October 9, 2023: Chad Webb, CTO at Rhaeos, joins Bill for the news. In this episode, they focus on the transformative role of AI and technology deserts. How do healthcare professionals navigate the balance between leveraging tech and ensuring its effective implementation? What challenges do underserved populations face in accessing modern digital health solutions, and how can we bridge the tech divide to provide care more equitably? As health systems explore everything from easy-button solutions to more complex, open-source models, how do they ensure their approach serves their unique patient demographics? Amidst these discussions, one key realization emerges: while tech is powerful, the real value lies in its tailored execution and broader accessibility.
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Today on This Week Health.
It's not about selling or driving tech and disrupting technology. It's about actually. providing a solution set that makes it easier on the provider side or on the, patient side, which should ultimately lead to better outcomes.
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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(Main) all right. It's news day. And today we're joined by Chad Webb, chief technology officer for Rhaeos Chad, welcome to the show.
Thanks, Bill. Great. Thanks for having
me. For those who aren't familiar what does Rhaeos do? And what do you do for Rhaeos?
Yeah. So Rhaeos is a company where a startup company is commercializing a new novel set of diagnostic systems really focused on hydrocephalus patients, which is a very specific. Neural, neurosurgery suite condition.
But with a technology set that we use for non invasive fluid flow monitoring that goes well beyond that. So, we're in the company space of wearable kind of IoT world hardware, remote patient care. So, hardware elements, software elements, and the whole suite of system in between.
Are you guys still in testing?
Are you out of testing? Is this something... Like, a gentleman I play golf with, his his daughter actually has had surgery and has the drainage essentially from what you said, it was hydrocephalus? Yeah.
So she has a shock system for her hydrocephalus.
And so, yeah, so it drains things out.
But if that ever gets blocked. She has significant problems. So that's what you guys solve. You put, you have some sort of wearable that monitors that flow.
Yeah, so the big problem with that is there is no real diagnostic for shunt malfunction, blockage, like you said, and it is an essential function. And it's a chronic condition, so people, if you have a shunt system, you're most likely going to have it for life,
since there's no diagnostic, they tend to CT scan the brain, MRI, a bunch of really high burden on non ideal things that aren't that great. We make wearable diagnostics that actually non invasively monitor spinal fluid flow through those shunt systems to monitor really, as a data point for clinicians on, is this shunt functioning properly
It's incredible that I had a conversation with the guy this week and that's exactly what you guys are doing. So that's great. Appreciate that. All right, we're going to talk about the news. We've got four stories here. We'll see how many we can get through. We're going to take a look at Oliver Wyman.
Had a conference. They had some luminaries speak, and they talked about disruption. We have digital divide in low income areas. And that was a leader in Indiana was talking about that. Seven AI pitfalls, and we can talk about the Transcaron announcement as well. They tend to get a fair amount of press, given that Glenn Tolman is is in that same category as you guys as a startup, but...
He has a a pretty big platform to get that out there. So the Oliver Wyman it's not about disruption, it's about impact. This is straight from the Oliver Wyman site. They did a Health Innovation Summit. They had a couple, so Mark Harrison, former CEO from Intermountain spoke.
You had gosh, you had a couple of others. Let's see, Austin Chang, MD, Sachin Jain. So you had a bunch of them. And what they were talking about is, let's stop talking about digital disruption. Let's start talking about impact. It's about having impact on these things. And that's how we should measure.
Is it making a difference in the patient? Is it making a difference in outcomes? Is it making a difference in the experience? And things that we're doing as you looked at that article, I mean, what jumped out at you?
Well, so I think it's exactly that, and I really like that one because I think that, it's so easy and ai, and gen AI and everything, and that'll come up in some of the other articles get so much of the spotlight today, but I mean, it's really tech.
Disruption versus impact in general but I liked all the input with these because I think you, so often it's really easy, especially when you have a bunch of, tech nerds like me trying to drive all these different areas and you get this with a lot of these AI platforms and it's easy to build measuring sticks that are Kind of measuring tech metrics, right, in, in deploying there.
But that's not really the metric that anyone cares about. It's, are you really impacting the actual outcome and patient's lives there? So I think it's a matter of, I like their approach on, you got to rethink that a little bit. What's your measuring stick of success with these? It's not about selling or driving tech and disrupting technology.
It's about actually. providing a solution set that either makes it easier on the provider side or on the, patient side, which should ultimately lead to better
I'm curious what you think about the tech, the big tech disruptors, right? So we, I know they're not a big tech company, but Costco announced this week 29 visits and some other things.
You have Amazon and one medical, you have all these different tech players. do you feel like they still have a tech approach to it or do you think they're also looking at impact to either outcomes or experience?
I think, and I think it actually comes up in one of the other articles we have, but, I think Amazon, I think those companies are actually pretty good at showing themselves to have the impact centered approach, right?
Where the approach there is, what's the actual problem we're trying to solve, and the impact we're trying to make. And then let's figure out the, the tech levers and things we got to invent to do it, right? It's part of why I think Amazon diving into the space, Costco diving into the space is a, is an interesting thing to watch because They've tended to have that mindset in the other places they've played in, and it's been a big part of their success.
It's interesting to me because there's whole swaths of people that aren't necessarily going after the health system space, the healthcare provider space. Like, they're not going to stand up hospitals. We're not seeing them stand up hospitals, but they're having a significant impact just because, in aggregate, their announcements are taking, a half percent of the people that used to go to primary care and used to go to these clinics and now they're going to a telehealth solution or that kind of stuff.
And it's not like the half percent that one medical is taking is a big deal. But you marry that with CVS's announcement, another half percent. Walgreens announcement, another half percent. CVS's announcement, another half percent. Costco's announcement, another half percent. All of a sudden now you're looking at it going, Hey, if you're in the Chicago market, you could be looking at, potentially five percent of your primary care visits and five percent of your visits that normally would go through your system.
And your referral patterns are being disrupted.
Yeah, absolutely. So, I mean, it's like you said, those little pieces add up. And I think that they mention it and talk about it in this article and specifically Tommy Patel, when they're talking about what Amazon's really good at, they use the word friction points, right?
And I mean, that's a big part of whether it's Amazon or Costco or a lot of these pieces. It's, at the end of the day, I think the perfect solution is you don't have to think about your healthcare at all, right? And that's obviously not the actual end outcome, but removing the friction points helps people think about it less, right?
So if it's just easier for me to go into Costco or do Amazon delivery or these kind of things. It's a big driver, right, for people moving over
as a patient, I'm really excited to be honest with you. I think there's, we have more options today than we, we've ever had. I want to take you to the 7 AI pitfalls that hospitals should avoid.
Have you been playing with AI
, our company is such an early stage kind of hardware, new diagnostic tech standpoint. we're specifically in this interesting phase where we're starting to build up enough data that, becomes a useful tool.
But, we're not a gen AI large liquid model type company by any means. So we're more like a time series sensor data kind of thing. So. Touch and go, AI itself, certainly not, necessarily my big specific depth on some of the things here, but I think the innovation side, and I think there's a lot of general themes that are around, whether it's AI or just how you try and bring in new cutting edge innovations.
And it's kind of this issue of innovation versus implementation versus impact on all these.
Suchi Saria, CEO of
Bayesian Health and Machine Learning Researcher at Johns Hopkins and Sam Glick, Global Leader of Health and Life Sciences at Oliver Wyman, also at the Health Innovation Summit that was held in Chicago, has these seven things. I'm just going to throw them out. Allowing big tech marketing campaigns to dictate your strategy.
I think we've gotten smarter than that, but still you can fall victim to it. There's an awful lot of it. Assuming AI isn't ready for deployment at scale. I have heard that I've heard some health systems saying to me, we're going to wait see how this whole thing sort of plays out.
However, AI isn't just gen AI, there's a lot of AI solutions, and some are already past the trough of disillusionment on the Gardner hype cycle and heading out. And worth taking a look at. Number three, doing it all by yourself. Number four, confusing AI with automation software.
Number five sitting idle and waiting for the perfect plan. Six, under investing in learning by doing. And number seven, separating clinical and administrative. Many hospitals are interested in the AI tools sold by big tech companies. And these firms often tell providers to start out using their technology in administrative use cases rather than clinical ones.
Saria pointed out, this is seen as less risky by big tech companies, which don't have always have deep clinical expertise, she explained. However, providers can't solve their biggest problems if they focus their AI strategy on administrative use cases. After all, the core mission of healthcare is care delivery, Saria said.
The reason I read that one is, I'm not sure I agree with that one. So, that's why I had to read it. so what are your thoughts? If you're a CTO by trade, if you were, say, a CTO for a health system, how would you be approaching AI?
So my take on that would be, and I think there's a couple, important ones of those seven.
There's, Underinvestment by learning by doing is one I try and think about. I mean, it is, and today's world, I live on the other side, right? I'm the, tech company trying to push tech into hospital systems. But I think either way, it's a, Ultimately, the real implementation solutions and the things that actually make it work have to be done by the learning by doing side.
And so, I think the same applies here, right? If everyone is trying to go after the same goal, right, which is we want to improve outcomes or, and maybe it's tied to value based care models, but Ultimately, the, the tech piece, like the AI tech itself is one small piece of the puzzle, but the more, arguably, I'd say the more important one is the actual implementation and execution on it.
So you got to do it on both sides and you're, frankly, it's not going to be perfect, the first time you do it. So, one of the other points was, you kind of mentioned systems, well, they want to sit and wait, be conservative and see how it goes with other folks. And, yeah, I mean, that you can get where that model comes in, but.
Somebody, some system has to be willing to iterate through that to, to figure out the execution model, because that's the only way it's actually really going to get there.
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we interviewed B. J. Moore with Providence, and he said the easy button for AI. I think there's three, three buttons.
There's the easy, there's the medium, and then there's the hard. The easy is... Hey, your vendor's going to come along, they're going to integrate it for you, they're going to integrate it into the EHR, they're going to integrate it into, and it's going to Nuance being a great example.
A lot of health systems have Nuance. Nuance used to be a whole bunch of people sitting in the back actually doing transcription, even though it looked electronic, it was essentially people doing it, and now they're essentially overlaying that with technology. And so, the people who are using it are now switching to DAX Express.
That's actually AI built in and moving forward. And so the easy button is your partners are all scrambling. A lot of them are scrambling right now to figure out, Hey, is there value in us integrating AI? So that's the easy button. You just, you sign a contract. It's integrated. It's just part of the workflow.
You got to still have to do some things and figure it out, but you have to introduce it to the organization. But that's the easy button. the medium button is you can now sign contracts with some of the large hosting companies, some of the large cloud players that essentially you can move your data up there and you can train these models and these models exist.
So that's sort of the medium button in that. You don't have to, you don't have to create anything and they've given you a sort of mechanism for training the model and you can train your own models now with that data through these things. I'll call that the medium button. The hard button is hey, there's a bunch of open source models out there now.
Like, I mean, there's Lambda 2, there's a whole bunch of them that you could just grab and start playing with. And the question is, and I asked the CIO this past week from an academic medical center, if they would be playing around with that. And in his words, he said, not officially.
But I'm unleashing my tech team to experiment like see what you can do with it let's see if there's anything interesting and it's such a cutting edge and fun kind of thing I think At least the systems that have enough resources have enough people and have the the inclination come up with some interesting solutions.
Now, will they productize those and take those to market? I don't really know, but I think those are the three buttons. Would you be leery of having your tech team sort of play around with these open source models and try to build something out? No,
I mean, obviously, I want to say, yeah, absolutely, let that go.
Obviously, every, probably hospital IT tech team is. strapped with not enough time and needs more people, right? So there's always the bandwidth. Question on that. But I mean, I think in terms of risk, it's you can do that in really low risk ways, right? And I think the big upside to doing that, if kind of on the hospital IT side, if you can strategically align the team around, look, here's a certain, here's the ultimate outcomes we're looking to get that, we think some of these new tools, whether we do them in house, hard button, medium button, easy button, but at the end of the day, There's a change that we think we can make in a beneficial metric, and especially if you can come up with ways to actually measure it early on, I think it just helps, when you've got the measuring stick, everyone knows they're trying to go after you, hopefully spend less time kind of spinning the, tech wheels on, on going down the wrong path, right?
Because that's easy to do with these kind of things. You start, tech team starts playing with all these tools, and can do really cool tech stuff that's Maybe not necessarily actually driving the solution outcome you're really looking for. So I think that's the biggest thing I actually try and be cautious of and watching on that side.
But doing it, I think the benefit of, sticking the team on it early, and as long as you have the right kind of strategic and leadership mindset that recognizes, there's got to be some opportunity for failures here, dead ends and wrong turns. But if you're doing that, if you're willing to take that approach, I think the long term, Really big benefit is you get to shape the system to what you're actually trying to achieve in the end as the impact outcome.
If you just wait for everybody else to do it and build the system that's what some hospital systems will have to do. But I think you miss the opportunity to really drive the maximum value for what you're trying to get out of ultimately these tools.
The next story is actually a LinkedIn post. It's Craig Kenyon, President and CEO of ReadHealth, talking about digital inequities in healthcare and social determinants. And he throws out some stats. 19 percent of Americans do not own a smartphone. I find that stat hard to believe, to be honest. I don't know anyone.
This could be the circles I live in. But I don't know anyone that doesn't have a smart, well, let me rephrase it. I don't know anybody who doesn't have a mobile phone. I do know some people who don't have smartphones per se. And he said, shockingly, 50 percent of households earning less than 30, 000 per year have limited access to computers.
While around 18 million households in the U. S. lack internet access. As we're thinking about healthcare, and and as we're thinking about, scaling solutions that impact healthcare around the country, how, even from your perspective you don't know the digital capabilities.
You don't know the you don't know the population that's going to need to utilize your thing. And I hit the website while we were on the thing. You guys have like a bandaid. All it looks like is it looks as easy to apply as. Putting a band aid on and then it just measures the flow.
Is it really that simple?
Yeah, it is just a band aid. To, and that's a really important part. Kind of, back to what we always drive with our team again is our job is not selling tech, right? Our job is selling solutions that make people's lives better. The whole bandaid, easy to put on, hit a button and it goes, is a big part of that mindset.
they don't have to sync, they don't have to sync it to their phone or you're not worried
about that stuff. So this is part of why I think this, the story's relevant is they do right. And the current iteration, it does have to sync to a phone. A big part of our population in hydrocephalus is generally an underserved condition anyways.
So you, you get a lot of patients both within the U. S. and especially globally that probably fall into these populations, right? Lower socioeconomic populations. And I think it's, there's similar relevance for even when you just think about telehealth as a whole.
In a lot of ways, telehealth is... most valuable to your patient population that, for one reason or another can't make it into a clinic or, as far away. And oftentimes there's a big Venn diagram with the lower socioeconomic pieces. So you have this weird. This challenging disconnect of a lot of the patients you're trying to serve with the new tech pieces are oftentimes also your patient population with the least access to the tech, right?
So there's this divide problem you got to deal with. We work on this, we try and drive this really closely with our collaborators and, potential solution options where if people don't have these technologies themselves, we have a distribution mechanism that it can actually be provided, right?
And you see that with some other remote health monitoring solutions. But, I think when, whether it's telehealth or AI solutions or wearable sensing, like we've got, I think It's an important aspect that has to be thought about upfront because it's a real part of the patient population that's in the most need to be served and the least accessible with tech.
just getting a solution out there that is tech enabled is the first step. The next step is to make it broadly accessible. by all populations. And I guess you could do asynchronous. You could do but asynchronous in your case, that would be, that wouldn't help. Like you need to know when it's blocked immediately.
Yeah. So these are challenging problems. And I think that the message of this story is we've got to go beyond the. Serving the 80 percent of the population, we've got to look at the other 20 percent that might be in rural areas and the other percent that might be Do we call them digital deserts or whatever?
I mean, they just don't have access to these things and whatnot. So there's still an awful lot of work to do. Chad, I want to thank you. I want to thank you for your work and I want to thank you for taking the time to come on and talk some of the news. Yeah, great. Thanks
a lot, Bill.
It's been great to be on.
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