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I caught up with Orbita President and COO. Nathan Treloar and Nick White the EVP of patient care solutions to discuss their new point solution which leverages a powerful platform for conversational technologies. Have a listen and I hope you enjoy.


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 Welcome to this Week in Health IT events where we amplify great ideas with interviews from the floor. My name is Bill Russell, recovering Healthcare, CIO, and creator of this week in Health. It a set of podcasts and videos dedicated to developing the next generation of health leaders. We wanna thank our founding channel sponsors who make this content possible, health Lyrics and VMware.

If you wanna be a part of our mission to develop health leaders, go to the homepage this week, and click on the sponsorship information. This week we're at the health conference in Las Vegas and during the conference I received a bunch of interview requests and I decided to highlight the solutions that I'm personally excited about and I thought would benefit my clients and listeners of this show, uh, within the health IT community.

Specifically I was looking at solutions that address clinician burnout, um, mass efficiency through automation, mental health, voice solutions among others. Uh, one of the things I'm always advising my clients about is the need to find platforms. There's a reason that the average healthcare system has 400 plus distinct applications.

Point solutions are great for a season, but if they don't leverage platforms, eventually you'll be looking to replace them down the road with something that could handle more use cases. Happens all the time. Uh, voice and chatbots are emerging and it is one of the areas that we have seen a ton of point solutions and I've been looking for a platform and I found one in Orbita.

I spoke with, uh, Kristi Ebon at the Health 2.0 conference, a few episodes back, uh, where she educated me on the space. And today I caught up with the president and COO, Nathan Tralo and Nick White, the EVP of Patient Care Solutions to discuss their new point solution. Which leverages a powerful platform for conversational technologies.

Have a listen and I hope you enjoy. Alright, another interview from the, uh, health 2019 conference here in Las Vegas. Actually, we're, we're on the, uh, showroom floor in a booth, and I'm here with, uh, one of the companies I'm really excited about on, uh, with conversational technologies. Orbita the, uh, uh, CEO Are you president And CEO President.

And COO President. And CEO. Yeah. The CEO. You don't know. . There you go, Mr. Man. Uh, Nathan, uh, tralo. And Nick. Nick White. Nick White. What? What's your title? I didn't, uh, EBP of Patient Care Solutions. Phenomenal. So, and that's what we're gonna talk about today. We're gonna talk about, uh, recent announcement and fact.

There's the, uh, what you're showing off here, orbit Assist, which I think is really exciting. But before we get there, uh, we had, we had Christie on the show a little while ago. . And she educated me on conversational technologies. And I, I was one of those people that probably creates the problem in healthcare.

I was ACIO and I would there and go, okay, we're gonna do chat bots and oh, okay, now we're gonna do a voice thing, then we're gonna do, and I would create that problem where you have 10 different things, but you guys have a platform. 'cause can you fill us in on, on sort of the genesis for it and where it's at?

Yeah, sure. Um, reason we got into this business is we recognized that, um, with the . Rise of things like Amazon Alexa and similar technologies. We're entering into a third wave of digital experiences in healthcare where if you characterize it as a first wave being web portals, second wave being mHealth, this idea of a virtual health assistant, a conversational agent, that can be an alternative to traditional UIs.

Engaging patients, engaging clinicians in and in and around care plan. Uh, the way we looked at 'em was, um, there are plenty of ways to develop point solutions that do this, but what was needed, just like in those first two waves, is a platform that allowed you to do this at scale with repeatability, with security, with interoperability.

So that's how we approached the market. So you wanted to develop a platform that would support doing this, um, with the operational sensibilities that large organizations require. So it's, yeah, so it's interesting. So this is, um. So you actually have point solutions and you have the platform. When health systems look at you, I mean, are, are you selling a platform or are you selling point solutions?

'cause I would imagine it's hard as ACIO unless I see it. Platforms are hard to sort of envision. It is. Platform selling is, uh, is an art form. It really is. And uh, you know, we're fortunate that, uh, the team that we built at ORBITA comes from a background with enterprise platform, uh, development and sales.

So it wasn't completely strange to us, but healthcare. They wanna see it, they wanna see the proof of the solution that that platform can enable, whether it's, uh, clinical outcome improvements or uh, clinical efficiency. They want data and that requires an actual solution. They wanna see something that, uh, targets a particular problem.

Once you've solved that, then the opportunities can you rinse and repeat that across other conditions or other scenarios. So, um, as we went to market, we, we realized we need to be really selling that solution, which means . Build, taking our platform, building additional capabilities on it, either ourselves or in support of a partner or the client themselves.

So often we become white labeled technology that's inside a solution that somebody else built. But like anything, the further away you are from that value, you know, the less that you can actually capture that and repeat it. So, uh, we've been very intentional, particularly in the last year of identifying the highest value solutions and, and moving up the stack in our technology.

So that we're adding as much value towards that new solution. So with, with Christie on the show, we talked a lot about the platform. Yeah. And how, you know, it's essentially, you know, you create the workflows, you create the, the interactions, and that's how a platform works. But today we're gonna talk, uh, so we're gonna talk about Orbit Assist, which is a point solution that sits on top of the platform.

Mm-Hmm. . So Nick, give us an idea of, of what this solution's about. Sure. Uh. We've been building it for about the last two years. Uh, a couple. An event happened a couple of years ago with a colleague of mine. His father, unfortunately passed away in hospital, um, after pressing the call bell button and, and nobody was able to get to him at that point in time.

He tried to get himself to the bathroom, uh, didn't want to have an embarrassing accident, and slipped and fell on the way, and unfortunately never left the hospital, uh, passed away in hospital. From that, we started looking at . What are some of the latent failures that exist in traditional call bell technology and, and, and the things that can go wrong.

And when we started to look at, uh, issues such as alarm fatigue, that that's really affecting the care teams, uh, the issues around patients not knowing whether anybody has heard them and whether anybody's coming and how long it will take. And we started to think about, okay, what sort of technology could we introduce?

That would allow for, uh, nurses to get that contextual information about what a patient needs when they're calling out for help, uh, but also to give some sort of feedback that someone's on their way and a kind of urgency that it's been treated with. Uh, from there, we, we started looking at the technology platforms we could use.

Uh, that's one of the, uh, uh, at the time we, we met the guys, uh, from Orbiter, uh, and, and started thinking about how could we build this as a vertical solution. Um, with an ecosystem play essentially underneath it and, and came up with the idea of putting a smart speaker into the patient's room, allowing someone to speak their request.

That request is then processed and passed through into a digital workflow and we're able to put priorities on it. We're able to route it to the most appropriate individual to respond, uh, and we're able to do automatic escalation if somebody's not able to respond. So it can actually step through a couple of tiers of escalation.

That's fantastic. So two years in the making. Mm-Hmm. , I imagine. 'cause it's. Maybe one of the first ones that you've done. The next ones I would imagine will go a little, well, we had it, we had it actually built as an MVP within three months. Oh, okay. Um, from that point we was about refining the solution.

Right. And getting it, getting our product market right. Difference, I mean Oh, yeah. Yeah. So, so getting your recognition levels up to an acceptable level to be able to put into a clinical environment was one of the key things we focused on. Um, in terms of . Thinking about the escalation models that works within work, within a a care environment.

Uh, and, and just working with the, the care teams, the, the nurses themselves to actually understand what's the user interface that works for them. How do we build this in a way that is minimally disruptive for them in terms of the way they work? So that adoption is just really easy. So you're gonna have different patients, different backgrounds, different uh, ethnicities, voice dialects and those kind of things.

Yeah, I mean, . Does your platform pick that up or is it the voice assistant, the smart speaker that's like figuring that out or? Um, the easy answer is that there's a very complex utterance model that we built behind the scenes, and the more mature we make that utterance model, the better we're able to deal with the variety of, of people who are using the solution.

So one of the things that we've been doing as we've, uh, had this live now for 18 months is we've been looking at how can we tune the model. To actually get better recognition across our broader representative set of individuals. But one of the first questions I get is, when can we go multilingual?

Mm-Hmm. . Um, and, and the most exciting thing for me at the moment is that we're working on that right now. Uh, and, and that's gonna be an amazing capability as we bring it to market for travel. Uh, so it's been live for 18 months? Yep. What kind of impact has it had? Uh, it, it's really interesting. The impact comes in different ways and, and for me, the easiest way to frame it is quadruple aim.

So thinking about what's the patient experience impact we're having for somebody who's isolated in a healthcare environment after some sort of serious trauma that's happened to them, the ability to reconnect with the world around them, to reconnect and, and have control over the environment that they're with.

And then also to, um, be able to reach out to the care team when they need them. That, that's had an amazing effect on patient experience. But also we've seen nurse times in terms of response times come down and so the nurses . Appear faster when they make a request. Uh, not only that, we've had the, the patients express that they feel less guilty about asking for something small like a blanket or a pillow because they know that the nurse can pick it up on the way through and just drop it off when they're going to do something else.

So they feel like they're less of a burden on the care team. From the care team's point of view, the really interesting thing is they've reported that they know what the patient needs before they walk in the room, and that's equipping them to deliver care much better than they've been able to do before.

Uh, and that's been fantastic. From a, uh, outcome point of view, we're really focused on quality and safety. So hospital acquired complications such as falls or pressure saws. How can we build, uh, the, the solution, the linguistic model that we use, the way it's all triaged to actually try and combat falls, pressure saws and other types of hospital acquired complications, which obviously if we can do, leads to a more efficient system in terms of costs.

So measuring satisfaction. Uh, I'll go to the nurse. I wanna go to the patient first, so. Yep. Um, how would you measure that? Or is it NPS or is it more We, we, there's a couple ways to do it. We did use NPS when we did our surveys, uh, but we also used another question, uh, which was, if you're in a hospital, would you want this in your room next time you're in hospital?

And a hundred percent of the patients said they would want it in their room next time they're in hospital. A hundred percent's pretty good. A hundred percent was pretty good. That blew us away. Uh, it's more than one patient in that survey. The net promoter score, just the straight net promoter score from that survey, we got a 92% score, which is also phenomenal.

Yeah. So that, that, that, those numbers blew us away. We, we then talked to the nurses, as you said, go to the nurses. Uh, we asked the nurses did they feel that it enabled them to deliver better care to their patients, and 87% of them reported that they felt it did. Yeah, because it fits into their workflow, right?

They're not adjusting. Yeah. Yeah. So it reduces the ambient noise on the, on the unit floor, because you're not having the bell go off as much that's alerting people. It's a, it's a smartphone in your pocket that's making a noise directly for you as the carer for that patient. And so the ambient noise levels come down.

You know that when your device is alerting you, you need to respond. So it's a one-to-one linkage in terms of alert to response. Uh, as opposed to some of the other alerts that go off that don't actually require a clinician's response that are causing some of the problems with alarm fatigue. Yeah. And Nick mentioned, uh, um, possible acquired conditions like, um, uh, bed sores, but also fall reduction.

I think you also mentioned some initial data coming out about reducing, uh. Uh, likelihood of falls because a patient unable to report that they're in pain and get assistance. Um, if they need to use the restroom, the toilet, they will get up and try to walk. And the example he gave at the top, so, you know, for some hospitals I know, uh, one hospital in the Boston area has told me that it's, uh, $17,000 per fall on average at cost hospital.

So any impact and they get, you know, 800 to a thousand a year billion. So any impact of reducing that has a real problem line. And we were looking at some really interesting, but uh, it odd technologies to reduce falls, you know, like pressure sensitive beds and just a whole cameras in the room, which I just, uh, and, and as we started talking about it, I'm like, man, equipping the whole hospital with that kind of thing is kind of cumbersome but necessary to reduce the

Uh, you know, and this doesn't preclude any of that, right? It, it's, uh, I would call it a sort, a supplemental, right? Yeah. In the sense that you're empowering the patient to be more communicative. Right. Empowering the nurses to have more context in how they respond to the patient's needs, but the ability to give them a simple instruction.

So if you, if, if somebody says, I want to, you know, tell the nurse I wanna go for a walk, just replying to them in a way that says, please wait. The nurse is on their way. Just that little instruction. Okay, cool. No worries. I'll sit here on the bed and the nurse will be with me soon. So it gives them that level of confidence.

Somebody's coming, somebody's heard what they want to do, they know what they want to, that they wanna get up for a walk, and the nurse is on their way. So it just, it, it just, what we've seen is that enables the patient to be more comfortable of. I'll just give it a couple of moments and then when the nurse is here, I'll get up.

Um, we did have a hospital report back on falls reduction. We had a look at the data. Uh, this, this won't hold true for every hospital system, but, uh, they're reporting a a 34% reduction in falls while we were, uh, doing their pilot. Uh, it's a combination of the cultural change that happens, uh, with the care team as they started to look at the, the patient experience and, and the way we're working and the ability to have, uh, a voice-based system available to those patients that could interact with.

Um, we also did have situations where we had falls. We've had reported falls during, during the time we've been live. Uh, a great example was a 14 second response time to a fall. Um, and, uh, we actually had one on day one of going live in one of our, one of our hospitals. Uh, it was a 22nd response time on day one.

Um, so, so really just, uh, some amazing data coming out simple and it seems like a simple solution, but there's pretty sophisticated technology in the background going on. 'cause all they see is the smart speaker that they're talking to. Yeah. So talk about, so platform point solutions. Yeah. Uh, what can we expect to, to see next?

Where, where will you be going? Well, I'll take a first cut. Um, the, uh, the, you know, we, we care a lot about the information that's coming through these kinds of applications from the patient. So what the patient says to communicate their needs, I need to use the toilet, I need my bed adjusted, I'm in pain.

That information captured in audio form is typically converted into text. And like Nick was described, it's prioritized using AI to recognize, alright, how, how do we score this for the nurse to respond? There's more information if you have the actual audio itself, right? So, um, you, there are techniques called, um, vocal biomarker.

Methods where you can analyze what's in their voice. And that technology is advanced considerably just in the last few years. Um, it's not intellectual property that Orbita has, but through our platform we have the ability to call out to services that can analyze vocal patterns for different types of signals.

Like, is this person depressed? Is this person showing indications of, uh, stroke or some other condition that needs. Um, escalation and escalated response. So the data really matters, uh, not just in terms of the upfront response, but also what can we learn from that data to be predictive and ahead of conditions that, you know, go way beyond avoiding fall risks and things like that.

Yeah, I, I, we already talked about multilingual capability. That's obviously something that's very topical. Um, it's one of the most requested features that we, we have had, and so it's great to see the, the technology platforms that we, that we use coming along that journey. And, and that's a key part of that.

Um, in terms of just thinking about the future of a hospital room and what technology's gonna be in there, um, one of the things that Orbit Assist really provides is a common alarming platform for the care team. Uh, there, there's a number of reports out there that talk about alarms in a clinical setting, and, and one of them says that as much as 85 to 99% of the alarms that go off don't actually require a clinician's response, what we're trying to do is get a little bit of control of that and, and provide the care team with

A predictable and a reliable means of getting an alert about something that they need to respond to, knowing that that requires them to take an action so that we can combat that alarm fatigue issue that exists within the environment. So, so really a lot that we'll be doing is thinking about the future technology enabled room, not just necessarily in a hospital setting, but also potentially in other settings.

Uh, and how do we provide an alarming platform, an alerting platform for care teams that really helps them to optimize the way they deliver care. It's interesting, there's a balance, uh, point solutions and platforms. Mm-Hmm. . 'cause there's part of me that's sitting back and going, Hey, I'd like to see this in sort of an agent, agent place kind of scenario.

But if I'm a startup, I could use your platform. Mm-Hmm. . I mean, that's what, and you'll white label it. And I just essentially, Hey, I've just created this, this new thing. Very sophisticated technology on the background and there's this whole . I, I just have to focus on this percentage of it. And you're taking care of all this other stuff.

Mm-Hmm. . So when you become multilingual, you become multilingual. That's right. And you push that concept, that capability down into the platform. So as a platform provider, the one of the most effective ways to innovate is to be close to a couple high value solutions that inform what you're gonna bring down into the platform.

Multilingual support, local biomarkers that can be applied not just for the assistant use case, but for other use cases that either are. Our OEM partners or their startups are very large population health companies, and we have them as well, um, want to take advantage of. So, uh, the, this kind of approach from a go to market plan helps us innovate and helps us, uh, focus on the, the highest value.

Capabilities to understand that it's exciting. Yeah. I, I'm looking forward to, to seeing what solutions, not only that, you, you guys a couple point solutions that you bring out. Yeah. But just, uh, now what health systems might do with their staffs Yeah. Is they sort of look at the problems and what, what the innovation community that's, that's here might dad.

Yeah. We're, we're . Fortunate at or orbit I to have some quite innovative partners that we've already been working with for quite some time. Like the Mayo Clinic has been a long time partner. They're exhibiting just around the corner. And, um, through that partnership, we've, they've learned from us and we've learned from them.

And, uh, we want to keep those kind of relationships, uh, strong and, uh, continue to innovate. So sound is like a big thing to you. What's that? Sound is a big thing to you. Yeah, I mean. We were talking earlier about, you know, play the trombone, play the, oh, me personally? Yeah. Yeah. Played the, yeah, played the accordion.

Yep. Played all the, the big, the nerd instruments. Yeah. just saved, just saved though. I banjo. I have a banjo, but I just loaned it out, so I'm not gonna count that one. , what other instruments do you play? You're like a, you are a one man band. You're like a dick Van Dyke on the, uh, , right? You don't wanna see that.

Um, um. I don't have time to tell you all these, but , that's fantastic. Well, it was, it was great. Great. Getting to, uh, meet you. Great. Uh, great solution. Looking forward to it. Thank you. Okay. Hearing more. I hope you've enjoyed the conversation. If you would like to recommend a guest or someone to be on the show, you can do that from our homepage.

Uh, recommend a guest. It's about three quarters of the way. Down on the homepage. Please check that out. And don't forget to please come back every Friday for more great interviews with influencers. And don't forget, every Tuesday we take a look at the news, which is impacting health. It. This show is a production of this week in Health It for more great content, you can check out our website this week,, or the YouTube channel, which you can get to from our homepage as well.

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