While There Should be Zero Tolerance for Failure, Embrace Experimentation to Drive Innovation.

 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.

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