Raising Tech

Patrick Leonard:
0:03

Welcome back to Raising Tech, a podcast about all things technology and Senior Living. Today. I’m your host, Patrick Leonard, and I’m really excited to welcome our guests, Charles Herman and Jessica Bradley from Somatix, Charles and Jessica, welcome to the show.

Dr. Charles Herman:
0:16

Thank you for having us.

Jessica Bradley:
0:17

Thank you. Happy to be here.

Patrick Leonard:
0:18

So I’m excited to learn more and educate our listeners on our topic today, which is really broadly around artificial intelligence and the power of AI and remote patient monitoring in senior living communities. Obviously, this is something that’s constantly a topic and there’s a lot of innovation happening in this space, I feel like right now. So really excited to get you all’s perspective and tell us a little bit more about Somatix. So before we dive into all that, Charles and Jessica, would you mind introducing yourself and your background and kind of role with Somatix?

Dr. Charles Herman:
0:48

Absolutely. So, appreciate being here. Look forward to a really engaging discussion. I’m the CEO of Somatix and working with the company for about four years. I’m a physician by training. I’ve worked in a variety of different roles from startups to venture capital through hospital and health system management, and Somatix is on the cutting edge, I think, of all three health systems and the way that medicines practice, the way that healthcare is invested and in and where startups are going in terms of leveraging technology and unique ways to bring patients together. So for me, it’s particularly rewarding to be in my role to, to bring all the pieces together in bringing a, a new technology to help patient lives.

Jessica Bradley:
1:30

I’m Jessica Bradley. I have spent my entire career in medical devices and the healthcare world. I recently joined Somatix last year as the full-time, Director of Sales, and I am very heavily involved with strategic partnerships as well as working with local long-term care communities, assisted living communities, independent living communities, bringing remote monitoring to their residents. I have extensive experience with remote monitoring, specifically in the world of diabetes and continuous glucose monitoring. Prior to joining Somatix, I worked for Medtronic for a decade, and I’m excited to be here now to bring remote monitoring more so than just in the diabetes realm, but to bring more insights and predictive analytics to, to our most at-risk populations than people that need it the most.

Patrick Leonard:
2:23

Awesome. Thanks for the intro to both of you and what amazing backgrounds to talk on this topic. So thanks for sharing that and giving that background to our listeners as well. And, and this may be a question for either or both of, of you, but I always love to hear, particularly in senior living, I, I’ve grown up in this industry on the operator side my entire life. And now kind of more on the business partner side, if you will, like you all. But I always love to hear how companies who are innovative come into this space. What is their entry point of steering living? Why and how did they get here for what you all know? Do you mind sharing how and why Somatix came about in the first place?

Dr. Charles Herman:
2:58

Absolutely. So, you know, as you know and have, have just said, the healthcare space in general, not necessarily the easiest market to break into. And the first priority I think, in analyzing the market to evaluate is, is there a need? Is there a need in the market for a service that you can provide Without the need, you can’t provide a product that someone is gonna use and, and potentially then provide value and and to whom you’re selling to. So we’ve seen for better or for worse in the last three years, how important leveraging new technologies are to taking care of the population because of covid. And two areas that have become catalyzed are remote monitoring and telemedicine. The need to extend the capabilities of our workforce, which is healthcare workforce is more strained than ever and to deliver services now that, you know, remotely efficiently and remote patient monitoring plays right to that need. So we had this technology that we created a number of years ago that it was very unique in that it leverages gestures, movements of the body in ways that other technologies can’t, to provide very, very powerful clinical insights purely from someone’s wearable, what they’re wearing on their wrist. We’re talking about very powerful insights like smoking, risk, of falling, hydration, pill, taking, sleep analytics, very, very powerful insights. And I think the clearly now the need for that is greater than ever before. When we first started looking at this technology, we looked at where could it be leveraged to provide value to patients because the technology in and of itself is not valuable unless there’s a need for it. And we saw that some of the highest risk members of our population, like patients with complicated medical problems older patients, elderly patients that have very unique risks, could benefit from having that angel on their shoulder, a technology that can monitor them more safely, keep them aging or healing in place better. And that’s what has driven Somatix over the last few years is taking a technology that was unique, finding the market for it, and now in the last three years since COVID really catalyzed by what’s happened in the last few years to deliver value to those patients who are most at risk.

Patrick Leonard:
4:58

Thanks, Charles, and that kind of leads me and may seem like a stupid question since it’s being talked about advanced in so many ways right now, but if you could just humor me for a second, and, you know, you can’t help but notice and and see so much these days, AI-powered artificial intelligence power. Can you talk a little bit more specifically for our listeners who maybe aren’t as familiar and for my own benefit as well, what does that actually mean, and particularly in this sense that you all are using it for today?

Dr. Charles Herman:
5:27

Sure, It’s a great point. We’ve heard a lot of promises of using AI, artificial intelligence, particularly in healthcare. A lot of them have been empty. We’re finally starting to see value from artificial intelligence. Now, what does artificial intelligence mean, right? It can mean many, many different things. Essentially it is taking big data and using computers to find insights, analytics, patterns in that data that could then be used in an application that can augment what we’re currently doing. So we’re finally starting to see things one another, another phrase that often goes along with artificial intelligence, machine learning, and that’s the a machine, a computer software learning something so that it can then deliver value based upon what it learned. So I’ll give you a, a concrete example of how we leverage it and artificial intelligence is that we have these gestures that the software in our band analyzes 24/7 and then goes into the cloud and gets analyzed again. Those gestures in and of themselves are not very useful. You know, it doesn’t really help us that we know that the person took their hand and moved it to their mouth 12 times in the last hour, or that their gates changed, that they’re using the bathroom more frequently or they didn’t put their hand to their mouth in a way that could have been them taking a pill. However, if we train the computer to learn the patterns in that behavior, give it an artificial intelligence to now know that that gesture was somebody falling or taking a pill or smoking a cigarette or how much fluid they drank based upon their movement. And now we’re training our algorithms to using machine learning to be able to provide these insights purely from these data that which is the signal from the band. That’s powerful. So we’re seeing many use cases now that suddenly are starting to provide value. We’ve seen in the last two years, FDA approvals for artificial intelligence around imaging of the chest, the lungs, the breast, and in many cases, I hate to say this, being a doctor myself, a lot of these artificial intelligence algorithms actually outperform the doctor in finding breast cancer and finding collapse of a lung or a lung cancer in colonoscopy. There have been several devices recently where the computer could look at the images while a doctor is doing a colonoscopy to pick up on any potentially cancerous polyps that might be missed and actually outperform the doctor and find things that augment the doctor, he or she doing the actual procedure. So the future is bright. A lot of the promises that were empty have now moved on to real value in, in finding ways to leverage, uh, machine learning to provide insights, analytics that otherwise human eye isn’t capable of doing. So if that, you know, giving you a few examples, giving you an explanation, I think the future is, is really, really bright for where these technologies can be leveraged in the coming years.

Patrick Leonard:
8:08

Thanks for that, Charles. That’s really helpful. Like to think being in the technology space myself that I knew quite a bit about artificial intelligence and machine learning, but even some of that explanation there really breaks it down practically and makes it real, and I learned something from that myself. So that kind of leads me to what, while you were saying that, I was thinking, and particularly with the application of senior living, there’s always a human element to this, and you know, you even said it yourself as a doctor, sometimes this technology is so powerful, can outperform the doctor or the human element in these cases. Can you talk to me a little bit more about how the human element is augmenting the artificial intelligence in the machine learning in the case of Somatix and what you all are providing? Cause I assume it is still prevalent.

Dr. Charles Herman:
8:50

Absolutely. So none of the technologies that are there are being developed really should be looked at as replacements for the caregiver. Computer can’t replace the human touch, can’t replace human intuition, can’t replace, human experience. So the way that you can, you can look at Somatix and other artificial intelligence powered devices is they augment what we can do. I’ll give you the example. We did a large study with several facilities affiliated with the Catholic church and the University of Pennsylvania a few years ago, and as part of that study we looked at how the technology’s being used, how it was perceived, and how outcomes were being changed by adding remote monitoring to what doctors, nurses, aids were currently doing, and the feedback we got is that number one, the data now that the caregiver is getting are data that that caregiver didn’t have before. So think about having a wearable on someone’s wrist. This is now a 24/7, 365 view of that patient. If you take someone’s vital signs or you check in on them and do an exam, that’s a snapshot. But providing a wearable that gives a longitudinal view of how someone is doing that is, you know, not just the trees, that’s also seeing the forrest, and we have a more comprehensive, larger view of how that patient’s doing. So now there’s more data that the human, the caregiver can act on. If we can, if we can use AI machine learning to predict if something’s gonna happen before it actually does and see someone’s risk, we might be able to prevent that person from getting sick. If we know based on our algorithms that they’re at a higher risk for falling or a urinary tract infection. If we can act and make an intervention sooner and keep that person from getting in trouble, we might be able to then, as we saw in our study, we reduced hospital admissions by double digits. We reduced falls, we reduced urinary tract infections. It’s the human making the decision, the technology is what we call a clinical decision support system or CDSS. It’s providing you another tool, it’s a blood pressure cuff on steroids. It’s another way of getting more information that’s more comprehensive, more insightful that the caregiver can then act on. But the eventual decision to administer the care to decision to, to help someone to deliver the care to someone comes down to the human. And I think that is never gonna be replaced. This is a another tool that that person can use in delivering hopefully better care to take care of that person. Jessica can speak a little bit about that in in the space she was previously in. If you wanna talk a little bit about Jessica, how technology really changed the way diabetes was taken care of. They’re very good corollaries there and how insulin pumps and, and blood and glucose monitors, you know, that got more advanced and some artificial intelligence got into those devices where they actually get dose people based on trends that didn’t get rid of the endocrinologist, the nurse or the aid. But maybe Jessica talk about a little bit, you know, how you saw that change that industry and how that might compare to what we’re doing at Somatix. I think it’s a very good case study as well.

Jessica Bradley:
11:39

Yeah, you know, Charles, I’ll follow that and one of the, the first things that when I meet someone new is I make sure that they understand what’s our, why<laugh>, why do we get up in the morning and do this and what do we really believe in? And something that I tell everyone is our mission statement. We truly believe in the power of developing artificial intelligence technologies that provide insights that empower people to thrive in their health and wellness. It’s ultimately about those insights. And like Charles was referring to, it is whether it’s an insight into a glucose level. I have diabetes myself, I’m a global diabetes advocate. I meet with people, you know, with all of these, these health conditions and comorbidities all the time. And it doesn’t matter what discipline you’re talking about or you know, is it diabetes, is it cardiology, is it nephrology? If you can provide insights into whether it be a glucose level or you know, what we’re doing with a hydration and showing people the risk of UTI, if you can do that and you can step in to provide predictive analytics before an adverse event occurs, that’s where the solution becomes valuable. And that’s truly what our smart pans provide to people living in Senior Living communities. It is, you know,<laugh>, I laugh, I do a lot of open houses and I meet with people and they say, you know, when I tell them that we can give insights to predict a UTI or a fall or pressure sore or something, they’re like, oh, can you predict a stroke too? It’s like, yes, we’ll get there, I promise. You know, as the technology advances a thousand percent, because truly that’s what they want. They want that safety net and they want something for their care teams and even themselves to understand more about their health, understand the quality of their sleep. It’s pretty powerful for them to really use it as a communication tool that they don’t need to communicate. They know that their care team knows already. So it’s, it’s, um, pretty impactful from a predictive analytics standpoint.

Dr. Charles Herman:
13:43

Yeah, totally. It’s, it’s empowerment. As Jessica said, what you do with the data is up to the caregiver and the patient, but certainly more information is better than none. And if we can predict things and prevent them from happening, we really can help, you know, make a significant change in how people are treated and, and keep them safer and healthier.

Patrick Leonard:
14:01

Absolutely. Yeah, it’s exciting to see with all of this and particularly, you know, the technology that’s coming out in this space, we’re continuing to learn and get better, as Jessica just mentioned, it’s coming, it’s coming and it’s just cool to see how this has really just taken us to a whole different level of healthcare for being preventative and proactive opposed to what we’re used to is, you know, calling the doctor, ignore the doctor reactively once a problem already occurs. So how can we touch this thing, you know, these symptoms and these signs of whatever it may be earlier and earlier. So it’s, it’s really exciting to hear you guys talk about this stuff. Can you, so in order for this, for the magic to work, right, obviously, you know, you mentioned the wearable, the smart band, obviously we’re reliance and dependent upon the residents to wear this for it to be effective. Yeah. Can you talk a little bit about how they’re responding to this? How are they reacting to it? How are we ensuring that they’re using it and they’re charging the battery and they’re keeping it on 365 days a year so we can get all these insights?

Jessica Bradley:
15:00

I’ll tell you, I think ultimately I work with communities and directors of nursing and executive directors on communication. Communication is absolutely key from a really, what we have to do at the very beginning is just tell people the why behind it, what’s in it for me and why should I wear this? If you can successfully communicate the peace of mind and what it does for them, not only to the resident but their family members as well as to staff, the staff needs to understand how is this gonna help me in my day-to-day? That is really important because depending on the level of care that you’re talking about, if we’re talking about skilled care, the staff is the one who’s throwing it on the charger every few days, you know, so they need to understand why am I taking this extra step? What is it doing? You want to think that they care only about, you know, the residents, but it doesn’t matter what you’re talking about. People wanna know what’s in it for them. So I think that I, I will tell you from an implementation and deployment standpoint, that’s my job.<laugh> that’s what I help the teams to do, is to help them develop those communication. We give them marketing tools and we have videos and YouTube and all of those things. But I think what’s really important is that the residents understand this is going to help their care, their care teams to have a bigger insight into their old, their overall wellness. It can help, like Charles was referring to, it’s a support system to help them potentially predict adverse events before they happen. I will tell you family members love it because it’s a safety net. They know that their loved one is, we have real time alerts, we have predictive analytics that they will, that they’re just, they have an angel on their shoulder ultimately, that if they can’t be there, that somebody else will be notified. So I think that that’s really powerful. And then from the staff standpoint, I’ll tell you, I really think it ultimately comes down to better communication. We saw in the study Charles was referring to earlier that, um, you know, we measured hard and soft metrics and some of the soft metrics that we saw was a greater empathy that staff had for the residents themselves because they had a better understanding of how that person was feeling. So it really helped with their communication and the relationships that they had from staff to resident as well.

Dr. Charles Herman:
17:17

Yeah, absolutely. We, we actually have data to study that. One of the greatest barriers to adoption and remote monitoring historically has been patient adoption. There have been a lot of barriers. Mo a lot of the earlier remote monitoring technologies required hardware, cameras, sensors in patients rooms, homes, servers there, the fact that we’re all cloud-based and that the band speaks to the cloud or through the phone to the cloud really helps and the other thing we spend a lot of time on is messaging to the patient and the patient’s family because remember a lot of older people, the families are driving a lot of the, the healthcare decisions. What’s the value? You know, there’s been historical lot of paranoia around collecting personal data, right? So it’s very clear for people to understand that the data we’re collecting on the risk is to keep them safer, healthier, allow them to age more independently in place. This is what people want. It’s not to check their buying habits out on Amazon or their commuting patterns to the local bar. This is to really keep them safer and think about it also engages their social network. Not only do we have the wearable, we have these very mature apps that a family member can go and see how their loved one is doing just through their app that’s connected to their band. They could see when they woke up in the morning, how much sleep they got last night, how much fluid they drank, get warnings if they’re at risk for a urinary tract infection, fall, poor sleep. So really engages the social and family network of the patient as well that gives buy-in. So we’ve seen very high adoption. We’ve seen 80% to 90% adherence over long periods of time because it’s an easy solution. It’s almost entirely passive. It doesn’t require any additional hardware. And Jessica is on the frontline in her role of communicating effectively to the families, the patients and the caregivers, that this really is valuable and, and can keep someone safer. And now, you know, it’s in other advantages we have the data to, to be able to back that claim up.

Patrick Leonard:
19:02

Thank you both for that. So I’m gonna ask you a question now. It, it just got me curious because you know, we, you do see more and more solutions coming out on the market today that are really at their core looking to solve some of these similar aspects, at least bits and pieces of what you all are talking about today. And I’m not asking, not not asking to put you on the spot or can you, I’m just out of curiosity, can you talk a little bit more, are there, is there something different in the technology that you’re doing? Is there something different in what you’re analyzing or measuring than some of the other more general, you know, remote patient monitoring or, or false prevention tools or anything like that out there in this space today we should be aware of?

Dr. Charles Herman:
19:41

Yeah, well I think there’s, yeah, I think there’s two differentiators. Number one is the ability to get such comprehensive, powerful insights purely from the wearable itself. The fact that we’re taking unique signals that other companies aren’t taking. The, the core of our technology is the gesture detection. There isn’t another company out there that can tell you whether someone missed a dose of their medications purely from the movement of their hand or how much fluid they drank purely from the movement of the hand, or how many cigarettes they consumed purely from the movement of the hand. So that’s our proprietary, our patented technology is leveraging those unique signals that another no other companies can do in creating unique insights based upon those signals, which as I said earlier, are otherwise worthless signals to know how someone moved their hand. It’s the insight that we can provide through the artificial intelligence algorithms. The second value is the big data. So every patient, every second, every day that goes by where someone is added onto our system uses the technology, the technology gets better, the technology gets better because it’s increasing the data that we have that we can now create more insights, update our algorithms, learn the patient, learn different type of patients. So, and then we can find patterns in the big data. We can find signals in the data that might predict whether someone is decompensating earlier. And so it’s finding patterns in the data that can predict and provide insights from that big data that as we grow our base, as we grow our patient population, we know we can create even more insights over time.

Jessica Bradley:
21:05

I will say there’s, there’s three things I always ask everyone to remember when they walk away. I say, one, we have passive remote monitoring. So a lot of times sometimes you’ll hear passive versus active. What’s the difference? It’s that like Charles has mentioned, you wear the band, you don’t have to do anything, right? It’s very easy. We’re not asking someone to check their own blood pressure. We’re not asking them to check their SPO2 value with you know, a thermometer or something to check their temperature. It’s doing it automatically. That’s number one. And I will be honest with you, that’s probably the number one reason why people reach out to us is we are looking for a passive remote monitoring solution because we’ve seen how difficult it is to get people to do things on their own. So that’s number one. Number two, like Charles referenced is that AI. The AI is so impactful, it’s so powerful. The insights really, it’s not just the data because frankly people don’t know what to do with all these data points that he is talking about. Well, you know like I can have, I can know how many hours I slept or what the quality was or how much I drank, but what does it mean? They don’t know, and that’s what we provide them through the AI, and then the third thing is those proprietary gesture detection patents that we have to monitor. Things like Charles referred to. We’re the only company that can monitor whether or not somebody took a pill, how much by gesture, what their fluid intake was. Did they actually smoke a cigarette or fall algorithms or very robust in the actual algorithm, but as well as our predictive capabilities to predict a fall from happening. So those three things, passive nature, AI, and gesture detection, I think are what really set us apart.

Patrick Leonard:
22:39

Fantastic. Thank you for that. So I feel like we, we’ve covered a lot today and I feel like we can go on and on about this. So interesting and particularly, you know, to get two people with your backgrounds talking about this subject and clearly so passionate about it, it’s a lot of fun. But I did wanna kind of end on and give you all an opportunity to, I always like to ask people, you know, what’s, we’ve talked about so much and how far we’ve come today, but what can we expect in this space next? Do you guys have any insights or predictions as to what’s coming next? We’ve come so far but would love to hear that and or any other words of wisdom as it relates to adopting this technology or thinking about this for folks who haven’t kind of dove in yet.

Dr. Charles Herman:
23:19

Absolutely. Well, I think number one, the technology continues to improve and we’re able to do things with our technology and we will be able to do things that we don’t even can’t even imagine today. We’re already working on next generation features, not just cigarette use, but e-cigarette use, detecting tremors and responses to medications. So there, the technology that we have is very, very versatile. The algorithms can be leveraged in ways that can detect new clinical insights that we might not even think of today. So that’s one beauty of the technology is it’s not limited to one particular use and that can provide even more value to a patient going into the future. The second thing we’re doing, which I think that which we’re seeing, which I think is very important, is that the adoption has finally started to accelerate. As we started this conversation, we talked about how it’s difficult to find markets and bring new technologies into healthcare because people are often set in their ways. But I think now finally the ice is broken and it’s very exciting now that we’re actually seeing value from new technologies like remote monitoring and that the caregivers, the patients and their families are appreciating it in the technology starting to get adopted. So that is particularly rewarding and exciting and I think as more people see the value and more patient lives are improved, the adoption will continue to increase. I think that that’s clearly the trend and that goes with other things in artificial intelligence and remote monitoring. I think it’s an exciting time. We’re finding all new ways of leveraging machine learning to bring value to patients that augment, that empower what we do. And never, as we said, it’ll never replace the caregiver, but we’re finding new ways now to augment our powers and be able to detect diseases better earlier and intervene better. And I think that it’s an exciting time to be in healthcare. It’s an exciting time to see what’s happening in remote monitoring. And I think, you know, this is becoming now part of standard of care. We’re seeing a lot of not just assisted living nursing homes, skilled nursing facilities adopt us. We’re seeing hospitals adopted into their remote monitoring, into their population health programs a nd into home care because, you know, we we’re getting to see that it’s not just what happens in the hospital setting that matters. I t often just as important as what happens to that person when they leave the hospital. And if we can keep them safer in their home environment, uh, that can often improve the health of the person. So it’s changing the way we look at caring for people. It’s making it a much more continuous process. That’s better I think, in the long run. And I think Jessica and I and the company of Somatics i s, you know, really provision excited to be part of that change.

Jessica Bradley:
25:37

Absolutely. I I say often that I think since COVID, like Charles had mentioned, remote monitoring has absolutely taken off. And the majority of people that I talked to, they just simply didn’t know that it was an option. They didn’t know that there’s a passive wearable out there that monitors gesture detection and can give insights. They had no idea. So at this point, I think what we’re, what we’re looking to do is partner with, you know, other business partnerships, work with groups like Parasol. Thank you so much for having us because I think ultimately it is getting the word out that this technology is available and that residents can, can use it to their benefit. So thank you so much for having us because I think platforms like this are really what are gonna help us to expand and bring this technology to people in the market.

Patrick Leonard:
26:22

Yeah, absolutely. Thank you both for being here. I am one of those people, by the way, Jessica, who didn’t know about this pre-COVID, really to the extent and the advancements that it’s made and, and the adoption that it’s starting to get here in Senior Living. So I am super grateful for both of you for being here and educating me and our listeners. I know they’re gonna get a lot out of this episode. So thank you both so much for taking the time to be here. I’m excited to release it.

Dr. Charles Herman:
26:47

Right, happy to be part of it and appreciate what you’re doing and thanks for having us.

Jessica Bradley:
26:51

Thank you.

Patrick Leonard:
26:51

Absolutely. And listeners, thanks for tuning into another episode of Raising Tech. I know you’ll pick up some valuable information from today’s discussion with Jessica and Charles. If there are any topics you want to hear about or want to be on an episode yourself, please feel free to give us a shout or reach out on our website at www.parasolalliance.com. Have a good one.

Patrick Leonard:
0:04

Welcome back to Raising Tech podcast about all things technology and senior living today. I’m your host, Patrick Leonard, and I’m really excited to welcome our guest today, Todd Owens, who is the co-founder and CEO of Kevala. Todd, welcome to the show. Thanks,

Todd Owens:
0:18

Patrick. Great to be here.

Patrick Leonard:
0:20

Yeah, we’re really excited to have you. I’m, I’m really interested to learn more in educate our listeners today on our topic, which is really around workforce management. Obviously this is currently and likely always will be a huge topic for the senior living industry. But before we dive into that, Todd, can you take a minute just to introduce yourself, your background a little bit, and tell us a little bit more about how Kevala came about?

Todd Owens:
0:42

Sure. Yeah. So my roots go back to the Navy. I actually grew up in a Navy family and, and, uh, was a submarine officer for about five years back in the 90s, realized that bureaucracy is not my thing. And so went to business school and, and became a product manager. And I would say, uh, product management experience at Oracle set me down the, the technology career path. I’ve always gravitated towards more growth stage companies, and that ultimately led me to my first CEO opportunity. So I guess I, you know, I, I I, I am either crazy enough or lucky enough to have been a CEO four times over, this is my fourth, again, I’m the co-founder and CEO of Kevala. After exiting my last business, uh, which was Azuqua was a future of work integration platform. Found myself on the beach and, you know, kind of wondering what what am I gonna do, uh, with the rest of my life? And, I, I paired up with Pioneer Square Labs. It’s a startup studio here in Seattle. There’s a great guy named Greg Gottesman, founder of Rover.com, our our favorite pet sitting site. He said,”Hey, Todd, you know, let’s sit down, you know, it’d be fun to build a business together,” and I knew I wanted to, to do something related to the workforce. I guess, you know, now I’m in the back half of my career, I’ve decided that I’m, it’s pretty clear to me the quality and the engagement of your workforce is really what drives success in business. And so I wanted to get back to doing that. It was the first company I ran, but then there were two others and they were more infrastructure and technology platforms and, and they were great. They were very exciting, but they didn’t touch people the way that I had always wanted. And so, you know, we sat, sat down in early 2020 looking at workforce dynamics, things that are going on, like for example, the increasing gig economy, the aging population, compliance and regulation, and how much friction that adds in the, in the kind of the, the process of, of building and engaging a workforce. And lo and behold, one day in February, maybe it was late January 2020, covid started to spread, and so, that, that notion, I think sort of was the icing on the cake that we, we should really dig deep into healthcare. You know, you turn on TV, CNN, and they were saying facilities needed to hire more nurses, right? And so we wanted to explore that and, and that’s how we did. We, we started talking to healthcare facilities whether they be skilled nursing or senior living. We spoke to hospitals as well, and we found the same thing. They were all looking for nurses. And so then what’d we do? We went to the other side, let’s go see if we can recruit nurses. And so we took a, a social media approach to recruiting nurses and we asked them, what are you looking for? Lo and behold, they had a capacity and a willingness to do more. And so that was the big aha moment for us today in healthcare, the way that healthcare facilities connect with various labored pools is very manual and it’s very fragmented. And oftentimes the operator doesn’t realize that right around the corner there’s a nurse that would love to pick up the shifts. And if we could get right into the middle of that and do that using technology, not text messages, not emails, not phone calls, that we might be able to be a better, do a better job of, of matchmaking, fill more shifts, um, and keep costs down. So that was the, that was D1 of Kevala that came out of Pioneer Square Labs.

Patrick Leonard:
4:09

That’s awesome! Thanks for sharing that background. I think that’s really helpful. And, and I learned a lot there just in that short nugget. And I think it’s interesting what you said and really valuable how you took really dove into depth on both sides and both perspectives of the operator as well as the nurse or caregiver. Cause a lot of times I think there is a huge disconnect and misunderstanding that, you know, people may say things like, there’s, there’s not enough demand for these jobs. These people don’t want to work, or, or whatever it might say. That just, you know, clearly when you hear things like that, you understand that they don’t necessarily know the interest of the industry or have taken the time like you all did to understand both perspectives. So I think that that’s really helpful and valuable that you shared that with us.

Todd Owens:
4:52

Yeah, no, for sure. I think that, you know, the workforce is changing and, and organizations that recognize that and adapt to meet the workforce where they are, are gonna thrive. So for example, in esp, and this was all exacerbated during COVID, their, their need for flexibility and control over their schedule, right? Whether they are student or a stay-at-home parent, you know, or maybe they, um, you know, aren’t looking for a full-time job or don’t want the pressure of being worked full-time and then asked to do overtime. An increasing percentage of the workforce wants that flexibility and control. So what we’ve seen is that there’s almost been a, a shift away from perm roles where they don’t have as much flexibility and they’ve got a lot of pressure to roles that give them that flexibility. And some of those are labor marketplaces. And you know, and candidly that’s how we, that’s how we cut our teeth at Kevala, right? Was as a labor marketplace ourself putting qualified, certified, um, RNs, LPNs and CNAs into shifts. You know, where are they coming from? It’s possible that they were coming from our, and they were, were looking for that freedom, that choice and that control, that option to work when and where they want to. And so the key here, and this is, you know, what I hope we can talk about is that, you know, we need to develop software that helps the industry deliver that same flexibility to their own employees so that they don’t have to go elsewhere to get what they’re looking for.

Patrick Leonard:
6:17

Yeah, that’s fantastic, and, and that kind of dovetails well into Kevala, hopefully, and, you know, the problem that you all are trying to solve. So for our listeners who aren’t as familiar, can you just give us a high level overview of what Kevala actually does and what it hopes to accomplish as it relates to all these things we’re talking about specifically in the senior living study?

Todd Owens:
6:39

Yeah. Highest level, the mission of Kevala is to improve the quality and cost of healthcare through smarter workforce management, right? If you look at the cost structure in the industry, over half of it is labor. And so it goes without saying that by bringing more intelligence, more data, more automation, more efficiency into that we can actually make care more accessible, whether it’s private pay or whether it’s, you know, a state funded facility. You know, we need to do more with less, not just because the talent’s not there, but because we need to keep it affordable for everybody. So that’s, that’s what we’re doing at the core of what we do. It’s about connecting, it’s about connecting labor pools to a schedule in a very inde, uh, in a very intelligent way. So as to whether or not it’s a permanent staffer that fills the shift, or if it’s a third party agency or another labor marketplace or the Kevala’s Care network, right? Our, we’ve got several thousand W-2 nurses that are there to fill shifts as well. We put the controls in our client’s hands so that they can achieve their outcome, right? And ultimately, I think we all know that the goal is to get agency to an absolute minimum, right? Especially in this industry. There’s not a ton of volatility as it relates to the census. And so we’ve gotta be smarter about making sure that those shifts are exposed in a very convenient and friendly way to the internal staff before they get opened up to, to third parties. And that’s what our ho our software’s gonna do. It’s interesting because on one hand, you know, we, we built our initial revenue stream around a labor market. And on the other hand, what I’m telling you now is that our objective is to, is to get to the right mix of agency, which may not be zero by the way, right? There’s, there could be the right mix. You could, you could argue that zero agency, you might be overstaffed too much agency, you’re probably understaffed, not recruiting well enough, but we wanna help our clients get to the mix that is right for their, their operation, their business.

Patrick Leonard:
8:34

Yeah. That’s interesting cuz you do hear about all those different factors, you know, the, the internal labor pool, the labor marketplace agencies. And so I haven’t heard a, an approach today that kind of integrates the best of all the worlds together. Are there other folks like you out there doing this? And can you tell me a little bit, bit more specifically about when you work with a organization, how do you work with them to find that magic mix between those different parties? Right. Can you tell me a little bit more about

Todd Owens:
9:05

That? Yeah, it’s interesting. So first of all, um, your various to, um, the, the unique value proposition of Kevala is that we are able to bring all of the facets of the workforce together. So there are vendor management systems that can help to bring the agency side under a single roof. Although VMSes tend to be more appropriate for hospitals cuz they tend to be big clunk, and there are scheduling applications that do a pretty good job of the, the permanent staff, right? Scheduling them. But how, you know, at the end of the day, it’s one shift, right? It’s one audit, one compliance audit, it’s, you know, it’s one P and L. And so how are you going to actually measure and understand where you are and where you wanna be if you don’t bring it all together? And so that’s a very core aspect of our strategy. We ha we have no choice but to go broad all the way across the workforce as it relates to, you know, how do we help to establish that proper mix. A lot of it is, you know, helping them to know where they are. You know, if you look at, um, the, the scheduling mix today, there’s a pretty good understanding of where, because you know, whether it’s on shift or you know, Paycom or Smart Links, they, they have really good management reporting and so you’ll know exactly what’s happening there. But then there’s everything else. The agency A, B, and C that each sent a nurse in as well. Oftentimes they don’t know who worked and when and how much until the invoice arrives. And unfortunately the invoice can show up sometimes 60 to 90 days later. So in a world where you’re trying to match the, you know, the schedule to the, to the census and the acuity and you’re trying to control costs in a very sort of thin margin business, and you have to make sure that you’ve got the right staffing ratios to, to sort of deliver the care and stay compliant, you know, it’s, it sort of, it’s do that without the data. And so by virtue of bringing it all together and creating these dashboards at the, at the community level, but then also at the home office level, at least they know where they are, right? They can identify problem areas or locations that might be struggling or they can identify opportunities to recruit a full-time person because you’re using agency in the same pattern week over week. There’s an opportunity to hire. If you don’t have the data, that stuff just isn’t gonna jump out at the scheduler. They’re, they’re sort of struggling to survive, right? 24 by seven job really. And so I’d say a, it’s data and second of all, um, you know, we um, we have a, a sophisticated tiering engine in our product, which effectively allows the, the shift to hit our platform and then go through a very sort of sequential marketing process to agencies. So the worst thing you can do is get into a rhythm where you take shifts that are four or sometimes even eight weeks out and publish them to agencies. Agencies should be there for a last minute use. It’s not there for eight weeks out because geez, eight weeks from now you might be able to hire three or four people to fill those shifts. And then you say, well, well then we’ll cancel the agency. But in reality, schedulers know that you can’t just start canceling agency cuz then the agency won’t work very hard for you. They’ll assume they’re gonna get canceled. And so, you know, I believe that this problem is, it’s a scale problem. There’s simply too many shifts coming and going with too many agencies, too many communications, all manual that you just can’t technology helping you. And that’s so setting up the right tiering so that shifts are exposed to agencies in a logical order so that they’re working on only the shifts that are of utmost importance and that ultimately you get the highest quality, lowest cost nurse into the shift is what the industry needs. It’s automation over, you know, it’s kind of the future, right? Is let technology do what it’s good at so that, you know, people are left to do the rest.

Patrick Leonard:
12:58

Yeah, definitely. So you, you talked a lot about the data from the operator side and there’s a lot of different systems and workflows going into play here. As you’re just talking, I’m thinking about the different stakeholders within an organization that this might impact. Can you talk a little bit about does your platform fully integrate some of these solutions so that all the data is in one place? I assume there’s some reliance on other platforms out there as well, whether it be related to, you know, HR, time sheets, scheduling, things like that, other platforms people might be using the conjunction to Kevala. Can you talk a little bit about that kind of data management and workflow management from that perspective, if you will?

Todd Owens:
13:42

Yeah, so we are ultimately a system of record for the, the shift. So, you know, what, what, who filled the open shift and we also have a time and attendance aspect, not attendance, but a time sheet aspect to it. Why? Because it’s better than paper, which continues to be the primary source of tracking time, you know, across the agencies. Sometimes there’s gonna be a scheduling system in place, not always surprisingly, you know, but you know, sometimes it’s, it’s still a spreadsheet, but sometimes there’s gonna be a scheduling system in place and that could be a, a system like an on shift or a Kronos and that’s going to, it’s gonna be necessary that we integrate with those systems. In fact, you know, I would tell your audience, like we absolutely can and we’ll integrate to any scheduling system that we need to so that we can marry together the permanent staff in that scheduling system with the site system so that you can get a combined view, right? That’s gonna be necessary in the cases where there is a preexisting scheduling system. If there’s not, we intend to develop the capabilities so that they can use, use our system as well. So that’s, that’s a big one. As you think about intelligent scheduling, it starts with knowing what census and acuity is in the building and knowing what the staffing model is based on the, the physical characteristics of the building, right? Number of floors, long hallways, teams zones. And so we’ve got a budding new partnership going on with point click care to, to look at how we can integrate the two systems of care data into Kevala so that we can create the most efficient schedule in the first place. So it’s constantly changing and I think the right answer is not to simply copy and paste what you did last week or the week before, the week before that, and then find that, oh you’re, you know, either you’re understaffed or overstaffed, there’s like drift that happens. The right thing to do would be able to have real-time data come in from the EMR and that’s a, that is isn’t gonna be an increasingly important point of integration if we’re gonna truly realize this goal of being intelligent. Then lastly, I’d just say, you know, by virtue of being in a position to touch the shift or the, the workforce in total, but also those that are on the shift, all of them, including permanent staff as well, we come, we become kind of a last mile point of connectivity to them. And so when you think of all the signals that are kicking off from around the, around the building, whether it’s a fall detector or whether it’s a, an alert coming out of an EMR, we’re uniquely positioned as a system that can deliver that message to those that are on shift at that point in time, and so that the, I guess I’ll, I’ll leave you with this, that, you know, the ecosystem of integrations is gonna be incredibly important to our ability to deliver value to our clients.

Patrick Leonard:
16:18

Yeah, absolutely, and I think that’s been a common thread for the last few years, but it just increasingly becomes more and more important with so many innovative solutions that are specialized in different areas of the operations of the community. You know, everybody has to play nicely together these days to really benefit the industry as a whole. So it’s, it’s really cool to see that happening more and more and then the, the depth of those integrations as well, getting better and better as well. So that’s fantastic. So this is a call to everyone out there<laugh>, to continue to do that, to continue to integrate and open up your platforms to play nicely with Get together. So we, we’ve talked a lot about, you know, and getting a pretty good sense from an operator’s perspective, how this kind of all works and comes together to, to manage these shifts. Can you talk a little bit more about kind of the nurse perspective? How are they feeling about this? How are they interacting with Kevala and what is ultimately the impact on that perspective that it’s having back to the operators and is that being communicated?

Todd Owens:
17:17

Yeah. Well because we started as a labor marketplace with our own W-2 nurses picking up shifts, we get their feedback every day. And the level of satisfaction that they have with Kevala as an employer is, is unlike anything I’ve seen in my professional career. So here we are in a segment of the workforce that is burning out, you know, treating quickly and yet they are incredibly happy. You know, our NPS has gotta be a nine point on average, if you use the true NPS of a hundred to minus 100, we’re at like an an 80, NPS which is exceptionally high. And what it is is flexibility. That’s that’s what it is. That’s what they like and then they like to be treated with respect. And so I think we’re pretty good at, you know, because because we are process-oriented people and we’ve got technology working to help us out, we’re able to manage our, our team very well, even with a light touch. So I, you know, last week we put 400 unique nurses into shifts across the country. Next week it’ll be a different set of 400 and it’s not us telling them where, where to work, it’s them picking the shifts they wanna work at. And so they’ll leverage technology to scale and to do it with a, with incredible loyalty from these these nurses is, is, is high. So flexibility is one, and then I think the other one is, you know, with technology we’ve gotta build highly usable software, you know, and I think it’s a real advantage to companies that are coming out of the gate more recently that we have all of the lessons learned from the last 10 years from the mobile economy, right? You know, the iPhone and apps and, and the gig economy and what it’s like to, to work, you know, a different, you know, gig every day and, and how your software and technologies should behave. So we, you know, our first hire at Kevala was a designer, and it’s something that, you know, we continue to take great pride in is designing a software that is designed first and foremost around the frontline care team. There’s a lot of software out there that, you know, just isn’t usable and therefore becomes shelfware. And so, you know, I’d say that that’s, that’s another perspective. They, you know, we wondered whether or not they would be able to embrace technology and there has been no issue with that thankfully, cuz that would’ve been really difficult to get’em off paper if, if they don’t really want to move off of paper, they all have smartphones and you know, that is how they communicate via text messaging. They’re on Facebook, I need to give them technology that is, that is just as usable as the software they use in their daily lives.

Patrick Leonard:
19:41

Thanks for that, and This might be a segment here. I was just thinking of this question as you were talking about these different, all the different 400 plus shifts being filled last week, I think you said across the country, it made me my mind go to just different labor laws and different credentialing or I guess the compliance side of things across the country. I don’t know if this has necessarily a huge amount of impact of what you all do, but it just made me think of that. Can you talk a little bit about that and how you all manage that, if that is something that you have to keep a pulse on?

Todd Owens:
20:13

Yeah, it does. Thanks for asking the question. Not everybody wants to talk about compliance<laugh>.

Patrick Leonard:
20:19

It’s not the always the most exciting topic, but it’s very, very relevant obviously and important in this industry. So I couldn’t help but think about it as you were talking about that and thought it might make sense to touch on it real quick.

Todd Owens:
20:30

It’s very relevant. I mean, if you don’t know who the individual is, not just where they are and what license they have, but what qualifications and skills and whether or not they’re current from a compliance perspective, it’s pretty hard to put people into shifts. So it’s actually kind of a core capability of our platform to marry up a workforce with a set of policies so that you know, whether or not somebody is either red, yellow or green red, meaning they can’t work yellow, meaning that something needs to be addressed in the next 30 days. And green meaning they’re good to go for for you, they may not be green for somebody else, but they’re green for you because of your compliance requirements or your state’s re compliance requirements, which could be different. So, you know, it is, it is very much a an aspect of, you know, making sure that you’re, uh, dotting your eyes and crossing your t’s with regulators, but it’s also relevant to making sure that you help to schedule so that people are working at the top of their license. So one of the things that we heard early on was, you know, if I, I, you know, if I can do with a, you know, a CNA, I, don’t need a med tech or somebody to pass meds. If I can do with an LPN, I don’t need somebody that’s that’s got a RN, and so again perfect with regards to the profile and the compliance status of the workforce in is a really big deal when you think about optimizing the schedule and getting the most out of your workforce, you know, that you possibly can.

Patrick Leonard:
21:56

Thanks for that. Thanks for, for touching on that side of things. How does it look like if I were a senior living community and, you know, I list this podcast<laugh> and all this sounds very interesting, obviously. What is the, can you break it down practically a little bit to how does, how does an organization go about implementing a solution like this based off of where they’re at today? I’m sure it depends a little bit of course, but, you know, take your, your typical, if there is senior living community and they want to go through this transition to really empower their workforce management solution after community. Can you tell me a little bit about what that process looks like?

Todd Owens:
22:31

Yeah, you know, so from the community-level perspective, it is pain free. So this is, you know, really a decision that, you know, I as a scheduler or an executive director or a GM want to unify and digitize my agency’s schedule so that everybody’s working off the same page. It’s the decision to do that. When we get engaged, we typically do, the agencies that our client work works with are invited to the platform very soon, you know, in the next month they’ll be able to invite their permanent staff employees as well so that they can see shifts before those same shifts get exposed to the agency and they can be up and running, you know, immediately. There’s no extensive configuration. It’s really just a matter of, you know, inviting the participants to the table. And so one of the things that we do to make that super easy for our clients is, you know, we let them make the invitation to the agency, but then we give the white glove onboarding treatment to that agency. And so of course there are questions, what is this technology like? Why are we doing this? Is this going to, is this gonna disintermediate me? And, you know, we’re able to very quickly get them on the same page too. So when we talk about net promoter score, customer satisfaction, our agency satisfaction is very high for the first time, they’re actually looking at a real-time view of the current needs of that facility, right? They’re not working on outdated information or shifts that have already been filled by somebody else. When they apply a few mouse clicks, they can apply a name to the, to the, the, uh, schedule and it can be approved so they, they don’t have to go to a phone call or to a text message, which again, takes it out out of band offline. And, and now you lose all of the efficiency and the trackability of the process, right? Time sheets. Now that time sheets are, are part of it. We introduced to them the ability to actually digitally, so now you and your client are looking at the same approved time sheet, talk about making it a lot easier to get through the, the revenue cycle, you know, in terms of the billing process and the accounts payable process for that agency. So we take them through that and by the end of the conversation they’re loving it. But the, from the, from the client’s perspective, it’s an intro introduction to the platform. We tell them how to, how to, uh, to create open shifts either in bulk or one at a time. We, we go through the process of inviting digitally the agencies into the product. We then take, we go offline and onboard them and they’re off to the races. The question then is this play in this, right? And, and ultimately this is really where the greatest success has happened is when the home office, usually the CEO, COO, CFO and sometimes the VP of HR agree that it is in their organization’s best interest to standardize around a digital process and one that will serve up all of the real- time data that they need to run a more efficient and effective business. And when we have that top down sort of, not pressure, but conviction and maybe a little bit of pressure that we’re, we’re going to the deployment process across a large chain can go very quickly. If that’s not there, then it’s sort of left up to the technology platform to convince every one of the locations. And that just delays progress. That’s all we can do it and we do do it, but I think that this industry is getting to a place here post COVID where change system, systematic strategic change, is gonna have to originate at the home office.

Patrick Leonard:
25:58

Yep, absolutely, and thanks for adding that on there and that, that kind of leads to where I wanted to end our time today, which is what’s next? You know, right now, obviously I don’t even like mentioning the COVID crisis and the, the subsequent staffing crisis as people are calling it, but you know, that is what it is. But looking forward, what, what’s next? Is there light at the end of the tunnel? And the second part of that question is, are there any other words of wisdom for our listeners, particularly the operators who are going through this and living through this every day? You know, if you can kind of leave yeah, and part them with one word of wisdom, what, what would that be?

Todd Owens:
26:33

I think there’s a ton of hope. So I think my sense is, and I I’m new to the industry, I’ve only been in senior living since 2020, so I, I’m only in for three years myself, was that it was a fight for survival, really. And it, it feels to me like we’re coming out of it and now learned as to what was working and what was not. There’s sort of like a, an opportunity to take a deep breath, rethink and reinvent for a better tomorrow. And you know, I think a big part of that is gonna be technology, right? Technology that helps the team be smarter, the team to do more with less, bring visibility and transparency and connectivity to the organization. And so, you know, uh, there is so much innovation going on in the world and when you poke your head into a typical healthcare organization in your living is no exception. There’s still a lot of that is sort of thankless work. And I think that with the right alignment and the right sort of ecosystem of, of innovators and startups and suppliers out there, you know, that we’re gonna be able to lock arms and, you know, and make real progress. So I would say better software, more intelligent software that, that helps to make recommendations, but also software that automates the, the mundane, repetitive task so that, so that, you know, a senior loving community can do what it really wants to do, which is focus on care.

Patrick Leonard:
27:54

Rethink and reinvent for a better tomorrow. That really stuck with me and your sign off there. So thanks for, I wrote it down and I’m gonna revisit that later. But, Todd, thanks so much for being with us today and for your time. I really enjoyed the conversation and I know our listeners will too.

Todd Owens:
28:08

Thanks, Patrick. It’s my pleasure!

Patrick Leonard:
28:09

And listeners, thanks for tuning in for another episode of Raising Tech. I know and hope that you’ll pick up some valuable information from today. If there are any other topics you want to hear about or want to be on an episode yourself, please feel free to reach out on our website at www.parasolalliance.com. Have a good one!

Patrick Leonard (00:06):

Welcome to Raising Tech, a podcast about all things technology and senior living. I’m your host, Patrick Leonard, and today I’m really excited to welcome our guest, Ramiro Maldonado from Nobi. Ramiro, welcome to the show.

Ramiro Maldonado (00:19):

Thank you so much, Patrick. So happy to be here.

Patrick Leonard (00:21):

Really interested to learn more and educate our listeners on our topic today, which involves Nobis innovative technology solution for fall prevention and detection. I was actually fortunate enough a few weeks ago to get a live virtual demo of the solution myself from Ramiro, and it was fascinating. But before we dive in, Ramiro, can you introduce yourself real quick, your background and role with Nobi?

Ramiro Maldonado (00:44):

Sure. Yeah. So, thanks so much for that. It was a lot of fun to kind of demo the product to you a few weeks ago. So, my background is, you know, somewhat interesting. So, for a long period of, of, of my professional career, I actually practiced as a clinician, as a physical therapist for roughly a little over 10 years, and I kind of geared my practice towards fall prevention and just fall kind of prevention in the community that I served. So, I got my certification of vestibular therapy and neurotherapy and kind of worked with the, the community in that way. So in that world of physical therapy, I got just kind of exposed to a lot of different kind of technologies that are available to individuals for, you know, improving their, their strength, improving their balance.

Ramiro Maldonado (01:36):

So, I just really kind of fell in love with the technology side of things. So, I transitioned my career into a more tech -related role. So, for few years I’ve worked with a few different companies as either their business development specialist or clinical application specialist, where I kind of served a dual role where I was, performed somewhat of a sales role as well as a clinical applications role of training clinicians on how to use these new devices and and rehab equipment. Then, kind of fast forward to me learning about Nobi and my interest and, and kind of, uh, passion towards kind of improving the balance of, of the community. I just really just saw the value of nobody right away. So, it’s a device that is able to kind of detect and prevent falls, which is exactly the kind of space where I wanted to, to be, you know to be able to get into a situation where we could start to help improve the health of individuals as opposed to getting them after the fact and trying to rehabilitate them after the fact.

Ramiro Maldonado (02:38):

Anything that could help beforehand, if I, we could if there’s a device that can kind of prevent that larger kind of severity of injury happening is where, where I kind of want it to be. So, that’s where I came in and with Nobi as their business development manager for North America, and I’ve been doing that since August of last year.

Patrick Leonard (03:01):

Awesome. Thanks for that background. I love to hear people’s kind of intro into senior living, into technology and, you know, your physical therapy background is certainly applicable and relevant here, so thanks for sharing that.

Ramiro Maldonado (03:15):

For sure.

Patrick Leonard (03:15):

So you touched on it a little bit and we’ve, we’ve said, you know, fall detection, fall prevention, that’s such a buzzword right now in this industry, and there’s certainly a lot of cool solutions out there, but yours is, is very unique at, at Nobi, um, that I learned, like I mentioned, really in depth a few weeks ago. Can you, from a high level, just tell people what is Nobi? Where did it come from, and what are you all hoping to accomplish as it relates to its presence in senior living?

Ramiro Maldonado (03:42):

Sure, sure. So, first and foremost, Nobi, we like to say that Nobi is the smartest lamp in the, in the world, right? So it’s a lamp first and and foremost and it’s you, it’s indiscernible from healthcare technology. You would walk into someone’s room, you would see it, you would just say, oh, that’s a very nice, nice lamp that functions very nicely. It actually even provides something called circadian light. So, as you start to rise in your morning, it’s just a very nice soft light to kind of help you with arousal throughout your day, becomes a little bit brighter, so again, can help with your arousal and, and make sure it’s you’re awake during your day. At nighttime, it starts to calm back down again because it’s allowing the resident to kind of get back into that nighttime routine.

Ramiro Maldonado (04:29):

So, even just as a lamp, it just functions very nicely, but the smartness behind it, so it’s an AI, so artificial intelligence enabled lamp that at its core can prevent and detect falls. So doesn’t matter what kind of fall it is, we have feted so many data points that it has learned any kind of fall that can occur. So should a fall occur, fall, you know, would it be a fast fall, slow fall, just kind of stumbling to the ground, whatever it may be, it recognizes that fall. At that point it opens up a two-way communication through the lamp, via the lamp, allowing you an opportunity to now speak to that resident and say, Hey, I heard you had a fall. We are, we are on our, on our way, you know, uh, so, you know, you can stay relaxed.

Ramiro Maldonado (05:17):

Caregiver comes in, they can now, uh, do whatever they need to do to help that individual and then also what they receive is feedback of how that fall occurred. So, The caregiver will have a 30 seconds of feedback of footage before that fall occurred until they closed that escalation, so that when they closed that fall, allowing them the opportunity to see what caused that fall. Was it that they tripped on something in the room? Did they just not have the strength to be able to get up or any number of, of, uh, of factors that could have potentially have caused that fall? And what we’re finding is that in facilities that have implemented Nobi, they’re on average per you know, producing about a one fall preventative measure per a residence’s room roughly every six days or so. So if they’re able to kind of prevent any type of major falls from, from happening to, and, and, and severity of injury and prevent that severity of injury for their resident, and that’s what it does at its core, and this is a, a lot more of other kind of interesting stuff as well. But at its core, that’s what it, what it does.

Patrick Leonard (06:25):

Yeah, that’s amazing and that status is impressive. One per resident room every six days. I didn’t butcher that too much. That’s a huge, huge difference in impact on senior living residents. So that’s awesome. Thanks for sharing that.

Ramiro Maldonado (06:41):

For sure.

Patrick Leonard (06:42):

So how are I, when I think of something like this, I think of two sides of it, the residents response and then the staff. Can you talk a little bit about both perspectives a little bit? You, you gave us a little, a nice overview of kind of how it functions, but can you dive a little bit deeper? How are residents responding to this? And then on the flip side, how are staff responding to it?

Ramiro Maldonado (07:04):

For sure. Yeah, so, we have some really interesting, uh, data coming out of some of our pilot studies that have been performed in Belgium. So, you know, small bit of background. So, Nobi is a company founded in Belgium 2018 by a lot of leaders and smart home and elderly care. They got together and developed Nobi, completely manufactured factories in Belgium. We control the process from manufacturing to, you know, just kind of conjuring it up and to getting it out there. So we have full quality control over the, over that device. So, and then in that situation, so we have a pilot study in an assisted living facility in Belgium. I’ll start from a resident’s perspective. So we do have this kind of really cool test testimonial on the website. I believe the woman’s name is, is Helen.

Ramiro Maldonado (08:00):

She had to enter an assisted living facility because she was just having more, more falls at home, brought her into this facility and actually on her very first day of, of being into, being in this facility, she ended up having a fall. She fell slowly. She was at her bedside and just kind of slowly fell down until both her knees touched the floor, very similar to the kind of fall that she had at home that brought her to this facility, and so because of that, you know, she has a lot of fall anxiety. She was just very fearful of falling and just kind of worried and now, she was in a situation where she just kind of like, oh my gosh, you know, it’s happened again. Here I am first day in this facility, and I’ve, and I’ve had a fall again, and I, and I just don’t know what to do.

Ramiro Maldonado (08:48):

You know, she knew, she kind of understood that there was a Nobi in the room, but didn’t really quite kind of grasp that technology, right? She wasn’t kind of there long enough. You had to really have that understanding of Nobi. So within just a few, few seconds of her being on the ground Nobi then asked her, “Hey, Helen, have you had a fall? I don’t, I don’t, I don’t see what I, you know, like, uh, I see that you’re not upright,” and Helen unbeknownst to her, she’s like, “oh my gosh, where is this, you know, voice coming from?” It’s like, you know, the voice of the lamp above, and she’s, she’s just like, “yes, yes, I’ve had a fall.” So, that nobody responds with okay, help is underway, opens up that two-way communication. The caregiver, the nurses at that site now have an opportunity to help decrease her anxiety levels, letting her know like, Hey, I heard you had to fall.

Ramiro Maldonado (09:36):

I’m coming to your room. I’ll be there at no time flat. So, and we were able to kind of find out what that timing was. So from the incident occurring to caregiver giving help was under two minutes of being able to help this woman off the ground and then help her, you know, with, with the kind of arrangements of the room that caused, to fall in the first place. So that’s what we’re getting from the resident’s side of it, that they just loved the peace of mind, the decrease of anxiety, knowing that they are always going to be helped, should a fall occur, which is you know, that’s, that’s a big issue with the elderly population and senior home facilities, right? The longer people spend on on the ground following a fall, it’s, it’s proven that there’s higher levels of severity of, of injury.

Ramiro Maldonado (10:26):

So the sooner we can get to them provide that help, decrease that fall anxiety is extremely important. So that’s the kind of feedback that we’re getting from, from the resident side of things. Now, on, on the flip side of that, the staffing, the, the clinical staff little bit for that aspect as well, right? So in a lot of these facilities, so let’s say in a memory care facility, right, where residents may not have the capacity to let you know that they’ve had a fall or, or when they’ve had a fall or, or, or, you know, if it falls even occurred often staff have to enter these rooms roughly every hour, right? So, this is a, a part of their workflow that they don’t necessarily enjoy. It takes away from other important tests they could be doing.

Ramiro Maldonado (11:12):

And on top of that it disrupts the sleep of whoever is in that room every single time you open that door which is, you know, I, not really the ideal case for someone that has memory care issues in a situation where you have Nobi. We found now, the staff can now kind of take a breather knowing that Nobi is in that room monitoring their patients, monitoring their residents, so that should something occur, they’re always gonna be notified because of that artificial intelligence within the lamp. We can, we can say that it has, it provides 100% accuracy and fall detection and in the situations where it provides a, you know, a false positive, we find that it’s often a situation where the nurses still want it to be notified of that event because they go into that room and it looks like the resident is in a situation where, you know, maybe something is just about to occur.

Ramiro Maldonado (12:06):

And that’s often a situation that we’re hearing whenever a false positive has occurred and and so 100% accuracy and fall detection, extremely low false positive rates and in situations where we get a false positive, it’s often a situation where nurse is like, you know what? I’m glad I got notified at this event. Now, I could help this in individual, maybe sit back up in a chair a little bit better, or whatever it may be. So to that point, we’re finding that there’s a lot of really beneficial kind of network effects, right? So, these, the nurses, the clinical staff are now able to kind of focus on, on, on work, that is, that is very valuable and more important to them. So if they could kind of continue caring for all their residents, they’re able to intervene sooner, before a major event occurs and then directors of facilities are telling us that this has helped them with their staffing as well. They don’t have to staff as much overnight reducing some of those staffing costs as well. So, and that kind of in a nutshell is what we’ve been finding out from both sides of the, of the camp of the, of the Nobi users.

Patrick Leonard (13:16):

Awesome. Thanks for providing those two perspectives. Those are some awesome kind of use cases, statistics, testimonials, um, from Helen in particular. I love, I mean, day one, no better. Yeah, unfortunately. I mean, obviously you don’t want to, to see a fall happen in the first place, but the fact that you’re able to have a response so quickly from the caregivers and going forward, I imagine Helen felt much safer at at Oh, yeah and much more at home after that experience of after getting over that initial anxiety. I’m sure that was, yeah,

Ramiro Maldonado (13:51):

Scary. And you think about the anxiety of, of, of her and then also, but the, and then the family, well, the, you know, the family piece, you know, the family hears about what nobody was able to do, and now they all of a sudden you could see the anxiety levels drop there as well. So, um, there is just kind of all the stakeholders that are involved, you know, the, the actual resident in the room, the the clinical staff the, the children of the resident, it all just kind of really kind of helps everyone just kind of breathe a little bit easier and knowing that their loved one is gonna be, gonna be cared for and attended to as quickly as possible. Another interesting stat that came out from that, pilot study as well was that so they, we outfitted an entire wing with Nobis, and then we had another wing where they’re were, you know, were without Nobis.

Ramiro Maldonado (14:42):

It just kind of compare and contrasted it two. So the wing without Nobis used there, a standard all preventative measures and what we’ve found was that the rooms where there were the Nobis that they identified 80% more falls than previous fall preventative measures that they were using beforehand. So that’s 80% more falls, right? So that says a lot, right? I mean, you know, CDC even mentions this, that most people have a fall, most falls aren’t as severe, necessarily one in roughly five falls is gonna be a severe fall but the highest predictor of whether or not you’re going to fall is a previous fall, right? But we also know that most people don’t like to fess up that they’ve, that they’ve had a fall because it might mean like some type of change and status of what they’re living or whatever it may be, that they don’t necessarily want to tell people just recognizes it. 80% more falls were recognized, which allowed them to do those preventative measures. So if these individuals can then continue to age where they want to be in, in the setting that they wanted to be in and didn’t necessarily have any kind of other, you knows severe effects from, from a fall.

Patrick Leonard (15:52):

Yeah. That’s fantastic. And that kind of leads into, you know, prompted another question as you’re talking about that I, I assume you’re, and what you just mentioned is you’re gathering all of this data, the Nobi is gathering all this data about their residents, their behaviors, and then that data is being used to take preventative measures and provide peace of mind. Can you talk a little bit more about kind of the technology piece of it, you know, what makes it different? What, what, where, what are you all doing with the data? What is the community doing with the data and, that leads into part two, I love part two questions, of course. Mm-hmm, the integration piece, this seems like, I’m sure a lot of this data is valuable in other systems within the community, can you talk about the data and integration side a little bit?

Ramiro Maldonado (16:41):

Most definitely. Yeah. So, so, you know, so again, we, we like to say Nobi is the smartest lamp in the world, right? So, it has a very strong processor on the lamp itself. What the, the lamp is processing at all times is, you know, what’s going on in, in the room? What is the individual doing? Are they just sitting it recognizes, are they just sitting? Are they sitting at edge of bed? Are they laying down bed? Are they just walking around their room? If that kind of data is what’s occurring it kind of records this data and as far as, an integration piece, we can integrate, via a API to electronic health records or via Bluetooth to any type of smart kind of device, smart scale, smart, blood pressure cuff, things of that nature.

Ramiro Maldonado (17:32):

So, in this situation where let’s say a wing wants to be notified, again, I’ll, I’ll use the, example of maybe a memory care unit, maybe in that wing, they want to be notified whenever a resident sits up at the edge of the bed because they know that they’re a little bit out of a, a higher risk for falls. You can program the no in such a way that it’ll notify the care station. Okay, Hey, John, in room 302 has now set up at the, at the edge of the bed, and you could fully customize that for the entire wing, or even by individual, let’s say on the other side, the independent living side, you’re fine with just you know, just having it escalate when a fall has occurred. But maybe you wanna know when you know Jane has been in the bathroom for a little bit over, some long, long period of time, you wanna be notified anytime she’s been in the bathroom for longer than 15 minutes.

Ramiro Maldonado (18:20):

Then Nobi again, can also notify you of that situation as well. You could customize that fully by wing or by by individual. All that data is processed on the lamp. Once it kind of does what it needs to, to do with that data, right? Notifying the nurses or putting, you know, some of that, those, that Bluetooth enabled like heart rate detection or blood pressure cuff, blood pressure monitoring into the electronic health record, the data on the lamp is, is purged off. You know, it’s important for us that the, that the resident knows that their data is their own, and we’re only using the data that’s important for their care staff to, to be able to make clinical decisions on. So that data is now purged once we’ve kind of used it, in, in the capacity that we need to use it in, in a situation of escalation, that’s when something gets pushed off into the cloud.

Ramiro Maldonado (19:12):

That’s the only time when you now have those video recordings that I was, that I was mentioning and by video recording it’s really more so a second by second snapshot of what occurred prior to that fall happening. Until you close that escalation, and by closing escalation, that means that you’ve gone to the room address, the individual and I have either closed it onto the app on your phone or onto dashboard on your computer. You now have a video image of that to be able to kind of, again, assess what occurred, why did that fall occur. Even that data that only exists on the cloud for two weeks before it gets purged off of the cloud as well, allowing the, the clinical stats, we able to make the reports and whatever they need to do. Now we’ve gotten a step further and protecting that privacy as well.

Ramiro Maldonado (20:02):

By allowing the resident, the resident now has to choose guests to choose how this video is going to present to the clinician. They have three options. They can say, you know what? I am okay with them actually seeing me fully in that video and that way the clinician would then see the full run video. What we see overwhelmingly is the second choice, which is, what, what happens is it breaks down the individual into a stick figure, a stick figure avatar. So an 18 figure, 18 point stick figure where you could see what’s going on, but you cannot discern if that’s a male, female or any other kind of demographics. But you can figure out what happened in that room and make the changes that are necessary. That has been by far the most widely adopted imaging that nursing homes and, and residents and assisted living facilities have selected.

Ramiro Maldonado (20:53):

and then on the very end what we’re fi we, there’s a, we also offer this selection of, I want nothing. I want no images to be shared with my caregivers. I am completely fine with them getting the escalation that I’ve had a flaw, but that’s where I wanted to stop. I don’t want them to see any images and at that point, no images get sent to the cloud and it just continues with business as usual and so that’s the kind of the data that we can put out there and how we use that data and what we want to do with that data and recognize that that data is owned by the resident. And again, with the, with the integration piece, again, we can integrate with any number of electronic health records or any number of smart devices via Bluetooth on the smart device end or via API into a software or like electronic health record end.

Patrick Leonard (21:50):

Great. Excuse me.

Ramiro Maldonado (21:52):

No worries.

Patrick Leonard (21:55):

Great. Thanks for thanks for walking us through that. That’s super helpful because I know that’s a big question you get these days and rightfully so with any new technology installation, you know, you wanna know not only what is it doing on a day-to-day basis, but how we’re using the data that’s being collected through these innovative solutions and use them to just make the community, the resident and the staff’s life easier.

Ramiro Maldonado (22:18):

Right. Most definitely.

Patrick Leonard (22:21):

So that leads me to a question around installation and kind of ongoing support that’s needed around this. Not to simplify it, but is it as easy as installing a normal lamp in a room? What does that look like from your, your perspective and how did the, from the senior living community’s perspective from the resident’s room, and how is it, how does it need to be supported on an ongoing basis?

Ramiro Maldonado (22:48):

Yeah, so great question and I mean, I can honestly say that it really is as simple as just installing a ceiling lamp into, into your room. I mean, I actually happen to have one in my home office that I was able to install myself. It is, long as you have electricity and wifi, Nobi can function in a space and again, if there was already a ceiling light or ceiling fixture or some type of fixture already in place there, that is as simple as just swapping that out down the line. We even intend to make this an even easier process of installation. There’s some really cool things on the product roadmap where they’re going to have an ability to kind of, you know, so you have that ceiling light fixture, you can adhere a magnetic plate to the, to the ceiling fixture, and then you could even do that before you even get the Nobi.

Ramiro Maldonado (23:46):

And then once the Nobi arrives, you just snap it into a place with the magnetic, and then that magnet will also provide the power to the Nobi as well. So, but right now it is as if you’re just hanging a normal hanging, ceiling light fixture. As far as kind of installation and ongoing support, we are actively working with our distributors who have a very strong installation network. They have their own level of customer support at the, at the first level. But again, since we control the process of engineering product you know, of manufacturing it from beginning to end, should there be a, a necessary, you know, they need to kind of escalate it up to headquarters. We have a direct line to our distributors, they can call our engineers and they have that level of support right there as well. But, luckily it is truly a very easy and simple device to use. Not a lot of issues with, with things kind of falling apart or anything like that. If typically if there’s any issue, it’s usually just something like just helping with the wifi connection usually.

Patrick Leonard (24:56):

That makes sense. Do you need to swap out light bulbs?

Ramiro Maldonado (25:01):

No, no, no. Light bulb swapping. Yeah, so, the LED I mean, you know, as far as, if it’s normal, normal usage, it’s, it should have a, a lifespan of, you know, normal LED, normal LED light.

Patrick Leonard (25:17):

Awesome. So this has been really helpful for me personally to learn more about it. I’m already looking up at my ceiling and wishing I had a Nobi instead of my boring ceiling lamp up here. But thanks so much for taking the time today. I know before, you know, we started chatting today, you’d mentioned, you know, recently being at the, out at the CES show in Vegas, the Consumer Electronics Show, and you had some exciting things, you know, on the horizon. Without sharing any secrets here, are you able to kind of tell us a little bit about what’s next for Nobi and any kind of final thoughts or words for our listeners?

Ramiro Maldonado (25:55):

Yeah, so, um, another really thing that I love about Nobi is that because it is a, a learning device and, we’re very much so committed to making sure that individuals in their home have the most up to date and, and kind of highly functioning Nobi. Whenever the AI learn something new or has a new functionality, we’re gonna push that functionality out onto all Nobis into the field so that a resident will wake up new the next day and they have this new functionality. So for instance if, uh, a senior home, a senior facility were to purchase Nobis today, they will get our, our newest model of the Nobi and this Nobi looks even closer to just kind of, a really beautifully designed lamp like I was saying before, I, I really enjoy the current design of the, of the lamp, but if you were to see it, you, you might say, okay, that looks like a high technology kind of, kind of lamp.

Ramiro Maldonado (26:53):

The newer design looks almost identical to something that you potentially purchase at, at like an, ikea. We’ve added some new hardware to this device as well. So it has radar technology in it as well and what this now allows for the device to do is vital sign detection. So we are now able to do breath rate detection as well as cough detection with the device, and very soon roll, rolling out likely at some point this year, because of the fact that this is alerting device, we’re gonna now be able to provide predictive analytics. So we’re, we’re finding with a lot of the data that we’re getting from, from the device and what the device is learning, is that an often 60% of cases, there is a very specific kind of way that individuals are moving that are highly predictive of a fall.

Ramiro Maldonado (27:47):

So we can now tell the nurses, the nursing staff, the clinical care staff, like, Hey, you know, resident room 302 is acting kind of strange. Again, this is highly very indicative of a fall. You should maybe go, go check on this individual because we could start to provide that and we’re gonna start to provide that very soon. So those are some of the cool things that are, that are on the way that are currently in the process. And then, you know, as the lamp new learns more things that, uh, that functionality will be out there so that any owner of a Nobi will always have the most up-to-date version with the highest functionality.

Patrick Leonard (28:24):

Fantastic. Ramiro, thanks so much again for being with us today. I really enjoyed the discussion and I know our listeners will, will get some great value out of listening as well.

Ramiro Maldonado (28:33):

Thank you so much. Thank you for your time. It’s been, it’s been great.

Patrick Leonard (28:38):

Awesome. And listeners, thanks for tuning into another episode of Raising Tech. I hope you picked up some valuable information today. If there are any other topics you want to hear about or wanna be on an episode yourself, please feel free to reach out on our website at www.parasolalliance.com. Have a good one!

(Amber 0.05)
Welcome to Raising Tech Podcast. I’m your host, Amber Bardon, and we are doing our first episode for 2023. So, to kick us off for the year, we have a guest who is a personal friend of mine, and I’m so excited to finally have her on show. Jackie Ramieri, welcome to the show today.

(Jackie 0.17)
Hey Amber, thanks for having me!

(Amber 0.25)
Jackie, you have done something so interesting with your company, and I think the solution that you brought to the market is something that’s really been needed in senior living for a long time. I think there’s been a really big gap that you’re filling with CareWork, which is your new company. So, to start off with, can you just tell me a little bit about your background? How long have you been in senior living, and then what led you to found CareWork and what is CareWork at a high level?

(Jackie 0.48)
Yeah, so, I’ve worked in senior living specifically since about 2008. Prior to CareWork, I was a fractional CIO for multiple operators,  kind of all over the country, and I was trying to buy something like CareWork. So, as a buyer I was demoing solution after solution and very quickly realized, and this was in early 2020, that what I was looking for didn’t exist at all on the market. So, I was frustrated.  I reached out to my clients and just asked them if they’d be willing to be patient with me so that I could see if it was something that I could build  and have developed, and they were very, very patient to the tune of about two and a half years, which has gotten us where we are today with CareWork.

(Jackie 1:40)
So what CareWork is, it’s the first ever unified operations platform, specifically designed for long-term care and senior living operators. We integrate agnostically with the systems that operators already use, tie that data together, organize it across their operational flows, but what makes us really unique is that we build in custom report automation and workflow capability.

(Jackie 2:06)
So, operators actually have the ability to add in operational data to this database that now exists. So, stuff that they could never really trend and track or have a part of their data. Picture things like how many state and federal visits have I had? We wanna be able to take that data off spreadsheets and put it into an intelligent platform so that they can use it to make decisions improve and get better.

(Amber 2:31)
That’s fantastic! To help our listeners who are listening to this podcast, can you sort of, can you describe what does CareWork look like when you log in? What’s the information that you see? How do you navigate through the system? Are you able to give us a, a visual picture of the system?

(Jackie 2:48)
Absolutely. So, the first thing I’m gonna start with is to say that it is ridiculously easy to use.  We designed the system to be usable without training because none of us have time for complicated, especially in long-term care and senior living. So it is a very clean layout. We do offer obviously new client, what you would call training.

(Jackie 3:12)  
We don’t even call it training. We call it a tour because training implies that it requires real time and effort to learn and it just doesn’t. So, the entire site is searchable. If you have a brand new DON who started in, you know, for example, day one, and she comes in and has never used CareWork and hasn’t had time for her tour yet, but just wants to see everything having to do with infection rate.

(Jackie 3:17)
She can type in infection rate and the search bar just like she would do in Google, which everyone’s familiar with, and it’ll pop up every report that contains the search term, requested. Every report and function task is favorable. So, you can very easily access the things that you use over and over again, and everything’s really organized across industry standard operational flows. So,  census labor, financial procurement, clinical quality, everything is very, very easy to find, and just super organized in a very, very intuitive way. We also have when you first log in, communication functionality, so multi-user, excuse me, multi-location users are able to broadcast notices out to specific title groups, specific  locations. We’ve built in some fun stuff like our, I call it the “Good News” reel.  It’s basically a highlight section so that the first thing you see every day is just a reel of everything that you’ve done really well, either really well or every improvement you’ve made. We have a lot of tools inside for fostering stafflove, right? So, we want to shout out staff work anniversaries, staff birthdays, also resident birthdays. So, I think that it’s really the key here, designed for the way that we should and want to operate in long-term care and senior living.

(Amber 5:07)
One of the key parts of CareWork that makes it such a great product is the integration piece and that you cross multiple platforms and you bring all that data together in one place. Can you talk a little bit about the types of systems that you integrate with, and how that data gets pulled into CareWork?

(Jackie 5:24)
So, sort of the beautiful thing about this, and this was by design, it was one of the number one things on my list of things that were important back in 2020 when we started to scope the system. So, we handled the integration piece as a service. There are operators that might use Power BI or Tableau, and those require a staff to support them or very hefty consulting fees, and we know that we wanted this to be something that was accessible to all. Operators, even smaller multi-location operators, not just the biggest of the big.

(Jackie 6:02)
So, the first thing we do is we handle the integrations as a service. So, commonly the core systems that we’re integrating with are going to be electronic health, health records, H R A S or time-and-attendance solutions, ancillary scheduling systems. There are a lot of common ones, also procurement systems. You know, you have the common ones in the sy in the industry, you know, DSSI, right? That’s a common one. Financial systems, a lot of times that’s found in the EHR, but we’re going to be integrating with actual other financial systems. So, people might use Acumatica, they might use, you know, Sage, whatever that is, right?

(Jackie 6:45)
So, the idea is to get the core business areas that those core systems are supporting, which is really gonna be, it’s really gonna be clinical labor, financial and staffing business development as well. So, like CRM systems, whether or not that’s part of the EHR separate system. So, we have a pretty organized way of approaching that.

(Jackie 7:05)
Many of the larger players in the space, the ones that are more widely adopted, we’ve already built those integrations, but when we start talking to a new client, and they are using a system that we have not yet built the integration for, we just build it. We just build it for the customer, and we know what we’re doing on that, on that side of it, we also know that every system vendor may have a different way of allowing customers access to their data but we nav we navigate that for the customer. We don’t want them spending time on that. We don’t even want our customers thinking of care and technology almost in the same sentence. Right? Because for them, for them it’s about simplifying operations and, and we’ll handle all the tech stuff, you know, we’ll take the complicated stuff on. We don’t want our clients doing that.

(Amber 7:56)
Yeah, and that’s, that’s what I love about it. I’ve seen the system, and it’s so easy to use and navigate through. It’s very intuitive and simple. Can you walk me through a use case for a community? What would a community look like that would be a good fit for CareWork, and what would be the important things that they would need to know when making a decision to purchase a system like this?

(Jackie 8:20)
Yeah so, really we are a fit right now for multi-location operators. Probably, I would say more like a five location plus operator right now. I’m hoping to change that in the future, but for right now, that’s sort of a sweet spot.  So, five locations and up, although we know CCRCs are sort of specific, right? So, a CCRC could be 16 locations in one. That’s a different story. It’s a different setup. It’s a different way of operating. So,  the other thing that, that I think is important note is that when we have a conversation with a prospective client, we like to talk about what systems they’re using or aren’t using, right?

(Jackie 9:06)
Because, if you, so for example, we engaged with,  and we work by the way, in both, in both long-term care and senior living. So, our clients operate everything from skilled nursing to, you know, assisted living, memory care, independent living, all of the above, right? We cater to all of that. I was speaking with a larger Al operator that was almost all, it was like they were almost exclusively Al, and they have 60 plus locations and were scheduling on paper. They weren’t using an EHR in a really, almost at all. They weren’t, their foundational systems were not ready for CareWork, right? They had a lot of work to do internally, I think, just to get themselves to the point where they had data to work with.

(Jackie 9:58)  
So, we don’t ever, you know, for us, we would never say, “okay, we’re gonna install CareWork.” If it’s not gonna do anything for you, you need to have that data. That’s really the way that it goes. If I have a conversation with a customer, and they’re not, at least at the core, sort of foundationally set up, What I like to do is refer them to the companies that I think might be the right fight or maybe like a top three or share with them some of the systems that our clients  are using and liking, and then we circle back.

(Amber 10:06)
Yeah, that makes sense. Think, speaking of implementation, you know, I think sometimes people hear system implementation and all they think about is how much extra work is this going to add to my day-to-day? So, can you tell us a little bit about what does an implement implementation plan look like? What’s the schedule? What do you need from clients to participate in that process?

(Jackie 10:53)
Absolutely. So, we need, we need input from. Ultimately, it’s three people, whatever that title may be but typically it’s at a corporate level, so it’ll be director level plus is usually who who works with us. So one operations, one clinical, and one finance. So, those are the three key players in the setup. What we’re gathering from them are targets, goals, and budget. So, really the first step is gonna be bringing those systems in. So, we have to work on getting the systems integrated, although we do some of this stuff in tandem, but the first step is bringing in the EHR environment because from the EHR, we’re able to pull information on how the locations are set up in the EHR, and information on how, for example, AR codes are set up that tie to both census and financial data. So, we like to start with that starting point because it gives us a visual of how they’re set up.

(Jackie 11:59)
Then, we take that and we have to work on mapping. So, targets, goals and budgets, and then how do we want the information to display? So, payer-type mapping because we wanna bucket that you might accept, you know, you might have 20 different insurance types, right? We don’t want, we don’t want 20 different rows of data. We want all of that to flow to a category called insurance or managed care. However, we wanna set that up, right, or both. So, the, the configuration, or excuse me, the effort from the customer is really what do you want it to look like? But we have that very structured, we run with all of the sort of hard work.

(Jackie 12:34)
So, once we get that information, we  first build the environment, and, you know, load out the locations and then we take it section by section and work on mapping. We also roll it out to the customer. Section by section, but in a three phased rollout. So, the first rollout is rolled out to the corporate users. So, it’s really the key stakeholders. They use it for a couple of weeks, make sure that we don’t need to do any final tweaks. Did we, you know, miss this in mapping or was there a code that should be there that isn’t there? You know, just kind of the stuff that when it’s brand new you have to deal with. So, they use that for a couple of weeks.

(Jackie 13:17)
Once they say, oh, nope, this is pretty good. Then, we roll it out to the regionals. We want the regionals to get comfortable with it before it’s rolled out to the facilities and the communities, because by the time it gets to the facilities and the communities, it needs to be just solid. The regionals are already using it and they really only need to use it for a week.

(Jackie 13:34)
I just want them to get used to using it. The other thing that we do is we provide customers and ourselves with a utilization tool. It’s built right into the system. So, we manage closely monitor the planners for the first couple of months and then once a month thereafter, the utilization down to the actual job title at each location, because the idea here is the users of CareWork are all management- level plus employees. So, the idea is that it should be used Monday through Friday consistently. So, we can actually drill down to that usage, and we can drill down to what is being used by what job title, because we CareWork as a company, and this was a huge peeve of mine in my CIO days, rolling out a system that wasn’t being utilized or adopted. We’re paying for it. I don’t wanna have, my personal goal is I don’t wanna have a single customer inside of CareWork that isn’t actually using this system. You know, 80% to 90% across the organization, because, you know, you’re gonna have some people that you have to maybe, maybe train a little bit more, but generally speaking, we wanna see 80% plus utilization as a standard average.

(Amber 14:43)
Yeah, definitely system optimization and usage is a goal to work on for all clients of all their major prize enter systems, and I would even say it applies to some of the systems that would feed into CareWork. You need to be able to fully utilize PCC or your financial system or whatever to have the accurate data go into care work as well.

(Jackie 15:04)
Can I make a point to that? Because that was a really good that, I’m so glad you brought that up. One of the, it was like an unintended afterthought bonus, right? Of using something like care work is that it shines a spotlight on incorrect data in the source systems. So on the clinical side, You know, it very easily points out when things aren’t charted properly, right? Or aren’t charted at all. On the financial side, it points out when things are maybe incorrectly added on the, I mean, everything, right? So, it’s such a shortcut to say, “oh, this is incorrect in the source system. We really need to fix this. Or we really need to train our teams how to input this correctly because we wanna have good data.”

(Amber 15:47)
Yeah, absolutely, and I think that leads to a bigger question about ROI. So, obviously CareWork is a system that that you have to pay for, but I think, the bigger picture is that there’s so much process efficiency that you’re gaining and so much more information that you have at your fingertips in addition to reducing a lot of manual and paper processes. So, can you talk a little bit about how you see CareWork replacing some of those inefficiencies, and how do you really sort of capture that full return on investment with this system?

(Jackie 16:18)
Okay, so I’m gonna talk about this in two directions. One is opportunity-cost savings. So, we’re talking about saving time, doing more with less and then the other piece I’ll talk about is hard- dollar savings. Our goal as a company is for CareWork to always pay for itself plus, plus, plus, right? So, from an opportunity- cost perspective, I’m gonna give you a few examples, but I’m gonna start with we believe that the system will reduce the administrative burden for management level plus employees by 80% or more.

(Jackie 16:51)
So, what that means is 80% time, 80% less time spent sitting at a computer, and 80% more time focusing on fostering, developing and retaining staff and spending time with residents and family members. So, from an oppor, that’s a high broad statement, right? So, let me give you a couple of real world examples. One of my VPs of clinical 27, facility-skilled operator, so she’s a VP of clinical. She spends a day and a half, this is her quote, not mine, a day and a half every month, compiling one quality measures report. So,  a day and a half of VP of clinical time, yes, there’s a hard-cost savings there, right? You’re paying a VP of clinical to sit in her in front of her computer for a day and a half, but she has other things to do.

(Jackie 17:42)  
So, we automated that report and now all she has to do is click it. So, it is five minutes to review the report, not a day and a half of manually compiling it. So, when I talk about custom report automation, our goal with CareWork is for these organizations to completely ditch the spreadsheets. We want them gone.  So, we want, we want over time zero spreadsheet and document-driven reports being emailed back and forth across departments, in between regions and up to up to the corporate level. So, we start by saying, “alright, let’s talk about what reports on a spreadsheet or a document. Do the department heads at the facilities or communities owe the regionals every month or every week or every day?”

(Jackie 18:27)
We start with that, and then we say, “alright, we’re gonna build those over time into CareWork. So, the idea becomes that any of those reports, here’s the, here’s the typical way those are completed, I open up my spreadsheet, I dig in three different systems to pull out all this information from a bunch of systems I have, I add in my notes and thoughts and feelings, and then I send it to my regional. My regional gets it from a bunch of locations. They roll it up and they send it to corporate. Next week, I go pull all the same information over and over again, and I might do three different reports that ask for 30% of the same information that I just had to do over and over and over again, right? So, when you build that same report inside of CareWork, what what we’ve found is 80% to 90%, I would say 80% on average, 80% of the data that li, that is requested in those reports, lives in a system somewhere. About 20% is what we call observational data.

(Jackie 19:24)
It’s my thoughts, my feelings, my notes. How many state and federal visits did we have? So, when you build that report inside of CareWork, the 80% that already lives in the systems, auto-populates for the person who is required to submit the report. So, that report we call a “task” in our system. So, if it’s a clinical report, it’s due every Wednesday, 80% of it auto-populates.

(Jackie 19:46)
I enter the 20% that didn’t, and I click submit. So, it just took me 80% less time to complete that report. So, those are, those are examples of opportunity-cost savings, and there are more than that. Just analyzing your data can bring tremendous opportunity-cost savings in, in, you know, things like overtime and all of those things, but I actually asked three of our clients to give me in their own, what they felt the cost savings would be just, and I mean, it was like a quick conversation and I put them on a slide. So, here’s what they gave me. Reducing labor costs, reduced waste, revenue loss prevention, and faster time to cash increasing revenue, and this is what they said about that allows us to do more reporting than we could do manually, which allows us to be proactive and more responsive. This results in better star ratings, making us more attractive to potential patients and residents, which leads to more revenue. They talked a lot about clinical insight, and I had one operator tell me the less time our ED has to spend doing administrative work and digging for information, the more time they have to focus on sales, and lastly, they said a reduction in fine by reducing clinical errors. So that’s just kind of a short list. I didn’t want to as CareWork answer that question. When people ask, I’d rather have our customers answer it in their own words.

(Amber 21:07)
I’m so glad you spent so much time diving into that because when I first met you and you described what CareWork was, I, this is what got me super excited because I know you’re, you’re talking a lot about bigger communities, but our clients are mostly single sites. They still spend so much time on these manual processes that you’re talking about, and I think the ability to just move all that to be completely automated is such a gift to the industry in general, which is why, you know, I’m so glad that you’ve developed CareWork and that, you know, you came on this podcast to talk about it.

(Amber 21:36)
So, do you have any other words of wisdom or advice or anything else our listeners should know about CareWork before we wrap up?

(Jackie 21:44)
No, I would just say with regard to words of wisdom, technology has historically been kind of a scary thing in our space for operators and for, you know, employees, but I would say that we’re at a point in, in our history in which it, it has to be adopted, and there are clever ways to do, but I would say make sure you’re looking at your core systems. Make sure you have the right ones in place, and once you do, you should be looking at unifying your operations to be more efficient.

(Amber 22:19)
I love that! I agree a 100%. Jackie, thank you so much for joining me today! It’s been really a pleasure to speak with you.

(Jackie 22:26)
Thanks for having me.

(Amber 22:27)
Listeners, you can find us online at www.parasolalliance.com and go to our Resources page where you can see all of our past episodes. If you would like to submit an idea or feedback or a topic you’d like to see on the podcast, please reach out to us on our website, and as always, thank you for listening!

Amber:
0:05

Welcome back to Raising Tech. This is your host, Amber Bardon, and today we’re talking about a topic that I’m actually really excited about. I’ve been really looking forward to this interview and this conversation. On today’s episode, we have Tiffany Naticchoni, hopefully I said your last name correctly. And she is a Regional Director of Sales for CarePredict. Welcome to the show, Tiffany.

Tiffany:
0:24

Hi, Amber. Thank you so much for having me. I’m excited to talk about the CarePredict technology and all the ways for innovating the senior living space.

Amber:
0:33

I wanna tell the story really briefly about how I first heard about CarePredict, because I was actually not aware of your product. And I’ve done,, several conferences at, local leadingage states over the year about innovation and technology, resident technology, technology, strategic planning, that type of thing. And one of the things that I talk about is new technology design and new construction. And I actually had an attendee at one of the conferences bring up CarePredict because we were talking about innovation and emergency call responses and how there hasn’t been a lot of change in that industry. And somebody brought up your company and I think from there we connected with you. And I’m just really interested to hear about what you’re offering and what you’re doing in this space. So can you tell us about what CarePredict is?

Tiffany:
1:15

Yeah, absolutely. So, so we are an AI technology platform. very technical, lots of features. but what we’ve done is we’ve, we’ve been built out to empower caregivers to provide better care for our seniors. we’re on a mission to, drive a purpose built company built for, built from our, CEO and founder Satishmo’s very personal need to take care of his aging parents. and he was also the successful founder of, a couple of other healthcare technology software platforms in the past. So he built us out. so all of the technicals involved, like you had already mentioned, um, call system, fall detection is another. Um, all of these point solutions that our senior living communities are shopping for and looking to upgrade and update and, they’re looking for solutions that are meeting the needs of the current and, modern operation. Right? And we’re facing staffing shortages. We’re facing occupancy issues. quite frankly, our staff just need an easier experience at work, right? So we’ve built our, our platform out to be easier for the end user experience for our caregivers. And we started basically focused on health insights in the congregate living setting. And then we evolved significantly to detecting falls through all of this. We’re reducing falls, unplanned hospitalizations, um, increasing the length of stay and of course improving the staff response times. So we do all of this through a wearable device called a Tempo that’s worn on the dominant wrist, and it’s going to, um, have some gesture recognition. Um, so it’s going to detect like activities of daily living, um, walking, um, brushing teeth, brushing hair, eating, all of those different activities and behaviors. Um, and also it has, real time location information in it, which allows, the AI platform to, to provide data to the operators, the caregivers on, you know, what activities are our residents and staff engaged in every day, and what type of utilization are our, um, residents and, and caregivers experiencing each day. so are wearable unobtrusively, and in the background collects data on activity behavior.

Amber:
3:26

That’s a lot of information. Let’s, let’s unpack and dive into that a little bit more. So I wanted to mention, you know, before we get into what some of these different offerings are that you just mentioned, I wanted to bring up sort of a, a case in point about what you just described. I was working with a client on, uh, new construction technology design, and we were specifically researching and looking for a solution. Like what I found out later that CarePredict has, and the conversation I was having with this client is, you know, we’re building a brand new building and we need to put in emergency call, we need to put in technology for life safety, but why does all of this technology look like it was made in 1980? And we don’t wanna be giving residents things that look like, you know, pieces of plastic that are yellow and not attractive, and we don’t wanna be putting devices on the walls that look like they were made, you know, several decades ago. And I think there is an importance on the visual aspect and the design of the devices. So can you talk a little bit about that and how CarePredict has approached that problem? And then can you dive a little bit more into maybe specifically to start with just the emergency call and the wander product that you have?

Tiffany:
4:31

Yeah, absolutely. So I’ll touch on all that and I’ll start with the caregiver’s experience using the product. So when we talk about modernizing technologies that they are using every day, we all know you and I know if, you know, if we’re using a, you know, a DOS system to do our job every day, we’re probably going to be less efficient, right? We’re probably not going to enjoy the process. It’s just not modern, right? So the design of our product is focused, on being user friendly to the person who’s using it, right? Our product is a dashboard displayed on a smart or mobile device, that your caregivers would use to take alerts and also see location, um, and interact with the, software on the dashboard. so number one, they’re, they’re using a mobile device on their shift, right? So m walkie talkies, and then the staff or, so the residents are then going to be wearing a, a wearable on the wrist that looks much like what their caregivers are already wearing, such as the Apple Watch or the Samsung Watch, or the even Fitbit style wearables. So the residents are actually adopting these a lot faster. In addition to, the staff members who are okay with wearing these in the sense that they are very modern looking, it’s a small, sleek design. the, there’s one piece of technology that we use, for the, location information, and it’s a beacon, right? The beacon and the tempo are both battery operated. so there’s no infrastructure needed as far as electricity or, or ethernet. It’s all wirelessly operated. very easy to use and maintain, no construction needed. So, um, the stigma of a pendant, right? So pendants are currently what are being used for call buttons, in most congregate communities. And so the stigma of a pendant can make a resident feel as if they are institutionalized. And so CarePredicts mission was to empower the dignified care and to reduce that, that stigma or, to make their residents feel at home because quite frankly, these are their homes most times. And so using technology that looks like the technology that the rest of the population is using is very important to our design.

Amber:
6:34

So can you walk me through what exactly can be done from that device? So can you maybe describe what it looks like? I know you mentioned a Fitbit, if you, you know, does it look like that, like an Apple watch? And does that device, does it have the capabilities to do all of the different things you mentioned with the falls technology the wander guard, the location management, things like that?

Tiffany:
6:52

Yeah, absolutely. So, the technologies that operators and caregivers are using and shopping for these days are the, you know, the laundry management systems, the fall detection, the two-way audio, um, and the staff communications devices. So what we’ve done is we have built out our own platform, um, that provides these four things and more, and I’ll go through the extra features, um, but to, to start at the top with those essentials that operators and caregivers are using every single day. so what, what does the device do? So, it’s not a touch screen. Like we may equate like our, like our generation uses, um, like on the Apple Watch, it’s not a touch s creen, and that’s on purpose, right? Because there are dexterity issues, there are visual issues. the device that’s w orn on the wrist t o the tempo, it’s, built. It’s just, it’s a black square much the size of an Apple watch. we compare it to that often because it just is very similar. it’s not an Apple watch. It could, it collects much of the information that the, uh, that those devices, those other smart wearables might heart rate activity level. it’ll detect falls because it has sensors on board that will, that will do that. It’ll detect acceleration, and, humidity sensing and all of these different pieces of technology that, that other, folks in the population are wearing. but it d oesn’t specifically for the senior living setting. So focusing on call buttons, right? So the face of the tempo wearable has a button. So if a resident presses the button, just quickly, it’s actually going to read the d ate, the date and the time. And then fourth, it’s going to tell the battery level of the tempo. so it’s always possible to know what, what the battery level is there. and the battery is swapable and we’ll get into to that technical, in just a few, but I wanted to mention that because it allows for 24/7 wearing, and so that’s going to, the call button’s going to connect to a caregiver in the mobile device that they’re carrying. And so that mobile device is going to be, we’re agnostic to which device you choose for your staff. but it’s going to show an alert on the screen much like your caregivers are used to when they accept a text message or a phone call, right? so they’re gonna open up two-way audio with their resident, and this is the most innovative in the space because no other wearable is doing everything we’re doing and providing that peace of mind to the resident to be able to speak with their caregiver immediately, right? What this does for the caregiver is it’s allowing them to prioritize their calls. So it is no mystery if you’ve ever been in a senior living community that at any given time, a caregiver has 10 things going on at once. Right? so this allows them to triage their calls, um, and prioritize their work.

Amber:
9:28

One of the things I imagine people listen to this podcast are wondering is that an investment in emergency call system or a call system or, uh, pendant system, things like that. It’s a pretty big investment. So if, if a community has recently made that investment or they’re not interested in reimplementing that, do you integrate with existing systems or can you talk about what would be the use case in that scenario?

Tiffany:
9:47

Absolutely. So we are, we are integration ready and we’re interoperable with other technologies as well. So in, in most cases where we use this is say, a, a operator has, pull cords and they wanna keep those pull cords in the community and they, they wanna keep the existing program, those are on. but they wanna use CarePredict primarily. this is specific in the case of, when you have a CCRC community, and you have a skilled nursing setting, and then you also have a assisted living, independent living. Well no doubt the, the uses and the operations are very different. but to unify across one platform, we pull those alerts from the, say the pull cords to the Care Predict platform. So, the caregiver, the end user is going to have the very same experience, despite having multiple softwares, pushing the alerts, they’re going to receive the alerts on one platform.

Amber:
10:38

Okay. Got it. That makes sense. And I know you mentioned earlier that these devices are dependent on wifi. So can you talk a little bit about what you’re looking for a community to have prepped or what should they know before they would be looking at a solution carepredict?

Tiffany:
10:53

Yeah, so we are wifi dependent, and that is, that’s been built out for the, uh, the, you know, the operator who’s focused on having a lower infrastructure. You mentioned, you know, in a construction planning setting, you we’re looking at infrastructure, right? Electrical happens very early on when you’re mapping out low voltage electric for, for, a call system that’s reliant on the low voltage, you’re gonna have to map that out with electricity and wiring and all of these things. Carepredict runs on wifi exclusively. for the very purpose of it being a simpler design, no need to map those out, no need to spend the extra, um, cash flow capital on that. w e, our infrastructure is built to be easy to use and there is no it, p rofessional requirements to, t o live on s ite as far as, y ou know, you don’t have to have, an IT person to manage your system. Your end u ser’s really going to be the driver of the, the input in addition to the most significant driver of the input is just, just simply the residents and staff wearing the wearable, c uz it’s gonna collect all of the information.

Amber:
11:57

Got it. That makes sense. And yeah, this, this is in line with something that I say at all the, conferences that I present at is that wireless is definitely sort of that, that core system we wanna have in place when we’re doing new technology design or new construction, to make sure that systems like this are able to be implemented and, for the community to be innovative. I wanna go back to in the very beginning of our conversation, you mentioned that Care Predict is an AI system. Can you explain what that means? Cause I feel like we hear the term, AI a lot and it can be used in a lot of different contexts. So can you just dive into that a little bit more?

Tiffany:
12:29

Yeah. The AI I involved in when we’re talking about Care Predict is, um, we’re using activity based information. We’re, we’re pulling data, from multiple different sensors and locations and, you know, folks who aren’t very technologically, you know, savvy or literate, you don’t have to be to, to really understand the background of it. We’re just pulling a ton of different information and we’re putting it all together in algorithms that are producing a consistent data result. And these data points are allowing, um, for easier operation. So for example, when we’re talking about, UTI prevention or detection or prediction, right? the data points that are being pulled through the care predict system would be, um, how frequently does the residents visit the restroom, right? And so this, this could be, uh, the restroom, whether it’s in their unit specifically or if they’re in a, a different level of care, if they’re using the, the public facilities, doesn’t matter, the system’s gonna pull the information frequency and duration of when that resident is interacting in with a bathroom location, right? So, it can be, it can be assumed that they’re using the bathroom when they’re in there, right? We even have a, detection on dwelling time. So if the dwelling time in the bathroom is, um, longer than the predetermined range, say 15 minutes, right? There’s going to be an alert that can be sent to caregivers to indicate that the resident is, has been toileting for far too long. They may need some assistance, right? And that alert will be driven directly to a caregiver. and on the screen you would see, the caregiver would see the name and the location of the resident, the location right down to the room.

Amber:
14:10

Got it. Yeah, that’s, that’s really interesting. Is there, do you know, is, I’m just curious, I dunno if you’re allowed to say this, are there other products in the marketplace that have that capability?

Tiffany:
14:19

So there are different products that do sensing, ambient sensing very, very well, and they should, um, our product follows our resident throughout the entire community. So yes, there are technologies that do, um, sense or, um, or monitor remotely the bathroom usage or, or the ambulation or, or different activity movements. what is unique about ours is we baseline the information. So we take the information after a resident has worn our Tempo device for, uh, greater than two weeks, um, they’re going to get a baseline established, right? And then every, four weeks, the baseline is calculated as a rolling baseline. So we know how often Jane Doe frequently uses the restroom. We know that it’s typically five times a day. What the AI does in this scenario is it’s going to detect when they’re outliers and then it’s going to, push a report through to the caregivers and management to say, Hey, Jane Doe and, you know, these X amount of other residents are outside of their baselines, for this, this week, the past two days, past month, right? So these reports are gonna be pushed to the caregivers. and this is a very attractive feature because they don’t have to go searching through medical records to find out, um, exactly what behaviors have gone on, what activity has gone on. This is what keeps our residents in their, their place longer. It allows them to age in place and reduce their hospitalizations. Um, as we know, those can tend to be factors that, that pull them outta the community permanently or it can bring them back into the community with other issues. or just simply the disruption of of them leaving the community can be, um, pretty significant to, a resident and the community both.

Amber:
16:01

Yeah, that’s really interesting. Are you able to integrate with the electronic medical record system so that all of that, health information could be pulled into one place?

Tiffany:
16:11

Absolutely. Absolutely. Operators are asking for, demographic information for that census based billing, for live and real time information to be transferred through. Um, and we are actually, yep, we’re in P’S marketplace, matrix Care, e t c etera. So we have an open internet api. we are willing to integrate if, if the other party is. So we’re very proud of that. That’s been s uper, super helpful for that interoperability, reform in h ealthcare, which is so necessary.

Amber:
16:40

Yeah, that’s really fantastic. I think it’s been an issue in this industry for a really long time to have so many disparate systems and the inability of those systems to talk to each other, to really give us this more complete picture to the residents health for better quality of care overall. So I think it’s really exciting to hear that you’re able to do that and to just take us a little bit closer to that, you know, ideal world in which we can have essentially managed location for everything to do with the resident.

Tiffany:
17:05

Absolutely. Yeah. And, and that’s our mission. We’re we’re here to provide that easier experience for the end result being so that everyone benefits.

Amber:
17:13

Yeah. So one of the things I wanna ask you about is, I’m, I’m curious to hear what are some of the common challenges that you, you have heard from your clients? And specifically I wanted to go back to what you mentioned earlier with the device and the battery. And I know I’ve heard some concerns from some of the people I’ve talked to about the, you know, kind of how that works. Could you talk about that a little bit?

Tiffany:
17:34

Yeah, absolutely. And, and that is a valid concern. I would say I hear from most prospects. They, they ask, help me understand this battery change because all my caregivers are hearing is one more thing to do, right? And that can be triggering or buzzing. when you have caregivers who’s, you know, quite frankly, their hair is on fire, you know, as we speak, like I said before, at any given moment, they have a thousand things to do, right? so Care Predict is focusing on putting the care back into the caregiver’s hands and allowing them to prioritize it and give it in the best way possible. So when it comes to the battery changes, so the battery and the tempo, and then the battery and the location Beacon are both, they’re both changeable. So the, I’ll talk about them respectively. The Tempo Battery has a 24 to 36 hour wear time, right? Depending on how much the resident is using it. I know when I got my Apple Watch, I was, I was surprised by, how long it would last if I didn’t take a phone call on it, right? and the utilization definitely correlated with the li the duration of the battery. So, um, same goes with our device. The reason we have the Swapable battery, like I mentioned before, is to allow that 24 7 monitoring. So with all of that being said, it’s being a very popular question. any of my customers would agree that it’s a non-event to change these batteries out. It simply pulls right out of the side of the tempo and gets replaced with a full battery. Each tempo comes with a duo battery charger, so they come with two batteries. and then of course, caregivers have a, they have a, plethora of, of charged full batteries too, and they have, um, chargers at their stations or wherever they choose to put it in the community. So there’s not typically a shortage of charged batteries. The caregivers find that it’s a non-event to swap these out, so they’re able to build it into their workflow. They’re already touching residents at least once per day. so it’s an easy task to add on. They can also, if they’re interacting with a resident, they can also press the tempo button, like I said, that one time and get the date, the time and the battery level. Also, the third precaution that we’ve taken is on the caregiver’s device, on the home screen of their CarePredict platform, they’re gonna see two little options. And one of those is tempos not worn, and it’s gonna show the number of tempos that are not being worn at the current moment. So it’s always on the dashboard, that the caregiver can access of who isn’t wearing their tempo. And that list can even provide qualified information on, well, maybe you have two non worn tempos. Well, maybe those are both out of the community at this time, and that’s why. So, um, that’s one report. And then the second report is the battery life. So the battery, report and status shows all of the battery levels. So as long as the tempo is being worn and it’s online, it’s going to report back to the system, tell the system the battery level. So with that being said, you can get alerts scheduled when the battery gets to be too low. So say you have 10 residents with a battery that’s on yellow, you have five hours to replace these. Um, typically it’s able to be built into the workflow.

Amber:
20:34

Okay. That makes sense. Are you considering doing a chargeable battery in the future?

Tiffany:
20:39

So the, interestingly enough, so I’m not, I’m not building the product out by any means, but I know that this is a pos or it’s a hot question because we don’t want to add any work to our, our caregivers, right? So this is essentially the only maintenance task involved since our system is picking up all of the information that it needs to based on just being worn. so to answer your question, I don’t know what’s in the, the pipeline for that other roadmap. but I can say that the function for 24 7 wearing is at the forefront. So that is the priority right now.

Amber:
21:11

Okay, got it. Are there any, one thing I always like to ask, vendors or partners who come on this show is, are there any specific clients that you’ve worked with or any success stories that come to mind that you can share?

Tiffany:
21:25

Yes. Yes, absolutely. So, we actually have a, a local CCRC here in Cincinnati, where I’m from, and they have, they’ve established care predict across their, their continuum of care, and they, they’re finding value in each level. a little bit to build on the last question you asked about, challenges that we see. and then to add that to the success story, um, in this specific situation, we had a resident who, um, who wasn’t bought in to care, predict upon initial installation and implementation, didn’t like it, didn’t wanna wear it. and this is representative of personalities who just simply feel like they don’t wanna wear it. And, and we have those. And so that’s, that’s no mystery, and it both certainly is something that, that can be overcome. so this specific community I’m mentioning, they had, a guy who didn’t wanna wear the wearable, didn’t agree, didn’t, didn’t see the benefit of it, just hearing, you know, um, the, the original pitch, so to speak. He actually experienced a fall, um, a couple days later after the Care Predict system was implemented. And, he realized how valuable the care predict, wearable would have been for him, how, much quicker he would’ve been discovered, and how much he, he could have gotten care sooner. and not to mention he could have been in communication immediately with a caregiver who could have come and helped him. but unfortunately he didn’t. and he, he suffered a little bit, he’s okay now, wasn’t, wasn’t a significant event, but he’s okay now. but he immediately saw the value in that and, and adopted it immediately. So, I don’t believe he’s had any subsequent falls since then, that were undetected, but the Tempo device is definitely seen as a safety feature, and it’s worn. It’s the only device that goes with the resident everywhere in the community. So he definitely saw the value in having that on him at all times.

Amber:
23:17

Yeah, that’s a, that’s a great example. Tiffany, everything we’ve been talking about is so exciting, and I just love that this type of technology is coming to the industry. Can you share what is in the future for CarePredict what are you working on in the next 12 months?

Tiffany:
23:30

Yeah, so I’ll, I’ll, before I go in, into what we’re working on, what’s going on in the future, I’ll say a few of the things that I haven’t mentioned yet. as far as features go, um, the, the device, the Tempo device is able to collect data through Bluetooth. So that’s something that we historically were working on and finally released recently. So, there we have some approved devices that, can feed information directly into the tempo and thus pushing it into the ADL activity. So example being, you know, a Bluetooth glucose meter or a Bluetooth blood pressure cuff, can, can these feed readings into the tempo? The answer now is yes. so that’s an exciting, uh, growth feature that we’ve had this year. so it, we’re allowing, we’re, we’re creating baselines, right? So every time a resident is recording their blood pressure or their glucose or their weight, right, these are now being pushed into the system to, to receive a baseline and then also detect detects changes and degradations and alerts the caregivers through that. that the changes and, degradations, or, sorry, degradations, report. So we called that the out of baseline report. So that’s been a, a huge feature that’s been new recently. Another new feature, is called Care Voice. care Voice is where we’re able to set reminders for our residents, um, in the voice of their choice, right? So maybe it’s their, their grandchild or their family member who wants to say, you know, at 4:00 PM every day the recording goes off and says, Hey mom, you know, it’s time to take your meds. Or, Hey, grandma, don’t forget to go walking today. so that’s a huge popular feature now too. Um, we are also able to open up electronic door locks as a key fob. So instead of a resident more in the independent and assisted realms, instead of them carrying that key fob or that key card or, um, where that could potentially get lost, or it’s simply just one more thing to carry, we’re taking that off their plate and we’re, we’re putting the key fob feature inside of the Tempo wearable so they can open up their unit door with their tempo. That’s been a huge sticking point for our independent living residents. and also passive check in for independent living residents. They’re able to simply wear their tempo. and then an exception report is sent to, the caregiving staff to let them know who has moved around, who has not moved around yet today, and, and maybe they need to be checked on. so those are just a few features that I hadn’t mentioned yet, that are pretty popular. But as far as what’s coming next, um, we we’re seeing some quality of life assessments and scores. in the future. Automated voice prompted assessments, so much like our care voice with a reminder, um, our care voice couldn’t, could prompt a, an assessment to ask, you know, scale of one to 10, how are you feeling today? Or, or, or, um, or any, any subjective information that needs to be collected, could be done that way. We’re also looking to detect early signs of mci. The mild cognitive impairment, as we know, is a prelude to dementia. So we’re looking at, cognitive impairment scoring and detection, um, sleep phases, duration, or even having some hardware evolution, so cellular and GPS detection for the residents when they’re outside of the community. So we think in the independent living space, um, these folks don’t stay at the community all the time, right? So, you know, if a fall is detected offsite, um, the caregivers are able to be alerted. And and that’s a huge feature, um, that’s, that’s popular with the independent, population these days. We are looking at FDA approval that should come in the next year. Um, we’re really, really excited for that as it’ll give, you know, that validation and that benchmark of, you know, how accurate our, our technology is. so that’s really exciting. Um, and then of course, continuous measurements on automated gate, stride length, et cetera. We are committed to meeting the needs of the industry. and one feature I didn’t mention, that demonstrates that was the contact tracing. So since we have all of this robust data on our residents, our staff, our visitors, we’re able to provide a contact tracing, dashboard that is very easy to use, very user friendly, and it has, um, it has real time location information so we can filter down to see a person of interest. So maybe someone was diagnosed with a contagious illness, um, and they need to be isolated, right? So we’re able to, to filter per date and in person and see all of their primary contacts, secondary contacts, um, and even the areas where they, where they, they hung out, right? So we can even decontaminate based on the report that is given to us, from the contact tracing solution. The cool piece about this is, and the reason I’m mentioning it now, when you ask kind of about what we have in the future, this was something that we, our, our engineers and technologists were able to build and release with from, from seven days, from inception to, to general release. So we were able to provide in the midst of the pandemic our caregivers with an automated solution to help them complete a contact tracing task that formally took them hours and days to complete. And it was exhausting. It took them out of their caregiving, right? So this just speaks to our, our mission and our commitment to evolving with the industry and continuing to deliver in whatever way that we are capable to our customers and to the industry.

Amber:
28:43

That’s fantastic. I really like the door FOB integration. That’s something that we hear a lot of requests on, is they wanna be able to manage everything from, from just the one device that they can wear. one of the things I wanna ask you before we wrap up, has Care Predict considered moving into the home care market? I’m wondering if some of this technology could be used to keep people in the home longer, or is this really meant for more of a residential situation where there can be, uh, staff monitoring the alerts?

Tiffany:
29:11

Great question and great call out. I, would be remissed if I didn’t mention that feature. So we actually are, are in with home care agencies across the nation, and these home care caregivers are utilizing the Care Predict at Home feature. and that division of our business is handled, in a different department. I don’t handle that at home, which is probably why I hadn’t mentioned it yet, I apologize. But we do facilitate that. And Home care is a huge, a huge source of information because we’re able to collect information and still provide that value to the resident while they’re in their, in their home. and then of course transferring that information, to their caregivers when they go into the community. so we are looking at, you know, some CCRC have home care businesses, and so we talk a lot with the CCRC that we’re with to, um, to build that out into their home care realm for expanding the care and expanding the, touch and the the ability to serve that resident longer.

Amber:
30:08

Yeah. And then there, there’s the home care side, which you’re talking about, which is the, you know, still provided by a community, but I’m curious if it’s just would be available to seniors just individually who live in their home independently.

Tiffany:
30:17

Absolutely. Yep. And we have a, we have a base of customers who actually utilize it just independently on their own, in their community. and it was cool. I was actually at the Ohio Assisted Living Association conference, and a woman came up to me and she said, we just got this from my father-in-law at his home. And we love it because we live two hours away and we’re able to see and check in on his activity, um, and also received critical alerts whenever there is something going on. so it’s really adding the peace of mind to the resident or to the, sorry, to the person in their home, and then also to their family members. So it is an exciting, and hot, um, hot feature for the at home product.

Amber:
30:53

Yeah. And really a lot of implications for seniors who wanna remain in their homes longer. So that’s really fantastic to hear. Yeah. Tiffany, is there anything we didn’t cover that you want our listeners to know?

Tiffany:
31:05

I think we covered most of it. we’re really just continuing to just emphasize how we’re built for caregivers, for residents, for family members to provide the safety to our seniors in a simple and easy manner. And, and even in situations where, operators are having staff shortages or they have agency staff in their buildings or, you know, there’s, they’re, they’re looking for utilization analysis. We have that data, so we’re able to provide data that operators can use in their own unique way. So we are not a one size fits all standard system. all of our alerts reports, data, everything is customizable in our Wonder Management feature. I don’t think we delve too deep into that, but the Wonder Management feature, is huge too because we’re, we’re able to detect when a resident is wandering outside of a predetermined boundary and that alert goes straight to the caregiver, and opens up a call or, or however that alert is customizably set to that, caregiver or operation. just continuing to build it out to make it easier with a low infrastructure and at a budget that the community can afford. Lot of lots of people ask, this all sounds wonderful and great, what’s the cost? Right? We’re very competitive, um, in the sense of we’re, we’re comparing very closely to just what is a call system. And so in that regard, people are finding that they have all of this, this breadth of feature and this robust data and all of these features, and they’re getting it at nearly the same cost as a call system. Um, so that’s something that I, I always like to shout out. We are budget friendly, um, and it sounds like a lot and it’s really good. and, and of course I’m passionate about it, right? I’m here. I was a formerly a clinical dietician in this senior living space, and so I get it, and I, I know how frustrating, it can be to search for data that you can’t find. and to have it in our system to be driven straight to us is just such a, a blessing and a convenience.

Amber:
33:02

Well, thank you so much for joining me, Tiffany. This is a podcast episode I was really looking forward to, I was telling people we’re gonna talk to Care Predict. I’m so excited to ask them questions and learn about their products. So really appreciate your time and joining the show today.

Tiffany:
33:15

Thank you so much, Amber. Yeah, no, I appreciate you, you having me on and, and then and tell people, more about us. So,, thanks. Appreciate it.

Amber:
33:23

Thanks so much again for joining me today. And listeners, if you have ideas or topics or you’d like to be featured on a future episode, you can find us on our website parasolalliance.com. And thank you for listening.