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Ryan Pfeffer: we make every single effort to make testing as easy as possible. Because if you can't test rapidly, that time to value just gets longer and longer. And so the more you can sort of reinforce those expectations and the ease of lowering the bar for testing that's really what drives the difference.

I'm Sarah Richardson, a former CIO and president of this Week Health's 2 2 9 community development where we are dedicated to transforming healthcare one connection at a time.

Newsday discusses the breaking news in healthcare with industry experts. Now let's jump right in.

Sarah Richardson: (Main) Welcome to Newsday! I'm joined today by Ryan Peffer, head of Engineering at Notable. Ryan is a highly accomplished technical leader who thrives at the intersection of deep expertise and breakthrough innovation. Known for building a plus teams and a plus products. He's passionate about creating exponential impact where one plus one equals 10.

At Notable, he's helping transform healthcare delivery through intelligent automation, data-driven engineering, and thoughtful production design. Brian, welcome to the show.

Ryan Pfeffer: Thanks, Sarah. Appreciate you having me.

Sarah Richardson: Absolutely. And we love our partnership with Notable, having spent time over two years now at the annual conference and being able to really see your product in action.

our summits, our dinners, any of our events, it's literally the topic of most evenings and days. This article explores how executives are evaluating the practical use cases amidst growing pressure to drive ROI and operational efficiency. Before we jump into some of the meat of the article, I literally wanna ask you are also AI component driven in your org, but what is the differentiator and however the last couple of years has it potentially changed some of the conversations y'all are having with clients at Notable?

So it's not just AI driven, it's really the engineering that goes behind creating a product that is truly giving physicians time back.

We will come in and we'll work across different categories of workflows. So whether that be value-based care or rev cycle or patient access or the contact center, we have something and we have capabilities that allow you to create your own something and use AI along the way to really take things that are sort of rote tasks that we would typically, have somebody do and, and turn them into automation so that those people can do higher value things for the organization.

on the tech side, the way that we make that happen is we sort of think about it two ways. First there is sort of the full agentic world that I think a lot of people talk about, which is sort of, you know, this idea that I'm gonna give this agent

Sarah Richardson: And there's a level of avoiding AI fatigue and being responsible in innovation. Yes. And it's real. The result of overpromising under Delivering IT Leaders or implementing strict pilot protocols. For the record, I'm not a fan of pilots, especially free pilots. And there's a sense of proof of concept, which could be akin to the same type of space, but you've got these time

boxed spaces where certain results need to be delivered. The ROI the components with your CFO outcomes, with the clinicians as an example, how do you help literally use the product to ameliorate fatigue while simultaneously not creating fatigue in just the type of energy it takes to put something like this forward?

that I'm gonna need to put in to making this thing go from, first touch on the integration and getting data into the system to actually making it effective so that I can turn it on with real patient and real data and feel confident that it's going to work. And so, any vendor that.

you wanna work with it can sort of show up with that plan on day one and, walk you through it with confidence and tell you what your part is through that experience. But also tell you how they're gonna show up as well within the product itself. really comes down to understanding that with this automation, it sort of feels like anything is possible.

Here is what decision, what was made, and here's how it continued to flow from there. The second thing is we make every single effort to make testing as easy as possible. Because if you can't test rapidly, that time to value just gets longer and longer. And so for those sorts of things, we think that, the more you can sort of reinforce those expectations and the ease of lowering the bar for testing that's really what drives the difference.

I loved when I went to your conference in the fall. And spending time with the team and literally using like the Viseo type diagrams to map out each of the workflows where that power is in the hands of your clients. When you go into designing with somebody, a new group and really thinking about how things are working, how often are they able to get better from things they've always done a certain way, versus how much learning is shared back to you?

Like where's that balance showing up?

Ryan Pfeffer: I love that you're asking that question. So, here in the San Mateo office in California. We flew a customer of ours, a longtime customer of ours from the East coast, and they've been here, it's their third day with us. And, some of their first questions to us as they started

But like, you know, the reality is, is like, do you know English? Great. Do you know any language? Great. Can you type in that language? Okay, then you can do something on our platform. And that just feels incredibly compelling and like eye-opening to people. So, what we've noticed is not only do they walk out of our sessions with us with.

A handful of each of them, right? Each of 'em has a handful of different use cases that they wanna bring back to their leadership to say, Hey, I think I can do this. But what's also fun is we have our engineers here too. And so, like right before this call I was on our release notes channel in

slack and one of our engineers who had been in the office this week was sort of watching them play around with the product and ship three new features to sort of like, help make that testing experience a little bit easier and help people work through, it's just minor UX things that, those really add up and they make the experience and make people wanna come back and continue building.

It saves time, it improves accuracy, it improves patient experience. When people come to you and they say, okay, tell us how this is playing a role in reducing documentation, burnout and error rates. What does that conversation look like?

Ryan Pfeffer: At the end of the day, people just want to be working and doing less administrative work and doing more care for the patients, right? And so, it usually starts there. Of why does this take so long? Why is it so hard? And frankly, like the technology is the secondary and a conduit there.

And once you walk through that, you start to pull out, okay, well what's actually happening in this spot? Why is it taking so long for. Referrals to get processed when they come in off the fax line. Well, it turns out that like we have one person who it's their job to take all these faxes that are dumped into this folder and then to just look at them and triage them.

But it turns out we have one of those people and we literally have like hundreds of those that things coming in a day. Oh, and by the way, that's like a side job that this person does off the side of their desk. Right? And so then you start having real conversations around, okay, well really what we're talking about here is like categorizing a fax, right?

They sort of form a representation of that using some matrix math. And then using that you can then start to determine what the intent is behind all the words in the document. And just empirically, you can then test and prove that with that technology, yes, this is always a referral order versus some other, random thing that can happen to come through the fax line.

And we see all sorts of crazy things that come through the fax line. And so again, this comes back to that testing thing I mentioned earlier. If you can then take in a bunch of faxes that came in over the last week and prove with a high enough accuracy rate that you can actually do the right thing

Sarah Richardson: every time I hear faxes, I realize they're E-fax now

but still every once in a while. Let's be honest, when we have major outages faxing is still a thing, and I keep waiting for pagers to make a comeback. It's kind of my inside joke. Most people, I'm like, they still work in the technology that never dies. What it brings though is a layer of instead of just predictive regenerative ai, it's solving pain points.

When we think about the NLP backend provider burden, documentation, accuracy, data abstraction doesn't overhaul all the workflows. It just streamline some of these capabilities. What are some of the biggest wins you have seen by, I'm off on the side of my desk trying to manage faxes as an example, and now bringing 'em in through these processes.

What are some of the coolest wins you have? Seen with clients that didn't know what the art of the possible was with Notable, and now they're like, oh my gosh, I have so much time back to do work that I wanted to be doing.

Their job is to get patients to see the physician and they had all these steps they had to do within the electronic medical record system to make sure that the insurance was done, to make sure that the, the co-payment was in and that all of the forms were filled on

and then they had to transcribe those forms from the paper into the thing. And so, there's, there were people who like. There were tears rolling down their eyes 'cause they didn't have to do this mundane task anymore and they could just get back to their work. And a lot of what we're doing today has those similar effects.

Right. So, classic easy one that people like to start with on Notable is like, Hey, like I know I need to reach out to this, large patient population about coming in for their regular screening can I do that? And of course the answer is yes. And they're like, okay, well how many weeks until we can run that?

Is because the more that people can sort of get their hands on it, the more they realize that there is deeper possibilities here. And so. a lot of ones that are coming up for us is just like, you know, two xing productivity on submission to prior auth for both clinical you know, sort of the deeply clinical things.

We have sort of this hybrid approach where we're doing all the heavy lifting to sort of take in the whole patient chart and then summarizing it and providing that data into a sort of a hybrid suggested model, so that's a big one for us. Of course the voice modality is just really compelling as well.

So being able to, not only text and do web chat, but also do a live voice call on sort of very specific tasks in order to do, basic data collection or checking on somebody after a, post-op sort of thing. All of these sorts of things tend to come up pretty quickly and once people start realizing what's possible,

Fantastic. When someone realizes, oh my gosh, my day is not spent hunting down all the ways to get ahold of a patient, just to get them in for some of their preventative screenings. And I've seen it live action where it's like calling and it's recording the information. A pretty special place to be in for sure, which is why I love the final article that we chose Shopify, CEO.

He put out a memo that said. AI integration is essential for workforce survival. So high level made headlines for saying that AI will soon become a baseline skill, asserting that employees who ignore it will fall behind and though written from a commercial tech perspective, the message does have wide implications for healthcare leadership and workforce strategy.

You're using it at work. And when they taught them the history of it, real-time application, and then had 'em come in and play with prompts, like how would you share a diagnosis with a medical professional? Versus an 8-year-old as an example and having the most fun with it. What I loved, Ryan, I said, who is using AI the most creatively in your organization?

The chaplains. Who would've thought that they would use that to be able to reach anybody on their domain of how you know, they need to see a patient. They can basically put the information in and understand all kinds of different cultural and religious preferences of their patients. So when you see something like that, hey, AI is now an essential skill.

Ryan Pfeffer: Yeah, it's such an important thing, which is the sort of that change management process. Right? And so I talked about this early on, but like generally there's this sort of have you heard of the J curve of any change, right? At first it sort of feels like you're going backwards a little bit, but eventually if, as you continue pushing through the change, you reach a higher plateau of outcomes.

And so again, working people through that change is an important part. But I would say in terms of technology, I've already sort of mentioned it once here, which is sort of that, like this idea that the future is for the builders, right? And the one thing that we're seeing, and it's happening in tech first, right?

And so, we, we certainly see that here internally at Notable, but sort of just sharing those anecdotes can be really helpful. But also just once you share people a tool like it clicks, right? This is something that I can use to get leverage for my health system.

Or this is something that I can do to continue to be relevant in my career. Right? I can't tell you how many physicians that I've ever talked to who said I loved doing medicine, but there was just so much administrative burden that like it weighed me down.

We always, people talk about pajama time and all these things, right? But at the end of the day what do they want to do is they want to have sort of like higher impact to improve the health of the people that they serve. And sometimes the best way to do that is to actually go fight that sort of bureau bureaucratic burden and, try and automate it, right?

And so, it's been really fun to see that transition happen.

Sarah Richardson: What is though the right balance of automation versus the human interaction piece. Because too often you worry about, okay, AI's gonna take over. It's not, there's humans in the loop and I've long said that the empathy component of the physician taking time with the patient, I go back to Covid when very beginning, especially when you have patient's dying and they just want someone to hold their hand.

What's the right balance right now of humans versus machine?

Ryan Pfeffer: I mentioned this earlier, that's the reason we start with that whole journey mapping to begin with is because you don't really, it varies as per part of the journey, right? But it also matters that you are including the humans at the right place and point in time.

So, for example, when you know, you're able to sort of take some of that administrative burden off of your plate, I'm not taking any notes right now. I'm back to back in meetings all day, but. When I'm able to have live transcription going in the background, right? It just reduces that mental burden.

Sarah Richardson: What do you keep an eye on between AI, healthcare IT? What do you believe isn't getting enough attention right now that has you most curious?

Ryan Pfeffer: I'm hearing about new cool things that are happening every day. And it's seemingly interesting to see how quickly we've gone from sort of these very primitive use cases to sort of like full blown experiences, right? And so, early on when it was, there was a lot of generative AI on images.

And so like in some regard. With that rapid progression, if we are not able to get much, much better at like testing, like you can easily see how that can sort of run away from us, right? Because that tests the ability for us to verify this is doing what we think it will do is what enables us to maintain that confidence that we are in control of what is happening here. And that's why I think, any vendor who is worth their salt in this space should be thinking about testing really first and foremost.

Sarah Richardson: Often you'll hear people say, well, it has to be X percent correct. But humans make mistakes all the time.

We don't necessarily have a way to prove all of that. What's the threshold of accuracy that is accepted right now?

Right. And so that's just how much ambiguity there is in terms of answering some of these questions. And so in that case we look at it, Hey, we need to at meet or beat sort of the 70% agreeableness on those things. And so it really comes down to what is the human equivalent in terms of achieving a certain outcome.

But obviously, yeah, if you can. Do things to maximize outcomes and you want to continue to push it further. If the juice is worth the squeeze as they say there's no reason to stop.

Sarah Richardson: One last question for you. When a CIO, CXO, anybody in the facility, let's say put this hat on, is looking to make a decision about AI investment, how does a leader know what to prioritize, what use cases should.

Be coming forward first so they don't get swept up in the hype.

You want to have that as part of your plan. But again, as part of that change management, it's better to just start with, okay, here's a simple thing to just see and observe the system. And when they do with us what they notice is like. I can see the whole workflow end to end. I have full transparency into what's happening.

And because the testing was built in as this thing was rolled out I can actually see and have confidence that not only is the product going to do what I expect it to, but the Notable team that as I'm working with them will actually help me and walk me through that.

And so that's what's worked well for us. And so that's what I encourage people to do is think about that. solution that isn't gonna just lock you into one use case, but really it's gonna allow you to sort of go where you need to go so that your spend always has the utilization and the value that you're hoping to get out of it.

Sarah Richardson: I love that. Thank you for taking time to cover how to make the right investments, how to appropriately transform an organization with the right parameters, and also how to create the right, I'm gonna call workplace survival.

And not because your role is going away, but because you actually know how to use the tools most efficiently and effectively that are being presented to you. And when you do that with a partner, like Notable, sky's the limit. Right. Awesome. Ryan, thank you so much. We appreciate you. Appreciate your partnership, and for those of you listening to Newsday, thanks for tuning in.

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