August 7, 2023: Curtis Hendrick, VP of Cloud Services at Optimum Healthcare IT joins Bill for the news. In a world where digital transformation is crucial, can a single empowered leader truly drive the necessary changes in large healthcare systems? How can organizations effectively adopt agile methodologies and embrace a culture of nimbleness to accelerate their digital transformation initiatives? What role does culture play in successful digital transformation, and how can leaders foster a culture that embraces innovation and change? Is it time for healthcare systems to move away from expensive, monolithic applications and embrace low-cost, agile products to tackle bottlenecks and achieve quick wins? What are the potential risks and benefits of adopting AI models in the cloud, especially in large healthcare systems with vast amounts of sensitive data? How can healthcare organizations navigate the complexities of data privacy and security when using AI and cloud-based technologies, considering the recent challenges faced by other companies?
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Today on This Week Health.
I've seen organizations just in paralysis and strategy, well, we gotta work out the strategy a little bit more.
And it's like, dude, it's been two years. You don't need to work out the strategy to where you start doing stuff
Welcome to Newsday A this week Health Newsroom Show. My name is Bill Russell. I'm a former C I O for a 16 hospital system and creator of this week health, A set of channels dedicated to keeping health IT staff current and engaged. For five years we've been making podcasts that amplify great thinking to propel healthcare forward.
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Now onto the show.
all right. It's news day. And today we have a lot of really interesting stories to talk about. And we're joined with Curtis Hendrick, the cloud evangelist. I'm sure that's not your actual title. You're probably like vice president of cloud services or something. Yeah,
something like that. There's some H. R.
Title that they've stuck me with the cloud evangelist. I think it's it's the spirit of what I do most of the time.
In health care? Are we still evangelizing cloud or is it more People are right there on the edge going, Hey, just give me one more reason and I'm going to do it.
No, you know what?
There is still an evangelism that's needed because I had a session at chime recently where I came up with the presupposition that, hey, cloud is the future. This is where we're going. And I had half the room be like, No, I don't think so. And I said, All right, well, then let's go back to the basics.
I understand why cloud matters and how it's strategic.
There are use cases where it wouldn't make sense if I thought about it but it's not based on size of the system because I think small systems could really benefit from moving to the cloud if I thought about it.
yeah. Yeah. Small systems actually can get more advantage from it, especially with with cloud first and the concept of going SAS first before you go IaaS and PaaS centric. That can be incredibly advantageous for smaller systems because they can take advantage of the scale of large systems and the manageability of having a vendor manage their environment.
So yeah it definitely is not just a big player game. I think small players get almost more out of it than big players
sometimes. Well, and the large players. We have a question now and we're going to talk AI. Can you believe we're going to talk AI? Oh my gosh.
How do you not talk AI, right? I mean, do you have any of these sessions where you don't
talk about AI?
I, no, the answer to that is no. I think it is, and the reason I'm allowing it is because it is my show and I can like take the conversation in other directions. I think it is transformative and I think it will be transformative. Just like I think cloud, cloud architecture, not cloud itself, just cloud architecture, I think is transformative.
The ability to have programmable services and the ability to utilize internet architecture for the sharing of data and the automation that's available. I think that's transformative as well. Because we're going to talk about AI, I think large systems have this question right now of are we going to utilize AI models in the cloud?
Are we going to build this out? And I think like 95% are saying, hey, we're going to utilize the cloud. And so now it becomes a question of proximity of your data to the source where you're going to be putting it and all those other things. So if you're a large system, you're looking at the cloud because it gives you access to tools that you're probably not going to build out on prep.
Yeah, I think you're spot on. And I think access to data and kind of data being the bedrock of training models with AI is essential. And so you see this base training that happens with large language models that exists with, the syntaxes and how humans understand each other. Like, the ability to talk about things, but the actual content of what it knows the ability for systems to be able to train those models on their data.
So that way, whether it's their patient data, it's their operational data, it's their financial data and having an actual AI assistant that is essentially like an equal employee that exists, that sits next to you, that kind of makes you a super employee. That's where I think we're seeing kind of the rubber meet the road because I think chat GPT and some of these things are novel and there's a lot of really great value that can provide.
It's very generalized and the health systems are very quickly realizing like you see the two sides of the health systems where some of them are blocking chat GPT at the network layer and saying you can't use it period, right? And they're taking that restrictive model. Other folks are like putting out guidelines.
Other folks are doing wild west with it. But what we're seeing is that organizations are trying to figure out how do I take my data? And how do I protect the information I'm putting into the, into these systems and asking these questions for like you've seen, like Samsung's, situation with their code, which at GPT and situations like that, they're showing the challenges that come with using AI without really understanding the implications of what data you're putting into it and what it's trained on and what it's doing with the data.
Yeah. Well, we're going to look at three stories. I think one of them is pretty dense, but we're gonna start with Ed Marks. So, Ed Marks, eight steps to digital transformation. I like this article in that it's born out of experience, right? This is not somebody just sitting there, like pontificating who hasn't done this and hasn't been a part of it.
Ed has done this at the clinic at Cleveland Clinic and at other locations. And I think this article is actually the launch of his consulting practice to help organizations do this. So we're indirectly helping Ed. To even take the message a little bit further But what I want to do is and this is dangerous territory for the two of you.
We're going to critique ed's Eight steps. Okay. And I have a ton of respect for Ed, so I'm going to just throw these out here. We'll talk about them. Eight steps to digital transformation. He has number one, one leader. Each system needs a single empowered leader to ensure transformation, not a title, not a committee, find the right person, align the resources and let them transform too many systems still run by committee.
with thousand points of veto. Stop it. Appoint a single leader and go. But what are your thoughts on that one? I mean, is that doable in today's large integrated health system? Yeah, I
think if you told a large AMC or some academic medical center, something like that, that there was going to be one person and they were going to make the decisions for your digital transformation.
I think you'd have a revolt. And so I like what he's doing here in terms of the centralization of power and centralization of decision making for the purposes of being agile and moving quickly. But I think it's one of those guiding principles that you probably say, Hey, the more centralized we can be, the more effective and efficient we're going to be.
The less centralized we are, the more democratic we are, the the Slower, it's going to be in the more likely we have to, like, never get off the ground. So I don't know about one leader, but, maybe a committee of three or a committee of five.
Yeah. I mean, one would be great.
A dyad would be okay. I got away with early on because we were in such a bad state of things where I was CIO. I got away with a a committee of four and it was perfect. You had clinical leadership. You had myself, you had, I guess, I don't you had a nurse, actually. We had a nurse on that group, and I forget who the fourth was.
I think it was finance. I think that was the four people that was, that were making the technology decisions for the first three years I was CIO. And I only got away with it for three years, and then they just looked at me like, alright, enough. You've got to make this bigger, more people.
And I'm like, it's just our natural
gravitation is to put 20 people on a committee and say. Move the organization and that does not work. I agree with that a hundred percent.
Well, I think part of it too is, healthcare has a lot of overlap with academics and academics seems to be very consensus oriented from a power structure perspective.
So I think there's just a play in there in terms of our proximity to the academic
world. So we're just mincing words here. He says one leader, but I would say as small a group as you can to move it forward. Go agile. Most modern organizations started and remained agile. Check Spotify, Google, Netflix, Facebook.
That is why you see their rocket outcome based evaluation. Smart, mature organizations have completely redesigned their operation and now run like their younger counterparts. And he talks about some that have done that. And you can't put new wine in old wineskins. Most systems still run organization hierarchies leveraged from the time of the pyramids.
You expect to compete, restructure to agile. And I assume he's talking about agile methodologies, an agile framework for decision making and managing projects and those kind of things. And I agree with that. I'm a huge fan of Agile, Waterfall. By the time you put that big Waterfall project plan together and you get like two months into the project, the world's changed.
I mean, I agree with this wholeheartedly. I mean, agile is the way to go. Do you disagree at all? I
would take his almost just philosophically from an agile perspective and less framework wise, where I think speed to making a decision, speed to delivery, speed to value, all being metrics that you would measure in that type of system.
And so, yeah, I. I agree with it probably in both contexts of the actually an agile framework versus just an agile philosophy of being able to move nimbly and quickly and making quick decisions. I've even seen organizations where when they've needed to move quickly, they've stood up essentially parallel it teams that I've staffed kind of net new to be able to be very agile in the delivery of something.
And then later worked on integrating it. Just because it was a necessity because you, again, the old wine skin approach. You may not be able to facilitate agility with your existing organization.
Well, it's interesting. I interviewed the CTO for Tivity, Sarah Richardson's organization and the CTO.
And he essentially said, we went in, we looked at all the legacy and we said, Oh, the heck with that. And they just, they essentially did Greenfield on the other side with cloud based models, internet architecture, automation, whatnot. And then they just slowly moved the. Not the applications, but the work, the workflows and all that stuff, they, and the data, they moved it over and put it into a new platform completely.
So that is in those sort of, you almost have to think differently and build new rapid plans is his next one. And he said, you can take a year and a million bucks, but you know, at the Cleveland clinic, they took 12 weeks and 150, 000 to develop a plan to move forward and you don't need a year and the bureaucracy and everybody to go through it.
I think we have to define what kind of plan we're going to put together in 12 weeks, clearly, you're not going to talk about the digital transformation of orthopedic workflows and the patient experience and all those things when I think he's talking about here is the digital transformation infrastructure and Framework for decisions and framework for the use of data and the use of digital tools.
And yeah, in fact, 12 weeks might be a long time. You could probably put it together quicker than that if I thought about it. Yeah,
I agree. And I think strategy very much dictates direction. And I think that's all of others. Like there's this graphic I like where it's like one big arrow and there's a bunch of small arrows in between it and just trying to align all the small arrows.
To point in the same direction as the big arrow. And so a lot of times strategy is just looking at every little arrow and making sure that they're all pointing in the same direction as the big arrow. And so understanding where the big arrow wants to go is usually the first step there, which I think is his point is great because I've seen organizations just in paralysis and strategy, well, we gotta work out the strategy a little bit more.
And it's like, dude, it's been two years. You don't need to work out the strategy to where you start doing stuff.
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Yeah. All right. So we'll move fast through these last one. Old school methods. I serve on a board. Jen, AI company that goes to systems in two days, a report out savings opportunities, 10 to 18% range on all non labor costs.
Systems resist as they have a GPO that they say do the same things, but don't supply chain leaders may stick to with archaic time and labor intensive processes, not nearly as precise. Territorialism takes over saying your lane, even with the time to achieve savings of 30 days, too many processes and leaders are crossed.
And the initiative stalls. We are talking about near immediate multimillion dollar savings. Stalled over nonsense and pride experiment and adopt new methods and tools, especially when there is significant resistance to change. And I think that gets to what we were saying in the last point, right? Get out there, start doing things, experiment prove the concept and gain as much buying as possible.
noting too. There's an old phrase, right? A cold treat strategy for breakfast. So all of these things, it's so important to underpin it with a good culture and taking, understanding what culture it is that you're trying to develop a strategy within and actually sometimes having cultural shifts be part of the strategy.
Yeah. Expensive applications, silver bullet, a large application and whatnot. And he says adopt a low cost agile product to tackle two to three bottlenecks in your source frustration and measure the results. Some of this, when I hear that. I'm reminded of the Cotter method of, identifying the burning platform and, gain successes and that kind of stuff.
This just born on that model, which says, get your quick wins, build confidence, build champions within the organization and build on those wins as you move forward. And maybe some people are looking at it thinking, digital transformation is going to cost. 50 million and we're going to have to do all these things when in reality, you can implement digital transformation in pieces.
this one's hard for me. I'll be honest because I'm like, I prefer the monolithic systems where I got, this is my ERP. This is my, this is where everything lives. And this is where we, how we facilitate stuff and there's value in that. But I think we might be breaking away from that as a, as an industry, because I think the development is just happening, the innovation is just happening too fast to be stuck with, Oh, this is my one system that does
Right. Committee bloat. I think we covered that a little bit earlier. Board savvy. We didn't talk about board savvy board savvy and active CEO. So, yeah, I've been quoted as saying the CEO is the head of digital transformation in any organization. And I think the CEO is the technology leader in every organization.
Now, I know we think it's the CIO, but it really, there is no organization anymore where leadership, the CEO does not have to be tech savvy. I wouldn't hire a CEO that couldn't articulate. A clear path for technology impacting health care today and almost the same with boards. If the boards, if they have specific expertise in legal or accounting, and that's the reason they're on the board, I think they still have to understand technology and how things like generative are going to impact the financial accounting systems and how it's going to impact contracts and legal and those kind of things.
So, Curious. Any thoughts on the leadership of the organization and their
can't keep it simple. And I usually ask CIOs, does your CEO get it? And that usually covers it, right? Like, do they get it? Because there are leaders that just don't see it.
They don't understand the value, the transformation, the change, the implications of what's happening in the culture and the world around them. And then there's those that do, and they understand the importance of investing and also allowing for some failure. Because when they get it, they are much more willing to allow that innovation, that risk, that failure that could come from doing things faster than they've ever done them before in different ways than they've ever done them before.
So I always like to say, like, does your CEO get it? And if they do, then you're in a bunch, you're in a much better place to digital transformation.
So since this is your second time on the show, I'm going to let you lead the next article. The next article is AI leaders from Google AWS discuss promise and perils of generative AI.
You selected this article. What jumps out at you on this article? Yeah. So
I think everything AI today, I'm just consuming as fast as I can. And so whether it's, Elon's launch of X. AI and trying to solve the big questions of the world, or it's, how chat GPT is being integrated into Epic.
I'm always very interested in kind of what the thought leaders in the space are saying. And so I think that's why I picked this AI one. And I think question that I'm probably left with the most is the risks of A. I. Because if you see folks like, Elon Musk is out there and there was what, 250 kind of tech leaders that all signed a letter saying that the government should, investigate.
Going after regulations and controls over how we do A. I. In the world. So I think that I'm always interested in hearing what people have to say about stuff. And I think that there's the data aspect of it, the privacy aspect of it. The risks and ethics concerns of it, the safety aspects of it.
Those are all very common in terms of my conversations related to A. I. Because I think that we're messing with something that is very powerful and we would be unwise to to not be very careful about that. And so I think their conversation and kind of how they want their perspective in terms of the importance of this and it's transformative aspects of it, but then also, the risks that come along with it and the perils that can come along with AI.
Bill, I'm curious on your perspective is, do you look at the landscape of AI and envision. Or see a possibility of kind of the Terminator type scenario taking place where AI becomes in charge of enough stuff and aware enough to start making decisions against what we would say is our best interests.
And the answer to that is absolutely the man has no bounds or no limits when it comes to doing evil. And so yes, I liken this to nuclear energy, right? All the amazing things that have come out of all the work that has been done there. And actually, it's interesting that we're having this conversation when Oppenheimer's coming out in the movie theater.
Because you're going to see that dilemma that the scientists went through. They're like... Oh my gosh, this is amazingly powerful and it has amazing implications for so many different things within the world. We can not pursue this, but it's the military that grabs them and says. Hey, this can end the war.
We need you to use it in this way. And I'm sure they didn't want to use it in that way, but that is one of the applications. And if you can't imagine putting chat GPT on a toaster at this point and giving it a gun, then you just don't have an imagination. I mean, but at the end of the day, it was how long ago that Steve jobs was on the stage and the Mac said hello world or just hello or something like that.
And we were all like, Oh my gosh, this is the future. Okay, the distance we have from where chat GPT is at today and where AI is at today and where robotics is at today and matching these two things together and having them carry a gun around is, probably, I don't know, 10 years, 15, 20 years. away.
But I believe people are right in that we need to be looking at putting guidelines around. And when we see applications that look like that, we need to make sure that they are controlled the same way we control where I don't know where uranium is. And we control, we know where all the caches are and that kind of stuff.
We need to be able to identify that's a bad use of AI. That's an inappropriate use of AI. We need to make sure that people don't take shortcuts. I'm more concerned in healthcare about the shortcuts people are going to take because we have hallucinations and those kinds of things. I think there's two big risks for healthcare right now.
One is. putting too much stock in AI and allowing it to make mistakes at the risk of individuals. And then the other is lack of embracing it and falling too far behind. And all of a sudden you're sitting there going, how is that health system so much more effective than we are? And we're right across the street.
And the answer is going to be. They adopted technologies that you didn't adopt. I
agree entirely. So there was a thought that came to mind with a recent Twitter space that Elon had hosted. It's not hard. We can think about, hey, we don't want to give guns to computers and that sounds like a bad idea.
But just from a cyber security perspective, if you see all those startups in the cyber security space, they're using AI to try to find vulnerabilities in systems. That gets not far fetched to think that you could train a model to not only find the vulnerabilities in the systems, but then to exploit those systems to be able to propagate itself.
And before, it has essentially distributed itself across the internet. Similar to, I think the premise behind Skynet, but it's distributed itself across the internet by leveraging exploits and open computing that exists through, vulnerabilities that it's able to identify and it would be almost impossible to get rid of.
And so I've been thinking on that one over, over the last couple of days, because I've been thinking how that's going to be situations like that aren't unprobable. And I don't think we're far off from having an AI sophistication that, I mean, we're already training the models to find vulnerabilities.
You just need to give it some level of self preservation as a desire. And you're not far off from it. And so I think it might be interesting in terms of the implications that in the next five years, if something like that takes place, the kind of counterpoint of AI protecting your environment and using the kind of inverse of it to protect your environment,
like we may have to rely on AI to protect us from AI which I think was a later Terminator, I think Terminator 3 kind of hit on that one where they had to unleash the robot or the artificial intelligence to protect them against a threat, right? So one of the reasons I picked this was just because.
The perils of A. I. Are just huge. And I think that we may not be far off from actually living through some kind of sentinel event that we have to. We have that kind of changes the paradigm for us when it comes to.
I have a lot more gray hair. Your hair is not nearly as gray. And I'm thinking by the time the Terminator robot comes to take me out I'm gonna be pretty old.
To be honest I'm not overly worried about it. First of all this type of technology has no feelings. It's not like I need to survive. That survival instinct does not exist unless we program it in. And so it literally will be people with ill intent taking these models and trying to propagate them.
And they're already doing it on the cyber security side. We already see sites. Or you can go in and, essentially it's identifying risks and vulnerabilities and that kind of this world
to say, Hey, here's a use for this technology. And we just see it over and over again. And so that's, that we, there's enough good in the world. That we're going to be able to stay ahead of this, one step ahead of this by using the technology to protect us from the technology.
So we'll see. I don't, this is, I love having the conversation and I, and I hope what people take from this conversation is there are amazing good that can happen with AI and there's amazing bad that can happen from AI. So, don't get, completely wide eyed and this is amazing.
without, being balanced as you look at this and think through how you're going to apply it to your health system. Yeah, I couldn't agree more. Oh my gosh, we are already over time. That was too much of a fun conversation. We were going to get to another one that was a really good conversation as well.
Oh, well, we'll have to wait until the next time we're together. Curtis, thank you for your time and good luck in your cloud evangelism. I believe in what you're doing. Awesome. Thanks, Bill. Take care.
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