Q. Thank you for joining the podcast, Sophy. It’s great to have you here.​ Likewise. I’m Rohit Mahajan, managing partner and CEO of BigRio and Damo Consulting, and the host of the Big Unlock podcast. As you know, it was started by Paddy a long time ago. We’re honored to continue this podcast. We’re now in the 150s episodes, so it has come a long way. Sophie, could you please introduce yourself?

Sophy:  Thank you. My name is Sophy Lu. I am currently the Senior Vice President of Digital Integration and Business Relations at Northwell Health. Previously, I’ve held multiple executive roles at Northwell, including System CIO, and I’ve been with Northwell for approximately 15 years. I grew up in the application space. Prior to that, I was trained as a chemical engineer. I enjoy continuous learning, integration, connecting people, and solving problems by bringing common to chaos. I live in Brooklyn, happily married with two grown kids. I have four Labradors and two Norwegian cats.

Q. That’s awesome. So, how does a chemical engineer like you, Sophy, wind up in one of the largest healthcare systems in the country? Please tell us a bit about your journey and about Northwell as well.

Sophy: Absolutely. I often say it’s a mix of luck, timing, and a lot of hard work, along with the networks you’re exposed to. Initially, I wanted to be a kindergarten teacher, but my love for science and math led me to chemical engineering. I worked in that field for about seven years after graduation, focusing on process and industrial design for chemical plants. This role took me across Europe and Indonesia.​

During that time, I was drawn to sustainability, working on clean energy projects. About 20 years ago, I was involved in expanding liquefied natural gas and combined natural gas. While these concepts are well-established today, back then, scaling them in the transportation and energy industries was quite ambitious.​

As the engineering sector shifted more towards the central United States, I wanted to stay close to my family here. I explored other opportunities, sending out numerous resumes at job fairs. A consulting company noticed my background and brought me on board to work on technology integration and implementation, leveraging my industrial gas experience.​

This consulting role involved extensive project management, business integration, and participation in mergers and acquisitions. Notably, I worked with St. Vincent’s Hospital, which expanded from a single institution to about seven or eight. Unfortunately, it eventually faced bankruptcy. This experience provided deep insights into management during financial crises and organizational turnarounds.​

This was my first exposure to healthcare—a sector dedicated to care and wellness but often challenged by reimbursement issues and technological limitations. After St. Vincent’s closure, I was recruited by Northwell Health to work in their application space. I joined during the inception of their revenue cycle implementation, marking the beginning of their patient journey and EHR initiatives. Since then, I’ve been with Northwell and have never looked back.​

Q. Oh yeah, yeah. So you spent many years at Northwell and that’s a fabulous, you know, segue from your industrial engineering and engineering background into healthcare. You know, and you got a glimpse up close of a, of an institution that, that went through that phase as well of M& A and, you know, turn around.

So Sophy, tell us about your new role. I understand that you have a new role here at Northwell and that you are looking at, uh, some very different initiatives. So how’s that coming along and, and. What can you share with the audience? 

Sophy: Yes. So as we started the digital transformation journey at Northwell, laying out the foundation of simplifying the ecosystem and selecting strategic functions that we wanted to implement relative to sort of the cloud foundation, the data platform and evolving our EHR for the entire organization, there was a need that we looked into that we wanted to focus on for digital transformation integration and business relations. And what does that mean? If you look at the heart of where technology and a seat at the table, along with operations and clinical care and patient experience has married, the new discipline of digital relationship management really is trying to make sure that we are bridging operations to technology to patient at the center.

Right. And some of those objectives, no matter whether you’re looking at an adoption of technology that you just are implementing, like an EHR or your new emerges and acquisitions of how are you going to integrate the business  looking at building out a new facility? And what are you thinking about relative to innovative workflows and engagement and experience for, for the patient and the families, right?

And so you look to bridge in that relationship, strategic alignment, you want to make sure that the stakeholders are engaged in the decision making and the journey. And you want to facilitate effective communications because everybody doesn’t always speak the same language at the same time. It is what’s important to me and what’s relative to my role at that time, right?

You want to get synergy across that and you promote the continuous improvement and selection of what works best to meet the mission and the vision of whatever that initiative that you’re working on. Always focusing on process improvement.  Efficiencies and helping out the users, whether the users persona is the clinician or the operations or, of course, the patient and the family as they’re going through the continuum and last, at least you want to ensure you’re translating all that into something that is executable, um, have a translation, understanding that the implementation is not technology only right that are addressing the problem you’re trying to solve, you’re addressing the vision that you have sort of enabled across the institution, and then you want to measure and look at how you’re doing in that implementation real  often and repeat. Basically, uh, there is constant tweaking and recalibrating because that changes life changes and roles change.

Q. Yeah, of course. And you mentioned Sophy previously, before we started the podcast, about change management and cultural alignment, right? Would you illustrate that with an example from your new role? What works, how does it work, and what works best? You also mentioned something interesting about measuring it—any such measures you actually use in the business enterprise?

Sophy: Yeah, I’ll use a couple of examples. Right now, our main focus is preparing for our EHR implementation. As part of this readiness, while we ensure best practices and enterprise standards in our processes, we also prioritize operational engagement. We work closely with operations to understand their needs, ensuring workflows complement and meet their requirements.

We focus on operational input regarding readiness and translating that understanding across departments. Another key aspect of cultural success is our partnership with perioperative teams. Since our organization has grown through mergers and acquisitions, we don’t have a standardized system across our 21 institutions. This presents challenges, especially in OR throughput.

Think about OR throughput—not just scheduling surgeries, but also coordinating surgeons, care teams, room logistics, pre-op, and post-op processes. We collaborated with operations to understand these challenges and explored technology solutions to optimize data and improve real-time decision-making. This turned out to be a great success. We now have significant measurable outcomes in optimizing OR scheduling and real-time adjustments.

Planning on paper is easy, but managing the complexity of multiple ORs, surgeons, and a triple-digit workforce in real-time is challenging. We successfully balanced workloads, improving clinician and patient experiences while optimizing throughput. While efficiency was a key outcome, we also increased volume and revenue. Most importantly, we brought joy back to clinicians and improved patient scheduling.

Q. That’s a great example, Sophy. Thank you for sharing that. You mentioned that Northwell has grown significantly through mergers and acquisitions, now comprising 21 organizations. Given your involvement in this process, could you tell us more about Northwell’s approach to M&As?

Sophy: Absolutely. Northwell Health is the largest healthcare provider in New York State and one of the largest employers, with nearly 90,000 employees. We have 21 hospitals—11 of which are Magnet-designated—and almost 1,000 outpatient facilities. Our workforce includes about 12,000 physicians and over 19,000 nurses. We continue to grow while investing in community education, research, and outreach.

One of our CEO’s key visions is intentional growth. We don’t expand randomly; we grow in a way that ensures integrated, continuous care for the communities we serve. This approach also applies to our M&A strategy. We prioritize synergies, ensuring that mergers align with our mission and values. We focus on contiguous growth, enhancing referral networks, and leveraging our size and capabilities to improve healthcare access and quality.

Most recently, we’ve been working on a major merger with a health system about a third of our size. While it’s not yet approved, it would be one of our largest acquisitions.

Q. That’s awesome. So, Sophy, you mentioned earlier in our conversation that there is no standard playbook for M&As and that success comes from finding complementary technology strategies. Could you share your thoughts on how mergers and acquisitions are approached at Northwell and what makes for some success stories? 

Sophy:  Yeah. I hear this a lot from our partners and customers—Northwell’s approach to mergers and acquisitions isn’t a forced takeover. It’s a very collaborative, synergetic process.

The key to our approach is thoughtfulness—whether it’s a partnership or an M&A, we prioritize cultural and value alignment. If those two things are in place, everything else becomes much easier. When you have similar mindsets and ethics, you’re already aligned on what you’re trying to achieve.

From there, we move into the business aspects. Every M&A is different because it depends on the type of deal, the initial objectives, and the long-term goals. Ultimately, the goal is to optimize and integrate the best of both worlds while learning from each other.

Our playbook starts with integrating people first—creating a sense of unity, where we operate as one team with one purpose. Next, we align on strategic initiatives, assess key risks, and map out long-term goals. We ask: What are your priorities? What challenges need to be addressed? How can we help each other move forward? These discussions help us build a roadmap for business integration.

From there, technology plays a critical role in accelerating and supporting these objectives. If there’s a low-complexity, high-impact opportunity that addresses a pressing challenge, we double down on it. That way, we can create immediate value while laying the foundation for future innovation and growth.

At the same time, risk mitigation is a top priority. We need to ensure that our infrastructure is solid—cybersecurity, resiliency, regulatory compliance—these are non-negotiables. They form the foundation that allows us to focus on investments that drive meaningful impact for both organizations.

Q: That’s great to know. And that leads us to the innovation and AI aspect of things. Sophy, no podcast would be complete without touching on artificial intelligence, augmented intelligence—any type of intelligence in today’s conversations! Looking into the future, especially regarding EHR adoption and the broader integration of AI in business, what are some things you see coming our way, and what might you be working on?

Sophy: Yeah, I want to emphasize again—and maybe it’s my bias now—that any successful AI initiative should always start with defining the problem you’re trying to solve and involving the operators in that process. We can easily get caught up in the tech itself, especially with the fast pace of innovation, and try to find sponsors and problems to fit the tools.

For AI to be successful and scalable, you really need to start with the operators in mind. And by operators, I mean the people who will be using it day to day. AI isn’t just about generative or machine learning; there’s a broad spectrum of AI that includes RPA and other technologies that we can leverage. But to truly scale it in clinical, administrative, or experience spaces, you have to go to the source.

When I talk about AI, I always remind people that AI has been around for decades. In the last five years, generative AI has taken center stage and is often viewed as the “magic” solution for everything. But we should remember that AI is much broader than just generative AI.

At Northwell, we’ve been exploring AI across multiple areas, including imaging and precision medicine, for years, and we’re now diving into generative AI. We’ve had an internal AI hub in place for about five years, focused on security and data protection, which are our most important assets. This hub allows our workforce to securely access generative AI and leverage it for a variety of use cases, all while protecting sensitive information.

We’ve also put in place a governance structure to better understand the needs of our team, identify high-value use cases, and drive innovation. One of the areas we’ve already made an impact is in administrative tasks, like using generative AI to search for information, saving time when employees need to sift through policies and documents. These small efficiencies can add up significantly across a large organization.

Q: That’s amazing! Giving time back to 90,000 people adds up to a huge impact. There are so many use cases that people don’t even realize. They might not be flashy, but they solve real problems that make a big difference in people’s daily work. As we come toward the end of the podcast, Sophy, I’d like to touch on something you mentioned before we started—the celebration of International Women’s Month.

Sophy: Oh, yes! Thank you, Rohan, for reminding me. I’d love to wrap up today by recognizing and celebrating International Women’s Month. Some people focus on just a day, but I say we should make it a whole month! It’s important to recognize the incredible women and all the support behind the agendas advocating for women. Let’s make sure we support each other, raise the bar together, and make a real impact in the world.

Lastly, thank you all for the work you do, and remember: self-care is just as important. It’s okay to take a compliment and take care of yourself, so you can give your best every day.

We hope you enjoyed this podcast. Subscribe to our podcast series at www.thebigunlock.com and write to us at info@thebigunlock.com   

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

 Q. Hi Soumya, welcome to the Big Unlock Podcast. It is a pleasure to have you here. Thank you very much, Rohit. Appreciate it that you are able to spare time for this. So Soumya, we would like to start with some quick introductions. So I’m Rohit Mahajan, I’m the CEO and Managing Partner at BigView and Demo Consulting.

We’ve been doing this podcast for a while, so it’s pretty popular with our listeners. So I’m sure they’re looking forward to understanding your thought process and, and what advice you have for them. So could you please start with your introduction as well?

Soumya: Thanks Rohit. Very nice to meet you again. I am Dr. Soumya Viswanathan. And I’m the Chief Physician Executive at BayCare Health System in Tampa, Florida.

That’s amazing. So what motivated you, Soumya, into this direction? That is my, one of my questions. And second is, what are the differences that you find between the two, let’s say, geographies or the roles that you had here previously in Massachusetts and now what you’re doing over there?

Soumya: Absolutely. So I heavy hitter on the clinical side. You know, I love clinical. My patients love me the typical clinician, but I started getting roles and opportunities to take on projects on the management side or so called the leadership side. When I took the projects on, I felt very comfortable. Then I was doing them and I started getting more projects because as you deliver on the outcomes and the results for each of the projects, people say, Oh, she’s done this.

So let’s give her more. So it ended up being that I was, uh, first I raised my hand for projects and then I just started getting them and I had some really good mentors. And the mentors trusted me, which is also important. So I circled back to them and said, you know, I like doing this, but I’m not sure do I want to give up clinical or not.

So that was the time when I decided to do MBA and MHCM just to make sure that I do want to go down this path of leadership. And it turned out that I started liking it a lot. I liked it as much as I liked clinical. So it came to a point where I couldn’t do both equally well if I spent 100 percent of my time on both of them.

So it’s 200 percent of my time. So I had to carve out and figure out which direction I wanted to go in. And finally, once I did my MHCM, I realized I really like leadership and I want to give it my best. Put my best foot forward and give it my best shot and see how well I do. And that’s what led me to taking on leadership role.

And Baycare has been pivotal because the health system is on a tremendous growth mode. We are expanding like crazy. So what also helped us in that journey is a lot of the health systems in Northeast North. I should say all the northern states through COVID  they allow their people to work remotely. And as you may have seen in the news, a lot of people gravitated or they move migrated down to southern states for warm weather.

And they could work remotely. So the fastest growing cities ended up being, at that time it was Austin, Texas and Tampa, Florida. So, the population here has grown so much that the system, and BayCare is the largest health system in the West Central Florida. So, and it is rated as one of the best in quality outcomes, patient safety, people provide clinically excellent care.

So, it became imperative that, you know, we are on a growth mode, we need to support the population that has migrated here. And I jokingly say, when people move down and move, migrate to other areas, they don’t bring their doctors with them. So we had to support, you know, we need more doctors here. That’s what helped me make the decision to make this my, my stop where I can contribute to leadership team and administration.

Big differences that I see is at least in Bay Care, I should say that, you know, Bay Care has traditionally come together as a health system with the acquisition of community hospitals. And then we set up a medical group. to move forward in expansion of the medical group. So there hasn’t been a lot of focus on academics, which is heavy in Massachusetts, as you know.

So for me, that was a big difference is okay. We need to support, we need to support our physician pipeline for the next generation with a pipeline for recruitment. So what we have done now is moving forward. I’m doing a huge. focus on building the academic mission for Bay Care Health System. We have not delved into academics, and right now we are on the run for being one of the fastest growing GME programs in the country, almost, with 650 residents who will be graduating by 2029, which means in three years we went from 24 residents to, we’ll be looking at 500 plus residents who are approved by ACGME next year, in the next year.

So it’s a very exciting time for us. I want to say academics is one big piece culturally or from a practice pattern perspective. Massachusetts and Northeast is heavily steeped in value based care and, um, the fee for service mentality is still a little bit present in some of the southern states. So we’re moving towards value and taking on more risk.

So that’s a difference I do see that the risk taking capability of physicians is definitely ramped up significantly over the past few years and at least in the region where I am.

That’s pretty cool. And, and I was noticing, uh, Soumya that, uh, you recently celebrated your 10th anniversary and, uh,

Sowmya: One of our hospitals, one, one of our 16 hospitals. So it’s St. Joseph South celebrated our 10th anniversary. And, uh, that’s one of the newer facilities we had built, which has been really, growth has been tremendous in that region, but Baycare by itself is 25 years old. As a health system.

That’s cool. And also curious, Soumya, that you are the chief physician.

Executive. Executive. What does that mean as in relation to, let’s say, a chief information officer, chief medical information officer, or a CTO? So what kind of roles do you play and where is the overlap or where is the synergy with your other?  Colleagues.

Sowmya: Yeah. So from the chief physician executive role has been evolving through many health systems where traditionally the chief medical officers would lead certain aspects of the health system such as quality, patient safety, you know, dealing with physician enterprise only in the form of peer review and clinical care.

The chief physician executive officer pretty much bridges a little bit more than that So what it does is it it requires us to have a little bit more input into operations A little bit more input into looking at financials and cost accounting and gap, you know So it’s kind of a well rounded Cmo role where you pull into tap into all the other aspects that are required for a health system To be very successful, I want to say.

So we form a very close relationship with every other aspect of our health system. Whether it’s the technology officer, informatics officer, CMIO, or the chief financial officer, the COO, we form a very close dyadic partnership with almost everybody in the organization. The CMIO and the CIO, so we do have an informatics officer and we do have chief medical informatics officer.

Work very closely with them because now that there is so much of enhancement and technology input into almost everything we do, especially for doctors to  raising the electronic health record and everything, you know, we cannot do without that kind of partnership. 

That’s awesome. That was my segway. I was going to ask you that you mentioned new care delivery models and also, you know, about patient engagement and technology now.

So how does it all come together for you? Some of your what are some of your digital, you know, initiatives? that you are, you are, you know, thinking about or you’re happy about that you have implemented? What are some of the things in the future that you’re looking for?

Sowmya: We have quite a few things, you know, electronic health record optimization obviously is one of the key areas we want to continue to focus on.

We have Cerner as our EMR, so we definitely want to make sure there is always room for improvement and how the clinicians are taking on the EMR. positives and the pros and cons within an electronic health record. So optimizing that flow. The second piece that we are working actively on is tele visits and tele health in general.

Tele health and remote patient monitoring is a big focus for us just because I already mentioned the population has grown and the access to care has been amplified several folds. So we need more visits. to be delivered to this community. The third one is AI innovation in all forms. So artificial intelligence, which is the buzzword these days and data driven, you know, a lot of data driven platforms that we strive to make sure that when we make changes that impact any workflow, that it’s backed up and validated by data.

So data driven platforms are very near and dear to us. The other most important one, I think, is the patient engagement. Bayfield is very focused on providing the right care at the right time in the right place. So we follow that mission to the T, where we want to make sure that patients Providers. So physicians allied health professionals as well as nurses are all taken care off in a similar manner.

So patients should have ease of access to care. So all that becomes very critical for us. And so patient engagement tools is another big portion that we’re looking at. And of course, you know, interoperability and cyber security come hand in hand with everything that we just discussed.

Yeah, yeah. So, Swami, you touched on a lot of things. Could you help us understand more in detail or with any examples that you might have of any digital health initiatives that you found, you know, success in the past with, you know, or that you’re moving in the direction of?

Sowmya: So, in terms of just the tools of engagement, we have engaged. So, we do a lot of  We have done a lot of pilots.

We have done a lot of phased approaches to engaging in digital health platforms.  So let me just share a few of them without mentioning specific names. So for example, we have engaged in a telehealth platform that improves the care coordination of patients. So we are working with a platform right now that actually engages patients.

And then they also have the care management or the care coordination support on the back end. So with the tools first, we risk stratify the patients on who is high risk for certain diseases and disease conditions. And then we have the care coordination team actually work with us on identifying the disease conditions.

So there is a patient engagement. There is a chronic disease management component to it. And then there is the engaging the patient through the care coordination team that we have. And then looking at, you know, how the outcomes measure out. So that is one we are actively working on. Then we also have like rehab potential, right?

So when a patient has acute hospitalization and they are discharged to home, for example, let’s say they have a heart attack, post heart attack. Oftentimes, the past would be that cardiac rehab has to, the patient has to come in. To the hospital to have the rehab done. Now we are looking at platforms that actually will engage with the patient at home so they are able to do rehab at home without having to drive around and having to take that long distance trial time for commute to come in and have the rehab option available to them.

The other piece that we are working on is early detection. So, early detection is critical. The speed to detecting certain conditions can actually change the outcome of that patient’s condition. So, how quickly do we identify a stroke in a patient? And is it a stroke mimic or is it a real stroke? We are working with a company that allows us for Accurate and early stroke detection.

That’s one of them We also have a couple of others where we have an eicu  platform Where it’s an electronic icu because we need to monitor the icu in patients, but we cannot have that many intensivists rounding 24 seven. So we have an electronic methodology to identify that. We’re looking at platforms that look at sepsis bundles, you know, so there is a whole host of conditions that they’re looking at, which are digitally oriented, that allows us to look at them.

You said what has gone well and what hasn’t, I will share with you that some of the exciting ones are. The radiology ones, the radiology digital analytics, because the radiology ones help to identify the accuracy is outstanding. It’s like they have done studies on how many AI driven platforms can actually identify incidental findings  versus a radiologist reading it or, you know, how many radiologists do you need to read X number of films? And so we are looking at platforms that look at incidental findings in the lungs, as well as lesions on the heart through echocardiogram.  So there’s a whole host of digital platforms that allow us to do this. One thing that we have to watch out for is the fatigue that can set alarm fatigue. So sometimes you have these platforms and it’s pinging away nonstop because it depends on how you set the platform. If you say that you need to alarm me when this happens and you have the metrics not correct, it will be blowing out of control and the alarm fatigue sets in amongst the end user.

So I want to say that we have had our mixed bag where we tested a few and we had to give up on a few and some of them we are many of them we are moving forward with.

That’s great to know Soumya. So is there a way that you think about innovation in certain areas and how about working with startups? Any thoughts or suggestions around those?

Sowmya: We are very open to the areas of focus are definitely driven by, like I said, the three pronged approach. You know, is this going to help our patients? Is this going to help our physicians in any way? Is this going to help our nursing team in any way? We are working with technology tool that’s actually looking at You probably have heard of this, the doctor’s dictations.

Yeah, it used to be transcription in the past. And now we are looking at a dictation modality that allows them to just have a conversation with a patient  and not have to worry about the dictation. And there is AI methodology that works on it. We have looked at a similar, we are working with another company that’s doing a similar modality for nurse driven, nurse voice is being recognized, that a nurse can walk into a patient’s room and have a conversation and not have to worry about, have I captured everything that the patient told me? So, you know, every aspect of clinical care is being looked at very closely to see, does it make sense for us to invest in this or not?

In terms of, you know, so we definitely look at the feasibility of. The patient, the physicians, the nursing, and if it helps improve the way we deliver care, we look at it more closely. The second thing that we do look at, you know, obviously there is going to be all kinds of macroeconomics that jumps into all this with, you know, funding and what is the cost and all that, but we, we weigh it very carefully.

As far as startups go, the one thing that Baycare is very open to is if there are programs that are going to deliver on improving care and help our trio team, as I mentioned, and they are willing to co develop a product with us. We are willing to look at it. So Baycare is not just going to say, well, I’m going to open up my purse strings and just, you know, invest in all this technology because there is so much out there.

So we want to make it appropriate, available for our team. But at the same time, if people are willing to co develop, we are willing to look into it. That’s fantastic approach.

Yeah, so as we’re getting close to the end of the podcast and this session here, Soumya, I would like to touch upon the subject of chat GPT, Gen AI, and all the new things which are coming our way in terms of agentic AI.

So any thoughts there or anything that you are, you know, kind of. Heading in the direction of.

Sowmya: I think it’s very fascinating. I’m waiting to see what the next generation of even chat GPT and Jenny do  because it’s mind blowing how data can be aggregated. Data can be utilized and how it can effectively help us.

But we also have to be cognizant that, you know, there is always, there could be a downside that we have to watch out for. And unless. It is fine tuned to the point where we feel comfortable, you know, all of us in the digital world feel comfortable that there is no harm, no threat that’s coming out of this.

I think we should forge ahead and move forward because that is the next generation that’s going to come our way, whether we like it or not. And, uh, it’s going to be in every industry, you know, healthcare has traditionally been. I want to say probably at the bottom of the totem pole trying to adapt and adopt technology because we always felt as a doctor, we always felt, well, technology can never overtake doctors and take care of patients, but.

When we started understanding how technology can help us drive better patient care, the adoption became easier. So we have to get to that stage where the chat GPTs of the world have to help us drive better patient care and better outcomes for our patients. Then I think the comfort level will set in.

Rohit: Absolutely. So on that beautiful note, Soumya, thank you so much for this interaction. Really enjoyed it. And, uh, if you would like to add anything, I really appreciate this opportunity. And, uh, so, so much appreciate your time too today.

We hope you enjoyed this podcast. Subscribe to our podcast series at www.thebigunlock.com and write to us at info@thebigunlock.com   

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

 Q. Welcome to the Big Unlock podcast, Mark. As you might be aware, Paddy used to do these, and I’m continuing after that. We’re up to the 150 to 160 range in terms of the number of episodes now. So it’s going pretty well. I’ll do a quick intro for myself, then I’ll ask you to introduce yourself as well. I’m Rohit Mahajan, the Managing Partner and CEO at Damo Consulting and BigRio. Mark, please go ahead and introduce yourself to the audience. 

Mark: Yeah, thank you. I’ve been on once before, probably about three years ago with Paddy. It was a great time, so I appreciate you guys having me back. I’m Mark Weisman. I am the Chief Information Officer and Chief Medical Information Officer at Tidal Health. We’re on the eastern shore of Maryland. We are a two, soon-to-be-three-hospital system, and we take care of a large chunk of the eastern shore. It’s a great place to be. Ocean City, Maryland, is probably the most familiar area in this region. Thanks for having me on. I look forward to talking, particularly about digital engagement, which is one of the areas I’d love to bring forth to our organization and help our patients and clinicians interact.

Q. That’s awesome, Mark. So could you please share with us how you got started? What attracted you to the healthcare industry segment and your role? How has it changed over the years? Please share the story. 

Mark: Yeah, sure. So I started as a doctor. Uh, if you go back to, to, to that beginning, and actually I started as a paramedic and a firefighter.

That was how, okay. When I was much younger and much stronger, I was involved with volunteer fire and rescue, and really loved it. I really loved the medical side of it and then went on to medical school and at some point got involved in in primary care and getting into data and analytics and quality measures.

It’s really where I got my start. I started moving over once I saw how dirty the data was and how much. I got more into the informatics side and eventually led to my role as a CMIO and then the CIO. I love being the CIO and the CMIO. I get to use my medical knowledge and bring the technology knowledge and say, All right, how do we make the technology better?

blend into the background for the clinicians and for the patients as much as possible so that let the people interact. That’s what we want. We want those interactions. We want people who are spending time on the harder level things, let machines do easy, repetitive, boring things so that, that the clinicians can really focus on the, on the important stuff and the patients as well. That’s how I got my start. It was really around data analytics and then more used the technology. 

Q. That is so interesting that you have both perspectives and you’re able to wear both hats in the same organization and add so much value to patient care. So, Mark, what do you think about—like you said—dirty data? That is something that caught my attention. How do you get from dirty data to clean data?

Mark: Yeah, good luck. But mostly, I think the most effective way has been getting operational leaders to look at the data. Until they can touch and feel, see it, and go, “Oh, that particular data point is wrong because we don’t do it that way. We do this other thing on the floor,” and then they realize the measurement is just totally wrong.

Without that operational engagement, I can’t know everything about how every different unit does it differently. And neither can Epic, Cerner, Meditech, or whichever. The data will always be dirty in healthcare until the operational leaders sit down, look at their data, engage with it, use it to make operational decisions, and then challenge it. They need to say, “This just doesn’t feel right. There’s no way our time to seeing the patients is that wrong.”

Well, because of the workflow, it’s not capturing something. And until you do the workflow the way the designers made the program to capture it, the data will be dirty. So healthcare is loaded with dirty data—it’s just the nature of the beast.

Q. Yeah, and I quite agree with you. This is a very interesting perspective. You said that operational people need to look at it. How do you do that at an enterprise scale, Mark, both from the people perspective and the technology perspective? If you can give us some insights into that. 

Mark: Yeah, our HR department authorized me to use tasers because it’s really effective on operational leaders. It’s the only thing that gets them to look at their data.

It is a challenge. One of the things we use is Epic, and the Epic Slicer Dicer is their self-service analytics tool. It’s really easy to use. Now, people are terrified of it at first. They’re intimidated. But once you get them to sit down and play with it a little bit, a portion—maybe 5, 10 percent—of the operational leaders will say, “Okay, I can use this tool and I can explore the data, start to ask questions, and then sit with an analyst and say, ‘Show me where this came from.'”

Then we start to realize, “Oh, how we’re capturing it—that little flow sheet row isn’t doing what we thought it should do.” The only way it works is if the senior leaders ask for data. If they ask data-driven questions, their directors and managers will go out and try to look at the data.

Otherwise, they do what they do today and don’t make data-driven decisions. It has to come from the top, with interested people who are willing to explore and experiment with data, and then you’ll start to see the ball move slowly. It’s a journey. There’s nothing quick about this.

Q: Absolutely. And what are your thoughts, Mark, on data governance? How did you put a structure to it, even though you mentioned Epic? How do you put a structure on the data governance piece?

Mark: I don’t want to mislead anyone into thinking that I’ve mastered this by any means. Let’s be realistic here. Yes, we’ve been trying for years to put in place the basics of data governance, particularly operational data governance.

I happen to have an excellent partner in finance. Her name’s Kathy, and she’s wonderful because she’s very data-driven and knows the value of data governance and how the “wild west” happens with people showing data that’s not finance-approved—particularly in finance. It’s all about the data, the numbers, and they’re data-driven. They deal with numbers all day. She’s really been a strong proponent for pushing it forward, and I partner with her.

We’re trying to get definitions for the major projects going on in the organization today. What are you measuring? How do you know if the project is successful? That’s where we start. We ask, “Okay, you’ve got this in your head about what makes it successful, but what’s the definition of that?” And we’re starting to collect these definitions. It’s just one of those things where you just get started—that’s the key piece. Start somewhere.

We then started to figure out how we’re collecting that information. It’s taking too long, so we need data stewards who are closer to the data. The world will start to develop, and it will begin to snowball. We’re still pretty raw at this, but I can see it starting. At least we’re making baby steps.

For so long, we’ve just said anyone who wants data gets data and can present it however they want. We’ve occasionally been bitten by that, and we’re finding that putting some structure in place and finding the champions—those who are passionate about it—is where it starts.

Our population health team is also very good, so we’ve started with some initiatives with them. There are other areas in the organization that aren’t as good, so I’m not starting there. I’ll go back and prove how this works in certain silos, and then we’ll work back.

Q: And Mark, we were talking before about some new Epic tools that are very easy to use and simple in terms of standing them up for patient engagement. Would you like to share some of those experiences?

Mark: There’s a new tool that’s out. Again, we’re an Epic shop, and so anytime I start to play with a new tool, I like to talk about it—especially if my colleagues get interested in these things. This new tool is called MyChartBuilder.

What it enables us to do is build a very simple one-page microsite. It’s a very static page—it might have a link or a phone number in it for people to take action. For instance, we have a new rheumatologist who just joined our organization. Well, maybe people who have rheumatologic diseases would want to know about that. Rheumatology is severely underserved in our area, as in most areas. So we’re lucky to have a new one.

I can now put in MyChart a link that says we have a new rheumatologist, but only present it to those where it makes sense using the medical knowledge we have in Epic. I can say, “Look, knowing that this doctor only sees people over 18, don’t show it to a 17-year-old. Show it to those who are eligible to see this kind of doctor.”

It’s that kind of tool where we can start to use this vast repository of data we have and actually use it to bring good education to patients. I should be showing diabetic education to diabetics, not those with some other disease. And so now we can do that.

What’s nice is that we can do this in IT. We took some of the templates to marketing and branding and said, “Look, I know your logo, we need to use it. This is what it’s going to look like,” and we take that. So when we’re building our microsite, it’s just these templates that the branding center gives us—colors we use. But once that’s set up, now IT can spin up a page in a matter of 20 minutes.

It’s a drag-and-drop website designer. I don’t know if anyone’s ever built a Wix website or one of those, but it’s that simple. These are drag-and-drop and repetitive templates you can reuse. And all of a sudden, you’ve got quick and easy tools to deploy that patients are now engaging with. You get analytics on that using Slicer Dicer—you can see patients are clicking on it when you set it up this way, they’re not clicking on it when you did it another way.

It’s wonderful to see patients engage with some of the tools that were early. This has been out for probably six months now, and we just picked it up in the last month or so. We’re starting to put these in place, and we’re just experimenting with a handful of them. But I can see this being really valuable in terms of things like lung cancer screening. We’ll just put that in front of those who qualify for the screening and not put the information in front of those who don’t. Stuff like that is going to be really powerful.

Q: That’s good to know. So, which are some of the other areas of either patient care or technology at the intersection, Mark, that you’re super excited about? Are there any new digital initiatives that you’re thinking about or seeing coming down the pipeline?

Mark: I think most CIOs are now focusing on virtual nursing and how to scale that. Most of us have done the pilots now. It’s a good thing. The nurses do seem to be responding well to it.

The technology’s in the room. They’re not bothered by it—the “big brother’s watching me” thing. No, it’s here. These are tools that are here to help you. And then the AI we can start to bring in.

Now that we have cameras and microphones going into the rooms, we can bring AI to detect when a patient’s moving out of bed. Right now, we have humans staring at screens, like little Hollywood Square screens—18 screens that they’re just staring at, saying, “Okay, is this patient moving?” It’s a very repetitive, boring job. Computers do that well.

Let’s let the computer do that work and then set off an alert. Let someone know this patient has moved out of a threshold of what we said was safe, and bring the human into the loop to correct the situation or go to the bedside.

This kind of technology is possible now because we’re really investing in virtual nursing. And, oh, by the way, there’s this AI that’s going to come with it, which I’m looking forward to working with these AI models and starting to deploy. So, I think virtual nursing, and all the benefits that come from that, is a great area that most CIOs are now starting to play in.

Q: So, any other aspects of Epic or any other tools that you’re using, Mark, in your health system that are driven by new technologies, like generative AI? Any thoughts on that?

Mark: We all talk about generative AI and some of the use cases—some are panning out, some maybe not so much. But what we’ve been discussing in our organization is the education needed about large language models—how they work, where they can be good, and where they may not be great. We also need to be careful because they could lead a doctor astray.

We have some doctors who are very seasoned and experienced, and I think they’re wonderful candidates to use a large language model because they’ll know when it’s wrong. Then, we have some new trainees who are willing and eager to use AI, but I’m not sure we trust them yet to know enough about medicine to spot potential issues. It takes intuition and experience to know when something doesn’t feel right.

So, the sweet spot for using AI seems to be with doctors who are willing, eager, and engaged to use it—but usually not the most seasoned physicians. My junior physicians are ready to try it, but they might not be quite ready yet. We’re watching and learning as we go, but we’re definitely exposing them to it and teaching them about it.

I think that’s essential for where we are now. As we start putting microphones in the exam rooms and recording conversations with patients, we can input that data into large language models to help with things like differential diagnosis or determining the next best cost-effective test to order. That’s coming—but not quite yet. I could take a transcript today, copy and paste it into a Microsoft Copilot (that’s what we have available), and ask questions about the data. That’s interesting, and in the future, it’ll happen automatically.

I could ask the large language model to develop a Python program for me, but I’m not that good at it myself. I don’t have the subject matter expertise to know if what it’s producing will launch a rocket or serve me breakfast. So, you should have some domain expertise when you’re working with a large language model. It doesn’t replace that, not yet.

Q: That’s true. Which other areas of interest, Mark, on the innovation side? How do you innovate in a health system like yours? How do you encourage innovation with physicians, nurses, or other staff? How do you bring in third-party startups into your ecosystem? Any thoughts on that or advice for fostering innovation?

Mark: It’s challenging. I’d consider us an academic community hospital system. We have residents, medical students, and fellows, but we’re not typically working with biotech startups. If we’re bringing in new tech, it’s because we think it solves a problem, and we see value in it. Sometimes, it’s from a startup, and there’s definitely room for that.

I surveyed my IT team—CIOs, I encourage you to do this. Ask your teams, “How many failures are you allowed to have this year?” Some will say zero (and those are my network guys!). I love them, but yes, correct. There should be zero failures on the network. But there should also be areas where we’re okay with experimenting—even in a network. What if we try something new, like a software-defined wide-area network instead of traditional MPLS? What if we try it in a small clinic? There won’t be any major fallout if it fails, but we get some experience.

Risk tolerance varies across teams. Most IT people are on the conservative side, favoring no failures, because they see a failure as a waste of time and money. But I try to push the team to say, “Let’s try this. It might not work, and I’ve had failures working with startups, but that’s okay.” One tool we tried didn’t work for us, but it will be successful someday. We had invested time and energy into it, but finance wasn’t comfortable with it. We moved on, and that’s the job of a CIO—taking losses and moving forward.

Advice: For other CIOs, assess your team’s risk tolerance. If your team says, “We can’t fail,” you’ll have trouble being innovative. On the other hand, if you have people willing to try, innovating while handling daily operations is hard. You must carve out time, protect it, and give it a safe space. In a community health setting, even with an academic background, it’s still tough to get daily operations to accept new pilots.

Q: I understand. So, Mark, as we’re coming towards the end of this podcast, what do you see in the next 1-3 years for your healthcare setting?

Mark: I see movement toward the cloud, and it should accelerate. Our data center has some weaknesses that would be expensive to fix. If I were to build another data center, AWS or Azure might do it better than we could, actually. So, we’re exploring that. I think we’re middle of the pack in this regard, but there are cutting-edge examples like Dr. Shafiq Robinson, who has gone all-in on AWS and done great things with Epic, or Sentara with all-Azure. Our teams are starting to get on board mentally—they see the benefits of cloud adoption, though it’s a new skill set for us.

That’s exciting. The computing power we gain will let us use data in new ways. And if we wanted to use our own large language model, I don’t know if we will in three years, but we should at least be positioning ourselves to participate in the game. Otherwise, we’ll be left behind.

Q: That makes sense. Thank you, Mark. This was wonderful. I really appreciate your thoughts, advice, and suggestions. We’ll have another session.

Mark: It’s always great to be on the show. I enjoyed the conversation—it was easy-flowing, and time flew by. If you ever need me back, just let me know. People can reach me on LinkedIn, that’s the best way.

We hope you enjoyed this podcast. Subscribe to our podcast series at www.thebigunlock.com and write to us at info@thebigunlock.com   

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

Q: Welcome to The Big Unlock podcast. It is great to have you as our guest. We are looking forward to an exciting discussion to share with our audience.

I’m Rohit Mahajan, CEO and Managing Partner for Damo Consulting and BigRio. As you may know, we’ve done over 150 of these episodes, and I believe this is our 152nd episode of The Big Unlock podcast. With that said, would you like to introduce yourself?

Jeremy: Absolutely. First of all, Rohit, thank you very much for the opportunity to speak on The Big Unlock podcast and to all the listeners out there—I appreciate it.

My name is Jeremy Cauwels, and I serve as the Chief Medical Officer for Sanford Health, based in the Upper Midwest. I have been in this role for roughly the last five or six years. Before that, I worked in direct patient care as a hospitalist at the Sanford USD Medical Center in Sioux Falls, South Dakota, where I still currently live.

At Sanford, we provide care for roughly 425,000 lives from a health plan standpoint and 2.4 million lives from a broader patient population perspective. We cover a large geographical area, stretching from Wyoming in the west to Wisconsin and even the Upper Peninsula of Michigan in the east. Our largest medical centers are primarily located in South Dakota and North Dakota, both affiliated with the universities in those states.

Recently, we also expanded through the acquisition of the Marshfield Clinic, adding additional clinic sites in and around Marshfield, Wisconsin. This has been an excellent addition to our system.

Sanford Health operates 56 hospitals, over 270 clinics, and 144 senior care communities. Currently, we have 4,500 physicians and advanced practice providers.

For perspective, I used to say that we covered a landmass the size of Texas. Now, we are even larger than Texas.

Q: Wow, that’s amazing. And in the rural setting too, Jeremy, so that makes it even more challenging in terms of being able to reach the patients and serve them in such a setting, right? Where you’re covering such rural areas.

Jeremy: Absolutely. If you think about the Dakotas, western Minnesota, and northern Wisconsin, all of those areas are known for relatively small towns and communities—lots of open space between people, generally farming or ranching communities.

So, it is not unusual for us to deal every day with patients who may have to drive an hour or two hours to see their doctor, and potentially even farther to see a specialist.

Q: That’s amazing. So, Jeremy, please tell us more about how you ended up on the technology side of things. You started, as you said, as a physician and were practicing. What attracted or motivated you to this side of the house?

Jeremy: For me, it was really about how we reach patients. When I stepped into this role, I wanted to quickly understand what technology could do to help us overcome the longstanding challenges of healthcare access in the Midwest.

What we know is that many of the counties we live and work in are considered healthcare deserts. Even more of them are mental healthcare deserts. It’s impossible for many families to take a full day off work to drive to the doctor’s office, have a 15-minute appointment, and then drive back home—especially for single-parent families or those where making ends meet every day is the primary concern.

What got me into this was the idea that we could provide virtual care to patients and meet them where they live. Rather than the old phrase, “Your doctor will see you now,” we like to think of it as, “The patient will see us now.”

Q: That’s beautiful. That’s a great flip. So, talking about all things digital—you mentioned telehealth and telemedicine as well. What are some of the digital initiatives you’ve worked on in the past, and what are you looking at for the future? Jeremy, can you share how this digital front door or digital approach is likely to increase access for patients?

Jeremy: Absolutely. Thankfully, Sanford has been blessed with philanthropic support dollars that have been earmarked for improving our digital health footprint. With that, we’ve been able to expand. We actually just opened our virtual care center, a standalone building outside of our hospitals focused on using technology to better reach our patients.

Inside, you’ll find everything from 3D-printed models that physicians can use to understand anatomy before they have to work with it firsthand, to virtual connections that allow physicians to see patients remotely. More importantly, as an educational organization, we have nearly 350 residents and fellows at any given time. So, having the ability to teach them “webside manner” instead of bedside manner—getting them comfortable interacting through a screen, just like you and I are talking today—is critically important.

We also have an innovation hub, a safe space where we can test digital tools in ways we wouldn’t be able to during an actual patient encounter. Alongside that, we house a significant portion of our clinical operations for virtual care in the same building. That way, if something isn’t working as it should, IT resources are right there to ensure smoother operations. They’ve done a wonderful job of putting all of these resources at our fingertips in one location.

Q: That’s awesome. And, Jeremy, in any podcast these days, it’s impossible to avoid the topic of AI and GenAI. So, of course, I have to bring it up—what are your thoughts on AI? Have you been using any traditional AI, and now more generative AI, in your innovation initiatives?

Jeremy: Absolutely. One of the things we’ve focused on with AI is making physicians more efficient in finding the information they already have access to—if only they had unlimited time to pore over the electronic medical record.

For example, we’ve published research with the American College of Gastroenterology showing that our AI can identify 85 different factors that affect an individual’s risk for colon cancer. It can literally score you and explain why my risk for colon cancer might be different from yours.

The upper Midwest has a higher risk for colon cancer, and it’s also an area where screening rates are lower than they should be. So, we’ve been pushing forward, gathering the evidence base we need to roll out a prospective study that proves this AI model works. The goal is to help physicians by giving them real-time insights—when they look at a patient, the screen next to them might say, “Jeremy is at higher risk, and we may need to be more aggressive with screening.”

Another challenge we’ve tackled is the shift in screening guidelines. A couple of years ago, the U.S. Preventive Services Task Force lowered the recommended screening age for colon cancer from 50 to 45. In the Dakotas and the upper Midwest, that change meant that overnight, 100,000 people who didn’t need screening yesterday suddenly did today.

So, we had to think beyond just colonoscopies. How do we reach people who may not be able to come in? One way is through stool-based testing that can be done at home. And as you can imagine, whether someone lives in Howard, South Dakota—a town of 848 people—or anywhere else, they’re used to getting Amazon deliveries. They know how that works. So, if we can put a box at their door that helps them stay on top of their healthcare, we’re moving them forward.

We’ve worked hard to bring all these programs together—not just for patients at normal risk but also to identify who’s at slightly higher risk versus significantly higher risk. Because of who we are and the extensive data we have on our patients, we can personalize care in a way that wasn’t possible before.

Q: I see. Just a curious question coming to mind, Jeremy—do you see a very diverse patient population speaking many different languages, or is it pretty homogenous? How does it look when you do population health analytics?

Jeremy:  Interestingly enough, we have more diversity than people expect in the Upper Midwest.

The largest ethnically diverse group is Native Americans. In some of our regions, the three counties surrounding some of our hospitals are entirely Native American land. In South Dakota alone, three of the poorest counties in the United States are on Native American land. So, those areas present unique challenges that we have to work through.

I’ll also say that one of the communities we regularly serve speaks 57 different languages because a large portion of that town and county is supported by the meatpacking industry. We have several areas like that, where different ethnic pockets of people absolutely need to be served and cared for—regardless of their ethnic background or the language they speak.

The key question is: What is the best way to reach them? How do we find the approach that works for them?

Q: And again, a curious question—one of our clients is one of the largest telemedicine companies. We saw a huge spike during COVID in telemedicine visits, up to 8,000%. But now, people seem to be going back to normal, and COVID is starting to be forgotten.

How has your experience been with telemedicine visits, given the geography and rural nature of your area?

Jeremy: So far, we’ve saved our patients roughly 33 million miles of driving. To put that in perspective, that’s about the closest distance Mars gets to Earth during its rotation.

In addition to that, we’ve now done over 800,000 virtual visits. Twenty percent of our mental health visits every month are still virtual—one in five patients still choose to see their mental health provider virtually.

Some of that may be because they simply can’t find a mental health provider in their area. But for others, it’s about privacy. I drive a blue Ford pickup, and in some small towns, there are folks who wouldn’t want their blue Ford pickup seen parked outside a psychologist or psychiatrist’s office. Stigma still exists, and giving people the option to see their doctor in a way that makes the most sense for them is extraordinarily helpful.

Q: That’s great to know. One other thought I wanted to discuss with you, Jeremy—there are three aspects I’m trying to think about together: What are patients looking for? What are caregivers looking for? And what are clinicians looking for in some of these digital approaches you’re taking?

Jeremy: Absolutely. So, from the patient’s perspective—you can see over my right shoulder, I have three children. They’re much younger, and I’ll tell you, my kids haven’t gone to an in-person medical visit in the last year, except when they needed a sports physical.

If they feel ill, they set up a virtual visit. If they have a follow-up with a specialist, they do it virtually. What’s great is that it allows flexibility for both the specialist and the patient. My kids have even had medical visits while eating breakfast at the kitchen table. That concept would be unheard of to my parents, who would much rather drive to the doctor’s office than try to interact over the phone.

So, from a patient’s standpoint, there’s definitely a shift happening.

From a clinician’s perspective, we’ve been lucky enough to implement AI-driven automated dictation technology with ambient listening. One of our busiest family practice doctors recently switched to it—he simply sets his phone between himself and the patient, and he no longer has to look away at the computer screen.

Not only are his notes completed by the time he finishes his scheduled day at 5 PM, but he told me just the other day: “I finished my day at five, my notes were done by 5:15, I made it home for dinner with my family—which almost never happens—and I even had enough extra time to take my daughter to buy her first used car.”

That’s amazing. Ambient listening is definitely proving to be one of the top use cases for generative AI. I completely agree—it’s only going to grow from here.

People always talk about the “good old days,” whenever that was for them. But many doctors remember a time when they didn’t have to be attached to a keyboard, constantly documenting. This brings us back to that—where the most important thing is the interaction with the patient.

Whether it’s through a screen like this or one-on-one in a room, it’s a much more satisfying discussion for both the doctor and the patient.

Q: Yeah, that’s amazing, Jeremy. What are some of the digital tools or new approaches you’re using for taking care of patients at home, including remote patient monitoring and home-based care?

Jeremy: Yeah, so one of the things we rolled out in 2023 was a text-based patient monitoring tool.

We can use it for common diagnoses like diabetes, heart failure, and depression. We also use it for patients who have been discharged from the hospital to ensure they receive rapid follow-up and scheduled interventions. The technology allows patients to provide feedback without having to call, wait in line, or book an appointment.

I’ll share one example. We had a patient who came into one of our emergency rooms for depression. It’s always heartbreaking when someone is in such distress that the ER becomes their only option, but unfortunately, it happens every day across the country.

After discharge, we sent her home with this monitoring tool, and about a week or two later, she responded to a mood scale with a score of one out of ten. That immediately set off an alarm for us. We called her back and found out she was a single mother, overwhelmed by life’s challenges. She had already written a suicide note and was planning to end her life.

Because of this tool, we were able to intervene, get her the help she needed, and months later, she and her young family are continuing to grow and thrive.

Q: That’s an amazing story. As we come to the end of our conversation, Jeremy, any other thoughts you’d like to share with the audience? Any news or new initiatives you’re focusing on this year?

Jeremy: Sure. I’d like to expand on what I just mentioned about mental health. Many places across the country are what I’d call “mental health deserts.”

In our region, about 95% of the Dakotas—95% of our footprint—is in a mental health desert. That means there are limited providers and significant challenges in getting timely psychiatric care.

To address this, in addition to the virtual visits I mentioned earlier, we’ve implemented virtual psychiatry consults in our emergency rooms. If someone needs to see a psychiatrist and they’re already in an ER—which is never an ideal situation—they often have to wait until morning, or worse, wait for an open psychiatric bed, which could take days.

Now, instead of waiting, we can connect them with a licensed psychiatrist virtually, right there in the ER, even if the psychiatrist isn’t in the same city or state. That immediate access makes a huge difference in getting people the right care when they need it most.

Q: That’s amazing, Jeremy. It’s incredible that technology enables us to do this now. Any closing remarks?

Jeremy: I just want to say thank you. Thank you for allowing me to share a little bit about Sanford and how we continue to reach out to our patients. Despite the distances, we’re doing everything we can to bring them closer to the care they need.

We hope you enjoyed this podcast. Subscribe to our podcast series at www.thebigunlock.com and write to us at info@thebigunlock.com   

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

Q: David, welcome to the 150th episode of The Big Unlock Podcast. Padmanabhan had done a lot of the previous episodes of this podcast and I’m carrying on his legacy.

So, David, would you take a few minutes and like to introduce yourself to the audience and talk about yourself and the health system as well where you have been working? 

David: Yeah, sure. Thanks a lot for hosting me. It’s an honor to be here with you this afternoon.

I’m David Berger. I started out as an academic surgeon and surgical oncologist. I did my general surgery training at SUNY Downstate and a fellowship in surgical oncology at MD Anderson Cancer Center in Houston, Texas. I initially thought I would become an academic surgeon—maybe a surgical oncology division chief, chair of surgery, or even a dean someday—but my career trajectory shifted due to unique opportunities.

Early in my career, I undertook a management role as the Chief of the Operative Care Line at the Houston VA, the Michael E. DeBakey Medical Center. It’s the largest, most complex, and busiest VA medical system in the country. Around that time, as part of the sandwich generation, I was also taking care of both my children and my parents. I realized how difficult it was to navigate the healthcare system. If it was challenging for me—someone who knows the system and has contacts—I couldn’t imagine how hard it must be for those without the same resources.

This experience shaped my career goal: to make healthcare simpler. The healthcare system is extremely complex, and I saw the potential of digital tools to transform care delivery, making it more accessible and effective. While at the VA, I implemented sophisticated digital health tools. One notable project involved real-time location systems (RTLS) for managing our operating rooms. We reduced turnover time between cases by nearly 50% and achieved a 95% on-time first case start rate—remarkable for any healthcare system, not just the VA.

Building on this success, I moved to the private sector as Chief Operating Officer at Baylor St. Luke’s Medical Center. There, we implemented machine learning tools to predict which patients were at risk of sepsis-related decompensation. By intervening early, we reduced sepsis mortality by almost 50%. This was back in 2014, well before the recent wave of AI publicity, but it reinforced my belief that digital health, AI, and machine learning are poised to revolutionize healthcare.

After Baylor St. Luke’s, I returned to SUNY Downstate, where I had completed my training, to serve as the Chief Executive Officer of University Hospital at Downstate. I started in September 2020 and recently left to focus on my passion: digital health and artificial intelligence in healthcare.

Now, I advise early-stage startups, participate in advisory boards and venture studios, and am about to become an LP in early-stage venture funds supporting digital health companies. That’s a little about me and my journey.

Q: That’s really great to know, David. It’s fantastic that physicians like yourself are taking on this journey because your deep domain knowledge can drive meaningful change in digital health.

I also learned that you’ve been an entrepreneur. Could you share a bit about your entrepreneurial journey and the kinds of software or digital solutions you worked with?

David:  So, about 10–12 years ago, I was approached by an early-stage startup company based in Canada. They had come across an article we published on early warning signs for readmission after colon cancer surgery.

We had identified at least 10 early warning signs and developed a machine learning algorithm to predict who was at risk of being readmitted. This software company wanted to integrate our findings into their tool. We conducted a couple of successful pilots and started discussing a long-term relationship. The idea was that we, as clinicians and researchers, would provide the intellectual property to power their software. 

But we thought they were undervaluing what we were bringing to the table. So we actually went to Baylor College of Medicine, and they spun us off as a company, as our own company, from Baylor Technologies.

I learned a lot from trying to start my first company. Not all the learnings were good, but they were important.

What I learned is, one, if you’re going to start a startup, you have to devote all your time to it. You can’t do it on the side. I was heavily involved as a clinician and an administrator, and I was trying to do this on the side.

Second, you must have alignment of your board. We had five board members—me, two from Baylor, and two from the company that was helping us on the IT side. Well, the people on the IT side and the people at Baylor College of Medicine were diametrically opposed on the direction, and we got stuck and couldn’t move forward.

So after about running through a million bucks, the company died. But what’s interesting is that there are a couple of startups just getting going with the same idea we proposed and were trying to move forward 10 years ago.

So, the idea was the right one, but the alignment was poor, and I wasn’t committing full-time to it. Those are really important lessons for anyone trying to start. 

Q: Great lessons learned there. Yeah. And then, David, you were talking about how AI is, you know, going to be changing the landscape, and you have a certain way of looking at it, especially for healthcare systems. So we’d love to learn your thoughts about that—about AI, GenAI, and where you think it is going, and how one should, you know, kind of embrace it and adopt it to get more value. 

David:  So I am extremely excited about the potential for artificial intelligence to help us provide healthcare because there are so many repetitive processes in healthcare that are being done by people that probably can be done by technology.

When I think about a health system—and, you know, I was running a hospital—about the different places where artificial intelligence could have a major impact, I break it down really into four different areas. This is general; there’s overlap.

So the first one is obviously back-office functions—things like revenue cycle, coding, billing, documentation, pre-authorization. All those things that have to do with revenue cycle.

Then I look at the front end or access—giving patients the opportunity to interact with a provider, giving them the opportunity to schedule, how they’re going to pay for their healthcare, et cetera.

And then on the care delivery side, there are things that help make care easier to deliver, and then there are things that actually help provide care.

So let’s break down those two things. When I say make it easier to deliver care, I’m talking about things like artificial intelligence scribes or ambient listening, ambient dictation.

When I talk about things that help actually deliver care, I’m looking at adjuncts to help read X-rays. So one use case that’s fairly well-developed is the issue around mammography. An important fact and something that radiologists look at in mammograms is breast density.

Breast density sometimes predicts further cancer down the road. Radiologists are really bad at quantitating breast density, and there’s a total lack of correlation from one radiologist to another. But using artificial intelligence, you can improve the ability to determine breast density to almost 95 percent accuracy.

So that is a place where artificial intelligence could augment care and improve how care is delivered and the diagnostic accuracy. That’s what I mean when I say help facilitate care versus actually help deliver care.

Q: Understood. And David, in particular, just for a moment to segue into all the new generative AI technologies that are coming our way. It’s not just about text; it’s also about so many different forms of care and media that it can transform. So any thoughts on where you think generative AI might play a larger role or be more conducive in the healthcare setting?

David: Yeah, so in terms of generative AI, one of the solutions we implemented is something called AVO. And what AVO does is ambient listening—it helps physicians to write the note. But that’s just part of it; that’s not really the full generative AI component.

What it then does is pull relevant information from the electronic medical record to create a real functioning note. It puts in front of the clinician a differential diagnosis, as well as the clinical pathways related to that diagnosis. So yes, it’s ambient listening, which is important, but it’s also natural language processing. It helps to generate feedback, a differential diagnosis, and then the proper treatment pathway for that patient.

It also presents the note in a way that facilitates coding, billing, etc., for the hospital or system to get reimbursed. That has been a game changer for our patients.

Thinking about implementation, though, the implementation of any new tool is really, really challenging. What we found with the ambient listening and ambient dictation is that there was a different level of adoption between specialists like surgeons and primary care doctors. Why do you think that is? I’ll throw it back at you.

Q: I couldn’t even guess that. First of all, I’m thinking to myself, is it the primary care physicians who adopt it more, or is it the—yeah?

David: It’s the specialists and the surgeons who adopt it more readily. For them, a note is something they have to do; it’s not really what they want to do. They want to focus on their operation, their procedure, etc. So, for them, the note is more of a barrier to doing what they really want to do.

For a primary care doctor, one of their primary goals is to create a detailed note. So, for them, the nuances around creating the note are really important. Whereas for a surgeon, they don’t care as much if it’s perfect—they just want to get it done. So, the adoption was much quicker with surgeons than with primary care physicians.

We also implemented it in the emergency room, which is a tight space with a lot going on. Some of the ambient listening got distracted because of other noises in the environment. We had to figure out ways to ensure that, during the interaction between the clinician and the patient, there was as little ambient noise as possible. But we worked through that, and the adoption was incredible.

People have talked about AI replacing physicians. Five years ago, someone came out and said that within five years, there wouldn’t be any need for radiologists. Well, clearly, that hasn’t happened. But I see AI being used as an adjunct to clinicians—helping them to be better at what they do, not just in terms of efficiency, but also in improving accuracy in care and diagnoses.

I think clinicians are going to become partners with artificial intelligence. Another area where I think AI, generative AI, augmented reality, and virtual reality are going to have a huge role is in education.

Even in teaching within the operating room. Right now, the way you teach in the operating room is by working with a resident across from you. Over time, you give them more and more experience and freedom to conduct the procedure. But think about this: if you have really good augmented reality, you could have them work with a headset in an environment outside of the operating room to hone their skills in a space where there’s no risk to patients.

So, there are amazing opportunities for augmented reality and virtual reality, not just in education, but also in surgery. For instance, I used to do a lot of liver surgery. The liver is a three-dimensional structure, but the inputs—like where the vessels are or where the tumor is—come from 2D images. These are from CT scans, MRIs, or ultrasounds.

Then, once you’re in the operating room, you’re trying to reconstruct that 2D image in your mind into a 3D picture, relating it to the organ in front of you. It’s challenging, but you get better at it with experience. Now, with augmented reality, you can actually see, right in front of you, where the tumor is in relation to other structures within the organ.

This has been really well-developed in neurosurgery, but it’s an exciting opportunity for AI, virtual reality, and augmented reality in other types of surgery as well.

Q: Yeah, great example, David. So, my last question is about your new venture or the new role you’re going to be taking on soon, as you described earlier in the podcast. Which aspect are you more excited about? Because you’ve seen the startup side of things, and now you’ve been in a large health system. Where do you think you’ll be spending more of your time and adding value?

David: So, I think healthcare is slow to change from the inside. A number of the bigger systems have developed innovation labs and are trying to move the field forward, but I think a lot of the change is going to come from outside—from companies outside of healthcare.

What I’ve decided to do is move away from running a healthcare system or hospital to being more involved in the digital health and AI ecosystems. I think the way I can best contribute is as an advisor to early-stage companies within this space, but also as an advisor to investors and venture companies looking at which technologies are actually going to make a difference.

Since I have the perspective of both a clinician and an operator within the health system, I think I bring a unique lens to identifying which digital health solutions are really going to make an impact.

Q: Awesome opportunity, David. I’m wishing you all the best in this role? And then would you have any other closing thoughts for our audience? 

David: I think we are at an inflection point, between technology and the desperate needs within the health system. The costs have risen dramatically, people do not have adequate access and there are huge problems within our health system. I think we have opportunity right now to make a difference. 

To move healthcare forward and to improve the healthcare system within this country, I encourage people who are thinking about careers within healthcare to think about the innovation side and the digital health side, because that is really going to have a huge effect and move the needle. 

We hope you enjoyed this podcast. Subscribe to our podcast series at www.thebigunlock.com and write to us at info@thebigunlock.com   

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

 Q. Please talk about a little bit about your business and your journey in the healthcare sector. 

Zafar: Thank you for having me. Pleasure to be here. I am Zafar Chaudry, I’m the Chief Digital AI and Information Officer at Seattle Children’s. I have been here for seven years. Seattle Children’s is a pediatric health system in the Pacific Northwest in the United States. We have 47 sites in Washington, Alaska, Montana, Idaho. 

In terms of my journey to where I’m at now, it’s been a very convoluted one. So, I’m a recovering physician. I started my career as a doctor. A doc practiced for a X number of years and then very quickly defected to the dark side.  Joined technology in the early 90s when clinical people weren’t necessarily doing IT stuff and I thought this might be a good idea and then went through that journey, did some dot com before it went dot bomb and then leadership roles in health IT and I’ve had many over the last 38 years, uh, in different parts of the world, UK, US, Middle East, Asia pack. 

So I’ve, I’ve seen a lot of healthcare delivered in different ways. And I work now in pediatrics because I have worked in pediatrics prior to this. And I like working in pediatrics because There isn’t a day you come to work where you have to think about why you do this job because protecting kids and helping them get healthy is an easy job to do. 

So that’s why I’ve been here such a long time, hope to continue the good work. So that’s sort of my very quick high level on how I got here. 

Q. So Zafar, tell us more about how do you think about innovation at your system and how do you involve other stakeholders and people in that journey?

Zafar:  Innovation is always an interesting one, right? Because I always say to people that first thing you have to do in any healthcare environment is make sure that the basics work really well. 

Because doctors, nurses, allied health professionals, patients, parents want your basics to be good. Your infrastructure has to be solid, your end user compute experience has to be solid. So it’s a parallel journey. So you do the, what I like to call the lights on, doors open very well, focus on that. The innovation piece comes in parallel from what you learn in that journey. So a lot of times you can take what you learn from the basics and then figure out, well, how do I make this better? How do I automate? How do I apply technologies that would change the way in which we do things? At Children’s, our digital strategy isn’t a strategy that I come up with. 

I have a group of parents and patients. We meet every month and they tell me. What we should build, why we should build it, what they need, because fundamentally, when you’re doing innovation and new developments, you can’t do those in isolation. You have to have stakeholder engagement. So whether you’re talking to a group of doctors about what is a problem they need solving to patients who tell you, They need a way to find locations in your facility. 

Those ideas then come together for you to decide what your next level of innovation is going to be. Right. Whether it’s building an app, whether it’s using an automation tool, or whether it’s using, you know, the dreaded AI, which everybody talks about. Of course, of course. Those are all things that you have to figure out. 

Yeah, by listening, learning, teaching and collaborating, and that’s what we do very well.  

Q. That’s great to know. This is very interesting that you have a group of parents and even, you know, patients. meeting frequently to kind of brainstorm on what the changes or the ideas might be. So Zafar, would you like to talk about anyone or one in particular, let’s say that you think was a good example of such an innovation project?

Zafar:  So I’ll give you a very good example. So in one of the discussions two years ago, actually, one of the patients, and what’s interesting about kids. Is the average 12 year old kid is a lot smarter than me when it comes to IT, right? They understand it. They grew up in it. I was having a conversation with a group in that group and the conversation came around. 

One of the kids said to me, well, he didn’t think we were doing a very good job because when he’s here for a really long period of time, there’s nothing to keep him engaged, right? And I said, well, that’s true. Okay, so what do you need? And his idea was pediatric hospitals should have a form of gaming to keep kids engaged. 

And so from that simple idea, yeah. We are the world’s first organization to have our own Minecraft server, and we built our entire hospital in Minecraft. And we just launched that eight weeks ago on Twitch. So you can come to our hospital as a child, you can become a character in our Minefield Minecraft experience. 

And you can do everything that you can do in Minecraft, and we partnered with Microsoft and others to make that happen. And that’s all live. So that’s an example of innovation that I didn’t come up with. Yeah. A child suggested. Yes. We took the idea and we built upon it. I made something amazing. And you actually can see this whole launch on YouTube. 

You’ll be able to see it. So that’s awesome. That’s to me is real innovation. Don’t come up with an idea yourself and think it’s amazing. Let somebody tell you what you need. And because it took us about two years to build it and get it ready. Lots of kids have been involved in helping us design, build, test. 

Oh, and I’m not a gamer because I’m old, but I can tell you that when I play Minecraft with the kids on launch, you know, I was killed in seconds to do this stuff, right? But they know it. I mean, they live and breathe it. They’re building things down. So I think that’s how you innovate. You find out what people really are passionate about. 

And Put some really smart people together, figure out whether that has real value. Now, of course, when I go and now talk to parents and patients about this innovation, we’re getting huge amounts of positive feedback, right? I talked to parents who kids have had serious surgeries who are telling me that by using this environment, their kid was able to manage through the pain, right? 

That’s huge. That’s huge. Absolutely. And gaming therapy is the whole area. So my eyes were open to that. We jumped on it. So that’s just one example of how stakeholder engagement. Yeah. Get you to an idea. You can get you to something workable, but you can pass through to a go live. That’s hugely successful. 

Q. That’s awesome. That’s awesome. What I’m also curious to learn from you Zafar is that when these ideas bubble up and you know that you have to spend basically time, resources, money behind these initiatives to make them successful, how do you filter or how do you allocate the funds? 

Zafar:  So we obviously nobody has unlimited funds including us. You do have to do a prioritization exercise, right? But when you’re looking at prioritization and how you allocate funds, you look at key things. Does it affect patient safety? Does it improve patient experience? Is it a quality issue? Is it just an operational issue that needs to be solved? So you set up a set of criteria, but you don’t use those criteria against the list of priorities by yourself in isolation, that’s also a stakeholder engagement process. 

So we have to include our clinical teams and our non clinical teams and ask them, would they rank these things higher? In terms of this gaming initiative, for instance, this was kind of different. We do assign some funds to what I describe as RD. So because it was something that hadn’t been done before. I didn’t know if it would actually work, but that fell under experimental R& D. 

And I do allocate some funds every year for experimental, because I think it’s very important to be agile and it’s very important to be able to do something well or fail fast. And learn from that and then improve. So this type of project would have fell into that category. Other basic projects would fall into the bigger prioritization matrix, patient safety, all of those things. 

And then based on the money you have, you get your list and then there’s a cutoff point, right? So if you have a list, if I look at AI as an example, we have a list of 300 things that people want to do with AI. And we only have funding for maybe the top three. So we had to do a big prioritization piece of work to make that viable. 

And then we’d pick the top three items. to fund and test in that sort of particular process when it comes to AI initiatives as an example.  

Q. That’s great. So talking about AI, uh, Zafar, I know that you have probably been on the AI journey for some time now. And of course, the Gen AI wave is coming at us fast and furious. Things are changing at a very, uh, So walk us through how you’re dealing with this change and how you have kind of set up the infrastructure for success.  

Zafar: So everybody has to look at AI. It’s not going away. So you have to put some focus on it. The way we looked at it was the first thing in any step is to educate people. 

So we have made AI training mandatory. So every year there is a module that you have to take that explains AI to you. It’s pros, it’s cons. It’s pitfalls and people then take a test and they pass the test and then they, that’s their mandatory training for the year. In addition, we’ve put together an AI policy that has been ratified by the board. 

So everybody knows what the do’s and don’ts are of this technology. Third step is we have an AI review board that has multiple stakeholders from different domains. And that panel meets to review any AI request that comes in. Not only for funding, but it also reviews it for safety. It reviews it for the technology that somebody wants to use to make sure it’s safe to make sure that data is not lost in any way. 

Yes. And AI is an evolution, I think, not a revolution. I think we’ve been using AI, most people have for a long time. It’s gone from automation processes to, you know, You have a small data language model that you’ve applied algorithms to, and now as you get to Gen AI. You have a much larger language model, a much larger database, and therefore, the bigger the data feed, the better the outcome will be. 

And so we’ve evolved through all of those stages. And yes, we’re now looking at, you know, what does gen AI, we have lots of access to more data points. But you have to protect the data, you have to do all these things, you have to make sure nothing gets out. So that’s the review board’s process. If it’s approved, then we will build it or partner. 

To build it to get to prototype because I think with every AI you have to prototype and then you have to test heavily. So to give examples, Seattle Children’s is very well known. You know, we’ve been a top 10 Children’s Hospital for 30 plus years and we’re very well known for our clinical standard pathways of treating certain conditions with kids and we’ve documented all those pathways and over time those pathways are now disseminated to different organizations even across the world and they use them as the standard way to treat conditions. The problem is, you know, It’s hundreds and hundreds, hundreds of PDFs. 

Yes. So the old way of looking at how to treat a patient using a standard pathway was to A, find the relevant PDF, then read it, and then figure out what are you going to do. Right. Really long winded process. So we decided, well, how can you make this, uh, a process where you can just use natural language and ask the question, how should I treat a patient with these symptoms and see if we could get the answer. 

So we did, we took all of our material and we put it into the AI and the AI obviously read it and tried to understand it. Then we put a series of clinicians To test it. And so now we’re at a point where you can actually ask the A. I. The question. I have a kid with cough with these symptoms. What should the treatment protocol be? 

And it will find the answer. It will tell you what to do, and it will reference it back to the document. So it’s instantaneous, right? It’s not, look at me, I’ll come back to this in 30 minutes after I read a whole bunch of documents, right? And it’s evidence based because it’s only based on our evidence, which is all validated evidence. 

So we’re in beta phase and it’s working very well. We’ve had 15 teams of people look at this and that’s going to revolutionize how quickly care can be provided. It’s also revolutionary for training new docs because they’re learning and they want to ask a lot of questions so they can learn about different conditions and how to treat them. 

It will avoid them reading thousands of pages of documents. But just going to what they need to know, so that’s just one example of how you can, but that was through the review board, built a prototype model, and that’s with Google on Gemini, and then we are testing it once it’s finalized and baked to be safe. 

Yeah, it will launch it for all of our clinicians. And that will be a huge win because it will give us speed of treatment whilst it’s still safe, right? Of course. Those are all the keys of biggest worry you have in May Isaac to hallucinate. Yeah. But in this scenario, because the language that you’re feeding into it, the data is restricted to our validated data only. Yes. It has less likelihood to hallucinate because it’s pointing back to the reference document.  

Q. Great. Yeah. That is, I think the way to go. In fact, at BigRio, we have an accelerator of which does such a thing using, I’m using a technical term here, Zafar, but I think in the audience, many people know this already, the RAG  techniques.

So this is a fantastic use case that you have there, you know, congratulations on this one. So Zafar share with us any other. Key initiatives on AI or Gen AI that either you might be looking at in the near future or you think other healthcare organizations might benefit from if you’re looking in the crystal ball, you know, in the near future, short term and long term future. What do you see?  

Zafar: I think in this particular model of Gen AI, the sky’s the limit. So for us, the next thing we’re testing already is. How do you, so when a patient comes, we send the patient home, we give them discharge instructions. This is how you’re supposed to take care of yourself after you leave. The challenge is in a multicultural society, not everybody is, primary language is English and what we found here in Seattle is. 

Yes, English is predominant, but so is Spanish, so is Somali, so is Ukrainian. So we were still giving people discharge instructions in English. So we’ve done the same thing. We’ve built a model in AI that can take these instructions, accurately translate them into the language that you want, and then we’re able to give the patient the right instructions in the right language. 

That will be a huge win because many patients aren’t primarily English speaking. Yes, it seems like a simple use case, but we were failing because we were giving people instructions in English. They weren’t following the instructions. The problem is if you don’t follow the instructions, there’s a high likelihood that within the first 30 days, you’ll come back and come back. 

You could be readmitted. That’s not a good outcome. It’s not safe. So we’ve done that same process design prototype test. It’s in beta, and it’s working very well. And once we fully tested it, that’s another one that we could launch. And actually, that’s not even a specific use case for us. Anybody Yeah, could do that because we are unique in the fact that we are treating patients who have multiple languages, right? 

Every region in the country has that. So that’s just another way of looking at it. But these are all prioritized things. Everything, of course, in AI is limited by the cash that you have. Yeah, some initiatives. Can be inexpensive, but many are very expensive to launch more of an invest to save scheme. Yes, can’t immediately get gratification and savings and AI, although many people tried to tell you that’s the case. 

It’s not the case. That’s true. But you have to be very careful in what you invest in and then you see what that return could be over a period of time. So you need, you need a lot of patience. Yes. Obviously some tech companies will want to tell you that launch this and immediately you will see benefits. 

You don’t always immediately get the cash benefits you need to pay for ongoing. So what I like to say to people is AI is definitely the way forwards. It is. Revolutionary and how it will assist people to work in health care in the future and scale faster our services in health care, but it is easy to launch is very hard to sustain. And that’s the big takeaway for me is I can do 15 more AI launches. Right. Within weeks, but they won’t sustain because what everybody fails to remember in any technology world, it’s about the people and process and change management is really important. The key actually. You can’t have an AI because think about the fear of it. 

So I want to do an AI that translates discharge instructions. I think it’s a good idea. We’ve tested it. It’s a good idea. But the change management for that is assuring the people that we have that somehow it’s not just going to take your job. So even though we will give you a printout if that’s what you want in the language of your choice, that doesn’t take away from the nurse Who still needs to tell the parents and the kid what they need to do to take care of themselves at home. 

Exactly. It’s not that we’ll miss that step altogether and just hand you this paper and say, good luck. Of course. But people immediately think, Oh my God, my job’s going away. My job is going to be minimalized and they’re going to reduce all these people. But we wouldn’t do that because in nursing, for example, we have a shortage. 

Yeah. So to actually allow nurses to do their job and not be as stressed. Burnout is real, right? In the clinical side of medicine, then these tools, you still have to educate the user on why this tool is good for you and how you can sustain it versus, oh, here’s just another great tech idea. Of course, of course. 

Q. So one thing which I would like to touch upon before we wrap up Zafar is around the idea of what would be your suggestions and advice for startups in healthcare. There are so many startups, some well funded, some less funded at various stages from seed to series E sometimes. There’s so many. So many. So what would you say to someone who was wanting to do startups in healthcare?

Zafar:  So my best advice is, is that if you want to understand how healthcare functions, there’s a couple of points. One is, healthcare is the long game. It’s not the short game. If you build a startup in healthcare, You really need to be ready to go the distance. This is not instant gratification. The margins in healthcare IT are much lower. 

So if you build an AI startup in healthcare, A, it’s going to take you some years to build traction. So you’re going to have to have funding to do that. B, If you think you’re going to make triple and double digit margins from a health system, you’re fooling yourself because you’re not. It’s always single digit margins. 

The benefit in healthcare though, is once you do good work and you have a relationship, you will get those single digit margins for a really, really long time. It’s a relationship business, right? Yes. So if you’re one of those entrepreneurs who says, I just want to build the next company and cash out, I wouldn’t recommend health it based companies because they don’t happen that quickly. 

If you tend to follow that model, they flame out. I would certainly, certainly say that. The other thing I would advise startups is if you’re in this new space of AI. And you really want to make an impact and build partnerships and get the logos you need to grow your business, build real use cases that people can test. 

Yes, don’t come in and say you can deliver the world if somebody pays you a whole bunch of professional services, because that’s too risky for people like me. But if you came to me and said, I actually have built five use cases. That we’ve tested with sample data, but we would like you to try with your data, then I would probably try it. 

What I don’t want to be is be a software development house, right? I don’t want to spend a year and a million dollars in professional services building an AI model that actually ends up failing. Because that’s not a good use of our money. Our money traditionally should go into getting patients better. 

Yes. And healthy, not, of course, we did a partnership with you. We lost 500 K and didn’t get any output. So if you are brand new and you’re funded, build three good use cases. How would you build those use cases? Make sure you have an advisory group of clinical people, people with healthcare backgrounds who can guide you on how to build those use cases three use cases, then bring those use cases to your sales cycle, and you’ll have more success.  

That’s awesome advice, Zafar. And with that, I would like to thank you for sparing your time for this podcast. Really appreciate it.  

Thanks for having me. 

We hope you enjoyed this podcast. Subscribe to our podcast series at www.thebigunlock.com and write to us at info@thebigunlock.com   

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

Q. Would you like to start with some introductions, Joel, and talk about a little bit about your journey so far?

Joel: Sure, thanks very much for having me, Rohit. I’m Joel Klein, the Chief Information Officer at the University of Maryland Medical System. We’re a 14-hospital system here in Maryland and one of the largest nonprofit employers in the state. I think we might actually be the largest.

We’re one of the dominant health systems in the DMV area. Our academic health system in downtown Baltimore provides everything from multi-organ transplants to high-acuity trauma care, bone marrow transplants, and other quaternary care services.

In addition, we have many community hospitals, rural healthcare facilities, and ambulatory sites across the state. It’s an integrated delivery system that operates in close partnership with the University of Maryland’s School of Medicine, School of Pharmacy, School of Nursing, and others.

Although we’re a private company established decades ago and not formally part of the university system, we work very closely with them. We operate very much as an academic health system with strong community components.

Q. That’s awesome. Joel, I understand you studied to be a physician. I’d be very curious to hear how you moved from being a physician, and perhaps a practicing one, to this side of things.

Joel: Sure. I’m an emergency doctor. I went to medical school back home in Texas at the University of Texas Southwestern Medical School and completed my emergency medicine training at Johns Hopkins. After residency, I was hired at one of our community hospitals in the system, where I still work.

I was the “night guy” for many years, working night shifts and taking care of everyone. It was a very busy place—at the time, it was one of the biggest emergency departments on the East Coast, with over 100,000 visits a year, which is massive by ER standards. The hospital was surrounded by nursing homes and assisted living facilities, so I saw a lot of elderly patients with sepsis, hip fractures, and other “bread and butter” community emergency cases.

I was eventually elected to lead my group of 60 doctors, nurse practitioners, and PAs. In that role, I oversaw incentive compensation, which was tied to performance metrics. To manage that effectively, I needed data—something that didn’t really exist at the time, about 20 years ago. Performance was mostly judged subjectively.

To get the data I needed, I began collaborating with the IT team. I worked with them to track metrics like door-to-doctor time, throughput time, admission rates, and compliance with treatment protocols, such as administering the right antibiotics for pneumonia or sepsis. This partnership with IT helped me access the data I needed to objectively evaluate and improve performance.

Around 2012, our organization embarked on a digital transformation journey, implementing a single electronic medical record (EMR) platform across the entire system. This unified platform gave us all the same situational awareness of our patients and allowed us to operate more seamlessly. I played a leadership role in that project early on.

By 2015, I had officially joined the IT leadership team, and in 2019, I became the CIO. This is now my sixth year in the role.

I still maintain my medical license—I just renewed it, actually—and I remain on the medical staff at that community hospital. During the first half of COVID, I split shifts with my old partners, working early mornings, from 5 a.m. to 9 a.m.

However, balancing shifts with family life and the demands of being a CIO eventually became overwhelming. I stopped practicing about three years ago. While I could still go back to it if needed, my focus is now entirely on my CIO responsibilities.

Q: I’m very, very impressed by your early decision in 2012 to go for the single medical record and also start your digital transformation journey. With over five years in the CIO role, could you share with the audience some lessons learned, roadblocks, or difficulties you found along the way? Where do you think you are in the journey? Do you think it’s completed, or is there still a lot more to do?

Joel: There’s a whole bunch to talk about here, obviously, but if I were to pick out one key thread, it’s this: the thing we’re really trying to do in medicine is reduce unnecessary variation in how we care for patients. There is a best way, for instance, to manage things like pneumonia, sepsis, hip fractures, prenatal screening, or how a delivery in obstetrics should be handled. There are best practices in all of these areas.

One of the biggest tools that any healthcare organization has to drive consistency and encourage all members of the care team—doctors, nurses, therapists, and others—to practice consistently is by having everyone on the same platform. A common set of tools and visibility into patients allows us to use data to address that variation.

If you’re all on different platforms—if, for example, the eastern half of your organization uses one system and the northern half uses another—you’re always going to be fighting against that variation. You’ve got to get everyone on the same playing field, not just to have a common situational awareness of a given patient or part of your organization but also because it’s the way to get to consistency.

There are so many tools within electronic medical record systems that can help drive that consistency. If we don’t move towards reducing unwanted, unnecessary variation, we’re never going to get costs under control, and we’re never going to see best practices done everywhere as they should be.

We’ve gotten onto a common platform and are very far along in driving towards consistency, but this is a never-ending journey. It’s still something we’re actively working on as a system.

Q. It is very interesting that you mentioned about reducing variation and driving consistency. How would that come into play, Joel, if there was any situation of, let’s say, acquisitions where you now have to deal with a hospital system that came into the same portfolio or a new set of physicians and they are not used to the same platforms or the tools or the systems that you are driving?

Joel: Yeah. A lot of health systems are dealing with this right now. I mean, this is true for any acquisition, any MNA activity. So I think you could generally speaking, divided up into two categories. One is an acquired entity or an entity that joins, you know, a health system or, you know, a larger company, um, that is smaller and less sophisticated and less mature.

And in that case, usually they welcome the help, you know, part of that’s the whole rationale for why, you know, we joined up in the first place. You know, I, I know. Um, some of the organizations that joined our health system, you know, it’s change and change is always hard, but the opportunity to to benefit from all the hard work we’ve done over the last, you know, 12 plus years in the journey that I just described, you know, they get to benefit from that without having to put in all that sweat equity, uh, that we’ve developed.

So that’s one scenario. The other scenario is harder, and that’s when you have two kind of like sized organizations that join forces to try to get some economies of scale. And the question is, how are you going to navigate, you know, the digital side of that merger? And it’s hard. Um, typically speaking, you’ve got to pick, right?

You’ve got to say, well, let’s go with this one and let’s extend that umbrella out, right? And the challenge is having governance to say, well, how do you do it? How do we do it? And I think the hardest part is, you know, getting that, um, that pattern getting into a groove of compromise. And, you know, it starts with trust.

It starts with dialogue. It starts with the leaders. Uh, not just the I. T. Leaders, but the clinical leaders and the operational leaders, you know, having relationships with each other, um, and realizing that, you know, it doesn’t really matter, uh, necessarily whether we do it, you know, whether the wallpaper is this wallpaper or that wallpaper, because they’re both okay, let’s pick some wallpaper.

Um, and, and that way, you know, we don’t have to spend a bunch of energy maintaining both kinds of wallpaper. Yeah, and you know, that’s some of the hardest work there is. Um, and, um, but it’s, it’s part of what makes the job fun and exciting.

Q: I’d like to shift gears a little bit, Joel, and ask about how you approach innovation. What’s your thought process? In a large system, innovation is usually difficult to do. How do you gather innovative ideas from patients, your nursing staff, physicians, or any other constituents or stakeholders in the organization?

Joel: Yeah, right. I think you have to approach it in two ways. One, you have to, right? Everyone knows you have to water the plants or they won’t grow. So you need a way to listen for innovative ideas, collect them, and then find a way to put some gasoline behind them and get them the resources they need to try to run with them.

Sometimes that involves identifying people out in the organization who are not part of IT and bringing them into IT, connecting them to larger teams that can help them. Clinical engineering is a great example in healthcare organizations, where people are out there repairing things and dealing with biomedical devices. They’re not always part of IT. You need to find talent in the organization that can benefit from the resources IT typically provides, whether that’s project management or infrastructure that isn’t intrinsic to clinical engineering. That’s just one example. So, you’ve got to be listening, and you’ve got to find a way to run with the ideas.

On the other hand, we have the “good idea fairy,” right? When the good idea fairy shows up, each hospital might have two to three projects or pilots they want to run. All of a sudden, you have 50 new projects, and that’s just not possible. So, you’ve got to have some governance.

Some of that governance requires command and control. You need people who have the right eye for success. If you have a big committee vote on ideas, you’ll get into groupthink, and sometimes real opportunities will be missed. You need people who can smell something good when they see it, and you need a process that’s not a dictatorship or some backroom deal. It’s a tricky balance, but you have to balance all of these things for innovation to be successful.

Q: Can you share some examples with us or anything that pops into your mind of something that you and your team have done that is innovative and that you are thinking of taking further along?

Joel: Yep. So, you know, there’s a ton of examples, some of which we’re really excited about in terms of products that we’ve developed that we feel have a serious future on the marketplace. But speaking generally, and running with the theme of clinical engineering, we believe that, just like all of us run around with our phones and use them for so much of our daily tasks, we’ve been spending a lot of time in our organization thinking about the devices in our nurses’ pockets.

How do we get more and more of the technology that patients depend on—everything from clinical monitors, cardiac monitors, fetal monitors, ventilators, nurse call systems, telemedicine, and, of course, the electronic medical record system—into a clinical device? The goal is to make it indestructible, vomit-proof, and in a form factor that our nurses really love using.

A lot of the devices we have to choose from, like an iPhone, are consumer devices, right? They’re not designed for healthcare. Whether it’s from a form factor point of view or user infrastructure point of view, iPhones are built to be used by individual users, not shared devices. That’s not what we’re going for.

So, you’ve got to wrap all of that together. It’s a lot of engineering and it has to unify a ton of vendors. What I just described isn’t the work of just one vendor, right? You need a team capable of putting that engineering together from so many different platforms. That’s an area where we’re really working hard to create something that our nurses will love to use.

Q: So, you mentioned something very interesting that ties into the environment many of us are facing right now, where you have to do more with less, in terms of budgets and resources. You mentioned throwing gasoline on a project, and to do that, you need money, resources, time, and energy to pursue these initiatives. How do you make that happen in an environment where budgets may not be available?

Joel: Yeah, so it’s a bunch of tactics. One, you have to look inside. In any IT shop, there’s probably stuff you’re doing that you don’t really need to be doing. You’ve got to be really thoughtful about that. I’m not saying stop keeping the lights on; I’m not saying that at all, but you’ve really got to be thoughtful about whether the work you’re doing is adding value. There are always people who will try to hide behind work because it’s easy, so you’ve just got to pay a lot of attention to that.

The second thing is, you’ve got to make it clear to your organization the value of what you’re doing. You need to talk about what you’re doing and what’s possible because, you know, we assume the budget is X. In my organization, the narrative from our finance community is that we need to find a way to get IT more resources. Yes, there’s the narrative of doing more with less, but remember, from a capital point of view, we’ve got to build new hospitals and buy new medical equipment. It’s a very capital-intensive industry. So how you frame all of that is key. Do they know what you’re working on? You’ve got to be able not just to tell the story, but also to demonstrate the art of the possible. Some of that involves making sure that everyday users feel the impact of what you’re doing.

And then, the last thing is good governance. You can’t just pull stuff out and say, “We’re not going to do this anymore.” A much better choice is to give the organization options. You know, say, “We want to pull X million dollars in costs out of the organization. Here are five ways to do that. They’re all terrible, but what do you think is the least terrible?” And you want the right people around the table making that decision rather than me making a unilateral one. As a doctor, I could do that, and it might be more credible, but it’s better if I do it in lockstep with my peers.

Q: Since we’re talking technology, Joel, there has been such a rapid change in new technologies like Gen AI and large language models that have really changed the AI landscape. Everyone is experimenting with Gen AI in some form or another, whether they like it or not. So, what are some of your thoughts around AI and Gen AI? How do you see these technologies accelerating innovation or improving patient care and healthcare delivery?

Joel: You’ve got to think about cybersecurity and privacy. You can’t dump a bunch of protected health information into some Gen AI platform and risk that data becoming public or leaked through a malformed or malicious prompt. That’s a real issue we need to address as an industry, and our vendors will have to help us if we want to really lean into these technologies.

That said, there’s a ton that the industry is looking at, and we certainly are, too. Ambient technology is a big piece of this. We’re piloting a number of solutions, and it’s promising, just like many new technologies are. The challenge is whether every doctor is going to appreciate ambient documentation the same way. This involves having a microphone in the room, typically on the doctor’s phone, that records the dialogue between the doctor and the patient. The output is documentation of the visit, which can take 5 to 10 minutes per patient if the doctor’s typing, or maybe only 60 seconds to review if they’re looking over what the AI generated.

It’s promising, but a third to half of providers love it, some aren’t sure, and others aren’t convinced. So, how do we get these providers to adopt it? How do we coach them? It’s like autopilots in airplanes—there will always be those who say, “Back in my day, we didn’t have that.” But it’s a tool for safe and efficient flight, so how do we get people to embrace it? That’s one example.

Another big area is idea generation. Whether it’s for an individual patient or hospital-wide strategies like patient flow, how can we use AI to come up with new solutions? What are we missing? AI excels at thinking about things differently, and that’s incredibly valuable in healthcare. Those are just a few of the thoughts we’re considering.

Q: So, you’re already looking at possibly using GenAI, and it’s crossing functional areas now, so you can actually use it in many different functional areas at the hospital system. You mentioned that you were at a VC conference and that you might want to share some thoughts and ideas from your visit at the conference. So what are some of your thoughts there?

Joel: Yes. Well, I’d say two things. It was an amazing meeting. There were about 250 or so CIOs from all different industries, including some of the biggest companies in the country. I think what’s fascinating is how all of us in IT leadership are fighting the same battles. We’re all dealing with vendors that are engaging in really punitive price increases. They’ll acquire something and then jack the price 500%. It’s not going to work. We will find a way out of that, and it’s a huge problem.

We’re all dealing with AI, productivity vendors, and capital challenges. Whether it’s an ERP vendor or CRM or anything IT-related, we’re all doing the same stuff no matter what the industry is. It’s just fascinating to hear that.

The other idea that I heard was using AI for idea generation. So, you know, here’s a business problem we have—give me five unorthodox solutions that I didn’t think about, or even some really crazy prompts, like, “Imagine the following business problem—how would the Middle Ages have dealt with this?” And it sounds ridiculous, but it’s not, because it gives you a spark, like a little way of connecting things.

What I heard from a lot of my colleagues at big companies is that that’s what they’re doing to try to get an edge on their competitors. I love it, because it sounds wild and fun. It’s a great way to keep us all collectively engaged at the highest levels, solving some of the toughest problems we’ve got today.

Q: I would love to get your thoughts on value-based care, Joel. Are you already in the midst of that? Are you planning for that? And what are some of your suggestions and advice for people who are thinking about that?

Joel: Yeah, so value-based care is not new. This is something that I think the whole industry has been trying to figure out, in some cases very successfully, and in some cases not so successfully. It’s this whole idea of having skin in the game, for some block of covered lives.

I think it comes back to how much we can focus on primary prevention. As long as we have contracts—this is Joel’s opinion— as long as we’re talking in terms of single-year, time periods of responsibility, primary care is always going to take a back seat. So, in other words, if I’m really accountable for getting patients to lose 20 pounds because of the health upside of that from heart disease or hip replacement, there’s just so many ways. But if I’m only responsible for, you know, between now and the end of the fiscal year, I’m not going to worry too much about that. It’s too short a time period.

So, how do we think about that? To me, that’s something that the whole value-based care space needs to think more about. Then, how can we partner better with payers? Who are the intermediaries here? A lot of people say the payers just suck money out of the system and they’re just bureaucracy, skimming 10-15%. But I think it’s more complicated and nuanced than that. They do have the ability to help providers be more strategic about how they apply resources. I think there’s more than just, “We’ll give you some analytics or a list of things to do,” but I think there’s opportunity there.

Q: Would you like to share some final thoughts on any new initiatives around digital transformation that you’re thinking of in the next few months or years? What do you see coming your way or our way as an industry?

Joel: Part of why I love my job is the whiplash. I’m going from this conversation to a meeting about how we can support philanthropy more aggressively, and then my meeting after that is with our CTO to talk about all the projects we have going on there. And then my afternoon is focused on our informatics team and how it’s, I mean, that’s like typical.

So, it’s great because there’s so much to do in our industry. I don’t think I’m alone. And, you know, to sort of point to any one thing would be saying, well, I love this child best. There’s just so much. And to me, that’s what’s so much fun about this job.

We hope you enjoyed this podcast. Subscribe to our podcast series at www.thebigunlock.com and write to us at info@thebigunlock.com  

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

Welcome to the Big Unlock Podcast, Piyush. It is great to have you as our guest today. I’m Rohit Mahajan, Managing Partner and CEO at BigRio and Damo Consulting. I would request you to please introduce yourself.

Piyush: I’m Piyush Mathur. I’m a physician, an Anesthesiologist, and work in ICU too. Originally did my MBBS in India from Armed Forces Medical College, Pune, and then subsequently through my journey came to Cleveland Clinic where I have been for more than 21 years now. Did further training in quality and education and for the last many years have been very focused on how can we impact the quality of patient care using artificial intelligence, which is a data driven science.

Q. Great to know that you started your journey as a physician. So, what motivated you? What choices you had at that point in time when you started your journey and how did you come to US?

Piyush:  The motivation was very simple. My dad, actually wanted to be in the armed forces and he always wanted me to be a doctor and always encouraged me to focus on that. I happen to be good in biology too, throughout my high school. So, it was a natural fit. I ended up at armed forces medical college for that reason, and then decided to further pursue learning and training in the US.

I didn’t know about Cleveland Clinic at all, being in India over two decades ago, and it was actually my last application for a residency program. When I matched here, I was really excited. Since then, I’ve pursued my career at Cleveland Clinic, training in anesthesiology and later in critical care. Working here with people from all over the world and learning from them has been an excellent journey.

Q. Piyush, I know that you’re pretty busy as a physician, but you still find time to do other business ventures. Could you tell us about those?

Piyush: Yeah, I always like to learn and grow. Being a clinician is important, but as we thought about applying AI in healthcare, we wanted to innovate and make it something sustainable—beyond a hobby or pure research. That’s when, along with Frank Pepe, chair of plastic surgery at Cleveland Clinic, we founded BrainX, an AI and healthcare company.

We were both very excited about this scientific opportunity for applying AI in healthcare. But there were a lot of challenges and there were a lot of misunderstandings somewhere around six, seven years ago and still continue to be. But that’s what we wanted to demystify, that how can we apply this exciting, rapidly growing science into healthcare to make our patient’s journey, a better journey, how do we empower our clinicians with this wonderful tools that the science represents so that they can be enabled to give better care to our patients.

How can we make the healthcare system more efficient using this data driven science so that the delivery becomes better? So those were all the questions that we were trying to trying to address. And we did believe together, collectively, that AI represented a great opportunity to solve that rather than just trying the tools that had been tried in the past.

And subsequently, we had other founding partners like Dr. Szymanski, Dr. Maeshwari, and Dr. Khanna join us. And we started working on exploring this, and over a time period, we had Raghav and Shreya join us as our technical leads and our research leads now. They are both PhDs in AI. And we have just subsequently grown leaps and bounds in this exploration.

Q. That’s great to know, Piyush. How many years has it been, and which are your focus areas? Tell us about work by giving perhaps one or two examples.

Piyush: We never anticipated that we’ll grow that rapidly. So, it’s just been six, seven years now since we started. Initially started with just our core team, the BrainX team. Eventually, there were so many other people who were asking the same questions what we were asking, and everybody was so excited. So, we ended up forming a community around us called the – BrainX community – so we can engage people from across the world. That’s a 6,000 plus member international community. Also, very active LinkedIn group with the same name called BrainX community. We have a website, a whole host of resources that are available over there. Free to join. All the content is free. As we grew, we also realized that, you know, we need to expand our research team.

We created one of the verticals that we have now within BrainX, our own lab called BrainX AI Research. Now we have people from across the world participating in our research work with all different backgrounds, all the way from undergraduates to PhDs. Everybody working together, trying to research different aspects of AI application in healthcare. All the way from basic data science, we are very focused on all those.

Q. We were very fortunate to have you as our keynote and spotlight speaker when we did our GenAI workshop near Cleveland Clinic. You spoke very deeply about the applications of AI in healthcare and GenAI in healthcare. Could you share with the audience some of the insights perhaps from either that talk or any others that you very frequently do otherwise as well?

Piyush: So, generative AI—or for those who may not know the term, AI like ChatGPT—is an application people are now familiar with. Tools like this have become widely available for public use, and there’s a lot of excitement around them. Our team was already focused on the predecessors of these tools, particularly in natural language processing during the pre-GPT era. So, as these fascinating tools became available, it was a natural transition for us.

It’s like being in a toy shop where developers are putting out all these different algorithms—we’re fascinated and excited to trial them. But it’s also a pivotal moment. Just like Steve Jobs made personal computers accessible to everyone, AI is now talking to people. People can interact with it directly, see how powerful it is, and integrate it into their daily lives.

This is generative AI’s “hello world” moment. But with all the excitement, we need to be careful, especially in healthcare. These tools need validation, testing, and possibly adaptation. One model might not fit all healthcare needs, so we and others worldwide are experimenting to understand the right approaches for applying these models.

What’s exciting is that these state-of-the-art tools allow people to interact in natural language, but we must ensure they are vetted and applied appropriately to help with patient care. That’s the exciting part.

Q. That’s great to know. And I am also super excited to learn that you have launched a new book, Piyush. I’m looking forward to reading it very soon. Would you like to give some insights to the audience about what is the contents of the book and what motivated you to write the book?

Piyush: Thank you, Rohit. We’re trying to put together our experience and expertise in that book. It’s called ‘Strategies for Artificial Intelligence and Healthcare.’ Y You can find it on Amazon. Frank Pepe, Jeff Mangus, and I co-authored this book. The idea was not to provide overly technical knowledge, as that already exists in other publications, but to focus on strategy.

Strategy is something I often find lacking across organizations or individuals—how to approach applying AI in healthcare. That’s why the sections of the book are laid out to address questions like why AI in healthcare, who, what, and so forth.

It’s an easy read and offers a framework for applying or learning about AI in healthcare, whether you’re a startup, hospital, or multinational company. We hope this book provides that key strategy element for mindful AI adoption in healthcare.

That’s great to know. So with that, I would like to finish our conversation for today. And I say this because we might have a follow-up podcast with you, as the landscape is changing so fast.

Q. What do you see in the crystal ball? What do you see in the next few months regarding healthcare adopting more AI and generative AI applications? If that’s what you’d like to talk about, or anything else you’re observing—whether it’s at the Cleveland Clinic or in your practice as a physician.

Piyush: The thing that excites me the most is the opportunity that AI brings. Look at this opportunity—right? You and I are talking about AI here, a physician and someone from the technological world. It’s brought all of us onto a common platform.

And what is it bringing us together for? It’s bringing us together for a common purpose, which is beautiful: to improve the delivery of patient care. That is what I’m most excited about, and that is what keeps me energized all day long about this opportunity.

I think we, on this platform, collectively working together, will clearly build great tools in the future, whether it’s with BigRio or through collaborations with many other companies we’re looking forward to working with.

The other part of this is the evolution of AI itself. If you see how fast-paced it is: we started with natural language processing a few years ago. It was slow for a while, and then suddenly, with the advent of generative AI, things accelerated.

Now, we are moving into multimodal AI. The excitement of a constantly evolving technology is exceptional. I haven’t seen such rapid growth in science or so many people engaged and involved in decades.

That’s what excites me and gives me hope. It keeps me optimistic that we are building a great future for our patients, our clinicians, and everyone involved.

We hope you enjoyed this podcast. Subscribe to our podcast series at www.thebigunlock.com and write to us at info@thebigunlock.com  

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

Welcome to the Big Unlock Podcast. We are carrying on The Big Unlock podcast, which was started by Paddy Padmanabhan. This is 146th episode and we are very excited to have you as the guest and looking forward to our interaction. 

Shakeeb: Thanks, and appreciate you having me on. Glad to be the 146th. My name is Shakeeb Akhter. I’m the Chief Digital and Information Officer at Children’s Hospital of Philadelphia (CHOP), where I oversee digital and technology services, our overall enterprise digital transformation strategy, and all things ranging from infrastructure, applications, cybersecurity, AI, data and analytics. I’ve been in that role for almost three years now, and it’s been wonderful. I’m looking forward to speaking with you about the work we’re doing.  

Q. Shakeeb, what motivated you to start off in your healthcare journey? 

Shakeeb: That’s a great question. It takes me back about two years. My background is in finance and economics. I’ve had two career stories: about a decade in finance, starting with big four consulting in financial services, then moving into banking, specifically in derivatives quantitative modeling during the 2008 financial crisis. That’s when I really began to understand the intersection of technology, banking, and quantitative modeling. 

It was an interesting time, using data, analytics, and technology to drive things forward. During that period, I realized I wanted to do something more meaningful long-term—something aligned with my values. I looked around and found healthcare to be a great place to build a legacy, contribute to humanity, and drive improvement. So, I made a conscious and hard pivot from finance to healthcare technology. 

It’s been a rewarding journey, full of change and opportunities to give back. I’ve learned a lot, and I’m really happy with that decision.

Q. That’s great to know, Shakeeb. Would you like to tell us more about what drives you at job from delivering the services that you do and touch on your digital literacy and culture initiatives?

Shakeeb: Sure. Just to give a quick overview of the Children’s Hospital of Philadelphia (CHOP), we have a very special mission: to solve the most complex problems and give every child hope for a healthy future. CHOP was actually the first paediatric hospital in the U.S. 

Yeah, many people don’t. We focus on three major areas: providing excellent patient care, driving innovative research, and offering quality education to advance the field. That’s what drives us.  

In terms of scale, we have three hospital locations, one of which is dedicated exclusively to behavioral health. While we’re based in Philadelphia, we have over 50 care network sites, including urgent care, primary care, and specialty care. We see around 1.5 million outpatient visits and 30,000 to 35,000 admissions annually. Although we’re located in Philadelphia, we have a global footprint, serving children from all 50 states and over 65 countries. 

We have about 28,000 employees, including 2,000 credentialed physicians and dentists, and around 700 beds. We also have a large research institute focused to drive research based breakthroughs in pediatric care. Our clinical operations, research, and foundation work together to drive transformation in pediatric care. 

Q. That’s awesome. I understand you’ve focused on some special initiatives around digital literacy, especially with all the changes we’re seeing, like AI and Gen AI. But things are changing and care needs to be more accessible. You have some good initiatives around training and teaching people about all things digital and also building a digital culture in the organizations. Could you please talk with us about that? 

Shakeeb: Sure. To answer that, I’d like to take a step back. When I became CIO almost three years ago, we embarked on a journey to develop a digital transformation strategy. Before that, we had an information services and technology strategy, but we took the time as a team across CHOP to define what digital transformation truly means to us. 

What does it actually mean beyond just being a buzzword? For us, it’s a systematic and intentional redesign of everything we do through technology. The key to our digital transformation strategy is that it was developed in partnership with our chief strategy officer, chief medical officer, and one of our chief operations officers, with input from around 200 people across the organization. We asked ourselves: What does digital transformation mean to CHOP? Where should we focus, and how can we create a digital culture here? That’s how the work began a few years ago. 

It was really valuable to gather ideas on where to focus and what matters most to CHOP—what leverages our strengths and helps us transform ourselves and the industry. We landed on three focus areas. 

First is AI and automation. No meeting is complete without mentioning AI, right? So, what does AI and automation mean for us? How can we use it to make our work easier, give time back to clinicians, improve efficiency, and drive innovation in both care and research? 

Second is the total experience—improving patient, provider, employee, and partner experiences. This includes our digital door strategy, where we’re focused on improving access, creating a seamless experience for patients to access care at CHOP, and reducing time to care. For providers, we’re tackling burnout, especially with documentation and EMR. How can we use technology to ease that burden, reduce workload, and improve satisfaction? 

The third piece is digitally enabled care models. How can we design care models that use digital tools to help us meet patients where they are? We’ve launched several remote patient management programs to discharge children earlier and provide care at home without sacrificing quality. 

These are just some of our initiatives. Our strategy’s success is rooted in integrating digital into everything we already stand for—high quality, the best patient outcomes, excellent patient experiences, and driving research and innovation. That’s our philosophy: digital is woven into our business strategy. It’s not something separate; it’s about being digital, not just doing digital. That’s how we frame it.

Q. That’s a really interesting positioning, Shakeeb. I’m sure that your background in data and analytics has helped really propel it forward. 

Shakeeb: I’m a big proponent of data analytics—it’s been in my DNA for a long time. I believe it’s the cornerstone of driving digital transformation. It’s the foundation for understanding our current performance, figuring out how we can improve, and measuring progress moving forward. We use data analytics as much as possible to guide our digital transformation efforts and to measure the outcomes. It’s really important to us.

Q. Can you share some insights from your journey, especially on managing data from disparate systems? How do you prepare it for a 360-degree view of the patient, or any 360-degree view, in a large system like yours with millions of patients and thousands of physicians?

Shakeeb: Yeah, absolutely. From my perspective, our data analytics strategy, which we built five years ago, has six pillars. The first is creating an enterprise data hub—getting all of our data into a single data warehouse or lakehouse. We have over 100 source systems feeding into this, with both structured and unstructured data, allowing us to ingest everything into one repository. 

The second step is modeling the data appropriately. We integrate, standardize, normalize, deduplicate, and trust the data. Data integration is crucial to our strategy. The next step is ensuring data trust. Without trusted data, it can’t be used for decision-making. We’ve created a data trust office focused on governance, quality, and stewardship, applying these standards at the warehouse level to build a trusted data layer. Our enterprise-grade analytics solutions are based on this layer, eliminating most of the usual questions about data origin and meaning. 

About a year ago, we launched our enterprise data catalog—a single front door to all data assets at CHOP. This includes metric definitions, cohorts, and dashboards, making data more accessible. 

Next, with trusted and integrated data, we can create a data-literate workforce. We’ve invested heavily in data literacy through our Data Analytics University, which has trained thousands at CHOP. We teach people how to use data, tell stories with it, assess its quality, and make data-driven decisions. 

The final two pillars involve deploying self-service analytics solutions. Thanks to our work on literacy, trust, and integration, we’ve seen widespread adoption. Now, we’re focusing on predictive data science and advanced analytics—how to predict outcomes before they happen. That’s the advanced analytics component of our strategy.

Q. All this seems to play into Gen AI as well, right? It’s democratizing access—anyone can use it in plain English. Can you share your thoughts or initiatives around Gen AI?

Shakeeb: Sure. I think Gen AI along with every other type of AI is highly reliant on large data sets that are of high quality. When my team and I talk about it, we said that the real limiting step to deploying AI at scale is data quality. So, we’re highly focused on measuring, monitoring, and improving our data quality. 

We’re implementing tools to do that, in addition to the data trust work I talked about. That’s the key. In terms of AI, I remind folks Gen AI is the newest form of AI. We’ve had deep learning, machine learning, natural language processing, and computer vision for decades—studied, tried, and true applications of AI—and they all rely on high-quality data. We’re focused on being inclusive of those other branches of AI and seeing how we’ll apply them. 

Gen AI has a ton of potential; it’s the newest and brightest in terms of attention. We’re testing what we’re calling CHOP GPT, our own instance of CHOP GPT. Our vision for AI is AI as an ally to our workforce. We want to position AI to help us work smarter and care better for our patients. That’s our focus for AI. 

For Gen AI, we’re developing CHOP GPT and working on other AI uses. For example, we’re training a large language model on our policies and procedures, making them searchable and accessible to staff. On a broader AI scale, we’re using predictive AI to predict claims denials before they spread and to predict other clinical events. 

With Gen AI, we’ve partnered with Epic. We’re the first organization to scale augmented response technology (ART) with Epic for all clinicians. This uses LLMs to draft responses to patient messages. Our clinicians get millions of messages a year, and this saves time. We’re also working on use cases with Epic, like note summarization, to reduce the burden for clinicians.

Q. Very cool. So, Shakeeb, moving on to another topic of interest. In large systems, one would imagine it’s difficult to innovate. What’s your approach at CHOP around innovation? And along with that, how do you work with startups? They’re innovating all the time, coming out with new solutions. If you could touch on these two areas, that would be great.

Shakeeb: Sure. From an innovation perspective, innovation is in CHOP’s DNA. It’s been a hallmark of the organization from a clinical and research standpoint for a very long time. We’re trying to bring that same thinking into the technology landscape. 

We do this in a couple of ways. One is partnering with our research institute to identify research scientists working on AI, machine learning, and other techniques in healthcare in novel ways. We figure out how to support them in their work. 

Second, our starting point for digital innovation is always defining a problem or challenge that’s impactful to CHOP, then working backward to determine the technology solution. We don’t look for technology in search of a problem. We focus on problem statements, outcome metrics, and prioritizing where to spend our time and effort. Our Chief Medical Officer has also launched an Innovation Catalyst Program to identify large, challenging problems. Our Digital Technology Services (DTS) team is embedded in those conversations to determine if there’s a technology solution that can drive innovation in that space. 

Regarding partnering with startups, our strategy is to constantly scan the market for new solutions that add value and help solve our pain points. We have a platform play strategy, where we first turn to our large, strategic partners to see if they have an existing solution that meets our needs. If not, we’re open to partnering with others. 

Long term, I believe we’ll move in the direction where, when we see a unique solution, we’ll approach startups with key problems we’re trying to solve at CHOP and open that up to other startups in the market. If they’re working in this space and meet our requirements, we’d love to hear from them. As we work on the Center for Digital Innovation, this is part of our vision for the future. We’d love to co-develop products with others and potentially share in their success. That’s what we’re thinking about for how we’ll partner with the startup ecosystem.

Q. So, Shakeeb, I would like to wrap up the session with your thoughts or insights on what’s coming next. The professor at Wharton I used to work with, Professor Jerry, would say, “the next big thing.” What do you think is the next big thing or the next big innovation?

Shakeeb: I think the next big thing is really bringing all the disparate data sets in healthcare together to analyze and predict preventatively which patients are at risk for specific diseases. This concept of precision medicine is on the cusp of becoming a reality, thanks to advancements in technology, the availability of data sets, and interoperability standards led by the industry. 

I believe this is the moment when precision medicine will be a reality for us in the next few years, allowing us to offer more tailored care to our patients. This brings together many elements we discussed: data, analytics, and AI, along with clinical decision support and informatics. These will be essential to integrate these ideas into workflows and identify patients at risk for particular diseases. 

We’ll use genomic data and other forms of data that patients may not even be aware of, helping them improve their outcomes through this process. So, I think that’s the next big thing in healthcare, and we’re at the right time for this tipping point. 

We hope you enjoyed this podcast. Subscribe to our podcast series at www.thebigunlock.com and write to us at info@thebigunlock.com  

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

Q: It is the 145^th episode of the Big Unlock podcast, which the previous founder of Damo Consulting started five years ago. It is very well received in industry circles, and it’s great to have you as a guest on this podcast. Would you like to start with a brief introduction of yourself?

Jawad: Thank you so much for having me. I’m the Chief Data Analytics Officer and Vice President at Akron Children’s Hospital. I worked at Tufts University Medical Center prior to my job here at Akron, and before that, I was at Rush University Medical Center in Chicago.

I have over 15 years of experience on the provider side, working in data and analytics at different institutions. It has been an amazing journey. I’ve seen the progress and transformation within data and data infrastructure for analytics. It’s been exciting, and I’m happy to share my thoughts with you today.

Q: Would you like to tell us a little more about how you started in the healthcare provider industry? What attracted you, and what keeps you motivated today? And can you also tell us about the organization you work for, Akron Children’s, as you mentioned?

Jawad: Sure. Let me first start with the organization, and then I’ll talk about my background and how I got into healthcare and specifically data analytics in healthcare. Akron Children’s Hospital is the largest children’s hospital in Northern Ohio. We focus exclusively on paediatrics—children are our specialty.

We are a two-hospital system with three ERs, four urgent cares, and about 44 to 50 specialty clinics across Northern Ohio. We are a fully integrated system and use a single EHR across our health system, which is unique and serves us well as we continue to grow in the region.

A bit about me: I’m a computer scientist by background with a degree in computer engineering, and I also studied electrical engineering in college. My first job out of college was in healthcare IT. Back in the day, we were developing serverless Java applications for handheld devices, or PDAs, as they were called. We created applications for checking formularies for providers as they prescribed medications, faxing prescriptions to pharmacies, and other functions. This was in the early 2000s, so it was ahead of its time, but a great learning experience.

Since then, I started in healthcare IT but moved to various industries, working in marketing, real estate, and capital markets. I was the managing director of a capital markets company in the Chicago area. I then moved into enterprise architecture, doing a lot of cloud transformation work for a large company. Eventually, I had the opportunity to join Rush University Medical Center in the data analytics space as a director, later becoming EVP. Now, here I am, 15 years into healthcare systems, with experience through pandemics and other challenges.

Q: So, Jawad, when you think about digital transformation and how it’s solving challenges for your patient population, which is essentially, like you said, paediatrics and children in the local area, and perhaps people coming from all over the world as well, what are some of your thoughts? How do you approach it with your team at Akron Children’s? Any other experiences from your past that you’d like to share with the audience?

Jawad: Our mission at Akron Children’s is to do everything for them that we would do for our own children. So, we don’t turn anybody away. That’s part of our core values and mission of the organization, and we’re very sincere and focused on that, on delivering value and fulfilling our mission. What that really means is our objective is always to provide the best possible care.

We always look at holistic care. We have several programs anchored in the community and in schools where we focus not just on sick care but also on wellness care. We want to make sure our patients stay healthy and remain healthy for the rest of their lives. And these are kids we’re dealing with, so we are very, very passionate about that.

Q: When you think about some of the challenges in the digital transformation space from your perspective as a children’s hospital, what are your thoughts? What are the initiatives or projects you’re currently working on, and what do you have in mind for the future?

Jawad: One of the challenges, and all challenges are opportunities eventually in healthcare, is that data is often locked in proprietary databases. At Akron Children’s, we’re fortunate because we’re an integrated system with a single EHR across our entire system. It’s a bit easier from the EHR perspective, but EHR is just one application among 300-odd applications that make up our entire IT ecosystem.

All of those systems collect data, and that data is critically important. It’s very difficult for any institution, including ours, to unlock all of that data, convert it into information, and eventually generate knowledge that can be leveraged. So that’s a very current and ongoing challenge. We’re looking at several ways to ensure we can extract data from all relevant applications needed for data analytics. We want to provide that data to the right people, who can then extract knowledge and make data-informed business decisions.

For the last 15 years, there’s been so much change in that space. We used to manage data in siloed databases. But now, we’re talking about integrating it into open platforms, like public cloud, using Lakehouse architectures to bring data together. The goal is to make data easier to access and remove as much friction as possible in making that data available to end users. It’s been a journey, and it continues to be a journey.

Q: When you say end users, are you also thinking end users in terms of the patients themselves for self-service applications? Or mostly when you’re thinking end users, you’re thinking of the application systems within the hospital that your colleagues, physicians, and nurses might be using?

Jawad: We are thinking all of the above. Today, patients can access their data within minutes of their visit. Labs become available to them on apps as soon as they get their labs done. So yes, we are providing access for our end users—patients—to the data in a timely fashion.

We are also talking about internal customers who are responsible for running the business. We are accountable for ensuring the system runs on data-informed decisions. So, all of that is part of our end users, and we strive to provide data to them by removing all obstacles and friction, organizing the data in a meaningful, usable way.

 Q: How do you wrestle with the challenge of when someone comes in from another hospital system that may not have the same EMR or EHR? Do they still bring their health record along with them, or do you have to request it from the other health system? How does the whole process work in terms of data platform interoperability?

Jawad: It has improved quite a bit. If folks come from hospital systems using one of the current EHRs, since we are an Epic customer, we have care everywhere in our backend to exchange data between Epic hospitals and even some non-Epic hospitals that participate in that network. We have backend capabilities that allow us to exchange information between systems.

Now, not everyone is part of that network or can share information programmatically in a timely fashion. When that falls short, we use older methods—calling on behalf of the patient, receiving data in CDC format, or even just a fax that gets scanned into our EHR, making the data available.

Yes, over time, it has improved, but we still rely on legacy methods that aren’t timely. There can also be compliance issues depending on the state, and patient consent is required, which can create obstacles. But we are able to exchange information using both advanced and older methods.

Q: Before I move on to more exciting technologies like AI and GenAI and how you’re thinking about those use cases, I want to touch upon innovation. How do you foster innovation in a large health system where clinical decisions impact patient care? Any thoughts or examples from either your current or previous experiences?

Jawad: Yeah, that also is an art and exercise in itself. There’s a lot of innovation happening now, and healthcare is at an influx point. Historically, healthcare has lagged in adopting innovation compared to other industries, but with GenAI and AI, it’s starting to leap ahead. I’m excited that healthcare is ready to accept innovation and address the challenges it can solve.

At Akron Children’s, we’re using GenAI for note summarization for physicians to reduce pajama time, meaning time spent outside clinical hours completing summaries of visits. GenAI was able to summarize them and even do other additional things to make it more time efficient for them to be able to document. Documentation is a big burden on healthcare and healthcare providers. Gen AI is obviously a very natural use case.

There are other areas, where automation and AI is becoming quite relevant and important, including pre-authorizations, where I’m seeing a lot of implementations on inbox management. Inbox management has been always been a burden for the providers. Automation of routing of messages, even auto replying some of those messages, obviously with human in loop to make sure that they are able to physically read the message that was generated, authorizes, and send it forward. These are the very low hanging fruit in terms of how GenAI is implemented. We are using data and analytics side also.

There is quite a bit of GenAI applications that I am seeing now. We haven’t implemented them yet, but we’re in the process of evaluating them and implementing them for folks to be able to use natural language process, like natural language to extract insights from the data.

You can come to the data and you can ask the question in your most comfortable language using your most comfortable phrases and the GenAI then provide the dashboard without anybody having to create a dashboard. Analytics is also becoming quite common now.

We are actually piloting it to implement it at our institution as well. GenAI is also being used in the background which front end users might not be able to see. To normalize the data, to curate the data, there’s a lot of solutions that we’re piloting and evaluating. We are working with various partners to see how it would make our processes or back-end processes effective.

This is a high interest of us right now because that directly translates to FTEs, that really translates to ROI, and things that we do, and even improved efficiency, integrity, and quality of the data as we look forward. So, I’m very, very excited about these solutions.

Q: That’s great to know. New technologies like GenAI often come with governance challenges. Could you share how you approach data governance in your organization, especially in the context of AI?

Jawad: Yeah, we should all remember that Gen AI is not an exception. Of course, we can discuss the risks of Gen AI and AI in general, but ensuring proper validation, data quality, and care quality has always been central to healthcare. We are a regulated industry, and we must make sure that since we are dealing with human lives, all healthcare solutions are validated, curated, secure, and have been thoroughly tested before they are implemented. This applies to any healthcare innovation.

With Gen AI, given that it’s artificial intelligence and involves machine learning, there are some added risks that require validation, like understanding the openness of the model and how interpretive it is. These aspects are critical. Regarding governance, when it comes to implementing AI or even non-AI innovations, we have established proper committees. We have an AI committee that reviews all proposed solutions. The team of informaticists carefully evaluates and validates these solutions to ensure they are feasible for implementation.

We also have a data governance structure in our organization with a steering committee and a data analytics committee. They oversee data curation processes, data definitions, and the validation of metrics. What I’m getting at is that we manage the entire end-to-end lifecycle of data—data and analytics. When I say analytics, I’m also referring to advanced analytics, including predictive modeling and machine learning, which all fall under the purview of our AI committee.

Members from various parts of the organization sit on this committee. Our Chief Informatics Officer leads the initiative from the Information Services Department. I am also a member, along with our CISO and key clinical staff, to ensure that new technologies are fully understood and vetted before they are implemented.

We have governance structures in place, and whether we use them effectively is something time will reveal. As new solutions and innovations are introduced, we will refine and adapt these processes as needed. But we do have a solid organization in place to implement AI innovations, and that’s reassuring.

Q: Any parting thoughts or suggestions for the audience on what you’re seeing for the future?

Jawad: If I summarize my 15 years in data analytics, especially in healthcare, the challenge is dealing with data and unlocking silos. Today, 80-90% of our analytics is generated using only 20% of the data. A lot of data is unused so as we look forward to sort of turn the curve on this, we really have to understand the best possible ways to be multi-modal in our approach to solutions.

So how do you not just do with discrete data? What do you do with unstructured data? What do you do with imaging data? All of these solutions, like we have to think through those things more carefully and not leave them behind, right? Not leave the 80 percent data behind to provide majority of the solutions.

We have to start becoming more data-savvy and multi-modal in our approach, considering not just discrete data but also unstructured data and imaging data. That’s really what we have been dealing with as we build warehouses, they cause us. The idea really becomes, how do you model the data?

My other recommendation to your listeners would be to adopt common data standards as much as possible. Whether you are good in FHIR schema or whether you want to go more on the research side and implement OMOP like, uh, schema to organize your data, all of those solutions are feasible and staying to the common data standards might help down the road as you exchange and become more interoperable with other institutions.

Also, think about how to present your data through APIs so that apps can consume it easily. Removing friction in data access will be key moving forward.

Today, most of the good innovations are happening on the app side, so apps are being developed that are more transactional with the data. So, how do you present the data as application programming interfaces or APIs so that those apps can consume your data? These are the things that we really have to think about and organize the data so that it becomes like we remove all the frictions for folks to access the data.

We hope you enjoyed this podcast. Subscribe to our podcast series at www.thebigunlock.com and write to us at info@damoconsulting.net

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

Q: Welcome to the Big Unlock Podcast, David. We’re really happy to have you here. This is the 144th episode and it’s been going on for a while and we’re happy to continue the legacy that Paddy left behind.  

David: Thank you for having me. First and foremost, I must say, I started recently listening to the past episodes and seeing the incredible lineup of guests that have been on it. I’ve been working for the Crystal Clinic for the past 15 years.  

Q. Tell us a little bit, about your journey, like how you came into healthcare and how you came to the Crystal Clinic and what has your experience been? How the healthcare field has evolved with digitization and the Affordable Care Act and how it’s impacted your work. Where do you see it going now with the trends in generative AI?

David: I’ll give you a brief story. So back when I was doing my first undergrad, I had a dream and a passion to get into healthcare, either be an anesthesiologist or a cardiologist. But then looking at my career, as it would extend and what age I would be at and when I would actually start being a real physician and getting paid that salary or that pay, it just wasn’t lining up for me. The rest of my family, almost the entire family is involved in nursing. I figured I would go that route because it does open doors for many opportunities. 

So, I got into nursing, and within the first week, in Nursing 101, they listed out all these opportunities. I got into nursing for two career paths: one was informatics, and the other was nursing law. Well, nursing law didn’t pan out. I had an opportunity developing with a woman who had a practice in town, and she was the consultant for all the major law firms in nursing law. The day I graduated from nursing school, I found out she had closed her practice. I was already working at one of the local hospitals in the ICU as a nurse tech, so I followed that path into ICU. Then, I got hurt on the job, which required surgery, and I was laid up for about 10 weeks. During that time, I started dabbling in website programming to pass the time.  

While I was sitting around, I got a call from a friend of my wife’s who was working with Cleveland Clinic to implement their EPIC system. This was about 16 or 18 years ago. I jumped at the opportunity to get into informatics. From there, I helped roll out EMAR, order entry, and worked with Children’s Hospitals and Cancer Centers, focusing on orthopedics and surgery.  

At the end of my contract, I was supporting all the ORs at the main campus of Cleveland Clinic, specifically in orthopedics. I started looking for a more stable position because I didn’t like not knowing if I had a job when the contract ended.  

Surprisingly, I got a call from Summa Health System, which Crystal Clinic used to partner with, about a clinical analyst position. I had applied for a similar position about a year earlier and heard nothing, so ghosting is not new. That was on a Friday. I went in for an interview on Monday, February 22nd, and they wanted me to start the next day. I asked for a day to think about it and started on Wednesday. By Thursday, I was neck-deep in programming the EHR, training on it, and more. Myself and one other person were responsible for it all. 

At that time, we had a deadline because Crystal Clinic Orthopedic Center is a physician-owned facility. There was a regulation, I believe from Congress, that physicians couldn’t own hospitals, with a hard stop deadline of June 30th, 2009. The project was about six months behind when I joined, but with a colleague’s help, we turned it around in three months and went live with our EHR, HMS (now Medhost), in May. That’s how my journey into informatics began. 

From there, I moved into management after a few years and, since 2015, have been working as a director. I’ve held that position ever since. Working on promoting interoperability and meaningful use allowed me to learn more about healthcare. 

Crystal Clinic is a physician-owned hospital system, with 16 clinic locations that are outpatient extensions of the hospital. We’re governed by the Joint Commission, unlike typical physician practices. We have a surgical hospital, an outpatient surgery center for orthopedic-specific urgent care, and as of last Friday, we have 51 physicians. We specialize in orthopedic and plastic reconstructive surgery, but also offer pain management, physical medicine, rehabilitation, and sports medicine, rounding it out with over 90 physical and occupational therapists. We cover the entire spectrum of orthopedic care, end-to-end. 

Q: Is this all in Ohio, David?  

David: Yes, it’s all in Ohio. We’re venturing out this year with something I’ll call “travel medicine.” It’s not exactly telehealth, but we’ve been ranked number one in Ohio and top 1% in the U.S. for orthopedic hospitals by CareChex Analytics. We have four certifications from the Joint Commission for disease-specific measures in total knee, total hip, total shoulder, and spine, making us one of only three in the nation. We do it better and cheaper.  

We decided to partner with local, regional, and now national organizations, many of them self-insured, because they find it’s cheaper to bring people here as a destination rather than have it done locally. For example, if you go to Texas for a total ankle replacement, it might cost $300k, while here, it’s less than half, including travel, room, and board. Plus, we have quicker turnaround times and better outcomes, so companies don’t lose key personnel for long periods. This is catching on with OrthoForum and others. It’s great because patients get the care they need faster with the outcomes they want. As we expand nationally, we still maintain our local presence. Rather than open facilities in other states, we bring people here. We couldn’t replicate our cost structure elsewhere like we have here in Ohio. 

Q: Yeah, that’s a really interesting model you’ve outlined because usually, when people talk about expansion, they think of opening new locations rather than bringing people to their existing ones. I think that makes digital health initiatives even more important. How do you see your vision for this, especially in terms of sharing everything back with other hospitals? Have you had to rework your systems, and what investments are you making to make this possible for Crystal Clinic? 

David: The nice thing about not expanding physically is that you avoid capital costs. If you have a platform like Zoom, you can use it no matter where you are, and it’s the same for us. We have availability with some of the new providers we’re bringing on board, and we have the capacity to fill up both our surgical and clinical schedules. 

We’re not doing anything different than if the patient were local. We have a care coordinator, or sometimes multiple ones, depending on the patient’s path. They handle all the details—booking travel and hotel stays—while we focus on the patient and the healthcare we provide. 

Q: I was asking more from the point of view of, because the patient isn’t coming to you pre-procedure, you need to get all their information into the system and make sure the pre-checks are done, maybe not locally. How does that impact your IT outlook, and how do you handle that in this model? 

David: Yeah, we manage that through the care navigator. Let’s say we have a patient in California who can’t follow the usual pathway. We have someone who coordinates with them ahead of time and arranges everything. We recently rolled out online scheduling. We’re probably a bit behind compared to larger organizations, but as a physician-owned facility, things move a little slower. We want to ensure physician buy-in because the last thing we want is to launch something that impacts them, and they don’t accept it—that’s just throwing money away. 

So, we started with a few interested providers, taking baby steps. We had them pilot the system, and from there, we went live with a beta test group. Within a few days to a week, we had over 100 people schedule online. As providers see their schedules filling up, they’re getting on board. Some providers are still a little hesitant, feeling like they’re losing control of their schedules, but we’re getting more people in here. 

The data shows these patients are scheduling in the middle of the day or even at night—times when they can’t call the office. That’s encouraging because we were missing these people before. So, that’s how people outside of the travel medicine pathway are accessing our care. We also learned this through patient feedback, seeing why calls were being dropped. Since opening up online scheduling, those numbers have declined. 

Q: So what were the major learnings? What do you think patients or consumers are looking for today in the digital health experience? What insights did you get from that, which you then used to improve the systems and make it work? 

David: That’s a good question. I’d say we weren’t really meeting the patients where they are. We weren’t providing the opportunities that newer generations—like millennials and Gen Z—are asking for. We were stuck in the mindset that our core population is Medicare. It was a bit of a misnomer on our part, thinking we shouldn’t roll out too much technology because older patients may not have it. 

We found out that almost everyone now has access to technology, or they have a caregiver who does. That realization was one of the driving factors. We also started listening more to our patients—reaching out to those who passed on scheduling or cancelled, and understanding why. Since implementing changes, we’ve seen a decline in cancellation rates in a short time. It’s not necessarily tailored medicine, but we’re definitely tailoring the experience to meet patient expectations, and we have to evolve with that. 

Q: So this leads nicely to the next question. I think it’s a valuable insight where you’re saying that you can’t just wait for things to happen. You can’t push back and say, “This group is not going to use the technology,” because it’s coming, and you have to be ready for it. That’s similar to how we feel about AI and generative AI. Every organization needs to at least recognize that it’s out there and consider the use cases within their own organization. How do you feel about that? I saw one of the questions you sent about AI said, “Just because we can, doesn’t mean we should,” but you also mentioned that you had to get on the technology bandwagon. How do you feel about something similar now applying to AI? 

David: Our short-term initiative right now is getting into ambient generative AI. We have physicians willing to participate, but we’re taking our time. It’s about starting small and not rushing, similar to how we approached online scheduling. We made sure not to rush through it or go big bang. We also had to ensure it integrates with our current EHR. 

What’s been great for us is that over the years, we’ve been able to customize and program our EHR to our specific specialties—orthopedics, plastics, and now pain management, among others. A lot of large organizations try to fit everyone into the same mold, but we’re customizing ours for our needs. 

The company we’re piloting with—though I won’t name them as we haven’t signed a contract—works well with our system. It outputs the ambient AI into specific observation terms, which go into our EHR’s fields. It’s just another means of getting data into our custom-programmed EHR. 

Q: So, this is during the patient consultation? 

David: Yes, during the patient consultation. As the patient is speaking, the ambient AI generates a note and segments it into different sections, like HPI, health history, past medical problems, and so on. The assessment and plan go into their own sections. The AI-generated text is then assigned to specific fields in the EHR. It’s almost like having a scribe, but it’s working ambiently in the background. 

What’s nice about our current system is that it’s all structured data. If we want to report on it, we can run a SQL query and pull it all out. That’s the beauty of it. Instead of having just a note or a searchable PDF, we have structured data we can run analytics on. This is where we’re at now and what we’re looking forward to—it’s a nice, easy transition. 

Some providers using scribes are excited about this. Scribing is a transitional role, often filled by those waiting for med school. With this AI, they don’t have to worry about things like a scribe calling in sick. It replaces the need for a human scribe and does all the documentation for the provider. It’s also exciting because the company we’re working with can control the EHR via voice, which makes it a great blend of both. 

Q: When we did our CHIME focus group, we found that a lot of work was happening in this area, and in our generative AI workshops, we presented ambient listening as one of the success stories. However, the CHIME survey showed that people still want a human in the loop. How does that work here? Do physicians still need to review everything done by the scribe and then click an approval button? Or does it just go into the system? How are you handling that? 

David: They do have to approve it. Nothing is final, even with a physical scribe in the room. The provider still needs to attest to what’s in the documentation. If you look at regulations, especially in Ohio, but also nationally, a scribe can’t place orders. So the physician still has to enter and sign off on documentation and orders. 

There’s also a need to handle anomalies. AI has come a long way, and it’s not just a transcription service anymore. But anomalies can still happen, and that’s why a provider must sign off on it. It’s human nature that sometimes a tired provider might just glance at the note and approve it without fully reviewing it, which can lead to mistakes. At the end of the day, no matter how the information gets into the system, the provider is responsible for it. They need to read it, agree with it, and sign it. 

Q: This leads to another question—do you think AI is contributing to the decline of critical thinking? For example, we see cases where LLMs generate care plans, and nurses go into review mode, just signing off if the plan looks okay. Do you think having everything pre-filled for you leads to a loss of core skills that professionals have spent years developing? 

David: That’s a great question. In our current setup, I would say no. We’re still having conversations with the patient, doing exams, and verbally documenting findings. We don’t yet have clinical decision support in place, and that’s where the line between AI and critical thinking can blur. 

I’ve seen this evolution in healthcare, from handwritten notes to electronic systems. Nurses in particular have lost some basic skills—like even how to sign their name—because they rely so much on the system. Some newer nurses, who have never worked with paper records, might say, “The system didn’t tell me to do this,” when it should be part of their critical thinking. 

One example from my time as a nurse involved a stroke patient. They passed all the cognitive tests, but they made an offhand comment that their loved one was in the basement of their house, which was actually the hospital floor below their room. AI probably wouldn’t flag something like that as an issue because it seems irrelevant. However, as a nurse, I alerted the attending because it was unusual for this patient. 

Unfortunately, while attending to another crashing patient, the stroke patient had a large hemorrhage, and the outcome was unfavorable. This is a case where critical thinking made a difference, and AI might not have picked up on it. 

That’s my fear with AI in healthcare. Just because we can use AI doesn’t always mean we should. AI can help with documentation, but we risk losing those small pieces of critical thinking if we rely too heavily on it. It’s a slippery slope—if the system doesn’t prompt you, does that mean you shouldn’t do something? Critical thinking should always be at the forefront. 

Q: Yeah, that’s a really interesting point of discussion. You hear that it can ace all the medical exams, learn everything, and you have these AI companions trained for mental health. But it’s paradoxical because the main problem in mental health is loneliness. If you’re substituting it with a computer that doesn’t have feelings but can talk to you, then it’s a paradox. We have to wait and see where this technology is going to take us, but it’s good to be aware of the pitfalls, limitations, and what to watch out for. That’s why we want to take it slow. We know it’s there; we don’t need to rush into it. We’re not being forced to yet. Because you’re dealing with patients and have a really interesting background coming from nursing, which is a great motivational story. Whenever we talk to people in healthcare, almost everyone has a special story about how they got here and what made them enter healthcare. 

So, from your perspective within your organization, what do you think could be a good use case for AI? Where would it directly benefit your patients and be a real win for your organization? If you had to choose a field, where do you think this implementation could be? 

David: That’s an interesting question. Honestly, I don’t know if I can answer that. I’ve never really thought about it. I don’t want to just say something specific without having a solid plan. For orthopedics, I think one area where we could potentially use AI is in radiology or imaging. AI could analyze digital images and create reports with findings, with a radiologist signing off to agree with it. We haven’t implemented that yet, but I believe it would be a huge win for us. 

It would improve accuracy in what we’re finding and help fine-tune what needs to be done. From a surgeon’s perspective, we have radiologists review our X-rays as a backup, but they may miss an anomaly that doesn’t seem right. They’re still held responsible if it shows up in the image, but with an AI layer, we could flag potential tumors or other concerns for further evaluation. I see that being ortho-specific and really helping us take better care of our patients. 

More issues are surfacing in patients, and I think we can provide more holistic care, even if we’re not directly treating those issues. We can refer them and ensure the patient is well taken care of. I also have another use case involving custom implants. We have a program that depends on MRI or CT scans to create custom implants for our patients. I see that improving and becoming more precise. For example, my mother had her knee replaced this year. After her CT scan, they sent the data to the vendor to design a custom implant based on her specific anatomy. It’s no longer a trial-and-error process. Now, it’s almost like plug and play. I believe we’ll see an increase in AI usage there, tailoring everything to each patient’s anatomy. 

Q: Personalization. Those were very good examples, David. Thank you for sharing. Regarding radiology, I have an interesting story. During a generative AI program at Harvard Chan School of Medicine, one participant, the head of NHS from England, discussed how every radiology report must have two radiologists sign off on it. This led to significant backlogs, causing people to wait a long time for reports. 

One AI solution they found was allowing AI to generate the initial report, with the second radiologist reviewing and signing off. This resulted in a significant reduction in wait times. 

So, your points about radiology and the custom implants are solid examples of AI’s potential. AI can also enhance personalized medicine. For instance, when treating a fever, the recommendation for Tylenol is based on an average weight. However, AI could tailor the dosage specifically to an individual’s body. This concept relates to digital twins, where AI could tailor treatments based on a digital model before applying them in real life. These are all interesting examples. 

This brings us to our next topic of AI governance. I’ve heard both pros and cons about having a chief AI officer. Some argue that with AI’s applications across many departments, having a dedicated officer could limit its scope. What are your thoughts? Is your organization considering hiring a chief AI officer, or is AI spread across different departments? 

David: Our system is set up as a small organization with big problems. We limit our chiefs, and I haven’t seen more than four during my time here, with each wearing multiple hats. I don’t foresee a chief AI officer; that could be both good and bad. Each department has unique needs or wants related to AI, but it ultimately ties back to IT. 

While we may not govern AI usage, we should support it. We have a physician director for IT who acts as a liaison to ensure we meet providers’ and patients’ needs and maintain appropriate communication for any system changes. He essentially fulfills the role of a chief medical information officer without the title. I don’t see a chief AI officer because we’re still early in our AI journey. Maybe a CIO could oversee it, or perhaps a chief informatics officer, depending on how we expand our leadership. 

I don’t think it should be governed by one person; it needs to be collective because AI touches all departments. A committee might be beneficial to ensure that while AI can be effective, we also consider fiscal responsibility. Just because we can implement something doesn’t mean we should if the ROI isn’t there. 

Q: So, do you have that committee in place? 

David: We don’t have an AI committee yet, but we have a technology committee that looks at these areas. 

So what do you think is your timeline for, you know, like, are you thinking of implementing this in the next six to nine months or maybe like a year? 

David: Me personally, it has to be the next six to nine months. And part of that committee  once formed is definitely we had to educate people. That’s the biggest thing I’m finding. In our organization and all of these conferences I’m going to and people I speak with,  when you say AI, everybody thinks chatGPT. 

Yes. It goes beyond chat GPT. I know we started writing AI policies and we’re really being vague. Um, but the first AI policy is it must be approved to go through these steps before we can. Start implementing it, but it was, it started out as a blanket AI policy and it’s like, well, wait a minute back when we started programming our EHR and yes, 2000, 2012, I think we sort of did AI there, you might not think it, but you look at how we programmed it, there is AI involved, granted, the algorithms and what we use are extremely small and not really large, but it was, we took point and clicks and And we created a narrative from that point and click based on everything that all the data was being fed into it. 

So that is definitely on my radar to make sure that we need to educate. I know one of the workshops this year in the spring that I was at, someone mentioned the difference between people Who have a job in the future and those who don’t are those who are AI and light. Yes, exactly. Yeah, you gotta be educated and you have to have a familiarity. 

You don’t need to know LLMs and everything else that goes along with AI and how is all there, but you need to be aware of it and we need to educate the end users. Not to be afraid of it, of replacing you, it’s going to help you do your job better and be more efficient. It’s a power tool and it’s, it should be in your, and you should be able to have that conversation. 

That’s how we budget, you know. And you should apply it to the right areas too. I mean, do the ROI on it. See how much time is being invested. And just project management is another one that I’m passionate about, that there’s a lot of stuff Where AI can really help out there and just doing the mundane task and helping up with the communication plan. 

Making sure everybody has all the information and it’s  nicely tailored and it looks pretty and the product manager didn’t have to spend the time to go through and redo all the stuff and make sure that the system does it for you. Let the system work for you where it can, but still have the checks and balances in place that need to be there so it can be, the anomalies can be addressed. 

Ritu: Yeah, we’ve seen a very good implementation of that with our client, like I was telling you about. They’ve been able to generate these comprehensive care plans, and then it goes into the nurses’ admin panel. Only once they hit publish does it go out, and that’s the beauty of it. It can read and scan a lot more data, understand, and remember everything, especially for people with multiple chronic conditions, and come up with quite a comprehensive care plan. They’ve launched it in a couple of hospitals already and have received really good feedback, but as you said, it’s all evolving and it’s very new, so we have to kind of wait and watch to see where it takes us. 

David: I just had a recent conversation at the beginning of last month, actually, it was the day I came back from holiday. I had a broken car in the middle of the highway, so I was doing a Zoom call with this woman discussing AI education. A lot of universities, like many healthcare systems, are struggling with budgets, but they know they have to have something AI-related to stay competitive. Otherwise, they risk falling behind, and students will choose organizations that offer these programs over those that do not. It’s not a choice, but it’s changing so rapidly that universities lack the financial backing or budget to keep up. They’re working with companies that specialize in AI education and courses. Ideally, it would be nice for universities to handle it all, but… 

Ritu: This was a New York Times article talking about synthetic data. I read it too. We’ve incorporated it into our workshop for the next session because it’s really interesting. Sam Altman said that billions of pieces of data are generated every day. Just like you said, these bots are crawling the web looking for new content to read and ingest, and they can’t tell the difference between human and AI-generated content. They’re reading their own content and building upon it. Once you go through several generations of this, it all starts evening out and becoming monotonic. A lot of the content that bots generate is very impersonal; you can’t add those little human stories. The example you gave about the patient won’t be there in ChatGPT-generated content. So everything starts becoming very vanilla and indistinguishable. That’s a big pitfall right now because they’ve run out of human-generated data. They’ve already read everything on Reddit, and now they’re moving to generated data, which is going to be a huge problem. Even in image generation, I saw an example, maybe in the same article or a different one, where all the faces of people start looking alike after about 10 generations of reading their own content. The differences and diversity get wiped out, and everything ends up looking the same. There are definitely a lot of concerns that need to be addressed, and regulations need to be put in place. But yeah, those are topics for another podcast. 

David: One thing I find interesting is realistic expectations. A couple of weeks ago, I spoke with a company that scrapped their AI initiative for social determinants of health. They were aiming for perfection—100% accuracy—saying, “We ingest all this data, and here is the guarantee that this patient will have no sugar for their next visit.” They found that the timing of when that data is ingested and documented affects accuracy. The algorithm runs only based on the data at that particular time. They didn’t want to sell something that might only be 75% accurate because life-changing events can happen after that initial visit, like losing a job or a family member. Well, you lose that AI data because it happened outside of when the algorithm was run. They were trying to gather everything to produce a very high percentage of accuracy but struggled to get even close to 90%. All those external factors come into play, and garbage in, garbage out—you have to document appropriately. So yeah, it’s a tough problem to solve. 

Ritu: The no-shows are a huge issue, like you said. There are so many variables and factors. In fact, we show that as one of our case studies of where things could go wrong because those no-shows are biased towards people who already have problems. That’s why they don’t show up. Maybe someone has to look after their kids or something, and when you build these algorithms, it kind of reinforces that and makes it worse for those people. It’s really a difficult problem to solve. 

David: Then you take that data and have an insurance company use it, designed specifically for one area but applied elsewhere, which it wasn’t designed for. It doesn’t support the decisions being made. It can be good and bad. I find myself sitting on the fringes, waiting to see where we’re going with this and whether it will ever truly be 100% effective. We’re heading in one direction while I’m not quite sure if that’s the way we should go or if we should just wait and see what others do and learn from their mistakes. 

Ritu: Thank you, David. It’s been great having this conversation. Any last thoughts before we conclude? 

David: Not really. I’m just excited about where AI is taking us. I’m excited about what Big Rio and Damo are doing and where this podcast has gone and is going. I thank you for having me on and allowing me to share my story and experiences. Hopefully, it benefits others out there. 

We hope you enjoyed this podcast. Subscribe to our podcast series at www.thebigunlock.com and write to us at info@damoconsulting.net

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