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April 5, 2024: In this episode, Brett Oliver, CMIO of Baptist Health System KY & IN, Lacy Knight, CHIO at Piedmont Healthcare, and Matthew Sullivan, CMIO of Atrium Healthcare, have open discussion around a variety of topics. Is AI at its current stage worth the challenges it poses in terms of cost, efficiency, and interoperability. They delve into the complexities of adopting AI platforms, the need for standardization in imaging technologies, and the role of clinical decision support in enhancing patient care. Thought-provoking questions arise, such as: How can healthcare organizations balance the rising costs of AI implementation with the imperative to drive down overall healthcare expenditures? What strategies can be employed to overcome the challenges of integrating disparate imaging systems and ensuring seamless data exchange? How can CMIOs leverage their influence to navigate organizational complexities and drive technological innovation in healthcare?

Key Points:

  • Smooth AI Integration
  • Imaging Standardization
  • Clinical Decision Support
  • Cross System Communication 
  • Large vs. Small System Issues

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Transcript

This transcription is provided by artificial intelligence. We believe in technology but understand that even the smartest robots can sometimes get speech recognition wrong.

 Today on Keynote

(Intro)   If you look at the executive order from the White House, it was 70 some odd pages. There's not one mention of patient outcomes.

Healthcare is mentioned a lot, you look at any study that's important to us, it's always about patient outcomes, and yet that's absent in some of this oversight and so that's what we're really trying to hone in on.

My name is Bill Russell. I'm a former CIO for a 16 hospital system and creator of This Week Health, where we are dedicated to transforming healthcare one connection at a time. Our keynote show is designed to share conference level value with you every week.

Today's episode is sponsored by Quantum Health, Gordian, Doctor First, Gozio Health, Artisight, Zscaler, Nuance, CDW, and Airwaves

Now, let's jump right into the episode.

(Main)  All right, it is keynote and for keynote today we have three special guests that that were recently with me at a 229 CMIO event. We have Brett Oliver, CMIO Baptist Health Kentucky, Lacey Knight, Piedmont Healthcare out of Atlanta, and Matt Sullivan, Advocate Health Southeast Region.

And gentlemen, welcome to the show. How are you, Bill? looking forward to the conversation. What we're going to do is we're going to do a recap. What's top of mind for CMIOs and what's going on? It was a great event. And I tell people that The 10 minutes before the show and the 10 minutes after the show, I wish I could record.

The best stuff happens 10 minutes before and 10 minutes after. People will just have to use their imagination of what we talked about 10 minutes prior to this, but it was a great discussion. I'm going to kick this off. So we had 17 CMIOs one of our 229 roundtables.

which is two half day sessions where we discuss things that are top of mind, challenges successes, and those kinds of things. What I'd like to do is just kick us off. Share the most significant takeaway from the recent CMIO meeting. What was one discussion that really particularly resonated with you?

And we're gonna start with the most responsible person here. We'll start with Lacey.

So I'm gonna Introduce at least a couple of different topics. So on the wins that I think really valuable to other groups, I would say a lot of folks are trying to figure out how to get more. Physician involvement and optimization and making improvements and looking at what types of structures are in place to be able to engage larger groups of physicians and some of the peer group did a really great job at that where they've got, dozens of physicians that are engaged in informatics or physician builder.

Method and partnering with their local service line representatives and really owning the responsibility of making sure that their peers within that specialty group are engaged in optimizing the EMR. I thought that was a huge win and others that were really anxious to learn a little bit more about that.

And then I'm sure others will add in terms of the opportunity. Everybody's trying to figure out how to manage this little AI word that has become very popular over the last year. I'll maybe leave it at that and let the other two kind of jump in on their

topics.

Brett, what about you? what's some things that resonated with you in the discussion? I think

along the lines of what Lacey had to say, one of the things I learned that a couple of folks were doing was having informaticists in the supply chain meetings. Just a very specific finding, but understanding, hey, wait a minute, we don't need that product.

We can build that. We already have something like that, that maybe supply chain isn't always You know, knowledgeable about. I know in my organization, that's one of the entry points for AI and technologies that we've had conversations with to try to say, hey, can you make sure that if the vendor says there's some AI on this, that we have an evaluation through our AI governance piece.

But I hadn't thought about having an informaticist actually sit in on the supply chain meeting, so that was one just personal takeaway that was related to what Lacey had to say. took both comfort continued stress about the AI word in the sense that, no one's got this Figured out fully my question to the group was, I don't have data scientists in my organization and for those that do or are thinking about that, can you get away with it without it?

Do you think, and really the consensus was you need some kind of data scientist involvement, whether that's a third party vendor that helps you out ad hoc, or you employ them, or you're, an academic medical center that already has a bunch, but figure out how you do that. You need that expertise.

Both in the evaluation of the model, etc., but I think even more so on the monitoring of it, especially the generative models as we start

to play around with those.

I'll leave it at that, Matt. What did you

learn? What do you think? Bill, you've asked really good questions about what is the theme and what would we take away.

this wasn't my first 229 event, and so I came to the table really kind of excited to hear how the collaboration was going to go, and there are a couple of themes I'll tag right on behind Brett. That theme of helping each other, which we were joking about a little bit right before we started this recording, but really, if you don't have the resources, who does?

And what can you learn from your colleagues at the table. And then afterwards, we've had a number of conversations around AI and around data sharing and around concepts, even since our event two weeks ago. And so that continued connectivity and the ability to share ideas and an understanding that you may not have all the resources in the world because you're a small hospital system or a single hospital and I think we've really started to.

Elevate that conversation where we are a trusted group. This is the group of people that I would go to ask a hard question. Hey, I'm struggling with, I don't know the right answer here. What did you do? How are you able to get this one across the finish line and, or pull this one back? And I think that's really.

What I came away reinvigoration of that team. And the other thing that ran thematically through all the conversations from all of our colleagues that got up to give the presentation was how the CMIO is influential and strategic in the organization. And so moving away from. What may have been the one techie guy who was willing to be a subject matter expert on your first EMR install 15 years ago, to someone that is sitting in the room, helping making decisions that influence the organizational outcome as it relates to physicians and nurses and patients, which is really our

passion and our

core driver. We were starting to hear that come up in lots of the portions of the conversation, regardless of the topic, whether it was AI or supply chain or whether it was some other topic that's brought up, everybody to be strategic in the work that they did, which I think is an elevation of the work that we do and gives our job a lot of purpose and a lot of influence, which I think is really a nice thing to have in a

career.

going to go in that AI direction real quick that was teed up, but first I want to recount the story we were talking about. I'm going to do the PG version of the story. We were talking about prior to this, and the reason there's, it needs to be a PG version is nothing can screw things up quite like computers, right?

So it just does it in a way that it's just out there, everybody gets to see it and whatnot. And Lacey, I'm going to have you share the story, but essentially my chart was displaying curse words in to through the interface and those kinds of things. Walk us through.

The process for troubleshooting that and how the event sort of plays into the troubleshooting process.

Be a little bit more generic, I think, in just describing it, but there's a patient that reached out to to us because of some concerns about an expletive displaying in their patient portal.

And so we looked at it, and I engaged our patient portal team, and they did some evaluation, they checked, and they couldn't find what that patient was seeing. So I thought, okay, this is unusual, maybe I'll check with a different team. And it happened to be a patient looking at a portal for organization, but looking at a result for my organization.

And so I thought, alright we've done our own internal looking, so let me just reach out to Matt, who I've know very well through these types of connections and network and reached out to him and he said, Oh, this is pretty interesting and connected with his team and they did some research and connected with the vendor and relatively quickly realized that this was something that was related to AI sitting on top of web browser for that patient.

We'd done all the due diligence in terms of looking at our internal software teams, looking at our information security teams, making sure there wasn't anything dangerous happening. And then just as a matter of the timing of this event we'd connected with someone who represented the company behind this AI and reached out to them directly and they got on it and within a few hours it was fixed.

And I'm not going to mention who the company was but a large, very large company that remarkably took such great attention to something that was impacting our patients that they had it resolved within a few hours. So it was impressive, and I think really highlights just the level of network that can be established that you wouldn't even think about needing to leverage the network for this.

Usually we're asking for, a little bit of advice and nothing that's time sensitive, but because of the relationships we developed over the last couple of years this problem was routed out in under an hour.

It was awesome. I want the three of you to sort of comment on?

the Discussion around AI itself are there concerns? Around the pace at which we're moving is there concerns around? the impact it can have on things, both positive and negative. there concerns around the transparency or lack of transparency around these models?

I mean, is the concerns that you're hearing with regard to AI? We'll go in reverse order. Matt, with you.

Happy to kick it off. The topic continues to hit the press at the highest level. Wall Street Journal article yesterday, not just about the things you've alluded to here, Bill, but the real question that we all struggle with, which is value.

Is AI doing what it's supposed to be doing from large corporations who are trying to tell you, oh, this will be the greatest thing? But the reality is, I think what they've been telling us is an excellent vision. We're not there yet. We're seeing small incremental pieces of it, but nothing that is supportive of the investment that you have to make at a large scale to deliver outcomes that change the game.

We're seeing in Pockets where it can be helpful but until we decide that we're going to get rid of all of our admins and use the computer to take notes at any meeting it's got to be pretty darn good, and that's just the simplistic large language model listening in over the top of, a standard Teams meeting and not to target one company or the other, but it doesn't matter whether you're listening to a company that wants to come in and Use AI to do data transformation.

Okay they're going to charge us for that. That charge we've seen has GPU cost that's really high right now, should come down over time, but really hard to fund with an ROI, unless you're going to get rid of all your data scientists, people, which we're not going to do. And so right now we're in that weird gray zone of we can see what's happening, not sure it's really effective, understand that it's very expensive.

And I think if you are really innovative, you can be on the cutting edge. If you are on the bleeding edge, there's a potential for some significant losses. But we'd like to watch it closely. We think the vision is right, at least I think the vision is right. And I'll leave the sort of safeguards and looking inside the black box and understanding to Brad

and Lacey

here.

Yeah, Brad, you guys have to be a little more selective, right? don't Have the budget to just go and start adopting all these different things. How do you determine which areas you're going to explore with regard to ai?

Not to be boring about it, but it's really where are the challenges and the problems that we have.

I'm not trying my best not to look at the bright and shiny and utilizing it because it's the latest, tool out there. It's what are our organizational priorities or service line priorities? And then, what am I seeing in the landscape? I would agree with Matt that, we're not doing anything in my organization, and I feel like we're leading on a few things, but nothing that's taking the human out of it.

It's always going to have a human in the loop right now. To add on to what Matt was saying, there was a paper from UCSD, like Science Daily, that really called out for patient outcomes to be the driving force. If you look at the executive order from the White House, it was 70 some odd pages. There's not one mention of patient outcomes.

Healthcare is mentioned a lot, but that's what you look at any study that's important to us, it's always about patient outcomes, and yet that's absent in some of this oversight and so that's what we're really trying to hone in on. We've got a few radiology algorithms that are in play now, and sometimes it's really hard to determine what that ROI is going to be.

The radiologist likes it they feel like it improves their efficiency, but it's not really a timestamp thing that you can do, or yeah, I think I found a couple extra pulmonary nodules it's kind of squishy right now, and I think it's probably going to stay that way for a bit and we have to develop some structures to help evaluate it more objectively.

But patient outcomes, I, it really bothers me that's not more of the industry discussion.

And Lacey, I'll change the question a little bit going to you, which is we used to have patients walking into doctor's offices with, all their Google research and WebMD research and plopping it on the desk and saying, I think I have this.

And the doctors would just roll their eyes like, Oh gosh, here we go again. Isn't that same thing going to happen with AI? I mean, I'm researching high blood pressure, I'm researching this, I'm researching this, and I walk into my doctor and I go, I think I have this. Really, where'd you get that?

I got it from OpenAI, I got it from ChatGPT, and it seems pretty reputable, it walked me through, these are my symptoms, this is what it said, I, isn't that going to happen, and how do we get in

front of that? Yeah, I think I think it will. I think because of Really open access to medical information.

Maybe we're a little bit more prepared for it than we were when Google first started. I think that idea of democratizing information allowed the physicians to change their perspective on whether or not they're the holder, the holders of the information or guiders, patient guides to how to navigate the information, how to deal with it.

I think one of the challenges with the, specifically the open AI framework, it's democratized access to AI in a way that not really many people have figured out exactly what it's gonna mean, and it's also en enhanced the ability of these companies to incorporate advanced tools that they may not fully understand.

And so for all of us. There's a hundred times more people bringing forward these types of tools than there were 12 months ago. Plus the patients asking about it. And we are still trying to catch up, I think, in terms of expertise. I think knowing what's right for the health system.

It's something we've all spent a lot of time doing. So making sure we're focusing on things where we have existing problems, having some sort of process for intake and process for evaluating what types of things get funded and invested in. Those, I think, stay the same for us. But I just think that there are just many more vendors and inputs and questions coming to the same groups of resources.

And I think maybe the thing that I would say, I'm trying to figure out how we need to prepare is really the overall competency and what depth of bench strength becomes the new norm. That's the part I think we haven't figured out. Matt referenced the data scientists. Brett talked about it also, how we kind of.

concluded that we need that level of expertise. But do you need one? Do you need 20? Do you need a partner? What is the next wave of healthcare look like with technology and what types of folks do you need to support it? I think that's a big question.

think it will be interesting to see if a health system trains a large language model and essentially becomes the trusted source.

Instead of going to just generic chat GPT, we have trained models. And you can go to ask Piedmont, ask Baptist, ask Advocate, and get some responses thought through and that really governed by our local health systems. Cause one of the things I've heard over the last two weeks, having been at different events is the national data, the big massive data is all nice.

But what we're finding more and more is that local data is really important when training these models because, asking the question based on training from Texas isn't going to help the Atlanta population or the Baptist Kentucky population or whatnot. Each population has. It's own different set of nuances and predispositions those kinds of things.

I don't know if there's a question there. It's just missed being in your meeting with you guys. It would have been fun to

talk. If I could add one more concept that I think how we've gone back and forth on. So 20 years ago, we had best of breed everything. Then we consolidated to one platform and then we've moved to where we were trying to augment this single platform with some of these other tools.

Most of these tools coming at us rely on some independent platform, so they're all supposed to be in a physician's workflow. But they create different workflows, so we're trying to think about, our physicians like your tools, but now the physician needs 20 different applications on a smartphone that don't work together.

And that's not an easier way to operate, too. But I thought that was, it's important to make sure that attention was brought to that topic as well.

I was just gonna say I think you're 100 percent right. I think that platform strategy slash concept is critical. The typical IT project, six, nine months, interfaces, integration, rollout, like it better work right at that point.

Versus these are new products. These are new ways of doing things. Can I try it? I get that from my colleagues. Can we just try this? Like no, it's a couple hundred thousand dollars of servers and interface. If you've got a platform established Where the platform itself is doing all the connecting with these third parties, then you can try it out.

Maybe even if this, for instance, CAT scan is done with the same protocol, you could run it retrospective on your data to make sure that the ROI they tout is what you see. I think we'll see. Some of those emerge, in different areas of the more traditional players that we have in

the market.

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Matt, I'm going to put you on the spot with regard to this platform thinking, which your two peers just brought up, because literally on my phone right now, it just came up.

A new approach helps atrium health reduce falls and the costs associated with that. When you're looking at those kinds of things, are you thinking platform, or are we still seeing Independent solutions come in for each one of these, this hand washing and falls and all that stuff.

For organizations, I think a platform has got to be the way you go because the iterations that are required, you've heard both my colleagues talk about three or four different ways to touch, where AI touches clinical care.

A huge push toward outcomes. You're not going to have a one trick pony. You're going to have a platform that allows you to do all of the things that we're hearing about. It can be subdivided into a couple of platforms, clearly things that do operational, visual things in a healthcare environment like falls and hand washing and patient turning and wound care and all the pieces that, that we could potentially improve.

are, is a little different than something that sits behind or on top of an imaging platform. And we split a little hair there to think about is radiology from a visual or an imaging perspective different than pathology, digital pathology? Or will one platform of AI have things that are applicable to both of those worlds because we're seeing it on an image?

I don't know the answer. I think we're early there but conceivably. And then you have, one thing to learn to manage. One thing to tweak, one thing to pay for. Again, cost becomes a huge issue here, and everything that we've talked about today from an AI perspective is an add on. It's not a add and replace.

Now, if you put AI into the behind the scenes and you're coding and you're billing and you're collecting claims, probably prior authorizations, you could make a case that these things covered their cost. In many other ways, it's just add on cost. And so The rising cost of health care, the United States already spending the highest percentage of GDP on health care.

All of these facts just sort of sit on the chalkboard and you just look at them, check them all off, and you realize we've got to do something different. We've got to drive outcomes in a different way that lowers health care costs. And raises the efficiency of the providers, which we know are diminishing, right?

We're not training physicians to accommodate the population growth. We're not training nurses. And some of those folks are leaving the workforce quickly. So can we use AI to help augment that? And if so, Do it on a platform so that you can also get a couple other low hanging fruit there and not have to lose your shirt and pay for it and drive the cost of healthcare up.

Add on to that, Bill,

one quick thing. I was at a meeting following our 229 meeting, talking to the lead radiologist for NAI, the organization you guys would all know. And even for Legacy AI products, I can say the stroke world, they are going and saying, when your contract is up, this particular agreement is up, you need to be on this network or we're done because they don't want all the maintenance.

They want that platform piece. And so I think, for any of the vendors listening, pay attention to those platforms because I think that's where we're going to be heading.

Imaging is a great example. I love facilitating these meetings because I get to poke at the wound a little bit here because when I sit there and I hear, yeah, we're going to platforms, we're going to platforms.

I'm like, all right, so what are we going to do around imaging? Because invariably, if I asked everybody for a document that shows your imaging platform, I'm going to see 5, 6, 7. The most I ever saw was 22. 22 different imaging systems different storage capacities and those kind of things. And then you're going to drop this AI in there.

And you go, all right AI typically resides in the cloud because it's high compute kind of stuff. You're not building those clusters on site. Now all of a sudden you're looking at these 22 systems saying, We've got to move this image from here to here, do the processing, bring it back down. And just from a, logistic standpoint, it's just not going to work.

But what's it take for a CMIO, a CIO, and the leadership to drive platform? stay in imaging, because it's it's one of the biggest failures I had. I thought, oh, this is going to be easy, and we did it in radiology, but I was unsuccessful in other areas. as the economic situation sort of driven realization that, hey, we have to do some of these things as a technology platform drivenness, or has the culture changed in such a way that we're able to drive these things, or is it just still incredibly difficult? Lacey, we'll start with you on that one.

I would say it's still incredibly difficult. But I think that over the last couple of years, because of the inflation costs and some of the agreements that had this built.

Then CPI adjustment. That model where the product didn't change, but the cost increased, it isn't sustainable. So that forced us, for example, to just rethink, do we want to have this type of interaction with a lot of different types of organizations? Or do we want to Pick certain types of partners that will set up a maybe more favorable relationship.

It's a little bit longer term, and we may do some co development together to try to achieve some of the needs that we have or test some types of things. So I think that framework of thinking is a little bit more, I guess, stewardship friendly, longer term. But it's as a Result of having multiple different types of kind of one off applications where the cost gets driven up without any change in utilization or any additional benefits.

But I think in terms of standardizing for, let's say imaging, I think it's maybe for us is about picking which problem to solve. So it might be the case where we won't select the problem that we can't apply to the various types of technologies. We'll try to pick a problem that allows for, all the varied connections on one side can meet in the middle for a some sort of software that may lay above everything else and see if it works that way instead of trying to pick what might be the absolute best for CT scans, the absolute best for MRIs, the absolute best for ultrasounds.

We may look for something that advances us, but plays well with the existing systems.

that was a great answer. Do you guys want to Touch on any further? I think

Lacey covered about 98 percent of it. Yeah, I would just

say at the times I feel blessed, I have one PAC system and one way of entering of the radiologist dictating the notes, which makes my process a lot simpler.

I haven't piecemeal together 22 different systems like that

and others.

Yeah, sometimes I'm speaking about this like it's so simple, but you're right.

It's

much more complex. of our prompts in the 229 project is, share a challenge that you're currently facing and whatnot. And one of the CIOs said, He put up his diagram, it had 22 PAC systems, and he's I am all ears whatever advice you have, help me out here, because this is killing me.

And it was a great discussion, but it is one of the more challenging projects. It's not a technology project, almost, very little of that is a technology project. It's a change management project. I do want to close On that question. what goes on in that room stays in that room.

I'd love to hear generically. Most pressing challenges identified by the group and how they're coping with some of those problems. And maybe you could share again, just high level, this is what the CMIO is looking at today. These are the challenges. This is how we're coping. Brett, we'll start with you cause I've started with these other two guys.

I've never put you on the spot,

I think

one thing that emerged for me was just. Clinical decision support in general, whether it's AI or it's not, and just how do we stay on

top of that, govern it,

And have teams built. I mean, the three of us can't be in all those meetings. How do we have teams built that can represent us well?

There's a level of, whether it's AI or just CDS literacy that I think we have a responsibility in our organizations to create a roadmap to develop over time. But yeah, I'll leave it at that. I think just overall CDS as a subset of AI.

Yeah, because there's an awful lot of AI that has been in place in CDS for a long time.

It continues to evolve. HCI, I think it's HCI 1. is the reg that people are talking about, which is requiring transparency on those things. And, that's something that's probably falling on your plate, isn't it? the government wants transparency on these models. Do we have transparency on these models?

Can we put those out there? That's going to be an interesting challenge over the next year or so, is how much transparency is required. Yeah, you

brought up, I mean, one of the CMIOs specifically, that was her challenge, was HTI 1. And Interestingly enough, there were several folks in the meeting that were like what?

What's that final rule? So it brought some transparency amongst the group. I will say that this is kind of both a comment as well as just to illustrate the connectedness of this 229 group as because of that question happened to go to this meeting last week where Mickey Trepathy was speaking, and it was a relatively small group.

And so I was able to bring the questions from this particular CMIO and that came from the group directly to to Mickey and again, I, it's just, it's a fabulous group to have together and now I watched it for three different sessions form and

it's incredibly valuable.

If anyone wants more information on HCI1, I interviewed Mickey Tripathi earlier this year on HCI1, and so there's an episode on this channel. Just go look for Mickey Tripathi, and we go into detail on some of those items, so it should be interesting. Matt, challenges that CMIOs are facing right now.

What resonated with you?

Yeah, I think depending on the organization, the CMIO sits in a different position often and with different levels of influence. And so one of the challenges that we heard in a couple of thematic presentations was how am I able to get something across the finish line? I still see that there's a big struggle there.

role of sometimes being in the position to say, no, that's not a good idea, but also wanting to champion things that drive clinical care, physician satisfaction, and patient outcomes, but still trying to figure out how to do it appropriately with the right security, with the right funding, with the right governance, and all those components, I would summarize in saying how to carry the ball across the finish line.

And that I think is a struggle

for everybody.

The thing I appreciate about you guys in your role is there's positions of authority, there's positions of influence, and the CMIO role as one of those rarely has the position of authority where you can just drop the hammer and say, this is what we're going to do every now and then you can do that, but it's rare.

It is a position of influence. It does require. A set of skills, soft skills, I guess is what we used to call them. I don't know if we still call them soft skills, but the ability to move an organization with conversations, with dialogue, with identifying champions, with demonstrating value. Matt, I'll throw it back to you on that question.

How do we get things across the finish line as a CMIO who doesn't necessarily have direct authority in a lot of these situations?

It is about influence, but it's also about combining the informatics skill of understanding the data, how to get the data, where the data lives, who manages the data, how do you transform that data, make sure that it's accurate to deliver.

the message, right? So data creates that story, that message, but then you've got to also create the clinical story, whether it's from physicians or nursing, from the patient's perspective, some sort of story that convinces people, ah, yeah, this is the right thing, because not everybody's going to sit down and pour through data.

Not everybody's going to believe you. But if they hear the story, so it's that skill set, those are the two soft skills that when put together, you can get people to understand, oh yeah, this really does impact healthcare organization. Oh, there's data behind it? Oh, great. Or vice versa. Oh, look at the data.

Oh yeah, it does really affect it. And it depends on who you're talking to. Having conversation with financial people is completely different than having conversation with physicians. And that's okay. That's the multiple costumes that one wears. Multiple hats, whatever your euphemism.

Sometimes it's a full different costume every day, four or five times a day. Get that across.

It is a picture in my mind, man. I'm

Sometimes the costumes are made out of Kevlar. Sometimes. But, Brad, you wear feathers. It's all

cool.

Yeah, and Lacey Question to you, your last one to answer this one challenges that you heard that resonated.

So I think the way I would think about it, first, I just want to be grateful. I think all of us would feel this way about the organizations that we're in because they have. This legacy of investing in these types of resources, informatics, and development in teams. And what that yields is high level of sophistication from the organization in terms of the types of information that they're looking for, the types of data, the types of solution.

So I think for many in the group trying to make sure that we have the right understanding. of what's out there and that the investments are made in the right types of technologies is a significant challenge. It requires a lot of time because the questions that our organizations are asking are again so sophisticated.

And then for some others that are perhaps in organizations where the role is a little bit newer and may not have the complement of informatics type resources across different clinical disciplines, it's really about developing a workforce. And an understanding of how the role fits in the organization, how the role solves problems for the organizations, and even how to support other types of clinical informatics leadership roles, integrating into the role, like the CNIO role, for example.

So I think hearing that was interesting to me because I think sometimes I don't always appreciate that these really tough problems to solve are only because, we've already had the opportunity to go through a number of the basic tools and questions along the years.

Do you guys find that the size of the system dictated the conversation a little bit?

I remember I was on a panel discussion and I'm sitting there, 16 hospitals, 700 staff, ridiculous budget. And the person next to me, Was with a single hospital system. Her IT staff was like 14 people and we started talking about the problems And I realized she still had cyber security problems She still had all these things that I had to do the EHR She had to do with her 14 15 person staff that we had.

I mean there's different set of challenges I mean, obviously when you're talking 16 hospitals, there's complexities, but I couldn't believe I was just I was looking at her like I don't know that, I don't know how she does what she's doing. Do you find there's a significant difference or is it very similar problems even small to, to large?

, I

think the problems are always there. We're, we actually intentionally put our group together this last round to be very mindful of who was there from a large system versus small. So we had a couple of people that had two to three hospitals and a couple of people that had over 60. And. And the problems are the same.

How you approach the problems and how you get to the solution is very different. And it's nice to hear. I think you hit on it, Bill. They have a very limited staff. They have to take things out of the box a lot. There's no customization. You just get what you get. On the flip side, larger systems sometimes over customize and then make a mess.

And then they have other problems that they have created. And it was a nice dynamic in this last meeting. with lots of different viewpoints on that.

I want to thank you guys for chairing the event and not only chairing the event, but hosting the event. So you guys did double duty and actually facilitated the conversation and kept the thing in line.

So I really appreciate you guys doing that and being a part of it and taking the time to come on the show today and share. So Thank you again. Really appreciate you guys.

Thank you.   📍

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