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Newsday: We Implemented Ambient AI Backwards with Angel Mena

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Speaker: I'm Bill Russell, creator of this week Health, where our mission is to transform healthcare one connection at a time. Welcome to Newsday, breaking Down the Health it headlines that matter most. Let's jump into the news.

Bill Russell: All right, it's Newsday, and today we are joined by hel Mena, CMO, for Simr. And of course our intrepid, Intrepid, that's a good word, intrepid, , regular

angelmena: Okay.

Bill Russell: To Ford and Sarah Richardson. Welcome everybody. Look forward to the conversation.

Drex DeFord | This Week Health: Good to.

Bill Russell: I'm looking forward to, I, I, you know, as always, I keep you guys in the dark up until the last minute because I like the spontaneity, of the discussion. which I know that some, some of you on this call may not like as much. But, uh, today we're gonna talk about, uh, you know, we are gonna, since we have a CMO here.

And now we have things like, uh, agent factory and whatnot coming down the pike. We have a lot of stuff. How are, what's, what's the mindset of clinicians as, as, uh, with regard to technology in healthcare today?

angelmena: That, that's a great question. But before I hit on the technology side, I, I'm gonna say that, you know, um, we are clinicians. That's true. And that's the difference between, you know, the four of us here. But I'll say something we've realized as physicians is that we can't deliver care. By ourselves. We really have to acknowledge that there's a team of specialists across our healthcare systems in our industry that are required to improve the outcomes of our patient care.

Early on in my training days, um, the first I, uh, I, I started in, in doing paper charts. So I was part of that transition from paper charts to EHR, and I saw how EHR retired a few physicians. Uh, so we, early on we acknowledged that there was gonna be a disruption of our workflows. And I think that's key here, right?

Is understanding how technology has. Uh, improved, you know, clinical outcomes and improved our work-life balances and, and how we deliver care. But it does disrupt our workflows and we have to understand and acknowledge that. Um, in, in coming to today, what is the mindset? Uh, I, I would go back, sorry, eight years ago where I first encountered the first ai, or at least the first company that added AI to.

Uh, it wasn't up until what I call the commercial ai, the gen ai, the chat GBTs of the world that we started to look into what other problems could we solve, what workflows could we solve? So the mindset now is that we can really implement the technology that we have today to solve the problems that we've been seeing for.

Decades in healthcare and deliver better care to our patients. But we have to understand it's still gonna disrupt workflows.

Bill Russell: I feel like Uncle Drex. What was your first recollection of AI in healthcare?

Drex DeFord | This Week Health: I think for us it was just the, know, I don't know that we necessarily called it AI at the time. A

angelmena: Yeah.

And it, so it was sort of like. Figuring out how to use data to intercept the past. It wasn't really AI in the AI sense of, of, you know, uh, GPT and anthropic and the things we think of today, but we were using it to try to do predictive analytics. And um, you know, that was kind of the, when you think about how long have we been doing ai, we've been doing AI ish stuff for a really long time.

They have a chief medical officer who's watching this stuff happen and maybe has their hand on the wheel, but for the daily frontline physician, are they just trying to make, make it through their day?

angelmena: For, for the most part, I would say yes. I mean, as you know, physicians are, are extremely busy and our quotas, uh, for patient care has have been increasing. We continue to ask ourselves how, how are we gonna, um, uh, finance the technology these days? And that, that comes at a cost. Now some healthcare systems are acknowledging.

That this has to be a pillar because it does provide efficiencies. It does bring better care to their patients, and it's, it, it, it really facilitates the day-to-day of the, the physicians. But for the most part, I don't think they're aware until it's in front of 'em,

Drex DeFord | This Week Health: Until the new tech

Drex DeFord | This Week Health: Mm-hmm.

Bill Russell: I go to see my, um. Uh, primary care doctor, I'll, I'll, I'll talk to the, the nurse who brings me in and, and whatnot. And they're, you know, if I say Agent Factory, they just look at me like I'm insane. if I ask them if they're using ai, they're, they, they have no idea.

But that was, that's what we want technology to be, right? want it to fade into the background. And we want people to go about doing their jobs like they normally do, but just with the assistance they're like, man, the, the, the machine has gotten smarter. servicing the information I need at the right time.

It understands that I'm seeing this kind of patient versus this kind of patient. Therefore, this information's more important to me. Uh, maybe it's doing some proactive things before, uh, Sarah shows up in the office. And it's saying, oh, by the way, you're seeing Sarah today. Boom, boom, boom, boom, boom. Make sure you ask her these questions.

angelmena: That, that's, That's, that's a great point. And, and I remember when we started having this conversations, um, uh, how do we implement ai? How do we understand what problems do we need to solve? You remember the days of the, the hype, you know, was it too much? Was it not enough?

Bill Russell: are we past the days of the

hype

angelmena: Yeah, exactly. But at the beginning it was, and I would say probably in, you know, in the past three, four years, it was more about everyone wanted to use AI for absolutely everything, and we really needed to organize ourselves and put a framework around that, put the right governance, because it's not just about how we implemented, but also does it have the right cybersecurity?

Um, the, we have to understand why documentation became such a problem, and that was because of all the regulatory needs that we needed to meet, but also the billing, the coding that was behind it. So I, I question myself as we implement more of this ambience ai, for example, should we have gone first to the.

Into the documentation, but there's still a lot of hallucination from the AI and we need to review the notes. So if we had fixed that other thing first, I think we would be in a better place.

Bill Russell: It's interesting, the starting point, you know, as we look at, as we look at transformation, if you were, if you were doing this. Greenfield. Like if you were coming in as a consultant, one of the first things you would say is, Hey, let, let's not, let's not just accept everything the way it is.

Drex DeFord | This Week Health: they're being paid, what the care actually costs. I mean, even that would be a debate point, but they're actually documenting all this stuff now. So, it is funny how the blame game around AI has turned into a

Bill Russell: Well, let, let.

Drex DeFord | This Week Health: AI versus provider

angelmena: Yeah, it's,

Bill Russell: let, let, let's go off, let's go off the, the cost stuff. Let's go to quality and safety,

angelmena: yeah.

Bill Russell: because I think we can all agree. We want, we want higher quality. We want, we want better safety, uh, within the system. We wanna make sure uh, you know, no more, uh, wrong side surgeries, no more, you know, just the quality events.

The safety events. Safety events go down, the quality goes up. Across the board. How is, how is AI technology being applied to those things, um, uh, quality and safety today? How are you seeing that?

To the right providers, to the right departments, to the right units in the hospital. And then we lack, uh, information in how do you make it actionable? What is the next step? And, and I think that's where AI has a big opportunity on helping in quality and safety. Um, also redefining. The goals, the targets, the, the, the benchmarks.

Uh, I feel we've been targeting the same quality and safety, uh, metrics, and we are not necessarily seeing an improvement on the overall health of our communities. So, going back, if you remember the, oh my God, the, the, the, in baseball, what's that movie called? Uh, the book? Um.

Bill Russell: Money.

I think we need to do that in healthcare. We need to start redefining quality and safety, and that's where AI can really help us.

Bill Russell: redefining it., Would, would we really redefine it or just redefine what, what, yeah. I'm trying to figure out what the question is here. It

angelmena: Yeah,

Bill Russell: It's, I mean,

angelmena: well

Bill Russell: The metrics are the metrics, right?

angelmena: the, the metrics are the metrics, but are they really capturing. Quality and safety. Um, uh, let, let me try to give you an example. Um, so in clinical practice, we, we go by, in diabetes care, right? We, we measure an A1C, which is a three month average of your sugars. Uh, now we have this devices called CGM, that, that provide you with, uh, a, a frequent reading of your sugars.

So that's my point is that we are gonna have to find out new metrics that are gonna help us def define how we deliver care.

Bill Russell: When we talk about the, the practice of medicine in terms of what, what are the biggest time wasters right now for, uh, for clinicians?

angelmena: Administrative tasks. So anything that, uh, uh, takes me away from spending time with the patient, it's, it's a waste of time. Um, and that's where we've implemented some technology that has helped us, obviously in documentation, you know, we call it pajama time, right? As a time that you spend documenting, putting orders, reviewing records, reviewing labs.

Um, it, it, I, I, I believe the, the latest figures that we have, it's more than three months. Okay. And that's just emails back and forth. Some systems still fax documents. I mean, we can't, we're 20, 30 years behind. We, we need to leverage the technology that we have in place to make those systems more efficient.

I mean, we, you know, they're not gonna show up and start doing surgeries tomorrow. Like, we, we will catch that if that happens. But, no, we don't have the li the list isn't something we could easily generate. I'm like, that's,

angelmena: Yeah,

Bill Russell: to me.

angelmena: you would, you, you would hope though, I mean, one of the challenges, like no one's gonna come in and do a surgery. I, I would agree with that, but then what if they have some certification that's last, you know, and, and, and I think we missed a lot of that. And, and then joint commission comes and see, says, I wanna see your list of doctors and can they practice?

And what are the quality metrics? Right.

I'm like, oh yeah, we're not giving you access. I'm like, I.

angelmena: it's, it's, I, I, I, I know of systems that, um, in, in their bylaws state that they have to vote for their officers, right? For the medical staff. And they've had to redo the votes or the, the, the, the, uh, uh, a few times because just they, they had the wrong list of, of doctors,

Bill Russell: This, this is one of those things where the more we, we dig in, the more we talk about it, you realize technology, um, technology still remains a small part of the answer to a lot of these

angelmena: of course.

Bill Russell: Like we, we, we have to, we have to, we have to plow through, the, the political environment that is healthcare.

We have to plow through the regulatory environment that is healthcare,

angelmena: Yeah.

angelmena: I believe you can do both separately. You have to review your processes and procedures and then see where the gaps are. Work in AI work, as you said, if you start implementing technology and the wrong processes, you're just gonna continue to get the, the not the desired result of the process.

And, and some places are missing. They, they don't have the right governance in place. Also, I have to say, I, I don't want to put more red tape around implementing technology that's gonna really help us. And, and I do see a lot of that happening because we're trying to be very, very careful about it and very structured, which I agree, but we have to be careful not to delay the implementation of the right technology.

Bill Russell: Right. Sarah, you've been quiet today. In fact, I'm not even sure you've said a word yet. Come on. What do you got?

Yeah, tenets along with those three human beings bring forward a perspective [00:21:00] that Dr. Mena and others would begin to trust more thoughtfully in an organization. And so if you don't have everything in place to make things work well, as Drex loves to say, you're just gonna make that training wreck go a whole lot faster.

Drex DeFord | This Week Health: Your point bill, uh. The idea that sometimes we, the processes that we do, the processes that we run, we run because it's part of a larger, very inefficient process.

And so sometimes we bring things like AI to that it just makes. Like it is, there's a lot of like, can we empty all the toys out of the toy box and figure out what's the right way to put this Lego set back together Again, understanding that it's inside of this much bigger Lego set, that there is no moving the parts of the federal government or insurance companies or whatever.

You have a finite amount of control, but trying to make sure that you're rejiggering that as as much as you can to, to make the AI work on the right things.

angelmena: Yeah.

And I think the advent of Agent Factory is going to make builders and coders out of a lot of people who are going to start to. Reach into that clinical data set and do certain things. I don't even know what those things are yet. I haven't had a really good, [00:23:00] discussion around agent factory. I know a handful of systems that are, uh, that are, early adopters and, and doing some things around it, but, uh, I don't have the use cases yet, but I think we will see those clinical use cases go up significantly in the next couple of months.

angelmena: Yeah. And, and if you don't mind, I'll touch in two points that we just made for change management. We would need another hour. Because I agree a hundred percent with you. I mean, you can have obviously the right technology, the right processes, but if you don't have that right change management, the stakeholders, your adoption is gonna be very poor.

And we, we, we tend to explore technologies and then we implement, or we, uh, adopt 10% of their capabilities. And then we have everyone in the healthcare system asking you. So, um, can, can this do this? And I said, yes. Since we implemented two years ago, we were able to do this, but they didn't adopt it, it well.

Uh, but we have to provide the data. So how do we create a framework around that so that they can validate their use cases, create the agents that are gonna truly solve the problems in healthcare, if we don't, if we don't collaborate.

Bill Russell: No, I think that's, I think that's true, and I think that's part of the. Observability of these models moving forward and, uh, and creating those, the ability to capture those statistics that we need in order to validate, uh, the use cases. And of course, ex examine quality as it its impact on quality and safety as it moves forward. and how Sarah Drex, that's all for today. But I wanna thank you guys for being here.

Sarah Richardson: Thank you.

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