Today in health, it generative. AI is next. Let's see, 48 months in healthcare. Let's go with 48 months. Four years. Sounds like a long time to talk about what's going to be happening with generative AI, but we're going to give it a shot. My name is bill Russell. I'm a former CIO for a 16 hospital system.

And creative this week health instead of channels, dedicated to keeping health it staff current and engaged. We want to thank our show sponsors who are investing in developing the next generation of health leaders, short test and artists. I check them out at this week. health.com/today. Having a child with cancer is one of the most painful and difficult situations a family can face. If you can imagine it.

Finding out your child has cancer has to be devastating. In 2023 to celebrate five years at this week health we are giving back. We're partnering with Alex's lemonade. Stand all year long. For the fight against childhood cancer and the search for cures, we have a goal to raise $50,000 from our community.

We're already at 34,000, a little over 34,000 for the year. And, , we are not doing a drive this month, the month of may, but in June, we'll be back with another drive. , we would ask you to join us the easy way to do it. To hit our website. Top banner has a logo for Alex's lemonade. Stand. Go ahead and click on that. And you can give today, we believe in the generosity of our community.

And we thank you in advance. All right. You can credit this. The conversation today to Taylor Davis. Taylor Davis, , formerly with class now with a new company, eye health. Oh, he, he, he's a founder of a new company, health it peak advisors. I think that's it. , yeah, that's it. , hit peak advisors.

, Taylor's a great mind in healthcare, loved the things he's done, especially around the arch collaborative. , we've interviewed him before on the show specifically around the arch collaborative. And it was a phenomenal show. If you're not familiar with it. I point you to that show. Great discussion. Great conversation.

A really good thinker. Well, he put a post out there on LinkedIn. Around generative AI. And it got me to thinking, you know, as a CIO, a lot of times I would sit back and I'd have these maps of different technologies. And I'd say, you know, I'm still in the hype cycle. Let's give it some time to bake before we decide where we're going to.

Utilize it within healthcare and what we're going to do with it within healthcare, that kind of stuff. Or I would say this is coming out of the hype cycle. This is where I think it's going to emerge. And that kind of stuff. And Taylor got me thinking, let me give you his post. First of all, because his post in and of itself is incredibly provocative. And here, here you go.

Again, it's Taylor Davis. Healthcare AI earthquake. Take your expectations for AI impacting healthcare. Triple them. That is probably not enough. This one is going to be big at hymns. In the last week I met with over a dozen CEOs. I mentioned AI in almost every conversation with only a couple of exceptions.

The common answer was AI will impact healthcare. Some. We are watching it closely.

So he hedges a little bit and he has the story, John Glasser talking about his belief that, you know, we get together before hymns determine what the buzzwords going to be. And then we. Amplify it. , exponentially, , that year that he was referring to John Glasser was population health this year.

So he goes on. And this is interesting. It is rare when this happens, but this time the hype is warranted. My predictions for AI in healthcare next 24 months, healthcare lags in uptake of AI compared to other industries for good reasons. Obviously we're talking clinical here. It's going to take a little bit of time.

By 2025. Other whole industries will have been transformed by AI. Sure. We will have some setbacks where it does not work as well as we expected, but in many cases, companies will shed 30% of their labor costs. Wow. He goes on how system CEOs will watch these self-evident and shocking transformations. They will realize that the race is on whoever masters, the AI transformation first.

We'll have a whole different cost equation. With which to grow market and transform expediency will be the new push revenue cycle in particular, we'll see greater than 50% of current workforce replaced by AI. And that's understandable. There's a lot of, I just think through that, that. That cycle that, that, , the revenue cycle workflows and the massive amounts of people and how much of that can be really fine tuned with these generative AI models. I'm pretty sure that 50% is an accurate assessment.

A few health systems will stumble in dramatic fashion, but public embarrassment is not the greatest risk. That goes to health systems that could not shed 10 to 20% of their costs. They fall behind competitors and are acquired. , hopefully acquired. Much as we have seen with epic this past decade health system acquisitions will be driven in part by the value proposition of expanding technology that is working across.

The new acquired group. Oh, and for hit vendors, I currently offer digital workflows for highly repetitive processes. Your solutions will no longer be needed as the whole workload is taken by AI automation.

And he closes with a little, a number of things that you can do, right? The races on time to prepare. Here's the four things. 1, 2, 3, 4, 4 things he gives to consider one crate governance plan for AI adoption, balancing speed, safety and responsible adoption will be hard. It will be easy to go to one extreme or the other.

That's number one, number two, decide now how you will approach staff replacement. It's a real thing. It's. Going to be happening. Get in front of it. Number three, create an analytic strategy that can monitor the adoption of AI. You'll need data to ensure that new automation is successfully replacing the processes. That's number three and number four, create the roadmap of what will likely be automated. And when helps you to realize how much work you have in front of you, and he closes with this.

We have never seen a technology so disruptive that can develop itself through recursive functions. The hype is warranted. And a bunch of hashtags.

I love this post as so many things to love about this post one is you, you see why I like Taylor Davis? He's a, he's a good thinker. He doesn't hold back. He gives you, , you know, the process and what he's thinking. , I think he's pretty well spot on. I think for the next 24 months, we are going to move slowly. I will tell you, in other industries, I'm talking to people in other industries.

And they are experimenting with some really cool stuff at this point. , think personal digital assistant. That you feed all of your personal documents into a feed in your insurance policy, your healthcare policy, your, , , your, , banking statements, your all that stuff. And then essentially you can ask a questions about you. Like, Hey, I just had this happen.

You know, where's the best place for me to, to grab cash, to pay this and it will go, oh, well, we, you know, we looked at all these things and here's the answer to your question. You will have a personal digital assistant. Actually. I heard bill gates talk about that. And that was. That was really, , an interesting concept that we would all have our own personal chat GPT. That's trained on our personal information.

You know, so that's one aspect. , one of my, , staff members. , was talking to me today about a new way of doing search. On this week health and they've been doing research and essentially we could feed our entire website. Into a generative AI model. That's actually, I think the backend is chatty PT.

3.5. And it will then take all of our interviews that we've done, which is thousands of interviews at this point. And it will take all the transcripts, put it all in there and then you can ask a questions. Like, you know, how has Intermountain approaching, blah, blah, blah. And they'll say, well, bill interviewed.

Craig Richard, Phil or bill interviewed, fill in the blank and it'll have the answers to those kinds of questions. So you see search being transformed, you see personal assistants being transformed. When he talks about accounts payable departments, there's a lot of repetitive tasks in that. And the thing about AI is it's amazing at it. Can watch those repetitive tasks.

Learn from those repetitive tasks. And instead of us having to program these very complex RPA things. It learns as it goes. And N essentially says, I know what the next step is. I know how to do these things. Now, granted, we have to put in these. We have to put transparency in to the cycles to understand what it's actually doing. How is it making its decisions?

, but for the most part, we can see how it's making this decisions. And if you can create that feedback loop where it makes us decisions, it says, okay, here's, here's the invoice I'm looking to send out or here's this I'm looking to send out. , then it's going to continue to learn and it's going to be quicker. That's where his prediction of 50% less people.

In your revenue cycle. , comes in, but think about this. How many times do you have a call center that gets asked all these various questions? I think generative AI, one of the places it's going to Excel. , we think chatbots today, but I think in terms of the, , replacing the overall agent. Because it's smarter than your agent because it can, it can consume.

The the. Just the vast amounts of information that you have available. And so instead of looking up this database and this, , knowledge base and this. , system and that kind of stuff, you're going to feed it. You're going to feed it with as much stuff as you possibly can. And then it's going to be able to answer questions.

, with a high degree of success. And especially on that administrative side, I think we're going to see things change. And I think he's right in that we will see other industries, other industries right now are looking at this saying we're going to redo our business model and they have a propensity to think that way, like we're going to redo.

How we approach our market, how we interact with our customers, how we interact. , with our suppliers and whatnot. So they're right now looking at this going okay. This is going to change how business is being done. It's actually what I'm doing right now as well. , and so that's, what's happening outside of healthcare, but I agree with them. It'll take us about 24 months.

We have to be careful , in the application of applying this to medicine, we have to be extremely careful. We cannot have mistakes. Therefore, we're going to, we're going to push this off. , even longer than the 24 months in the 24 month timeframe, we are going to see things happening in other industries. We're going to see new products start

, to spawn and come up. And then we were going to essentially, we're going to adapt those to the back office of healthcare and health systems. The same way we were talking about RPA is the same way we're talking about this right now. Which essentially it's going to be applied to the administrative. The financial side is going to then be applied to the logistics side. How do we make the consumer experience of interacting with our.

, health system easier. , I would say you're looking at , 24 to 36 months and then 36. , plus I think we're going to see a rapid adoption , Of these models when we can train them on our specific data, on our specific EHR data, on our specific, data banks, research, , information around our, , communities that we serve. , we're gonna see it start to get applied much more to that interaction with the patient.

And I don't know where it starts and I don't know where it ends,

This is going to be a wild ride and it remains to be seen where it can take us. But I'll tell you, I'm talking to technologists. Who have been in the industry for a long time. Talking to technologists who have seen things hard to impress people who are looking at me saying, no, this is a game changer. This is truly going to change how we conduct business. This will change how we approach workflow. This will change how we interact with our customers.

And so it's really hard to know where this is going to go. I mean, we're seeing so many different applications of this technology even today. I'm just pulling up videos. I'm talking to people, . And what I'm hearing is the use cases are all over the board. In fact, that's one of the coachings that I would give you is to not limit people. I mean, obviously give them guardrails in terms of how they can use the data that is proprietary to your organization or the data that is protected.

Data of your patients. But outside of that, let them experiment. They will surprise you. It's amazing. The use cases that we are hearing as this progresses. All right. That's enough for today. Do you know, if someone that might benefit from our channel, please forward them a note. They can subscribe on our website this week called.

Dot com or wherever you listen to podcasts, apple, Google, overcast, Spotify, Stitcher, you get the picture. We are everywhere. In fact, I w you know, if you do have, you know, some use cases that you're seeing that you think are really interesting, shoot me a note, bill it this week, health.com. I'd love to hear about it.

Uh, finally, we want to thank our channel sponsors who are investing in our mission to develop the next generation of health leaders, SureTest and 📍 Artisight. Check them out at this week. health.com/today. Thanks for listening. That's all for now.