Data and insights shed light on the power of technology in value-based care. Satish Movva, Founder and CEO of CarePredict, joins Josh and Lucas to discuss how CarePredict’s data is changing the way communities operate. Hear about the exciting new development of CarePoint, a location-aware, camera-free platform that automatically activates when a caregiver enters and exits a resident’s room. Tune in for all the details.

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Produced by Solinity Marketing.

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Intro

Welcome to season eight of Bridge The Gap, a podcast dedicated to informing, educating, and influencing the future of housing and services for seniors. Powered by sponsors Aline, NIC MAP, Procare HR, Sage, Hamilton CapTel, Service Master, The Bridge Group Construction and Solinity. Produced by Solinity Marketing. Bridge the Gap in three two.

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00:00:51:06 - 00:01:07:10

Lucas McCurdy

Welcome to Bridge the Gap podcast. The senior living podcast. We are here at spring NIC in a beautiful location here in San Diego. We've got a wonderful guest on today. I want to welcome Satish Movva. He is the CarePredict CEO and founder. Welcome to the show.

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01:07 - 01:09

Satish Movva

Thank you very much, Lucas, for having me here.

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01:09 - 01:46

Lucas McCurdy

Yes. We've been really excited to sit down with you. You have an incredible background. You have created an incredible company that offers real solutions to our industry that are so important. And for our listeners, this is actually a very exciting episode because you have created something with CarePredict, called CarePoint, that has never been created before. And we're going to walk through some of the details, around this new launch, and bring us up to date. Talk to us about your reasons behind launching CarePoint and how it's going to change everything around caregiving.

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01:46 - 06:24

Satish Movva

So in our current industry, we've had this perfect system where we have high staff turnover and increase resident frailty coming into our buildings. And on top of that, increasing staff wages and all that. So it became very, very important to truly understand where care is being consumed, by whom and how much. And we've never had that amount.

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And if you think back for the last 2 or 3 decades, the way the industry has tried to solve the problem is to do a time motion analysis and say, okay, a bath takes 30 minutes or escorting somebody from their room to the dining room takes 12 minutes, whatever happens. And we've come up with these very, gross average minutes of how much a care task is supposed to consume. But the problem with that is it's not really personalized to the frailty of the individual, the efficiency of the staff member and all of that. So we've always had, you know, this issue of really not matching the care plan in minutes to the real world minutes of care consumed. And so if you look at any care plan in any building today, it's going to have pretty standard templates.

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Bathing takes 32 minutes. Showering takes 12 minutes, whatever it is. And they're basing their levels of care and the staffing model on those minutes. But the issue becomes because of the changing frailty of an individual which ebbs and flows. I could take 20 minutes to be late today, and somebody could take 30 minutes to be back tomorrow. It doesn't really take that into account. And because the staffing is based on care plan minutes, we are completely blind to how much we're actually putting the staff through and how much work they have to do. So this, you know, this discordance between the two has really become one factor of the net operating income leakage.

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So with CarePoint, we are tracking every minute of care consumed, no matter where the persons are in the building, whether they're in their bedroom, bathroom or living room, common area, or in the corridor. And the way we are doing that is, you know, our company is predicated on everybody wearing wearables like the resident has a wearable, the staff member has a wearable, and we have ultra precise real time location tracking. We have 22 issued patents in the company. So this is real technology. So it allows us to track proximity of each caregiver to each resident no matter where they are in the building. And so now we can look and see how much time each person is actually consuming off direct. So if you see Joe walk into my apartment and Joe and I walk into my bathroom, and then our device detects a bathing event, we know that Joe bathes Satish and it took 22 minutes. So that goes towards my campus, my care plan, and it automatically fills out that actual number of minutes in the year or whatever else. So that's care tasks and scheduled tasks, and you're getting ultra precise, personalized time of how much time I'm taking. And then the other aspect that really has been a blind spot in this industry is the on demand events.

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Everybody knows care plans, what I'm supposed to get on a periodic basis. Three bathings given some week or what have you. But then what about as I am more frail and I'm constantly summoning assistance and pushing a button, summoning assistance on a pull cord? And we have always been blind to that and never really tracked it. Not in our staffing models and not really in our level of care. So with our system that's being tracked as well. So if I were to summon assistance, the system is tracking how long it takes for somebody to respond to me. And once they are in my presence, how long are they spending with me and exactly what tasks are being done?

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So where care point helps in all that is, especially with the staff turnover in this industry, it's very hard to train people because they leave and then you're back to training a whole new set and it's never the same as the first time. So with our system, the minute somebody walks into my apartment, the caregiver, their CarePredict app automatically pings and says, “Hey, you just walked into this room.” You know, the five scheduled tasks are due to be done. And here are the 3 or 4 tasks from earlier shifts that were deferred. And so you get a real quick reminder of everything that needs to be done.

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06:24 - 06:34

Lucas McCurdy

That's huge. Just that right there. We need to be reminded. And caregivers are pulled in so many different directions. This is really, really kind of groundbreaking, right.

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06:34 - 08:05

Satish Movva

And especially as new caregivers enter the market, you know, they're not these shift workers of 20 years. These are more the gig economy workers that are coming in for sewed staffing, 1 or 2 or 3 hours, and they may only work three times a month, and you cannot afford to train them at the same level. So you need systems that drive all of that work, so you could get a brand new aide into your building. And they're using CarePredict. The minute they walk into my apartment, they know what needs to be done. The minute they step out, the app forces them to document exactly what they did for me. And it says you’re in Satish’s suite for 28 minutes. What did you do? And it's just quick taps, you know, I bathed him in 12 minutes. I changed the bed sheets or whatever. Six minutes. Boom boom boom. Done. And by the way, while I was in his room, he asked me to do his laundry. Now, that's incidental care, right? That wasn't in the care plan, but it's something I asked to be done that also gets documented.

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So now you have scheduled care, which is the planned care you have on demand events which are unplanned care. You have the incidental all together in one, no matter where they are in the building. And that's huge. That's unique. There's some systems out there that try to do this when you're in the bedroom of your suite and they're using cameras, radars and whatnot. But those don't scale beyond that one room. So whatever happens to all the care that's been provided throughout the building?

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08:05 - 08:12

Lucas McCurdy

Aren't there some liabilities with cameras? This is a camera free process right?

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08:12 - 09:20

Satish Movva

Yeah. So that's something that, you know, I created this, company to take care of my own parents, right? My mom was 87. My dad's 97. My mom hated the idea of cameras. So right from inception, I was never allowed to even think camera. So we really came at it from a very privacy centric view of, you know, what is the least intrusive way to collect all this data?

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And what we came up with was a variable that sits on the dominant arm, and we have a lot of machine learning and artificial intelligence in this. And we've been doing that since 2013. So this is not new. Nothing new for us. And so it actually knows when you're reading down to the fourth being lifted to the mouth, it knows when you're brushing teeth, it knows when you're washing your hands and all of this kind of stuff. And because it's a wearable, it can work anywhere in the building. There's no issue of privacy around cameras and stuff like that. Cameras are still a red line for a majority of, maybe you can get away with putting it in the bedroom, but no way is it going to be in more intimate spaces of a suite. Nobody's going to allow it in a bathroom, no matter how much you say it's obvious data.

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09:20 - 09:23

Lucas McCurdy

Sure. Which. Which is where a lot of care takes place.

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09:23 - 09:24

Satish Movva

Exactly. Yeah.

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09:25 - 10:37

Josh Crisp

Well, the implications are vast. Changes in a positive way for our industry, for the consumers of our industry services, for quality of care. We've heard personalized care and individualized care for years, but this is actually revolutionizing the way that we actually can deliver on that promise. I'm also, you know, thinking. So for an operator, an owner and operator, a management company right now, obviously, driving NOI while providing high quality care is a goal.

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But you touched on so many of the different aspects of how difficult that is when you have inefficient staffing, which is already a challenge in and of itself. So this is helping. You're in a way helping quality. I'm wondering, with all the data points that you're collecting in real time, do you think you're going to be able to help the industry, navigate the future as well? Because, you know, just as our industry has traditionally done these time studies, right, and applied averages, you're more able to see what's happening in the industry in real time with the aging population based on acuity sectors. Right?

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10:37 - 11:25

Satish Movva

Yeah, absolutely. That's a very good point. Just in terms of data collection since 2015, when we launched our product into senior living, we have today the largest database of senior acuity and behaviors anywhere in the world. We have the largest real world file database anywhere in the world, right. Data is huge in all of this, but data by itself is not enough.

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You need to draw insights from it. So and that's what we are trying to build on top of this, the integrations we are doing with folks like ALIS and others. So the data can actually become an insight that the operator can look at and understand. So for us, while data is the lifeblood of the company, it's how it's utilized. And the insight that comes out of it is much more important.

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11:25 - 12:25

Josh Crisp

Yeah. Well, and I'm seeing, an opportunity insert, my favorite phrase, which is bridging the gap. Right. Because we're here at NIC and, you're, you're hearing the operators and the owners meet up with the capital markets. Everybody's talking about the challenges of providing high quality care that are the most affordable way for our industry. You've got investors talking with operators and saying, how are you going?

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How are you operating differently? How are you operating more efficiently? So here comes care Point. Announced at NIC. We're awesome, partners of NIC. And so happy to have you on the show to talk about this, but it seems like this is an amazing tool to be able to, engage with operators. So when they're having those discussions with their capital providers of how are we maintaining quality while driving down cost, here emerges CarePredict’s new CarePoint. And you're right at the start of the show here.

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12:25 - 16:00

Satish Movva

Absolutely. And we're really happy because the timing worked out really well. This is something we've been working on for almost eight months. We had the data, but we had to get into a form where it's usable to the operator instantly. And I think to your point, you know, our industry is kind of at a fork in the road, too.

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You have the One direction trying to go back into hospitality a little bit, and you have the other one that's been pulled more towards the healthcare side of the equation. But underlying both is the REITs. And as far as the REITs care, it's net operating income. So now that you can, you know, rightsize the care plan to the actual care consumed, that's going to help drive the profitability of the industry to be more sustainable.

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But it's also going to help with a lot of the challenges that are coming up around caregivers. We don't have enough caregivers entering our industry, and that's an issue. But the kind of caregivers that are gonna enter this industry in the future and not the shift workers of the past, they're going to be the gig workers of the future. And in that model, you really do. You really need to understand what part of the day is your highest demand for on demand services and things like that. And looking at our data, we can at one glance tell you, you know, Monday between 2 to 3, you have a major haul because the demand is outstripping supply. And we can see that by the delay between when somebody summons assistance to when somebody actually shows up.

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So now we can say, “Hey, you need to start staffing there not to uplift the whole shift.” So how that's going to help the operators and the reach underlying them is basically to do predictive staffing models of exactly how much staff you need, during what times of the day and which days of the week. That's in touch with moderation, and that's going to help drive the profitability of this industry tremendously. But on the flip side, because of the data we're capturing, it's going to be the foundational data that's going to drive value based care. Sure. I know tomorrow we have a whole bunch of sessions on value based care and whatnot, but to operate in value based care without data is to be, you know, in a dark room trying to find a black cat.

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Just not possible. Yes. And so that's the light we are sharing. How much frailty is in each individual and how do you predict that this person is going to have a UTI in 3.9 days? I mean, we've been doing predictive analytics for eight years. We can predict a UTI in 3.9 days, or a risk of malnutrition or a fall in 24 hours.

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You're preventing stuff. Those are going to be hugely important to value based care. And why that is so interesting for our industry is, you know, no matter what our operators do to keep their restaurant safe, right. Yes, we get some benefit out of it. We have increased occupancy and we're taking good care of the residents. But the primary beneficiary has always been the healthcare insurer, and they never had to pay a dime for everything we do.

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And they are the beneficiaries because we are preventing hospitalization. Who makes out like a bandit? It's a healthcare payer though, and so it's time for them to step into this world and actually start, you know, putting their share into it. And with value based care they can get there. So if you're preventing hospitalizations, then somebody is going to be, you know, giving you shared savings or whatever to them. And that's gonna help subsidize technologies like CarePredict for our industry, which is for the benefit of all.

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16:00 - 16:08

Josh Crisp

So with CarePoint’s data, how long will it take before you have information that informs our industry on certain benchmarks? What would that look like?

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16:09 - 16:12

Satish Movva

So we think that's a quarter away.

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16:12 - 16:12

Josh Crisp

Wow.

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16:12 - 17:46

Satish Movva

That passed. Yeah, that's only because we have already a widespread adoption of care throughout the industry here. We've always been doing peer level benchmarking. So for our operators, for example, we'll begin building. And when we do the quarterly report for them, we'll compare it to anonymized for other buildings that are about the same size. And we are showing them what the response time there is, what the frailty level and the frailty indexes.

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Now we can do it at a much larger scope and we can add these additional data elements. So since we've always had this data engine, it's very quick to ramp up. And we'd love to get some of this data into the NIC data analysis side of things so they can start understanding where we are making these residents' lives better. Because this is important for the policy side. When we go up to DC and say senior living is that way, well, where's the data behind it? This is the data that can make that case for people. So we expect in the next quarter we'll have enough data through CarePoint that we can actually start driving metrics on what is the average amount of time something takes and what's the level of frailty. How does it flow within a building? Because we are not static creatures, right? As an older, especially as an older aging resident, we have ups and downs and then flows. One week I might be very frail and I might have a good week. The following week we are going to track all of that here. So this data is going to be really, really interesting.

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17:41 - 17:47

Josh Crisp

It's very interesting. It's very important. Lucas, you and I are lucky we get a front row seat here at NIC at CarePoint.

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17:47 - 18:10

Lucas McCurdy

Smart guy. This Satish. listen to all this stuff. I mean, I'm just blown away by how thoughtful you've been in really approaching some of the biggest problems in our industry and then providing a solution for it. I know this is just launching, but have you had any conversation either with your existing client base or any conversations here at NIC?

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18:10 - 18:12

Lucas McCurdy

And what has been the response to this?

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18:12 - 19:11

Satish Movva

So definitely with our existing base. So one of the ways that CarePoint can truly work effectively is if there's a very deep integration with the care clients. So which means we need an integration with the electronic health records. ALIS by Medtiligent, which is the first launch partner for CarePoint, where complete care plans come over, our system automatically fills out how much time it took for each task, and pushes it back. And who the staff member was. We are working on the same trajectory with all the top users in the market, but they're a few months behind. So as and when each one of those comes online, we are going to have saturation coverage where we can get that absolute system of record data into our care plans, into our, care point, which allows every staff member walking into a suite to know exactly what they're supposed to do, when and how much time they took. And that's going to change this industry, I guarantee you.

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19:11 - 19:12

Lucas McCurdy

Awesome.

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19:12 - 19:26

Josh Crisp

Awesome news and information. Thanks for all you do for the industry. You've been at this a long time. Yeah. And you continue to evolve and just tackle some really, really major challenges. So congratulations on all your success on that.

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19:26 - 19:42

Satish Movva

No thank you. Thank you very much. It's been a long road and, for a long time, you know, you're alone on the mountain top shouting into the wilderness, but the industry has caught up to where we are, and this data is making a huge difference. So we're really, really happy that, you know, that we are where we are today.

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19:43 - 20:47

Lucas McCurdy

Well, we're honored to have you on the program. And also appreciate your personal story. Bridge the Gap is really a platform to bring this type of thought leadership and content. But we also love getting personal stories. And there's so many people in the industry that have that family story where, you know, this idea was born out of a need to care for somebody I love. And those connection points and that thread, that common thread is really what makes this industry so great. So thank you, Satish, for your story and your company and your hard work. And we're really looking forward to seeing this, and we'd love to have you back on, to get that benchmark. We want to follow up and make sure we're sharing this information.

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So we appreciate it to our listeners that want to connect with Satish and also their platform, you can scroll down into the show notes there. Hit that link, your podcast player, and you can connect with them at their website as well as LinkedIn and go to btgvoice for all content and connect with us there.

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Outro

Thanks for listening to another great episode of Bridge the Gap podcast with Josh and Lucas. Connect with the BTG network team and use your voice to influence the industry by connecting with us at btgvoice.com.

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