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The most important healthcare decisions don't happen in isolation. They happen when leaders come together. Becker's 16th annual meeting brings together more than 3,500 hospital and health system executives this April in Chicago. With 800 speakers from Ascension, Cleveland Clinic, Common Spirit, and more, the conversations get real. Leaders will share how they're scenario planning for policy shifts, breaking through value based care barriers and building clinical teams that translate new ideas into real world care care. Join top decision makers in the room April 13th through the 16th. For the agenda and event details, visit BeckersHospitalReview.com and click on the events tab in the upper right.
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This is Laura Deardo with the Becker's Healthcare Podcast. I'm thrilled today to be joined by Dr. Mark Mabus, Chief Medical Informatics Officer at Parkview Health. Dr. Mabus, it's a pleasure to have you on the podcast today.
C
Thank you so much, Laura. It's a great opportunity to be here and I'm excited to share with the community.
B
No, absolutely. And this is going to be a fun conversation because I know there's so much you're doing right now at Parkview, some really cool things in generative AI and more. And so I know we'll dive into some of that, but before we do, can you introduce yourself? Just tell us a little bit more about yourself and Parkview Health.
C
Sure, sure. Like you said, I'm Dr. Mark Mabus. I'm a practicing family physician. Still see patients a day, a week. CMIO at Parkview. Parkview is a large, not for profit health system in northeast Indiana and northwest ohi, Ohio with multiple hospitals, a large employed medical group, a strong focus on community health. We have, we have urban centers, suburban centers and rural, all within our area. There too, my role, you know, I, I sit at the intersection of, you know, clinicians and technology and then governance too. The application analyst for the EHR report to me, but I'm also in charge of, you know, provider efficiencies there too. So making sure that EHR AI, which we'll get into, and all these digital tools, you know, create efficient workflows, safer care for patients, and quality care for patients, you know, it's a, it's a fun job to be in between all of that and be able to see all the different areas of care throughout our health system.
B
I love it. That's, you know, so cool and definitely an interesting place to be. Having that clinical background, the technology and bringing that all together, you know, is truly a view of health care that not many others have. Now I'm curious When you think about the last year or so, could you tell us about the most important initiative that you led? What did you do and what were the results?
C
I think our most important initiative last year was getting assistive AI, you know, generative AI deployed throughout our health system. We did that in a couple different ways. The ambient documentation was a big one for our providers. You know, we partnered with a vendor to provide that service through epic. And we use a lot of epic's generative AI tools that they have available as well. And in fact, we just got our recent class Research Arts Collaborative survey that that said that 88% of our providers also said that the best improvement in 2025 to our EHR was the deployment of generative AI in some form or another like that assistive AI. We moved from limited P pilots to broad access, you know, and made sure that we were able to deploy these tools across all areas of care delivery, you know, ambulatory, emergency department and inpatient. And at the same time, we were very intentional about how we message this to providers. You know, this was the advent of assistive AI. We know we're not getting into automation and, you know, computers making diagnoses for you. Nothing like that. Nothing going to replace clinical judgment. It's kind of, you know, building that trust with your providers. Hey, we've got these new tools that can help you be more efficient and then, you know, deploying that out with piloting, first we're able to make sure it works for our workflows. Then we have the mass adoption. So very early in 2025, we had let our ambient documentation be available to all of our providers. And then In October of 2025, we made generative AI features available in EPIC to all of our providers as well. So looking at, you know, different areas where we can deploy AI and do so at mass scale, you know, we prepped it with all these little pilots, especially using some of our super users are what EPIC calls physician builders, you know, to help us with testing and feedback and then getting it, you know, out to the masses that, you know, specific points in time and bang, big bang. I'll give you another statistic with the generative AI features. Like I mentioned that we deployed in October. We were running at about, you know, 60,000 tokens per month or something along those lines. In October, since we turned everything on, that jumped to 2 million tokens in that month. And just this past January 2026, we hit 3 million tokens. So it was like, yeah, just a little bit here and there, you know, Getting our pilots under our ground and then you know, throughout the whole health system these things are available, people are using them, you know, not just our providers. You know, there's, there's obviously things that help our providers but you know, we also deployed in coding and revenue cycle side of our non clinical folks can benefit from AI. But yeah, planning those things out took a lot of work. And then you can go at scale and get these in the hands of everybody. Yeah, generative AI is the thing, it's what everybody needs to be doing across their healthcare system to enable these tools for efficiency, roi, all those things, it's here, use it.
B
I love that. Such a clear call for having this technology and doing what you can do in order to make the most of it. And it seems like you've got a really strong process not only for having some of those tests and those pilots, but then bringing things to. And I think that's the place where a lot of health systems and organizations really struggle to, you know, do that effectively. So what have you done or what have you found, you know, worked well, when you are taking some things from, you know, those smaller pilots into a broader and scalable space and seeing this kind of like adoption, which is wild,
C
a lot of it is figuring out workflows and where this fits properly. You know, you can have your vendors give you the instruction manuals or you know, how this actually works technically, you know, but when you dive into the workflows of an actual user and start using these things, you get to figure out that maybe it's not so cut and dry out of the instruction manual. You've got to create those best practices. That's what pilots were able to do for us on these, in these scales. And you know, it does take you adopting the right people for your pilots. I mentioned that we used physician builders, but you know, those physician builders are also in tune with non savvy users Workflows too. There's kind of that spectrum. You got your, your early adopters and people who do great with anything that you throw at them technology or change management wise, got your middle of the road folks and then you got your, your we'll just call them slower folks, you know, that, that little more resistant to change or you know, you know, the, the ones that take some extra education. So you've got to keep all those different areas in mind. And so when we are developing best practices, we don't just look at those high technology adopters, we look at everyone across, across the board. How can a workflow fit everyone at the same time. And that's what becomes our best practice. We use our informatics teams to write those best practices up, you know, document in, in educational emails or in, you know, in workflow education as well. We utilize in basket messaging for a lot of our informatics type and workflow education because people actually look at their in baskets in, in the EHR rather than having to go out to, to you know, their email program to look at it that way. So connecting with providers, getting boots on the ground. Our informatics team knew that these were high init is for the year, so they actually scaled back some of their just kind of regular scheduled clinic supports and instead focused on these high level deployments. Whether it was ambient documentation or you know, October when all 18 of these features went live, they made sure they scheduled time in each of the departments to go over the features that applied to the users in those departments. So, so it's possible to get this out to all those users. But it is a lot of coordination, a lot of effort and kind of all hands on deck when these things do go live. Think of it like a mini EHR go live. You want to be as prepared as possible because these are high impact tools and kind of a different type of tool that they've had available to them than in the past. So we made these, you know, kind of our two big key points. You know, ambient documentation and then the big bang of generative AI high points for the year, big focuses for those months that that happened. And I think that targeted approach, targeted education and targeted feedback, you know, being able to take that back to our vendors and have improvements made from there that all led to very successful deployment of of these tools,
B
that makes a lot of sense and is, you know, really helpful to understand that mindset and how you go into understanding where different people are at along the adoption scale and then, you know, looking at those workflows and figuring out how to communicate with them and having AI really be supportive to the things that they're doing on a daily basis. Now something else you mentioned there too is thinking about the value to the health system and the roi.
C
I would.
B
Do you think about that, how you're measuring that? I think, you know, it's one thing to look at some of the soft roi, time saved and everything else, but you know, when you're thinking about the big investments that you have to make in order to get this right, what makes the most sense for you when you're trying to figure out, hey, is this actually doing what it needs to do? And you know, what is that? Return on investment?
C
For sure. With today's financial climate and uncertainty in health care, you do want to be a good steward of the resources that you are provided the kind of initial approach that we took, you know, with, with ambient documentation, we knew there could potentially be a financial ROI with that. Yes, there are soft ROIs with like you mentioned, decreased time in notes, decreased time in the ehr, more time with patients, decreased burnout. Those are all kind of soft and hard to quantify financially there too. But if you have you know, say an extra 15 minutes, were you actually, you know, using that 15 minutes a day to throw another patient on you? That those questions were, you know, of course big on our, our finance side and actually with some of our pilots, we did require that our pilot users, if they were going to use the technology to help cover the cost, you know, that they would have an additional patient per, per clinic day there. But as we went on and saw some of the other benefits of this, a little bit lower provider turnout rate and definitely decreased burnout metrics that we were seeing, you know, we did become a little more la on on that requirement. And I know a lot of other health systems have done this, the same thing there with some of the generative AI functionalities. I mentioned the non clinical side of things in coding revenue cycle, those are ones that are kind of, I would say no brainers to implement. You know, that is something that can absolutely potentially get you a financial roi. We even have one for our providers that helps them calculate their standard level of service, E M codes based on decision making. Were they coding things properly with mild, moderate or high levels of complexity there they have a little calculator that AI can read their note and tell them, you know, which, which level of service to code. So that brought a little bit of financial ROI there as well. The inpatient folks, you know, being able to get their discharge summary done faster too, you know, so they could move on to, to see their, their patients. Those key AI functionalities where you absolutely can see a financial ROI is kind of key to getting things started. And then those help to pay for, you know, some of the other functionalities that may have more of that soft ROI based more on efficiency and time savings. I can use some of these to pay for those. That was kind of the mentality that, that we. It's also nice to have. For example, with EPIC systems you can have a monthly fee for many, many different generative AI functionalities. So you know that you are getting your money's worth by having the revenue cycle side to help pay for the clinician side of the AI functionalities there too. So focusing on, I guess I could mention that too, you know, focusing on your key strategic vendors that you already have. There are some vendors that health systems, you know, pay seven figures or more too, that offer embedded generative AI. Now, why not use those as opposed to searching out a third party? You know, that is a, that's a niche area. You know, get your money's worth for what you're, for what you're doing. I think with financial headwinds this year, there's going to be a lot of health systems that have to think that, you know, you know, if they do have to prioritize things, prioritize what is already included or included with a minimal or a bump in, you know, licensing fees as opposed to, you know, a huge investment in something else, you know, we, we have to weigh the options of each of those and what works best for our system at that time. What works best for that service line or service area that time. There's, there's a lot of different ways to go about it while still being, you know, financially responsible.
B
That's helpful to understand. Thank you so much for providing a bit of extra context there and, you know, seems like a very important thing to be thinking about as you're looking into the future. Speaking of that, what are some of your big priorities and headwinds that you're focused on for 20, 26?
C
Oh, for sure. It's, it's the scale of AI, you know, not just getting, you know, things available, our providers, because it's really, you know, even though it's available to all of our providers, not all of them are using it. I'll be, I'll be honest. We have about a third of our providers who are in that high user category that we will, you know, see broad adoption of. We have another third that are middle of the road where they'll use some but not the others, and another third that seem to be a little bit more disengaged. So our focus is going to be this year on the education of that middle and lower thirds. And maybe we can hit know, 50, 50 or 60, 40, you know, this year. I think education and, you know, perhaps even one on one training on some of these things may help us move that needle for clinicians and how they are utilizing this AI. Another big area is to be able to, you know, properly inventory and document now that all these, these AI functionalities are live. You know, you got to make sure there's ongoing review, make sure there's not bias or drift that happens with, with some of the models, you know, making sure that these tools are still functioning in a safe and high quality manner. We're doing some of these things through our, what we call AI steering committee. You know, every health system should have some sort of AI governance, we call it a steering committee and then that is overseeing and directing some of these tools as we're waiting on different regulatory bodies or legislation to specifically say things, be proactive and start audits yourself and keep track of all the functionalities that you already have live. So this year is the age of continuing education for users. It's the age of inventories, libraries and feedback mechanisms and upkeep all wall weighing additional options with not just the generative AI solutions, but agentic and even perhaps autonomous in the coding arena. Non clinical, definitely best to go non clinical for automation there first as we're waiting on some of the other things to happen with regulatory there too, but getting that groundwork. So you're prepared to take on additional functionalities or more advanced functionalities while keeping in the back of your head, you know, how do I educate my users, how do I ensure safety, quality and regulatory compliance as all these tools are there?
B
And that makes a lot of sense. And I know it's always that fine line between wanting to be innovative, continuing to push the boundaries, but also not taking on too much risk within the system in the healthcare space too. Yes, yes, absolutely. Well, what do you think the hardest thing you're going to have to do in the coming year will be?
C
I think it's saying no actually because of that pacing. Are there things that need to wait, my health system in particular? We're one of the leading medium sized healthcare organizations in the country. We don't have unlimited resources, so. So what makes sense for us, you know, may be something that is provided through an existing vendor, like I was saying, rather than some new, latest and greatest things. What can we take on throughout all of this? It may. We may have to say no to focus on instead upscaling what we already have, educating who we already support and things like that. We don't want AI to overwhelm all of our users, but we do want to be transparent with what's available, how we can support things now, things like that. I guess you could call it pacing yourself. Yes. We deployed all this stuff, we got things going. Can we maintain that pace? We'll see. We have to balance the yeses with the no knows.
B
Absolutely. And I know that can be certainly no small task, especially the volume of things that are coming at you and your colleagues on a daily, consistent basis. And so, yeah, I know you've mentioned being able to, you know, kind of like make sure you've got things covered with your existing vendors and partners along those lines. And so, you know, when you do have folks that are excited about something new or coming through, how do you communicate, you know, and identify the things that are going to actually make a difference and decide on taking on new partners when that situation arises?
C
That's one of the ways that our AI governance helps out as well. We do have an update to our vendor intake forms. Everybody's got their own way of getting new technology or new services into a health system. So embedded within that, we now created our own AI review. The AI does focus on generative, agentic or autonomous. We have other mechanisms in place for machine learning and some of those, quote, older forms of AI. And one of those questions that's on there, first off, what's the need? Why are you looking at AI for this? And then another question is, does our are what we call trusted vendors? You know, those vendors that you spend a lot of money on and you better be getting your money's worth from, do they offer a similar technology? And have you explored that? And there's always that. If not, please discuss with information services or informatics because they're, you know, up on this technology. They're in the know of what our vendors are bringing. They know the road maps of where our vendors are going. And so that is that point of entry for our vendor. I think if it hadn't happened before, then it gets caught in that process and it allows our informatics and IS teams to take that opportunity to work with the requesters and show features that are available. And our vendors have plenty of documentation on that or happy to jump on calls to explain some of those things. Embedding that in a review process or that formal intake to get your budget dollars approved, that is our way of making sure everybody knows what's going on.
B
Got it. That's helpful to understand. Well, before we wrap up here, I wanted to ask you about growth. Where do you see some of the best opportunities for organizational growth in the future, especially considering all the different use cases for AI and how quickly the technology is evolving?
C
AI itself can bring so many efficiencies there, you know, to give time back to our providers, our nurses, our care teams. You know, one of the, one of the top reported benefits of using AI, charting from our providers has been, I get to spend more time with the patients and that's what's medicine is, is all about. And we've thrown so many other, you know, hoops to jump through just to be able to deliver care to patients. So I'm very excited and glad that AI Charting has been able to provide that connection back with our providers. And as we take things live with our nurses this year as well, our nurses can spend more time with their patients too. So giving time back that, that is precious and is so helpful for growth for our, you know, employees there too, our users of this technology of AI. You know, the same thing can happen on the, on the non clinical side of things. Getting administrative tasks done faster, getting through that coding work queue a little faster, that will, will help in their efficiencies too. As a, as a health system, we are blessed with organizational growth as well, where we are expanding our reach throughout the state, able to support especially some of our rural hospitals in the state of Indiana with our technology too, offering through our EPIC Connect program as well, and also some managed services agreements. Rural health is very important and is very much struggling and, and so we're happy to be able to provide services there. You know, some of this, this AI technology, you got to think that there is some equity concerns going on too. How can a small hospital or maybe FQHC clinic, you know, afford some of these technology tools? And you know, there are larger health system partners that can help out in that area too. There is some growing change, at least at Indiana's legislative level, to also offer assistance to critical access hospitals and others that may need access to these tools too because, you know, the technology will help promote safer and higher quality care. All areas of care delivery should have equitable access to these tools. And I'm happy to be part of a system that wants to share that, you know, with these other areas that may, you know, have a bigger bit of a struggle to, to get there.
B
Absolutely. I think that makes a lot of sense. And certainly, you know, having that ability to support other facilities really keeps that care local and makes sure everybody has access to what they. So I think that's very much a point well taken. And thinking through how quickly technology is changing, there's so much possibility and potential. It seems like a really exciting time in healthcare right now.
C
100% agree.
B
Absolutely. Well, Dr. Mavis, thank you so much for joining us on the podcast today. This has been a really fun conversation. I can tell you're very passionate about everything you do, which is so much fun. And look forward to seeing you as well at our annual meeting. I know you'll be speaking on a panel. We'll be dig deeper into many of the things we talked about today. And so I'll look forward to seeing you there.
C
Thank you so much. It's been a pleasure.
Becker’s Healthcare Podcast
Episode: Scaling Generative AI for Safer, Smarter Care with Dr. Mark Mabus
Date: March 3, 2026
Host: Laura Deardo
Guest: Dr. Mark Mabus, Chief Medical Informatics Officer, Parkview Health
This episode features Dr. Mark Mabus, CMIO at Parkview Health, discussing how his health system scaled generative AI to drive safer, smarter patient care. The discussion covers Parkview's journey from AI pilots to full-scale deployment, practical lessons in change leadership, strategies for measuring ROI, governance and risk management, and future opportunities and challenges in AI for healthcare.
Dr. Mark Mabus’ Role: Practicing family physician; Chief Medical Informatics Officer (CMIO) at Parkview Health, overseeing clinical-technology intersection, EHR, and provider efficiency.
"I sit at the intersection of clinicians and technology...making sure that EHR AI...create efficient workflows, safer care for patients, and quality care." [01:20]
About Parkview Health:
AI Deployment Strategy:
Provider Reception & Measured Impact:
Key Takeaway:
Workflow Customization:
Education & Communication:
Process Management:
Soft and Hard ROI Metrics:
Budget Strategy:
Broadening Adoption:
Governance & Safety:
Preparing for Advanced AI:
AI's Equitable Efficiency:
Network & Rural Health Extension:
Addressing Equity:
On Building Trust in AI:
"We know we're not getting into automation and, you know, computers making diagnoses for you. Nothing like that. Nothing going to replace clinical judgment." — Dr. Mabus [03:22]
On Practical Change Management:
"You got your early adopters...your middle of the road folks...and your, we'll just call them slower folks...So when developing best practices, we don't just look at those high technology adopters, we look at everyone across the board." — Dr. Mabus [07:32]
On Financial Stewardship:
"With today's financial climate...you do want to be a good steward of the resources that you are provided." — Dr. Mabus [11:24]
On AI's Biggest Benefit:
"I get to spend more time with the patients—and that's what medicine is all about." — Dr. Mabus [23:32]
On Growth Through Collaboration:
"Rural health is very important…and so we're happy to provide services there…technology will help promote safer and higher quality care." — Dr. Mabus [25:45]
Dr. Mabus brings a pragmatic yet optimistic perspective, emphasizing partnership, measured growth, and equity. He advocates for scaling proven AI uses, robust governance, and keeping patient care—restoring provider-patient time—at the center of technology choices.
“100% agree.” — Dr. Mabus, closing