officer. Then I came back to Indiana and worked at the Indiana Health Information Exchange, which is now the only exchange in Indiana. I had been involved with it since 2005. I worked there for a little over four years, and then I took this role here. That’s my stint in healthcare, which has spanned over 50 years.

Rohit: That’s awesome, Chuck. You’ve been there, done it, and seen it as well. I was curious because a few days ago, when we were chatting, you were talking about being either back from UGM or about to go there.

We all know it’s a week-long affair, people go deep, and there are so many things to cover. We were wondering if you could share some of your experiences or a heads-up on topics you see coming our way.

Charles: Sure. I came home with a great deal of anxiety because of trying to figure out how we’re going to do everything and where healthcare is going. The nice thing about Epic is they now cover the entire gambit. I remember when Epic started; they were only in the ambulatory space and then only in large academic medical centers. They cover quite a scope of product these days.

Now that they have grown the applications, they have de-identified shared data, which I think is going to be a plus. The two-letter acronym was everywhere, AI, and how it’s going to be leveraged and used. They did a nice job showing scenarios of how it could be used and how organizations are using it.

We’re a risk-averse organization. We’re taking a more moderated approach. We’re getting our governance in place first. We already have a few things going through the AI mill, and we will have more. We split it into two pieces, one on the clinical side and one on the operational side. Epic has both, and I think they’re well positioned to do that work. They partner with Microsoft, and they continue to do so.

They announced they are working on their own ambient listening. They have business partners already, but they are creating their own product. I assume it will be predicated on the Microsoft stack, but they didn’t say, so I don’t know.

They also mentioned they are working on their own ERP and starting with workforce management. That makes sense because the workforce is in Epic all the time. Nursing staffing, scheduling, shifts, and how all that ties together. It’s an interesting leap.

Years ago, when Lawson, before being purchased by Infor, said they would create a patient accounting platform, I was in a CHIME focus group. When they mentioned that, a bunch of CIOs in the room asked why they would do that. You need to get your ERP right first. But I think the way Epic is approaching it makes sense.

It was great. I was there for about four days and spent most of the time listening to presentations. Judy did a great job with a big screen about what’s next and what’s coming. The rest of her team did a great job showing what you can do now and what’s coming. They do a good job setting expectations around timelines. They release quarterly. We do two a year, so we’re current from their perspective but behind. We don’t have the wherewithal to immediately adopt everything when they release it, so we have to plan accordingly.

Ritu: Yeah. So Chuck, when I was reading about the UGM, it was interesting because they said their unique proposition with AI is the de-identified patient records they have in Epic Cosmos, which is more than 15 billion patient records. They said that for the first time, it can actually move toward healthcare rather than sick care because doctors can predict trends. And I think they released two new things called Emmy and Penny, which will help doctors see the trajectory of what is going to happen with patients.

So I was curious about your thoughts because you’ve been in this industry for such a long time. Do you think that this USP—this huge bank of patient records—is really going to set them on a differentiating path compared to all the other AI startups trying to do the same thing?

Charles: I think that having the data is huge, honestly. It reminded me a lot of—if you remember years ago—they had a thing called PatientsLikeMe, where people with unique and rare diseases could find others and compare notes and treatment approaches. Working at the Indiana Health Information Exchange, I know they have about 30 years of data. Not all of it is discrete, but the majority is.

One question I asked the CEO, who is a friend of mine—and a lot of researchers use that de-identified data—is that when you create an AI model and just let it learn, there are all kinds of interesting determinations you can make once you have the data. So I think it’s going to be a game changer. Epic is also trying to outdo themselves. Given the market of EHR vendors, there aren’t many left standing. There are three or four. Others are creating similar repositories, but I’m not sure they have the long-term vision or the wherewithal to get it done. Knowing the talent Judy has pulled together, I think it will be very interesting to see what comes down the pike.

Ritu: Thank you.

Rohit: Chuck, you mentioned you’re taking a conservative approach to AI adoption and setting governance before taking major steps. How do you think about innovation or typical problem-solving—for example, reducing cognitive load across the organization? How do you balance this conservative approach with the fast-paced changes happening in the marketplace?

Charles: I think we have to be very clear about what problem we’re trying to solve. There are so many solutions being thrown at us—“Hey, we can do this, we can do that”—but often it’s not a problem we actually have. So we’re trying to pick and choose which targets to shoot at.

I’m married to a critical care nurse, so I’m very careful about getting in the way of the nursing staff. She’s retired, but for me, technology needs to be invisible. If it gets in the way of people being able to do their job, then it’s a problem.

If you think about it for a minute—and I’ll give you Chuck’s opinion—we don’t really have electronic medical record systems for documenting the care of the patient. What we have are electronic systems that capture information required for billing. That’s part of the problem. We have all these required elements clinicians have to document—physicians have to dot all the i’s and cross all the t’s—to get the appropriate words in so it can be translated into billing codes, ICD-10 codes, HPS codes, and so on. It truly gets in the way of taking care of patients.

But once we get that discrete data, we can use AI and other tools to help determine a better course of treatment. You’re never going to hear me say that we should depend solely upon AI. It has to be moderated and reviewed by someone with clinical training. Physicians have shown me I’ve been wrong more times than you can imagine. Working together and having good data aggregation is important.

One thing I learned early on when implementing the first physician order entry and clinical documentation systems was that physicians said: “Don’t tell me what I already know. Tell me what I don’t know. Better yet, tell me what I need to know about the patient in front of me right now.” There are things they don’t know. That’s where data aggregation from health information exchanges helps, because patients don’t get care in one location or from one physician.

I’m living proof of that. I get care in two—actually three—health systems because that’s where my specialists are. My primary care doctor wants to know what my orthopedist did or what my cardiologist’s course of treatment is, because he’s managing my diabetes and a few other things. Having access to information—recent labs, imaging studies—is extremely important.

We talked about interoperability, and that’s where it comes into play. Most hospitals in Indianapolis are on Epic, so you can get data easily. From non-Epic systems, there are mechanisms too. When I see my cardiologist—who uses a different system—and he already knows what my medications are because they were recently changed by another physician, that’s positive. I don’t have to list everything. When they know my latest labs, that’s positive too, because we’re not hunting for information.

It’s about providing information that is important to the treatment at that moment.

I had the privilege of sitting in a presentation—maybe eight or nine years ago—at Scripps Institute. They showed a demo of what a patient encounter could be. It was very Star Trek–like. The computer or AI interacted with the physician and patient appropriately. It listened in the background and captured information about the encounter. When the physician said, “We need to order a CT scan of your lower abdomen,” it was already getting that scheduled. When the patient was ready to leave, everything was set. It was also checking for recent labs and reminding the physician if the patient—say a diabetic—was due for an eye exam or foot check.

I think it’s about having access to the information so we can inform—not determine but inform—the physicians. Because at the end of the day, physicians are accountable for the outcomes. They have to be in control, not the AI.

Ritu: Yeah,

Charles: we’re not ready for Skynet yet.

Ritu: I think you described a multi-agent system where the agents are off doing things and then bringing it all back for the physician to review. With that being said, we all know that AgTech is one of the top trends everyone’s talking about these days. What are your thoughts on voice agents? Where is Franciscan with that? Have you had exposure to or tried voice agents in the hospital?

Charles: Yeah, we’ve got a trial. We’ve got over 200 physicians working on those. Is it going to be the end-all, be-all? I don’t know. The physicians seem to like it. It assists them; it helps with their pajama time.

I’ve listened to conversations from other health systems that were early adopters, and I have to go back in time to when we were looking at automating physician practices in Southern Indiana. We visited a group of 14 family practice doctors. The husband and wife who started the practice mostly did OB and family medicine. Their use of computers was minimal—they were still mostly on paper. But they had other physicians who, I think, slept with their laptops.

The interesting thing was that depending on how well a physician adopted the computer system and molded it to how they practiced, they got to take advantage of it. I think it’s going to be the same with AI and voice agents. If they allow it to help and figure out how to incorporate it into how they think and practice, they’ll see the benefit. The systems are pliable enough now that it’s easier to do.

When I was in Georgia, we needed to automate a lot of OB practices on the same platform. One OB had been practicing almost 30 years and already had a solution he had customized. He told me I would tear it out of his cold, dead fingers. So we worked with him. The new system was more flexible and pliable than his old one, and he became a champion because he was willing to take the time to understand how he could use the technology to help him practice.

I think that’s the key. If you’re resistant to it, that’s fine—that’s perfectly okay. But people who write software often think all physicians think the same way. They’re absolutely wrong. It depends on where they trained. I learned that when implementing emergency room electronic medical records. The physicians who helped design the software were trained with a very different approach to critical thinking than our physicians. We had to relearn and figure out ways to adjust, because once clinicians are trained a certain way, it’s hard to change those habits and the way they gather and maintain information.

Ritu: Thank you. Great answer.

Rohit: Chuck, I’d like to ask your thoughts about the innovation process. How do you approach it, and what are some of the things you do to foster innovation?

Charles: One of the things we did was stand up a Tech Innovation Lab. Honestly, it was a selfish move because people were just bringing technology into the organization. All the enterprise architects report to me, and we work together to understand what will work in our environment and what won’t. We try to standardize as much as we can.

So I created the Innovation Lab to bring these innovations into a controlled environment and try them there. It’s a walled garden. It’s not connected to the rest of the network. It has its own connections to the internet. So if we blow something up, it only blows up in the lab. That’s why we did it.

What we’re able to do is bring ideas in and fail fast—figure out what works and what doesn’t. We’ve done that several times. Virtual nursing is something we’ve worked on a lot. There were all kinds of interesting opportunities brought to us. One facility went ahead and put a solution into a live patient population, and we found out quickly that’s not how you do it. You don’t test that kind of thing in a live environment. It frustrates the staff and patients, and it leaves leadership thinking, “We already tried that—it doesn’t work.”

Well, you tried what doesn’t work. Let me show you what will work.

We needed the opportunity to rapidly figure out what would work. One issue with that failed experiment was that the people who built the carts didn’t understand our environment. They put a wireless access point in the cart that was incompatible with our network. Once we got the cart, we figured it out quickly. We re-engineered it, and it works fine now—but we’re not using that cart because it was over-engineered and very expensive.

We’re trying to use standard components that can be supported and replaced quickly. The idea is to generate a lot of ideas and figure out how to use them appropriately without getting in the way.

You also have to think about the aesthetics of the equipment you’re bringing in. The first cart had a big five-wheel base—kind of a star shape. In some patient rooms, it was in the way. Nursing quickly said, “That’s not going to work.”

So we found an iPad holder that hangs on the patient’s bedroom wall when not in use. It’s out of the way, easy to access, and uses magnetic connectors so if someone snags it, it just comes apart. No trip hazard.

You must consider not only the technology but how it fits in patient rooms.

Originally, the idea was that the Innovation Lab would review the technology, understand how it fits together, and then install it in our SIM labs. We have two—one north, one south. Then the simulation teams would put it in a physician office or patient room and see how it fits before we use it in live care. That’s our next step with virtual nursing.

We also have a lot of conversations with organizations that have fully rolled out these solutions. We learn from their experiences. A mistake is only a mistake if you don’t learn from it. If you do, then it’s experience. We leverage their experience so we don’t repeat the same things, and so we can move quicker.

Rohit: That’s awesome. As we are approaching the end of the podcast, I would like to ask if you would touch on the mentorship program.

Ritu: Yes, I would really like to hear more about that, Chuck, because it’s something unique and I think it would be interesting for our listeners as well.

Charles: Just making sure we’re talking about the virtual mentoring program. After COVID, we were bringing on a lot of new nurse graduates. When you bring someone into that role, they need a more experienced nurse for a procedure they may have never done before. That usually means waiting for that nurse to come to them.

We had a couple of nursing staff in the mentorship program who came up with a way to use technology for an on-screen virtual visit with the new nurse. The experienced nurse could walk them through the procedure and be there with them, or if the new nurse had a question, they could step out into the hall, ask it, and go back in. It improved speed to delivery of care more than anything else.

It also gave seasoned nurses a chance to step away from what they were doing instead of traveling to another location. If they need to go in person, they still do, but this gave us another option. We got great feedback from both the new nurses and our more mature nursing staff, and we rolled it out through the enterprise. I haven’t checked in on it recently, but I assume it’s still running. I only hear when things break, and if it’s not broken, I’m not going to fix it. I assume the technology is still working and paying dividends.

Ritu: Thank you so much.

Rohit: So, Chuck, as we come to the end of the podcast, any closing remarks or thoughts you’d like to share before we finish?

Charles: I’ve been in healthcare a long time. Healthcare is a target rich environment for creativity and innovation. But we’re still taking care of patients the same way we did, and it’s about the human touch and caring for people.

When I first started in radiology years ago, I was taken aback that people weren’t always treated as people. They were exams. Do this gallbladder in this room, do this hip nailing in that room. I was reminded they’re people. They could be my family. They could be my children. That’s why I’m passionate about making sure the technology works and doesn’t get in the way.

Have we reached the pinnacle? No. Is it better? I think it is. But we’re still trying to figure it out every day. As long as we have great people passionate about providing outstanding care and we understand where that ability comes from, we’ll keep moving forward.

We’re a Catholic healthcare system, and our rule is we start most meetings with prayer. We are called to love one another as God loves us, and we need to remember that every day. That’s why I keep doing what I’m doing.

Rohit: Awesome.

Ritu: Thank you so much, Chuck.

Rohit: Really appreciate it.

Charles: Okay. Thanks for the opportunity to share.

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Subscribe to our podcast series at www.thebigunlock.com and write us at [email protected]   

Disclaimer: This Q&A has been derived from the podcast transcript and has been edited for readability and clarity.

About the Hosts

Rohit Mahajan is an entrepreneur and a leader in the information technology and software industry. His focus lies in the field of artificial intelligence and digital transformation. He has also written a book on Quantum Care, A Deep Dive into AI for Health Delivery and Research that has been published and has been trending #1 in several categories on Amazon.

Rohit is skilled in business and IT  strategy, M&A, Sales & Marketing and Global Delivery. He holds a bachelor’s degree in Electronics and Communications Engineering, is a  Wharton School Fellow and a graduate from the Harvard Business School. 

Rohit is the CEO of Damo, Managing Partner and CEO of BigRio, the President at Citadel Discovery, Advisor at CarTwin, Managing Partner at C2R Tech, and Founder at BetterLungs. He has previously also worked with IBM and Wipro. He completed his executive education programs in AI in Business and Healthcare from MIT Sloan, MIT CSAIL and Harvard School of Public Health. He has completed  the Global Healthcare Leaders Program from Harvard Medical School.

Ritu M. Uberoy has over twenty-five years of experience in the software and information technology industry in the United States and in India. She established Saviance Technologies in India and has been involved in the delivery of several successful software projects and products to clients in various industry segments.

Ritu completed AI for Health Care: Concepts and Applications from the Harvard T.H. Chan School of Public Health and Applied Generative AI for Digital Transformation from MIT Professional Education. She has successfully taught Gen AI concepts in a classroom setting in Houston and in workshop settings to C-Suite leaders in Boston and Cleveland. She attended HIMSS in March 2024 at Orlando and the Imagination in Action AI Summit at MIT in April 2024. She is also responsible for the GenAI Center of Excellence at BigRio and DigiMTM Digital Maturity Model and Assessment at Damo.

Ritu earned her Bachelor’s degree in Computer Science from Delhi Institute of Technology (now NSIT) and a Master’s degree in Computer Science from Santa Clara University in California. She has participated in the Fellow’s program at The Wharton School, University of Pennsylvania.

About the Legend

Paddy was the co-author of Healthcare Digital Transformation – How Consumerism, Technology and Pandemic are Accelerating the Future (Taylor &  Francis, Aug 2020), along with Edward W. Marx. Paddy was also the author of the best-selling book The Big Unlock – Harnessing Data and Growing Digital Health Businesses in a Value-based Care Era (Archway Publishing, 2017). He was the host of the highly subscribed The Big Unlock podcast on digital transformation in healthcare featuring C-level executives from the healthcare and technology sectors. He was widely published and had a by-lined column in CIO Magazine and other respected industry publications.

How Rush University System for Health Is Advancing Generative AI Innovation and Digital Transformation

Digital transformation in healthcare has accelerated dramatically over the past few years, driven by changing patient expectations, demographic shifts, and rapid advances in artificial intelligence. At the center of this transformation is Rush University System for Health, a Chicago-based academic health system known for its clinical excellence and forward-thinking approach to innovation. In a recent episode of The Big Unlock podcast, Anil Saldanha, Chief Innovation Officer at Rush University System for Health, offered a wide-ranging look at how the organization is advancing generative AI, expanding digital care models, and tackling systemic health inequities.

Anil’s role sits at the intersection of public health, community health, and care delivery – an ideal vantage point for understanding how technology can reshape health outcomes. His insights highlight not just where Rush University System for Health is today, but where healthcare as a whole is heading.

A Virtual-First Foundation for Digital Transformation

One of the most visible components of digital transformation at Rush University System for Health is the shift toward a virtual-first ecosystem. While the pandemic accelerated telehealth adoption nationwide, Rush took the momentum and built an intentional strategy around it.

Anil explained that Rush began by strengthening virtual primary care, followed by virtual urgent care and specialty care. The virtual urgent care service stands out for its ability to address more than 40 different conditions with a waiting time as short as 20 minutes. Patients who once needed to travel to a clinic for issues like cough, rashes, prescription refills, minor infections, or follow-up questions can now get the care they need from home.

Virtual specialty care has expanded across eight service areas, helping patients access high-quality clinical expertise without the typical logistical barriers.

This virtual backbone laid the groundwork for one of Rush’s most innovative offerings: Rush Connect Plus, a subscription-based service that reflects new consumer expectations in healthcare. Through Rush Connect Plus patients anywhere in the United States can get 24/7 access to a care team, digital triage support, referral pathways, and seamless connection to Rush specialists. As Anil explained, many younger patients “are not interested in having a dedicated primary care provider. They want care whenever they need it, wherever they are.” Rush Connect Plus reflects this shift and meets patients on their terms.

 

Addressing Chicago’s Life Expectancy Gap Through Data and Community Strategy

While digital convenience is important, Rush’s transformation is equally focused on tackling some of Chicago’s most deeply rooted public health inequities. The Chicago “death gap,” an extreme difference in life expectancy between neighborhoods, has long been a defining challenge for the city.

Anil described it clearly: “If you take four subway stops west of Michigan Avenue, life expectancy drops by 16 years. In the south of Chicago, it drops by 30 years.” Rush has made it a corporate mission to reduce this gap by 50% by the year 2030.

Several factors drive this disparity, including cardiovascular disease, cancer, firearm injuries, stroke, and uncontrolled hypertension. The social determinants of health adds another layer of complexity. To address these issues systematically, Rush secured a $7.5 million grant to build a Health Equity Analytics Studio, an advanced data environment designed to unite clinical data, census information, wearable insights, and community metrics into a single analytical foundation.

This ecosystem of data will allow Rush to identify “hot zones” of chronic disease risk across the region. The goal is to provide public health teams, community health workers, and clinical service lines with actionable insights so they can deliver targeted, high-impact interventions.

In Anil’s view, this kind of population-level digital infrastructure is essential for equity: “This will be a major digital aid for our public health and community health departments and help us understand the complex chronic care needs of our population.”

 

Transforming Cancer Care Through Early Detection and Strategic Collaboration

Cancer care has been another area of exceptional focus at Rush, supported by both clinical partnerships and bold technological initiatives.

A key strategic collaboration is Rush’s partnership with MD Anderson Cancer Center, widely recognized for world-class oncology care. Through this partnership, Rush has established several Rush MD Anderson Cancer Centers across the Chicago region, enabling patients to receive cutting-edge treatment and participate in advanced clinical trials without traveling to Houston. As Anil noted, this partnership ensures that “our patient population doesn’t have to travel to Houston to take advantage of MD Anderson’s excellence.”

Complementing this is Rush’s pioneering move into multi-cancer early detection. About a year ago, Rush began offering the Grail liquid biopsy test, which can identify more than 50 cancers and many of which have no other detectable biomarkers.

Anil described the decision to adopt Grail as a “bold bet,” grounded in scientific promise and clinical necessity. Despite the $750 out-of-pocket cost and lack of FDA approval, community demand has been overwhelming. “We’re not able to keep up with the demand,” he shared. Rush has systemized referral pathways and follow-up procedures to ensure patients receive timely support if they receive a positive signal from the test.

For Rush, early detection represents a shift in how society invests in cancer care. Instead of devoting most resources to end-of-life treatment, Anil and Rush’s CEO, Dr. Omar Latif, emphasize the need to invest earlier in the patient journey to prevent severe outcomes. This philosophy aligns with Rush’s broader mission of prevention, equity, and long-term community health.

 

Generative AI at Rush Health: Thoughtful Deployment and Research-Driven Innovation

Generative AI is becoming one of the defining forces in healthcare transformation, and Rush is embracing it with both enthusiasm and caution. Anil made it clear that Rush wants AI to enhance, not replace, clinical expertise and patient relationships.

Ambient listening technology is one area where generative AI is already making an impact. Rush uses Suki to reduce clinical documentation burden, allowing providers to focus more on patient care. Rush also deploys an AI-driven symptom checker across its website and mobile app, helping patients navigate symptoms and access appointments more efficiently.

One of the most groundbreaking, and lesser known, AI initiatives at Rush is the Socrates behavioral health kiosk, part of its RODO program supporting veterans with PTSD. The kiosk uses a multi-agent AI system built on OpenAI models. Patients interact with an AI therapist, while an AI rater and a third monitoring agent work behind the scenes to prevent hallucinations, avoid looping behavior, and maintain clinical relevance.

Anil highlighted the importance of this multi-agent design: “It allows us to make changes in real time to ensure looping doesn’t happen and hallucination concerns are mitigated.” While still in a research environment, Socrates represents a promising direction for behavioral health innovation at a time when staffing shortages persist across the country.

Beyond behavioral health, Rush is monitoring advancements in diagnostic AI, such as cardiovascular algorithms, vision-based imaging tools, and cancer detection systems. Saldanha views these developments as signs of a “hopeful” future, where traditional machine-learning models and generative AI will coexist to support clinical care.

 

Looking Ahead: A Connected, AI-Enabled Future for Care Delivery

When asked about what’s next, Anil spoke about the emergence of hospital-at-home programs and ambulatory-first models, reflecting a broader movement toward decentralizing care. He expects generative AI to play a growing role in patient education and preparation, a trend already visible in clinics.

He referenced a recent story of a patient who used ChatGPT to learn about a “Tilt Table Test” before coming in for vertigo. The clinician was surprised by the level of detail and preparation. For Anil, this is a sign of what he calls a “connected care ecosystem,” where patients become empowered partners in their own care.

“Patients are partners in their care,” he said. “The more they’re empowered and educated, the better society will be.”

 

A Model for the Future of Healthcare Transformation

Rush ’s journey reflects the intersection of technological progress, clinical innovation, and community responsibility. Through virtual-first care, generative AI adoption, early cancer detection, and data-driven equity initiatives, Rush is building a healthcare model that is not only future-ready but deeply human.

Anil concludes the podcast episode with optimism: “Healthcare affects all of us. Don’t give up on it. Be part of the solution in whatever way you can.”

The digital transformation at Rush, and its thoughtful use of generative AI, offers a powerful blueprint for any organization striving to deliver smarter, more equitable, and more connected care.

A First Look at Our New Book: Generative AI — Unlocking the Next Chapter in Healthcare

The Beginning of a New Era

When we began writing Generative AI: Unlocking the Next Chapter in Healthcare, we set out to capture a moment we could feel unfolding all around us. Hospitals were experimenting with generative models to summarize clinical notes. Pharmaceutical teams were using AI to design molecules. Patients, whether through voice agents, virtual coaches, or precision-care tools, were starting to experience medicine that learns from them in real time.

Healthcare has always evolved with technology, but something about generative AI feels different. It doesn’t just automate; it collaborates. It drafts, hypothesizes, and reasons. It changes how humans and machines think about each other and with each other.

Our goal was to document this transformation honestly, its potential and its pitfalls, and to offer leaders a practical framework for navigating what might be the most consequential technological shift in medicine since the discovery of antibiotics.

Inside the Book

In the opening chapters, we invite readers to step into the clinical frontier of this technology. Here is a brief passage from Chapter 1:

“The first wave of AI in medicine focused on detection, spotting a tumor, predicting a lab value, flagging an anomaly. The next wave, powered by generative models, focuses on creation, drafting treatment plans, designing trials, even writing the code that powers health systems themselves.”

Another early excerpt explores how this evolution is changing the physician’s daily experience:

“When an algorithm can generate a differential diagnosis or summarize a complex chart, it doesn’t diminish the clinician’s value. It redefines it. The new skill set is interpretive intelligence, the ability to question, contextualize, and apply machine-generated insight with empathy.”

Throughout the book we weaved together interviews, case studies, and lessons from our work at BigRio and Damo Consulting. Readers will find examples ranging from AI-assisted radiology and conversational triage tools to synthetic data pipelines accelerating clinical research.

But we also look beyond the technology. Each chapter ends with a reflection on governance, ethics, and human trust, because AI’s success in healthcare depends as much on values as on code.

From Algorithms to Empathy

One of our favorite sections explores the paradox at the heart of digital medicine: how machines that generate text, images, or predictions can actually restore the human connection in care.

“The gift of automation is time; the one resource healthcare professionals never seem to have enough of. When AI writes the discharge summary or reconciles the medication list, the clinician gets something priceless back: more time to give to the patient’s story.”

Generative AI, when properly implemented, becomes a quiet collaborator that amplifies compassion instead of replacing it. That vision runs through every chapter of our book.

Why This Book, Why Now?

We’re often asked what inspired us to write this book at this particular moment. The answer is urgency.

In 2025, healthcare organizations are under unprecedented pressure to modernize. They face clinician burnout, labor shortages, and an avalanche of unstructured data. At the same time, generative AI technologies are moving faster than regulation, raising new questions about bias, safety, and transparency.

We saw a need for a resource that bridges innovation and accountability. A guide written by those of us who have built AI systems inside real healthcare environments, not just in research labs.

Our message is simple:

  • The technology is powerful, but context matters.
  • Generative AI can democratize expertise, but only if governed ethically.
  • Healthcare’s next chapter must combine precision with empathy.

This is not a manifesto for automation; it’s a blueprint for collaboration. It is about ensuring that, as AI learns to write prescriptions or generate treatment options, humans remain the authors of care itself.

The Collaboration Behind the Pages

Writing together allowed us to merge two complementary perspectives. Rohit brings systems-architecture and data-science lens from decades of work in health IT and consulting. Ritu brings leadership and education focus, guiding organizations through responsible adoption and change management.

Our shared mission—reflected in the book and in The Big Unlock podcast—is to make AI accessible and actionable for healthcare executives, innovators, and clinicians alike.

We wanted the book to feel both visionary and grounded: rich in insight but practical enough that a hospital CIO, a data scientist, or a medical student could, or even a patient, could all find value in it.

Looking Ahead

As the launch approaches, we’re encouraged by the early enthusiasm from reviewers and peers who describe Generative AI: Unlocking the Next Chapter in Healthcare as “a rare combination of technical rigor and human empathy.”

In the coming months, we’ll continue the conversation through live webinars, podcast interviews, and case-study spotlights drawn from the book. Our hope is that this work sparks collaboration across disciplines and across the globe on how to responsibly unlock the full potential of Generative AI in medicine.

Order and Launch Details

Generative AI: Unlocking the Next Chapter in Healthcare
By Rohit Mahajan and Ritu M Uberoy
Published by Taylor & Francis Group
Available November 17, 2025, in soft cover, hardcover, and eBook formats.

Order or learn more at the official author webpage.

Generative AI: Unlocking the Next Chapter in Healthcare

Generative AI: Unlocking the Next Chapter in Healthcare

New Book Provides Insider Insight on the Impact of Generative AI on Healthcare!

CAMBRIDGE, Mass.Nov. 13, 2025 /PRNewswire-PRWeb/ — Artificial intelligence is no longer a future promise in healthcare, it’s the driving force behind how care is delivered, research is conducted, and data is transformed into lifesaving insight. A groundbreaking new book, Generative AI: Unlocking the Next Chapter in Healthcare, [ISBN: 9781041125693], published by Taylor & Francis Group, explores this evolution and what it means for clinicians, researchers, innovators, and policymakers worldwide.

Authored by Rohit Mahajan and Ritu M Uberoy, leading voices in healthcare technology and digital transformation, the book demystifies how generative AI and Agentic AI are reshaping patient engagement, drug discovery, diagnostics, and the very fabric of clinical decision-making.

Mahajan and Uberoy draw upon decades of experience driving AI innovation at BigRio and Damo Consulting. Through real-world case studies and expert insights, the authors examine how hospitals, payers, and life sciences organizations can responsibly implement generative AI to enhance both efficiency and patient care in healthcare delivery.

Mahajan and Uberoy draw upon decades of experience driving AI innovation at BigRio and Damo Consulting. Through real-world case studies and expert insights, the authors examine how hospitals, payers, and life sciences organizations can responsibly implement generative AI to enhance both efficiency and patient care in healthcare delivery.

The most balanced and forward-thinking treatment of generative AI in medicine to date.

“Healthcare stands at the crossroads of innovation and compassion,” said Rohit Mahajan, CEO of BigRio and Damo Consulting. “Our goal was to provide a playbook that helps organizations harness AI not just to cut costs but to elevate care quality and human connection.”

Co-author Ritu M Uberoy added, “We wanted to move the conversation beyond hype. Generative AI isn’t about replacing clinicians or healthcare decision makers, it’s about giving them superpowers through technology that learns, reasons, and collaborates.”

The book provides an accessible yet technically grounded guide to AI governance, data ethics, regulatory implications, and the emergence of agentic AI systems.


Early Reception

The release of the book comes at a pivotal time. Healthcare systems globally are accelerating digital transformation while grappling with workforce shortages and data fragmentation. Analysts forecast that AI-driven solutions could save the U.S. healthcare system more than $360 billion annually by 2030 through automation, improved diagnostics, and streamlined administrative tasks.

Early reviewers have praised the book as “the most balanced and forward-thinking treatment of generative AI in medicine to date.”

Industry thought leaders and academic reviewers note its blend of technical insight, ethical reflection, and pragmatic leadership advice.


About the Authors

Rohit Mahajan is the author of Quantum Care: A Deep Dive into AI for Health Delivery and Research, a number one Amazon bestseller exploring how AI is transforming healthcare. He is the Founder and Managing Partner at Saviance Technologies and serves as CEO of both BigRio and Damo, where he leads innovation in AI and digital health transformation.

Rohit co-hosts The Big Unlock podcast with Ritu M Uberoy, engaging senior healthcare leaders in conversations about the future of care delivery. In 2025, he received the GHLF Global Impact Award for Digital Health Innovation in recognition of his contributions to the field.

Ritu M Uberoy is a technology executive, entrepreneur, and educator with over 25 years of experience in the global software and IT industry. As Founder of Saviance Technologies and Managing Partner at BigRio and Damo Consulting, she leads digital transformation initiatives across healthcare and life sciences.

Ritu heads the Generative AI Center of Excellence at BigRio and the DigiMTM Digital Maturity Model at Damo, guiding healthcare organizations in adopting AI at scale. She is also the co-host of The Big Unlock podcast and a recognized voice in healthcare innovation.


Publication & Availability

Generative AI: Unlocking the Next Chapter in Healthcare is published by Taylor & Francis Group and will be available November 17, 2025, in print and eBook formats through Amazon, Barnes & Noble, Taylor & Francis (ebook only) and other online retailers. Discounts are available for bulk purchases through Taylor & Francis. For price quotes, please contact [email protected].

For more information or to join the launch mailing list, visit the official authors’ webpage.


About the Taylor Francis Group

Taylor & Francis Group partners with researchers, scholarly societies, universities and libraries worldwide to bring knowledge to life. As one of the world’s leading publishers of scholarly journals, books, eBooks and reference works our content spans all areas of Humanities, Social Sciences, Behavioral Sciences, Science, and Technology and Medicine. From our network of offices in Oxford, New York, Philadelphia, Boca Raton, Boston, Melbourne, Singapore, Beijing, Tokyo, Stockholm, New Delhi and Johannesburg, Taylor & Francis staff provide local expertise and support to our editors, societies and authors and tailored, efficient customer service to our library colleagues.


About BigRio

BigRio is a leading AI, Gen AI, Voice Agents, Data and Analytics professional services company. We are focused on Healthcare, Pharma, Digital Health, Provider, and Payer Industry segments with several innovative solutions. For more information, visit us at bigr.io.


Media Contact

Rohit Mahajan, The Big Unlock Podcast, 1 (857) 557-4302, [email protected]https://thebigunlock.com/

SOURCE The Big Unlock Podcast

Technology Must Remain Invisible, Yet Empower Caregivers to Deliver Care Better

Season 6: Episode #187

Podcast with Charles E. Christian,
Vice President of Technology and CTO, Franciscan Health

Technology Must Remain Invisible, Yet Empower Caregivers to Deliver Care Better

To receive regular updates 

In this episode, Charles E. Christian, VP of Technology and CTO at Franciscan Health, shares reflections from his five-decade journey in healthcare IT and how Franciscan is blending mission, compassion, and innovation to transform patient care.

Chuck explains how the health system is approaching AI adoption through strong governance and a clear focus on solving real problems, from reducing clinician burden to enhancing care delivery. He highlights several key initiatives, including voice agent pilots that help physicians reclaim after-hours time, a Tech Innovation Lab that allows teams to safely experiment and “fail fast,” and a virtual nurse mentoring program that connects senior nurses with new graduates for real-time guidance.

Chuck states that technology should serve, not distract, and the true goal of digital transformation is to enable better care for people. Take a listen.

Video Podcast and Extracts

About Our Guest

Mr. Christian is the Vice President of Technology and CTO for Franciscan Alliance, a thirteen (13) hospital system serving Indiana and Illinois.

Prior to joining Franciscan Alliance, Mr. Christian served as the Vice President of Technology and Engagement at the Indiana Health Information Exchange, the largest and oldest HIE in the country. Mr. Christian also served as the Vice President / Chief Information Officer of St. Francis Hospital, a free-standing, acute care, community hospital in west Georgia, a position he held for 2.5 years. Before his role at St. Francis, Mr. Christian served as the Vice President / Chief Information Officer for Good Samaritan Hospital, in Vincennes, Indiana. A position he held for almost 24 years. Before joining Good Samaritan Hospital, Mr. Christian worked in healthcare IT for Compucare and Baxter Travenol, in both management and implementation roles. Mr. Christian started his career in healthcare as a Registered Radiologic Technologist, serving in various Radiology roles for 14 years.

Mr. Christian holds a degree in Radiology Technology from Gadsden Community College and studied natural sciences at the University of Alabama in Birmingham.

Mr. Christian has delivered presentations on wide range of healthcare technology topics and is frequently quoted and published in national trade publications. He and co-authors, Judy Kirby and Steve Bennett published “Make I.T. Known-Marketing Strategies and Cases Studies in the Healthcare Environment.” Mr. Christian is also a frequent author in Modern Healthcare. Mr. Christian is also the author of the Irreverent-CIO health care blog. Mr. Christian has also authored chapters in multiple published management and college level textbooks.

Mr. Christian is a Life Fellow of the Healthcare Information and Management Systems Society (HIMSS) and is a Past Chair of the HIMSS Board of Directors, and past Chair of the HIMSS BOD Executive Committee. Mr. Christian was previously a member of the HIMSS Analytics Board of Directors. Mr. Christian is a Life Fellow and charter member of College of Health Information Management Executives (CHIME) and served on the CHIME BOD from 2003 through 2004 during which time he chaired the Membership Committee of the CHIME BOD. Mr. Christian is credentialed by CHIME as a Certified Healthcare CIO (CHCIO) and a Certified Digital Health Executive. Mr. Christian is a charter member of the re-established Indiana Chapter of HIMSS and served as a BOD member from 2000 - 2009. Mr. Christian served as a member of the Executive Advisory Board for Advance for Health Information Executives magazine. Mr. Christian served as a member of the Board of Directors of the Indiana Health Informatics Corporation by appointment of Indiana Governor Mitch Daniels. Governor Daniels also appointed Mr. Christian the Indiana Healthcare Information Technology Board of Directors.

Mr. Christian served as the CHIME Foundation Board of Directors as Chair and is the Past-Chair of the CHIME Board of Directors. Mr. Christian has served as the Chair of the CHIME Policy Steering Committee and continues to serve as a contributing member and is the Past-Chair of the SHIEC Advocacy Committee and is a past member of the Indiana HIMSS Chapter Board of Directors. Mr. Christian served on the Georgia HIMSS Board of Directors from 2013-2015, the KLAS Advisory Group from 2009-2013, and the CDW-Healthcare CIO Advisory Council from 2005-2010. Mr. Christian served the AHA Strategic Development Advisory Committee as a charter member. Mr. Christian is a past member of the Symantec Healthcare Advisory Group, and several other industry advisory groups/councils. Mr. Christian currently serves on the Virtustream Customer Advisory Board, the Hyland Executive Advisory Council, the Fortinet Advisory Board, HealthsystemCIO Board of Advisors and a member of the Indiana Hospital Association Information Management Council.


Charles: I am Chuck Christian. I’m the Vice President of Technology and CTO for Franciscan Health. Franciscan is a 12 or 13 hospital system, depending on how you count them. We cover a swath of the Midwest from just south of Indianapolis all the way to Chicago, basically following the I-65 corridor.

We have between 350 and 400 locations, including physician practices, imaging centers, lab draws, urgent cares, and oncology centers. It’s a pretty large organization. We have about 29,000 team members, both employees and contractors, at Franciscan Health.

We are truly mission focused. We are a Catholic healthcare system with a big C. We are owned by the Sisters of St. Francis of Perpetual Adoration. That means there are two sisters in the chapel praying for whatever they deem important and anything we ask them to pray for, 24 hours a day, seven days a week, 365 days a year. That’s where the “perpetual adoration” comes in.

We are a mission-driven organization. I believe in that. A lot of our hospitals are smaller and in underserved places, and we take care of that patient population. I think we’re really good at it.

I’ve known this organization almost 40 years. The CIO previous to Charles, who is our current COO, was a good friend of mine. I was CIO of a hospital in Southern Indiana for 24 years, and Bill and I ran a similar software stack. I watched Bill and learned a lot from him as far as how he ran this large organization.

I’ve been here for six years. I joined in April of 2019, so in dog years that’s like 35 years or more. We are very busy. I’m very blessed to have an outstanding team that manages all this, and I get to stand in awe and watch everything we accomplish every day.

Rohit: That’s fabulous. Thank you, Chuck for that intro.

Ritu: My name is Ritu Roy, and I’m the Managing Partner here at Damo and BigRio, and also the co-host of The Big Unlock podcast with Rohit. Thank you for being our guest today, Chuck. We are looking forward to an engaging and insightful conversation. With that, we can dive right in and get started.

Charles: Thank you.

Rohit: Hi Chuck. I’m Rohit Mahajan. I’m the Managing Partner and CEO at BigRio and Damo Consulting. It’s great to have you on the podcast. Like Ritu said, we’re looking forward to an engaging discussion. I’d like to start with the first thought on my mind. You’re in a mission-driven organization, and you’ve been a healthcare leader for many years. What started you on this journey? Tell us how you got started in healthcare, what attracted you, and what you’re passionate about.

Charles: Well, it depends on how far back you want to go. I’m an X-ray tech, radiologic technologist if you want to use the term. The first 14 years of my career were in radiology.

I stepped out of high school on June sixth in 1971, and on June seventh I stepped into the hospital, and I haven’t left since. Interesting enough, I did a lot of things in the radiology department and became part of the management team of that department. I guess if the chief tech had not been just a few years older than me, I’d still be there, because that was the role I wanted. But Roy just retired a few years ago, and I wasn’t going to wait that long.

I’m a geek, I’m a nerd. I was a nerd in high school. It wasn’t cool to be a nerd in high school back then, but it’s cool to be a nerd now. I did a lot of programming classes on the old System Threes with punch cards. Then I learned how to code for Z80 processors.

When we started automating hospitals back in the mid-eighties, I got chosen to run the ambulatory implementation of order management after we had put in patient management. I realized I liked it, and I knew that was where healthcare was going. Radiology has been a high-tech department in hospitals for a long time. I was trying to automate the patient record in radiology, but it was so expensive I couldn’t get any funding for it.

So I jumped ship and moved over to the vendors for about five years. Eventually I was asked to move to either an implementation manager role or the director of an outsourced IT department in southern Indiana. I did that. I had four daughters at the time, and it was the right thing to do because it was a great place to raise my girls.

I spent 24 years there. It was during the time the role of a healthcare CIO was defined. When I left that job, I was Vice President and CIO. I moved to Georgia to a health system there as Vice President and Chief Information Officer. Then I came back to Indiana and worked at the Indiana Health Information Exchange, which is now the only exchange in Indiana. I had been involved with it since 2005. I worked there for a little over four years, and then I took this role here. That’s my stint in healthcare, which has spanned over 50 years.

Rohit: That’s awesome, Chuck. You’ve been there, done it, and seen it as well. I was curious because a few days ago, when we were chatting, you were talking about being either back from UGM or about to go there.

We all know it’s a week-long affair, people go deep, and there are so many things to cover. We were wondering if you could share some of your experiences or a heads-up on topics you see coming our way.

Charles: Sure. I came home with a great deal of anxiety because of trying to figure out how we’re going to do everything and where healthcare is going. The nice thing about Epic is they now cover the entire gambit. I remember when Epic started; they were only in the ambulatory space and then only in large academic medical centers. They cover quite a scope of product these days.

Now that they have grown the applications, they have de-identified shared data, which I think is going to be a plus. The two-letter acronym was everywhere, AI, and how it’s going to be leveraged and used. They did a nice job showing scenarios of how it could be used and how organizations are using it.

We’re a risk-averse organization. We’re taking a more moderated approach. We’re getting our governance in place first. We already have a few things going through the AI mill, and we will have more. We split it into two pieces, one on the clinical side and one on the operational side. Epic has both, and I think they’re well positioned to do that work. They partner with Microsoft, and they continue to do so.

They announced they are working on their own ambient listening. They have business partners already, but they are creating their own product. I assume it will be predicated on the Microsoft stack, but they didn’t say, so I don’t know.

They also mentioned they are working on their own ERP and starting with workforce management. That makes sense because the workforce is in Epic all the time. Nursing staffing, scheduling, shifts, and how all that ties together. It’s an interesting leap.

Years ago, when Lawson, before being purchased by Infor, said they would create a patient accounting platform, I was in a CHIME focus group. When they mentioned that, a bunch of CIOs in the room asked why they would do that. You need to get your ERP right first. But I think the way Epic is approaching it makes sense.

It was great. I was there for about four days and spent most of the time listening to presentations. Judy did a great job with a big screen about what’s next and what’s coming. The rest of her team did a great job showing what you can do now and what’s coming. They do a good job setting expectations around timelines. They release quarterly. We do two a year, so we’re current from their perspective but behind. We don’t have the wherewithal to immediately adopt everything when they release it, so we have to plan accordingly.

Ritu: Yeah. So Chuck, when I was reading about the UGM, it was interesting because they said their unique proposition with AI is the de-identified patient records they have in Epic Cosmos, which is more than 15 billion patient records. They said that for the first time, it can actually move toward healthcare rather than sick care because doctors can predict trends. And I think they released two new things called Emmy and Penny, which will help doctors see the trajectory of what is going to happen with patients.

So I was curious about your thoughts because you’ve been in this industry for such a long time. Do you think that this USP—this huge bank of patient records—is really going to set them on a differentiating path compared to all the other AI startups trying to do the same thing?

Charles: I think that having the data is huge, honestly. It reminded me a lot of—if you remember years ago—they had a thing called PatientsLikeMe, where people with unique and rare diseases could find others and compare notes and treatment approaches. Working at the Indiana Health Information Exchange, I know they have about 30 years of data. Not all of it is discrete, but the majority is.

One question I asked the CEO, who is a friend of mine—and a lot of researchers use that de-identified data—is that when you create an AI model and just let it learn, there are all kinds of interesting determinations you can make once you have the data. So I think it’s going to be a game changer. Epic is also trying to outdo themselves. Given the market of EHR vendors, there aren’t many left standing. There are three or four. Others are creating similar repositories, but I’m not sure they have the long-term vision or the wherewithal to get it done. Knowing the talent Judy has pulled together, I think it will be very interesting to see what comes down the pike.

Ritu: Thank you.

Rohit: Chuck, you mentioned you’re taking a conservative approach to AI adoption and setting governance before taking major steps. How do you think about innovation or typical problem-solving—for example, reducing cognitive load across the organization? How do you balance this conservative approach with the fast-paced changes happening in the marketplace?

Charles: I think we have to be very clear about what problem we’re trying to solve. There are so many solutions being thrown at us—“Hey, we can do this, we can do that”—but often it’s not a problem we actually have. So we’re trying to pick and choose which targets to shoot at.

I’m married to a critical care nurse, so I’m very careful about getting in the way of the nursing staff. She’s retired, but for me, technology needs to be invisible. If it gets in the way of people being able to do their job, then it’s a problem.

If you think about it for a minute—and I’ll give you Chuck’s opinion—we don’t really have electronic medical record systems for documenting the care of the patient. What we have are electronic systems that capture information required for billing. That’s part of the problem. We have all these required elements clinicians have to document—physicians have to dot all the i’s and cross all the t’s—to get the appropriate words in so it can be translated into billing codes, ICD-10 codes, HPS codes, and so on. It truly gets in the way of taking care of patients.

But once we get that discrete data, we can use AI and other tools to help determine a better course of treatment. You’re never going to hear me say that we should depend solely upon AI. It has to be moderated and reviewed by someone with clinical training. Physicians have shown me I’ve been wrong more times than you can imagine. Working together and having good data aggregation is important.

One thing I learned early on when implementing the first physician order entry and clinical documentation systems was that physicians said: “Don’t tell me what I already know. Tell me what I don’t know. Better yet, tell me what I need to know about the patient in front of me right now.” There are things they don’t know. That’s where data aggregation from health information exchanges helps, because patients don’t get care in one location or from one physician.

I’m living proof of that. I get care in two—actually three—health systems because that’s where my specialists are. My primary care doctor wants to know what my orthopedist did or what my cardiologist’s course of treatment is, because he’s managing my diabetes and a few other things. Having access to information—recent labs, imaging studies—is extremely important.

We talked about interoperability, and that’s where it comes into play. Most hospitals in Indianapolis are on Epic, so you can get data easily. From non-Epic systems, there are mechanisms too. When I see my cardiologist—who uses a different system—and he already knows what my medications are because they were recently changed by another physician, that’s positive. I don’t have to list everything. When they know my latest labs, that’s positive too, because we’re not hunting for information.

It’s about providing information that is important to the treatment at that moment.

I had the privilege of sitting in a presentation—maybe eight or nine years ago—at Scripps Institute. They showed a demo of what a patient encounter could be. It was very Star Trek–like. The computer or AI interacted with the physician and patient appropriately. It listened in the background and captured information about the encounter. When the physician said, “We need to order a CT scan of your lower abdomen,” it was already getting that scheduled. When the patient was ready to leave, everything was set. It was also checking for recent labs and reminding the physician if the patient—say a diabetic—was due for an eye exam or foot check.

I think it’s about having access to the information so we can inform—not determine but inform—the physicians. Because at the end of the day, physicians are accountable for the outcomes. They have to be in control, not the AI.

Ritu: Yeah,

Charles: we’re not ready for Skynet yet.

Ritu: I think you described a multi-agent system where the agents are off doing things and then bringing it all back for the physician to review. With that being said, we all know that AgTech is one of the top trends everyone’s talking about these days. What are your thoughts on voice agents? Where is Franciscan with that? Have you had exposure to or tried voice agents in the hospital?

Charles: Yeah, we’ve got a trial. We’ve got over 200 physicians working on those. Is it going to be the end-all, be-all? I don’t know. The physicians seem to like it. It assists them; it helps with their pajama time.

I’ve listened to conversations from other health systems that were early adopters, and I have to go back in time to when we were looking at automating physician practices in Southern Indiana. We visited a group of 14 family practice doctors. The husband and wife who started the practice mostly did OB and family medicine. Their use of computers was minimal—they were still mostly on paper. But they had other physicians who, I think, slept with their laptops.

The interesting thing was that depending on how well a physician adopted the computer system and molded it to how they practiced, they got to take advantage of it. I think it’s going to be the same with AI and voice agents. If they allow it to help and figure out how to incorporate it into how they think and practice, they’ll see the benefit. The systems are pliable enough now that it’s easier to do.

When I was in Georgia, we needed to automate a lot of OB practices on the same platform. One OB had been practicing almost 30 years and already had a solution he had customized. He told me I would tear it out of his cold, dead fingers. So we worked with him. The new system was more flexible and pliable than his old one, and he became a champion because he was willing to take the time to understand how he could use the technology to help him practice.

I think that’s the key. If you’re resistant to it, that’s fine—that’s perfectly okay. But people who write software often think all physicians think the same way. They’re absolutely wrong. It depends on where they trained. I learned that when implementing emergency room electronic medical records. The physicians who helped design the software were trained with a very different approach to critical thinking than our physicians. We had to relearn and figure out ways to adjust, because once clinicians are trained a certain way, it’s hard to change those habits and the way they gather and maintain information.

Ritu: Thank you. Great answer.

Rohit: Chuck, I’d like to ask your thoughts about the innovation process. How do you approach it, and what are some of the things you do to foster innovation?

Charles: One of the things we did was stand up a Tech Innovation Lab. Honestly, it was a selfish move because people were just bringing technology into the organization. All the enterprise architects report to me, and we work together to understand what will work in our environment and what won’t. We try to standardize as much as we can.

So I created the Innovation Lab to bring these innovations into a controlled environment and try them there. It’s a walled garden. It’s not connected to the rest of the network. It has its own connections to the internet. So if we blow something up, it only blows up in the lab. That’s why we did it.

What we’re able to do is bring ideas in and fail fast—figure out what works and what doesn’t. We’ve done that several times. Virtual nursing is something we’ve worked on a lot. There were all kinds of interesting opportunities brought to us. One facility went ahead and put a solution into a live patient population, and we found out quickly that’s not how you do it. You don’t test that kind of thing in a live environment. It frustrates the staff and patients, and it leaves leadership thinking, “We already tried that—it doesn’t work.”

Well, you tried what doesn’t work. Let me show you what will work.

We needed the opportunity to rapidly figure out what would work. One issue with that failed experiment was that the people who built the carts didn’t understand our environment. They put a wireless access point in the cart that was incompatible with our network. Once we got the cart, we figured it out quickly. We re-engineered it, and it works fine now—but we’re not using that cart because it was over-engineered and very expensive.

We’re trying to use standard components that can be supported and replaced quickly. The idea is to generate a lot of ideas and figure out how to use them appropriately without getting in the way.

You also have to think about the aesthetics of the equipment you’re bringing in. The first cart had a big five-wheel base—kind of a star shape. In some patient rooms, it was in the way. Nursing quickly said, “That’s not going to work.”

So we found an iPad holder that hangs on the patient’s bedroom wall when not in use. It’s out of the way, easy to access, and uses magnetic connectors so if someone snags it, it just comes apart. No trip hazard.

You must consider not only the technology but how it fits in patient rooms.

Originally, the idea was that the Innovation Lab would review the technology, understand how it fits together, and then install it in our SIM labs. We have two—one north, one south. Then the simulation teams would put it in a physician office or patient room and see how it fits before we use it in live care. That’s our next step with virtual nursing.

We also have a lot of conversations with organizations that have fully rolled out these solutions. We learn from their experiences. A mistake is only a mistake if you don’t learn from it. If you do, then it’s experience. We leverage their experience so we don’t repeat the same things, and so we can move quicker.

Rohit: That’s awesome. As we are approaching the end of the podcast, I would like to ask if you would touch on the mentorship program.

Ritu: Yes, I would really like to hear more about that, Chuck, because it’s something unique and I think it would be interesting for our listeners as well.

Charles: Just making sure we’re talking about the virtual mentoring program. After COVID, we were bringing on a lot of new nurse graduates. When you bring someone into that role, they need a more experienced nurse for a procedure they may have never done before. That usually means waiting for that nurse to come to them.

We had a couple of nursing staff in the mentorship program who came up with a way to use technology for an on-screen virtual visit with the new nurse. The experienced nurse could walk them through the procedure and be there with them, or if the new nurse had a question, they could step out into the hall, ask it, and go back in. It improved speed to delivery of care more than anything else.

It also gave seasoned nurses a chance to step away from what they were doing instead of traveling to another location. If they need to go in person, they still do, but this gave us another option. We got great feedback from both the new nurses and our more mature nursing staff, and we rolled it out through the enterprise. I haven’t checked in on it recently, but I assume it’s still running. I only hear when things break, and if it’s not broken, I’m not going to fix it. I assume the technology is still working and paying dividends.

Ritu: Thank you so much.

Rohit: So, Chuck, as we come to the end of the podcast, any closing remarks or thoughts you’d like to share before we finish?

Charles: I’ve been in healthcare a long time. Healthcare is a target rich environment for creativity and innovation. But we’re still taking care of patients the same way we did, and it’s about the human touch and caring for people.

When I first started in radiology years ago, I was taken aback that people weren’t always treated as people. They were exams. Do this gallbladder in this room, do this hip nailing in that room. I was reminded they’re people. They could be my family. They could be my children. That’s why I’m passionate about making sure the technology works and doesn’t get in the way.

Have we reached the pinnacle? No. Is it better? I think it is. But we’re still trying to figure it out every day. As long as we have great people passionate about providing outstanding care and we understand where that ability comes from, we’ll keep moving forward.

We’re a Catholic healthcare system, and our rule is we start most meetings with prayer. We are called to love one another as God loves us, and we need to remember that every day. That’s why I keep doing what I’m doing.

Rohit: Awesome.

Ritu: Thank you so much, Chuck.

Rohit: Really appreciate it.

Charles: Okay. Thanks for the opportunity to share.

————

Subscribe to our podcast series at www.thebigunlock.com and write us at [email protected]   

Disclaimer: This Q&A has been derived from the podcast transcript and has been edited for readability and clarity.

About the Hosts

Rohit Mahajan is an entrepreneur and a leader in the information technology and software industry. His focus lies in the field of artificial intelligence and digital transformation. He has also written a book on Quantum Care, A Deep Dive into AI for Health Delivery and Research that has been published and has been trending #1 in several categories on Amazon.

Rohit is skilled in business and IT  strategy, M&A, Sales & Marketing and Global Delivery. He holds a bachelor’s degree in Electronics and Communications Engineering, is a  Wharton School Fellow and a graduate from the Harvard Business School. 

Rohit is the CEO of Damo, Managing Partner and CEO of BigRio, the President at Citadel Discovery, Advisor at CarTwin, Managing Partner at C2R Tech, and Founder at BetterLungs. He has previously also worked with IBM and Wipro. He completed his executive education programs in AI in Business and Healthcare from MIT Sloan, MIT CSAIL and Harvard School of Public Health. He has completed  the Global Healthcare Leaders Program from Harvard Medical School.

Ritu M. Uberoy has over twenty-five years of experience in the software and information technology industry in the United States and in India. She established Saviance Technologies in India and has been involved in the delivery of several successful software projects and products to clients in various industry segments.

Ritu completed AI for Health Care: Concepts and Applications from the Harvard T.H. Chan School of Public Health and Applied Generative AI for Digital Transformation from MIT Professional Education. She has successfully taught Gen AI concepts in a classroom setting in Houston and in workshop settings to C-Suite leaders in Boston and Cleveland. She attended HIMSS in March 2024 at Orlando and the Imagination in Action AI Summit at MIT in April 2024. She is also responsible for the GenAI Center of Excellence at BigRio and DigiMTM Digital Maturity Model and Assessment at Damo.

Ritu earned her Bachelor’s degree in Computer Science from Delhi Institute of Technology (now NSIT) and a Master’s degree in Computer Science from Santa Clara University in California. She has participated in the Fellow’s program at The Wharton School, University of Pennsylvania.

About the Legend

Paddy was the co-author of Healthcare Digital Transformation – How Consumerism, Technology and Pandemic are Accelerating the Future (Taylor &  Francis, Aug 2020), along with Edward W. Marx. Paddy was also the author of the best-selling book The Big Unlock – Harnessing Data and Growing Digital Health Businesses in a Value-based Care Era (Archway Publishing, 2017). He was the host of the highly subscribed The Big Unlock podcast on digital transformation in healthcare featuring C-level executives from the healthcare and technology sectors. He was widely published and had a by-lined column in CIO Magazine and other respected industry publications.

How to Build AI Literacy Programs in Healthcare Organizations

How to Build AI Literacy Programs in Healthcare Organizations

As artificial intelligence (AI) reshapes every industry, healthcare stands at a critical inflection point. Generative AI, predictive analytics, and intelligent automation are changing how clinicians diagnose, treat, and manage patients. Yet the biggest challenge isn’t technology – it’s people.

AI literacy has become essential to bridging the gap between innovation and real-world healthcare impact. It involves equipping professionals to understand, evaluate, and responsibly collaborate with AI systems. Without it, even the most advanced tools risk underuse, mistrust, or outright rejection. Building AI literacy goes beyond learning how to use new technologies, it’s about preparing the healthcare workforce to partner effectively with AI, interpret its outputs, and make informed, ethical decisions in patient care.

In one of the recent episode of The Big Unlock podcast, Jan Beger, Head of AI Advocacy at GE HealthCare joined hosts Rohit Mahajan, Managing Partner and CEO at BigRio and Damo, and Ritu M. Uberoy, Managing Partner at BigRio and Damo to share insights from GE’s global experience in building large-scale AI literacy programs. His perspective offers a practical roadmap for health systems, medtech firms, and digital health leaders who are navigating this transformation.

Why AI Literacy is the Cornerstone of AI Adoption

AI literacy sits at the intersection of technology, people, and culture. As Jan notes, healthcare conversations about AI often “get technical very quickly,” leaving behind the clinicians and professionals expected to use these tools in their daily work.

To make AI adoption sustainable, organizations must focus on the human side of innovation – helping staff understand what AI can and can’t do, building trust in its outputs, and empowering people to see it as an enabler rather than a threat.

According to a study by Workday and LinkedIn, 70% of job skills are expected to change by 2030, with AI driving much of that shift. In healthcare, where regulation, risk, and ethical complexity are high, this means rethinking skill sets and workflows in real time.

AI literacy ensures that clinicians, administrators, and executives can use AI responsibly to improve patient outcomes and system efficiency.


Defining AI Literacy for Healthcare

Jan Beger offers a simple but powerful definition of AI literacy built around three competencies:

  1. Collaborate responsibly with AI: Understand the fundamentals of AI, from machine learning to generative models, and how they integrate into clinical or operational workflows.

  2. Explain AI outputs: Be able to interpret what the AI system is showing — for example, how an algorithm supports a diagnostic decision or a chatbot retrieves information.

  3. Critically evaluate AI outputs: Avoid blind trust. Clinicians and employees must question results, verify data sources, and know when human judgment should override machine recommendations.

This mindset shift, from passive use to active collaboration, is the foundation of effective AI literacy.


Designing a Scalable AI Literacy Program

GE HealthCare’s approach provides a template for others to follow. Their Responsible AI strategy integrates literacy into employee education through multiple channels:

Live sessions and workshops with AI experts for hands-on learning.

Best-practice sharing sessions where teams demonstrate how they’ve applied AI in real workflows.

Self-paced learning modules tailored for different roles and levels of expertise, from basic AI terminology to deep dives into specific use cases.

For example, GE’s Hello AI program offers foundational and professional courses for healthcare professionals and students. The free foundational module introduces key AI concepts, while the professional course provides 25 hours of specialized healthcare content for a nominal fee. Over 5,000 healthcare professionals from 70+ countries have already participated.

This layered, accessible model helps organizations with large, distributed workforces like GE’s 51,000 employees across 160 countries — develop AI fluency at scale.


Building Engagement and Overcoming Resistance

Change management is at the heart of any AI literacy initiative. As Ritu M. Uberoy, co-host of The Big Unlock, noted, healthcare professionals often approach AI defensively: “Why should I do something that’s going to take my job away?”

To address this, organizations must position AI as a tool for empowerment, not replacement. Jan emphasizes that in every conversation, “we need to remove worries and fears among healthcare professionals” and show how AI helps them do their jobs better by increasing accuracy, efficiency, and patient satisfaction.

Face-to-face engagement remains key. Jan, who travels extensively to meet clinicians and hospital teams, finds that in-person discussions build trust and reveal practical barriers that online training alone can’t address. However, hybrid approaches which is a combination of digital learning and local advocacy can make programs more sustainable and scalable.


Measuring Success and Evolving Continuously

No literacy initiative is complete without metrics. Organizations must define what success looks like, and it will differ by role.

For example, GE HealthCare measures tangible productivity gains among software developers using AI coding tools. But for field engineers or clinical teams, success may initially focus on engagement, confidence, or adoption rates rather than speed or output.

As use cases evolve, KPIs must evolve too – from tracking participation in AI courses to measuring how AI literacy translates into improved workflows, reduced errors, or better patient outcomes.

Another lesson from GE’s experience is – AI literacy programs are not “set it and forget it” initiatives. They require continuous updates, new content, and maintenance to reflect the pace of innovation and regulatory changes.


The Broader Mission: Rethinking Roles in an AI-Driven Future

AI literacy isn’t just an education program, it’s a mindset shift. As Beger summarizes, everyone in healthcare should “start rethinking their job descriptions with AI in mind.” Understanding how AI can augment one’s role fosters curiosity, confidence, and innovation.

Moreover, Jan’s call to action extends beyond healthcare: “We have so many great AI experts working in gaming or banking. If they truly want to make an impact on society, they should consider joining healthcare.” That spirit of collaboration across domains, between technologists, clinicians, and educators, is what will truly accelerate the responsible use of AI in healthcare.

Building AI literacy programs in healthcare is not a technical challenge, it’s a leadership one. It requires empathy, structure, and a relentless focus on people. GE HealthCare’s example shows that when organizations invest in education, trust, and responsible innovation, they don’t just prepare their workforce for the future, they help shape it.

Empowering Patients and Closing Health Gaps with AI and Connected Care

Season 6: Episode #186

Podcast with Anil Saldanha
Chief Innovation Officer
Rush University System for Health

Empowering Patients and Closing Health Gaps with AI and Connected Care

To receive regular updates 

In this episode, Anil Saldanha, Chief Innovation Officer at Rush University System for Health shares how Rush is addressing deep-rooted health inequities in Chicago by targeting the life expectancy gap through bold, system-wide interventions.

Anil highlights Rush’s commitment to public health, chronic disease management, and early cancer detection by referring to innovative initiatives like Rush Connect Plus, which is an on-demand, subscription-based virtual care model, and the rollout of Grail’s multi-cancer early detection test. He explains their use of cutting-edge AI technologies, from ambient listening and AI-powered symptom checkers to novel behavioral health kiosks leveraging multi-agent generative AI for PTSD care.

Anil points to the impact of consumer-driven digital tools, health equity analytics, and a data warehouse that will enable targeted interventions for chronic care. He closes with optimism about AI’s future in healthcare, the shift toward “connected care anywhere,” and the growing role of empowered, informed patients. Take a listen.

Video Podcast and Extracts

About Our Guest

Anil Saldanha is the Chief Innovation Officer at Rush University System for Health. With a background in business and technology, Anil has the advantage of having learned skills and experiences in non-healthcare fields to now transform healthcare at Rush. He operates at the intersection of public health, community health, and delivery. He was a founding team member of Tempus AI in Chicago and has held leadership roles at companies such as GoSecure Inc., Trustwave Inc., Red Hat Inc., and Sun Microsystems. He is a strategic advisor on innovation and transformation to clinical, research, and technology leadership at Rush.


Ritu: Hi Jan, welcome to our podcast. We are so happy to have you here on The Big Unlock podcast, season six, and we are headed to 180 plus episodes now. Really great having you on the show today. Just a brief introduction — my name is Ritu Roy. I am the Managing Partner here at BigRio and Damo Consulting and a co-host of The Big Unlock podcast with Rohit. And with that, I’ll hand it over to Rohit. He can give a brief introduction and then over to Jan. Thank you.

Rohit: Hi Jan, great to have you here, like Ritu said, and thank you for making the time in the evening from where you are in Germany. Really excited to have this conversation. I’m Rohit Mahajan, CEO and Managing Partner at BigRio and Damo Consulting. And with that, Jan, would you like to start with your intro?

Jan: Absolutely. First of all, thank you both for having me today and for the invitation. Truly appreciate it and looking forward to a good conversation about this exciting topic of artificial intelligence in healthcare. As you mentioned, my name is Jan Beger, Head of AI Advocacy at GE Healthcare. My mission is to transform AI in healthcare from a conceptual promise into a high-impact reality. I focus on equipping healthcare professionals, executives, and the next generation—like students—with the knowledge, skills, and mindset to thrive in this AI-enabled future of healthcare.

Ritu: That’s really great. Wonderful introduction and really interesting title you have, Jan, because we’ve talked to CIOs and CMIOs, but you’re someone who’s the Head of AI Advocacy. I think that’s something new. Would love to hear about your journey—how you came to be in this role, how you combine expertise in healthcare and AI, and what your vision for AI is at GE Healthcare.

Jan: Thank you so much. I hope you agree—based on the many conversations you’ve had in this space with different experts—when we talk about AI in healthcare, those conversations very quickly get technical. But I think in healthcare, and maybe as an entire industry, we have not focused enough on one important aspect: making sure that those clinicians and healthcare professionals we expect to use AI technologies are taken with us on this technology journey.

So, things like change management and education—making sure we focus on the human aspect—is something I think has not been emphasized enough across the industry, maybe even to a point that it slows down AI adoption. This is what I’m really focusing on—what we need to do to remove worries and fears among healthcare professionals, help them gain a solid understanding of the technology, build basic trust in AI, and get them interested in testing and piloting these solutions. Ultimately, the idea is this could lead to faster adoption.

Ritu: Yeah, that’s an extremely valid point, Jan, because I was just at a conference at MIT yesterday, and this was one of the key things that came up — that it can’t be a top-down approach because whenever you ask somebody to do something, their initial reaction is to go into defensive mode and say, “Why should I do something that’s going to take my job away?” or “What’s in it for me?”
So we would be really interested in hearing from you how you are able to get buy-in from the teams across GE and get everybody on board, making sure everyone has the literacy skills, like you said, to understand that AI can actually be a tool to do your job better, increase productivity, bring efficiency, and do all the good things AI promises.

Jan: First of all, I think across different domains and industries — in a health system, but the same in a medtech or healthtech company — everything is being reinvented right now in real time. There’s a lot of activity in that space.
We at GE also look into processes and how we can support our workforce with generative AI technologies. Again, the technology is one part of the story; the second is how we make sure we enable our workforce — 51,000 employees across the globe in 160 countries — to leverage this technology well and responsibly, to truly make a difference in their day-to-day work.

This is exactly the same in the healthcare space as well. We are entering a state of skill redefinition in real time. Things that were important in the past — like routine execution, static expertise, or hierarchical knowledge — are becoming less relevant. And on the flip side, we see more important skills emerging, like adaptability, systems thinking, tech fluency, and AI know-how.

We all have to prepare for this. There was a study recently done by Workday and LinkedIn, which said that 70% of job skills are expected to change by 2030, with AI driving much of this shift. This is not just healthcare — this is across different industries.
Maybe in healthcare, this kind of change will feel a little bit slower because it’s highly regulated. But what I want to say by mentioning this number is that there is a massive technology transformation ahead of us, and a lot of people don’t even understand that this is coming — and coming with quite some impact.

We not only need to continue building great technologies and integrating AI into products and workflows, but also need to create awareness and build AI literacy so that everyone across the healthcare ecosystem can use this technology responsibly for better care and improved patient outcomes.

Ritu: Thank you, Jan. That answer leads into two follow-up questions. First, like you said, the speed of invention is at an unprecedented scale, which we haven’t seen before. The speed is also leading to democratization, where anybody can do low-code or build a tool or a prototype.
That leads to the next thing — this whole concept of AI literacy. If the tools are so easy to use and can unlock so many new ideas, you want everybody across the company to understand how to use them and be fluent. So, how does GE, with such a large employee base — 51,000 employees across 161 countries — handle this? Do you have an overall AI literacy program with different levels, or what systems are you setting up to address this?

Jan: Great question. First, I should define what AI literacy means to me, because it could mean different things for different people.
In a nutshell, I would say it’s three things: one is the competencies required to collaborate responsibly with AI and interact with technologies such as large language models and generative AI.
The second is to be able to explain their outputs.
Third, it’s to be able to critically evaluate those outputs — and then do something meaningful with them. As you know, the worst thing would be to blindly trust those outputs and leverage them in your day-to-day work. So, critical evaluation is a very important part of AI literacy overall.

At GE Healthcare, there is an AI literacy program in place, which is part of a broader Responsible AI strategy. We have different ways to educate our teams — live sessions where they can dial in and learn from experts on how to use generative AI integrated into our tech stack, best practice sharing sessions, and self-paced learning offerings for employees at different levels — from a foundational course covering basic AI terminology to more use-case-specific, in-depth training for specific groups and roles.

Rohit: I was just wondering, Jan, about the key initiatives you’re taking, which are so valuable moving forward for the company and the employees themselves, because they’re basically increasing their skillset as well. We’ve been thinking about some success metrics for our own organization and for some of our clients who’ve been asking for similar services. Any thoughts or ideas, Jan, on what success metrics one could track for such initiatives in any organization setting out on this journey?

Jan: I think those success metrics and KPIs are critically important to measure traction and see where we’re heading and if the investment in these efforts makes sense. For instance, one area where we’ve seen early positive results is with our software developers. With AI capabilities, we’ve seen improvements in speed—getting code done, getting code reviewed, those kinds of things.
So this is maybe one area where, across industries, we already have several best practices and standard ways to measure performance and progress. But then there are other groups of employees where those measures are harder to obtain, or maybe it’s too early because we just started using these capabilities.

For instance, our field engineers—people who visit customer sites to check or repair MRI devices—now get AI support through tools we’ve developed where they can have a natural language conversation with the service manual of a specific device or get help with scheduling. Those are new use cases, and we’re still defining the right success measures or KPIs for them.
There’s a wide range of capabilities and use cases across different groups and business units. Over time, we’re getting better at measuring progress. As I mentioned, in software development we already have specific measures in place and are seeing the benefits of AI, but there are other areas where it’s still greenfield, and KPIs will evolve over time.

Ritu: Thank you, Jan. Our listeners—and most of us—always like to hear about success stories and success metrics, but it’s also important to learn from failure. It would be really interesting to hear from you about a couple of cases where things didn’t go so well, what you learned from that, and how you came back to do something even better.

Jan: I’ll give you an example of a tool we built in-house to support our marketing teams with approved external communication content. We’re feeding a retrieval-augmented generation model with external content so that when a communications specialist gets a request from the media, they don’t need to start from scratch—they can leverage this chatbot, get approved responses, tweak and refine them, and then use them.
It’s useful, but it’s also a lot of work—making sure the knowledge base of the chatbot is always up to date. Maintenance is a challenge and requires manpower and effort. So it’s not just a one-off where you build a cool AI tool and send it out for people to use. A lot of those tools require continuous focus, effort, and maintenance.

Rohit: While you do this at such a global scale, are you traveling a lot and meeting people in person to motivate them, or are you using online tools to make this happen? What are some of the key tools or methods you’re using for the advocacy you’re doing with such a large group of people?

Jan: That’s a great question. When I introduced myself, I should have mentioned that I focus most of my time on our customers—health systems, hospitals, and healthcare professionals—and focus my AI advocacy and literacy work mainly on clinicians.
To answer your question, I travel about 80% of my time. I’ll be in the US next week in Seattle and Atlanta. It’s important to meet medical and clinical experts in person. I always learn from them—I want to understand their concerns, fears, issues, what works, and what doesn’t. Even with great remote technology, face-to-face works best for me.

Of course, there are things that can be done online too. For example, for a few years we’ve been running an AI literacy program for healthcare professionals called Hello AI. When you go to helloai-professional.com, you’ll find more information. It’s a self-paced e-learning offering with two modules where clinicians, students, researchers, and executives can educate themselves about AI in healthcare.

We’ve received great feedback. So far, we’ve educated more than 5,000 healthcare professionals from over 70 countries. Later this year, we’re launching a new learning module built specifically for healthcare executives—because this population is becoming increasingly important in the overall transformation.
Over the last few years, healthcare systems have made progress adopting and piloting AI, but mostly through point solutions—like a decision-support tool in radiology or something with EHRs. Executives now need to think about AI strategically—how to plan, deploy, and measure ROI at a system level. That’s why we’re launching this new offering for healthcare executives on the Hello AI platform later this year.

Rohit: That is fantastic. I think there’s definitely a need for such a thing. Tell us a little more about Hello AI. How did it come into being? Did it precede your joining GE Healthcare, or is it a GE Healthcare initiative? We’d love to learn more about this venture.

Jan: Thank you so much. First of all, when we think about AI in healthcare, there’s often the impression that this is a domain led by big tech or the innovative healthcare AI startup ecosystem around the globe. But that’s only partially true. The reality is that when you look into AI and machine-learning-enabled medical devices, you’ll quickly realize that it’s also a huge play for traditional medtech.
Companies such as GE Healthcare and Siemens Healthineers are leading the pack. The FDA has authorized more than 1,000 AI-enabled medical devices so far, and about 100 of those come from GE Healthcare.

We feel a responsibility as a leader in this field not only to build and integrate great technologies into our devices but also to focus on the change management and education for those we expect to use these technologies. This is how it started—and what Hello AI is.

It’s a learning offering for healthcare professionals and executives built by a network of partners—GE Healthcare, universities, and technology companies—working together to spread the word. Our mission is to make AI literacy accessible and affordable for healthcare professionals worldwide.

We’re trying to provide healthcare AI–specific education, not just general AI education. There’s a lot of free AI content online from big tech, but we focus on healthcare-specific AI education at no or low cost. For instance, we currently have two modules: a free foundational course for everyone, and a more in-depth Professional course with 25 hours of content for just $99.

Rohit: That’s awesome. Would you be open to licensing this as well? In case a large enterprise is interested in your offerings, I’m sure you’re looking at some licensing deals too.

Jan: Our partnership model is threefold. First, we look for partner institutions to join Hello AI and co-develop new content. AI is a fast-paced field, and there’s a lot happening. For instance, earlier today we had a session on federated learning, which is part of new content we’re adding to our modules.
Second, we focus on co-marketing and co-promotion.
Third, when an institution joins us and contributes in these areas, we provide their employees or members free access to Hello AI content.

Rohit: That’s awesome. This is great—you’re offering such a robust platform to increase awareness and education in this space. As we come to the end of the podcast, Jan, any other thoughts or predictions in AI? There’s a lot of agentic AI coming our way—any thoughts for the future audience?

Ritu: And I think Jan wanted to show the device, which might relate to my question: do you have an example where AI has made a difference in patient outcomes—something you’ve put into a device that really made an impact?

Jan: Maybe just quickly, Rohit. I’ll share a use case that’s been very impactful, and then I’ll give a few takeaways. First, as I showed earlier, this is a handheld wireless ultrasound scanner for specific use cases. Imagine an emergency doctor carrying this wherever they go—a powerful imaging tool with no radiation. But one limitation is that it’s very operator-dependent. You need a certain level of education and experience to get high-quality medical images.

So a few years ago, we embedded AI into these machines. It tells you, while scanning the patient, how to move the probe to get high-quality images. This means even less-experienced clinicians can achieve excellent results. The idea is to democratize ultrasound so it’s accessible to more users. That’s just one of many examples of AI making an impact in healthcare today.

A few takeaways for your audience:
First, I strongly recommend everyone—whether in tech, corporate, or healthcare—start rethinking their job descriptions with AI in mind. Think about what you do every day, how AI could support you, and how it changes your role. When you start thinking this way, you’ll begin learning about AI, open your mind to opportunities, and adopt the right mindset to embrace this technology.

Second, we have so many great AI experts, data scientists, and developers worldwide working in industries like gaming or banking. If you know them, tell them about healthcare. If they truly want to make an impact on society, they should consider joining healthcare. It’s still early-stage and slower because of regulation, but if you have this expertise, the industry would truly value it. We can make a real difference here.

Ritu: Thank you, Jan. This was awesome. I’m sure listeners have a lot to absorb and reflect on. Your call to action is excellent—this is an industry where we can see the maximum impact and really help people. Thank you.

Jan: Thank you so much for inviting me.

————

Subscribe to our podcast series at www.thebigunlock.com and write us at [email protected]    

Disclaimer: This Q&A has been derived from the podcast transcript and has been edited for readability and clarity.

About the Hosts

Rohit Mahajan is an entrepreneur and a leader in the information technology and software industry. His focus lies in the field of artificial intelligence and digital transformation. He has also written a book on Quantum Care, A Deep Dive into AI for Health Delivery and Research that has been published and has been trending #1 in several categories on Amazon.

Rohit is skilled in business and IT  strategy, M&A, Sales & Marketing and Global Delivery. He holds a bachelor’s degree in Electronics and Communications Engineering, is a  Wharton School Fellow and a graduate from the Harvard Business School. 

Rohit is the CEO of Damo, Managing Partner and CEO of BigRio, the President at Citadel Discovery, Advisor at CarTwin, Managing Partner at C2R Tech, and Founder at BetterLungs. He has previously also worked with IBM and Wipro. He completed his executive education programs in AI in Business and Healthcare from MIT Sloan, MIT CSAIL and Harvard School of Public Health. He has completed  the Global Healthcare Leaders Program from Harvard Medical School.

Ritu M. Uberoy has over twenty-five years of experience in the software and information technology industry in the United States and in India. She established Saviance Technologies in India and has been involved in the delivery of several successful software projects and products to clients in various industry segments.

Ritu completed AI for Health Care: Concepts and Applications from the Harvard T.H. Chan School of Public Health and Applied Generative AI for Digital Transformation from MIT Professional Education. She has successfully taught Gen AI concepts in a classroom setting in Houston and in workshop settings to C-Suite leaders in Boston and Cleveland. She attended HIMSS in March 2024 at Orlando and the Imagination in Action AI Summit at MIT in April 2024. She is also responsible for the GenAI Center of Excellence at BigRio and DigiMTM Digital Maturity Model and Assessment at Damo.

Ritu earned her Bachelor’s degree in Computer Science from Delhi Institute of Technology (now NSIT) and a Master’s degree in Computer Science from Santa Clara University in California. She has participated in the Fellow’s program at The Wharton School, University of Pennsylvania.

About the Legend

Paddy was the co-author of Healthcare Digital Transformation – How Consumerism, Technology and Pandemic are Accelerating the Future (Taylor &  Francis, Aug 2020), along with Edward W. Marx. Paddy was also the author of the best-selling book The Big Unlock – Harnessing Data and Growing Digital Health Businesses in a Value-based Care Era (Archway Publishing, 2017). He was the host of the highly subscribed The Big Unlock podcast on digital transformation in healthcare featuring C-level executives from the healthcare and technology sectors. He was widely published and had a by-lined column in CIO Magazine and other respected industry publications.

The Healthcare Digital Transformation Leader

Stay informed on the latest in digital health innovation and digital transformation.

The Healthcare Digital Transformation Leader

Stay informed on the latest in digital health innovation and digital transformation

The Healthcare Digital Transformation Leader

Stay informed on the latest in digital health innovation and digital transformation.