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I'm not sure it'll be all that different, but we've

had a lot of fun on the virtual options.

I was talking to somebody yesterday. And HIMSS went through their struggles through the pandemic and other things. They had a significant drop off I'm sure before I give you my impression.

I'm curious what your impression has been so far of the conference.

I'm just blown away by the number of people even before COVID coming to HIMSS, you'd have some areas of the conference that were busy, but it's just an ocean. of traffic. I've been really blown away.

So it's been great. It's,

The number of people have really been really helpful. Surprised me. Yeah. So I went to the opening session this morning and listened to that. I looked at the AI session yesterday. There had to be a thousand people at the AI session. Not a surprise, yeah, of course.

What do you expect to see from AI? I looking at this thing here. You guys have a new virtual care assistant and has a persona, has a name. feel like that's going to be a Hal Wolf joked that we're gonna have a bingo game and see if you can find 10 booths that don't talk about AI.

Oh, it's impossible. There's no way. I honestly don't believe you could find 10. It's everywhere. Maybe some of the consulting booths, but Oh no, they're still

talking about AI. Yeah. So what do you think's gonna be the key things? We haven't had a chance to really walk around the booths.

Yeah, it's, I would say Whether it's hosted buyer sessions or separate meetings that our customers have requested. Everywhere, every conversation we have is pretty AI heavy.

And I think the thing that I think all of us in the industry are really anxious to find over the coming months is the balance between augmentation and automation. It's a really consistent refrain. Human in the loop. When do we need them? When are there cases Where we keep them out of it because we're not wasting their time.

We're trying to get the right caregiver to the right place. And I think really being clear and honest about maturity of AI models and what they should be able to achieve and where they need to grow more.

So one of the things I like to do with people is from a leadership standpoint, have this principle where I spend about 50 percent of my time right here.

I want to talk to you about the pace of AI, where it's going, what we're seeing. One of the things I'm talking to people about is, at this pace and the idea that they're going to start. Creating these models that are more narrow and specific, and they're going to get better at a very specific thing, like the human brain works, so you could have a front end chat bot, if you will, and it comes in there and says, All right, I'm going to ditch this over to oncology.

I'm going to ditch this over to a nurse practitioner. And essentially, these AI agents will act as such and give information back. I think in three to five years, we could see that from here. We could see, potentially, interactions with the health system, where each health system is going to have their own persona.

And you have, what's the name of your persona? Vicky. Vicky. You have Vicky up here, but I think you're going to have Cedar Sinai is going to have, Joe, and this one's going to have Betty, and

We can give her a name on behalf of a health system, right? All of those things. Yeah,

and three to five

years

from now, I could see Medicare and other payers saying, Look, we are going to reimburse for certain medical events that happen strictly through AI. Yeah. Because you're investing in this infrastructure and this architecture, and it's keeping people out of the hospital.

It's driving down the cost of healthcare in general. Yeah. Especially Medicare, I can see them going, Hey, this is better. for us long term.

Do you see that same thing three to five? So when I think about the future, one of the things I spend a lot of time thinking about is a future where A. I. Models work together without humans having to bridge the gap.

I. It's not just decision support for clinicians, but it's these things working in concert that allow clinicians to then be doing just the things that make the biggest difference in providing care and you could see setting where you're now having AI that's thinking about care gaps and access to care and quality indicators and remote monitoring.

All these things coming together.

Once people get the hang of this new kind of agent operating within the workflow. Yep. I think the sky's the limit in terms of how people think about these things.

Yeah, think about the number of workflows. In healthcare that involve triage by some sort of coordinator, right?

Somebody who's coordinating caseload, somebody who's coordinating, response to a patient's request. Somebody who's coordinating where a patient goes and when and why, right? We've got all of this more manual work and we struggle to keep up at pace as an industry. In what way do agents displace all of this work?

Coordination, so to speak.

So that's bringing the five years down to the next six months. The next six months. The question is where do we put agents? How do we keep agents is managed the right word in check? How do we keep them from making mistakes? Yeah. I don't,

The only way we're gonna get to smart management of AI driven tools and agents is if we are working together, vendors and health systems in partnership to, to conduct experiments, workflow at a time, use case at a time and being mindful of what we see. And then when we start to see outcomes in this particular workflow and another one and we can connect them together, then that's where the magic is going to happen.

That's really interesting. What do you expect to see on the floor today? Like where are we at today?

On the floor today, boy feel like especially as it relates to how we work with the rest of the market at Avajor, it's really all about interconnected workflow. It's amazing. I feel like we've been talking about that as an industry for 20 years.

And why we're going to help create that experience for health systems the best way possible.

I think what we're going to see is a lot of new solutions around age old problems. Interoperability, access cost of care physician burnout, those kind of things. And they're going to organize around those things and say, hey look, AI can solve this.

But, my coaching, I'm curious what your coaching would be. My coaching to people who are buyers of this is to think in terms of a system. So you don't want to implement 70 different AI systems and then go Oh my gosh, like these don't really work together. So think in terms of a system probably the first thing.

The second is understand what AI actually means. What are you looking for AI to do? Because there is, whenever I'm talking to a real nerd around this, they'll say machine learning is a subset of Yeah, exactly. It's a Venn

diagram.

Yeah, I'm like, okay but if you're a buyer, you should understand those things.

I like what you said in terms of giving advice about, choosing the right partners, the right platform. What I would say is yes, choose your partners based on vision, but only do that in a case where you've got a partner who can help you start with an ROI to build from, You've got to have a beachhead. You've got to have a place to begin. All the AI in the world that you're willing to experiment with is great. As long as there's a place where you can begin from that you know you can count on to produce an outcome.

Yeah.

They're looking at changes that are going on in Washington right now and they're going, we're not getting more money. The reimbursement is going down, it's not going up. It's the general feeling. Medicaid's going to be redone. And so they're sitting there going your concept of where you start is absolutely right.

It's gotta be something that delivers ROI out of the chute. It used to be we could say, and this becomes one of the tougher ones. Because we used to say this is for clinician satisfaction. This is for clinician burden. We've had trouble to quantify that. Now some people will hear this and they'll get mad at me.

They usually do when I say this. But I'm like, okay, start quantifying it. How many people did we lose because we didn't have the state of the art fill in the blank? How many people? Yeah. I think that's starting to become more real because let's just take ambient clinical listening. Yeah. For example, I was talking to somebody yesterday who said he's interviewing physicians and the physicians are asking that question, what are your tools?

On the keyboard. Yeah, I think this is really an important question for everybody here is the philosophy of openness for access and for connectivity versus protecting a particular workflow by keeping it somewhat walled off.

From our perspective, everybody we talked to were being clear the future demands if we're going to be the virtual door to the room, we better be capable of allowing third party algorithms and applications to use our devices as their own. We've got to be able to do that.

So you want them to look for open systems. And we want to partner with other systems who are the same, so that our platform and those platforms can take advantage of each other's endpoints.

Alright, so let's take your platform here for example. There's a bunch of different things.

There's the video feed itself. There's the data that's coming. There's the outcome from your analytics or your AI engine and that kind of stuff. Are you saying that, essentially, somebody else could plug in and grab?

We're not going to be doing anything with large language models connected to clinical language. That's a whole different ball of wax. So we will let a third party, their AI, consume audio from our microphone. They can interrogate that, they can take unstructured data, turn it into structured, send it into EMR.

They can do what they will based on their agreement with that health system. And so we just become an endpoint that's accessible with health system's permission through a secure RESTful API any party that wants to do that. And that's why I say, we're looking across the show floor for other organizations that have that same philosophy of secure openness.

Absolutely. What else do you expect to see? going to give you the last word. else do you want to talk about?

It's one thing to say, oh, our system will deliver on these workforce productivity outcomes. And we're all talking about productivity. It's all, it's everywhere. But what kind of hypotheses are we starting with? And how are systems willing to come together to share an outcome? value do we attribute to different systems and how they contribute to those?

Productivity outcomes. I think that's going to be really fascinating thing to see. It is going to be fascinating. Jacob,

always a pleasure. It was

fun. Thanks.

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