56. Raising Tech Podcast Live- Unlocking the World of AI for your Community

We have a very special episode for you.  Amber Bardon hosted a live episode of Raising Tech Podcast in which we had multiple panelists that spoke on AI. The full video is available on our YouTube channel.

This is your chance to redefine your approach to senior living and stay ahead of the curve in innovation.

In this pre-recorded episode, you'll get an overview of:

📌How AI can be used to increase resident engagement
📌Overcoming data privacy
📌Accessibility of AI in senior living
📌How AI & robotics play a part in facing front line staff
📌Approaching residents that are concerned about AI technology

Get ready to dive into engaging discussions and valuable insights with industry experts.

Download our paper on AI here.

Watch the full video here.

Panelists:
Sanjeev Shetty from HelloGard/vCare Companion
Jonathan McCoy from vCare Companion
Jessica Junkins Bradley from Somatix
Steve Mika from Skypoint
Ryan Galea from Icon

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Transcript

Welcome to raising tech podcast. I'm your host, Amber Barton. Today, we have something very special for you. We recently hosted a live episode of raising tech podcast in which we had multiple panelists that spoke on AI. It was a really great conversation, a great discussion. The full video is available on our YouTube channel, which we will link in the show notes.

In the meantime, here is an audio version of the events and we hope you enjoy.

Welcome everybody. Today we have a very special live recording of our podcast raising tech. 

 We recently published an AI white paper. So we had multiple clients coming to us asking us what's going on with AI? What have you heard?

Their board members are coming to them and asking them and AI is just a buzzword right now. We're hearing it everywhere. So what we wanted to do was speak to key industry leaders across a lot of different sectors, a lot of different platforms and get all of their insights. And information and exciting developments that are coming [00:01:00] out.

So please check out our AI white paper. It is on our website. It is a free resource. And then today we're doing our live podcast, which where we brought some of the people from our white paper onto today's episode. And we're going to hear from them directly. So we have some prepared questions that we're going to walk through, and then we're going to open up to audience questions.

So please feel free to put any questions you might have in the chat. I'm Amber Bardon. I'm the founder and CEO of Parasol Alliance. Parasol Alliance is a full service technology company. We do day to day IT support onsite services, resident technology, as well as strategic planning and project management.

And I'm going to turn it over to our panelists and have them give a brief introduction as well. So we're going to start with Jonathan. Do you mind doing a brief introduction for our audience? Sure. Thank you, Amber. So I'm the CEO of V Care Companion. As a co founder with Sanjay, who's also on this call Sanjay brought the robotics capabilities with to, to myself.

I'm the founder of a company called [00:02:00] Family Care Space. We've built a variety of applications built on real time and the merging of those workflows within a robotic environment to help address the really critical labor issues in healthcare. That's what we've done and then in that process. We developed applications that, again, are at the point of care.

So we have an autonomous, we call CC, our care companion. And CC provides access to the data lake, all the various information that could be in an EHR, et cetera. In addition, we have a gen AI application that deals with. Ambient dictation, the idea that a nurse can talk. To CC about a status update with a resident.

That tech, that voice gets turned into text when you use artificial. Intelligence understanding large language model to be able to create the text into the specific form, send that out to the, you are [00:03:00] probably talking about 3 hours of savings just in that alone. We're adapting in the field for the folks that are facing the challenges of.

I can do quite a bit with a lot less than they did before. And an administrative workload, it's just really burdensome to say, at least. The care is all about helping those that care for those that care and the setting can also be to be in a community and can also be in a home care setting. There are a variety of other elements that come into the care.

We get added. We are adding biometric devices, things like this. Again, everything that can help that care worker that home care provider at the point of care with our friend. Cc is what we're all about. Thanks for that introduction. Sanjeev, how about you go next? Thanks, Samberg, for having me on your podcast.

HelloGuard Robotics was really started based on my passion for robotics and AI. You can think of us as your 1 stop trusted partner for all things, robotics and AI based [00:04:00] workforce automation solutions, such as what Jonathan just spoke about. V Care is another company that I co founded with Jonathan.

And we fully integrate into your current system. So we make it real easy for robotics and AI workflow solutions to integrate into your current, whether it's your EHR or your operational systems. And our mission is really we wake up every day. And all we want to do is automate the everyday mundane work so that you can elevate the more important work, such as taking care of your residents in your community.

And by shifting the burden of repetitive tasks from humans to robots HelloGuard believes that you're solving the most important challenges that person centered communities face today. Which is really a shortage of qualified personnel, exorbitant staffing costs, overburdened and burnt out employees, all the things you hear about with.

With that and a lack of new ways to really upscale existing staff so that you can reduce attrition. But before I jump into some of our AI [00:05:00] solutions, I just want to give you my view of the AI world, because everyone views AI slightly differently. I think the simplest analogy out there for AI is that, AI is simply a utility.

I liken it to refrigeration, that's the simplest thing I can think of, when refrigeration first came out the ones who really benefit benefited from refrigeration is companies like Coke and Pepsi and similar to browsers, what browsers did to the internet really AI began its sort of evolution by leveraging, a ton of data to predict probability of an outcome.

So think of, a chess game where, AI is gathering a lot of data on possible outcomes and trying to find the highest probability of winning a game. Obviously, since then, AI has advanced with supercomputing. Now becoming reality and machine learning getting more advanced. There's this concept of super intelligent AI or generative AI which is where we focus most of our efforts on [00:06:00] and we're able to provide, those types of tools now and everything that we do specifically in in 2 buckets the 1st bucket Where we provide AI solutions is what I call is a hardware bucket.

We carry world class robots that boost productivity, whether it's in cleaning, whether it's an indoor outdoor delivery, whether it's in patrolling the outdoors for security, or whether it's simply in. Interactivity and entertainment those are the areas where we provide robotic solutions and what's unique about our robotic solutions is that we integrate with all of your operational systems, like elevators, we can open doors, we provide 24 by 7 proactive monitoring.

So think of us almost as your outsourced robotic service provider. The other side of our hardware business is that we spend a lot of time. Leveraging the AI chips and 3D LiDAR technologies that exist within our hardware. For example, our cleaning robots can remember if they missed a [00:07:00] spot, they'd go back to that spot and clean it.

They also know how to map their surroundings. They're able to know when they have to refill the water and go back to the docking station when they're running out of charge. And things of that nature. That's the hardware side of our business. The 2nd bucket of is on the innovative services and solutions to solve for staffing workflow challenges.

And be care companion is just 1 such key example of this where we're using generative algorithms. At the point of care to help clinical staff make better decisions. And we care in this instance becomes what I call as the face of the data lake to solve everyday challenges that a nurse faces with administrative tasks.

And we think that the solution is really going to revolutionize care delivery and senior living very quickly at scale for all communities. So that's where we fall in terms of AI. All right, thank you so much. Jessica, you're next. [00:08:00] Hi, everyone, my name is Jessica Bradley. I am the director of business development and strategic partnerships for semantics.

I live in the Lehigh Valley. So I'm right on the, I know you guys are all talking about where you're from. So I figured I'd mention where I'm from. I live right in between New York City and Philadelphia. I've worked in health care my entire career, and I worked in medical devices. The majority of the time, but I transitioned over to semantics where we do.

Remote patient monitoring services through the use of a risk based wearable. I transitioned over to Somatics two years ago and have since been introduced to Parasol Alliance. We're excited to be on the webinar. We'll dive in when we get into the webinar about what makes our wearable and remote monitoring different, but it's nice to meet you all.

Thank you so much, Amber, for having us. Thanks, Jessica. Ryan, your turn for an introduction. Awesome. Thanks for having me. I'm Ryan Galli. I'm the CEO of Icon. We are a software company that [00:09:00] focuses on engagement and communication for staff, residents, and their family members. From the perspective of, holistically, what we're trying to do is really make and give you the tools to deliver a phenomenal experience, the kind of experience that creates advocates for your communities.

To make it so that if you're getting word of mouth positive social presence that's going to attract and retain more staff and residents. What we've been doing on the side is what we're calling smart aging, which is our proprietary platform. That is really focused on 2 things. 1 is synthesizing down all the complexity and noise in your community to personalize.

Experience for individual residents in the community and the 2nd piece is getting predictive and trying to understand how we can improve the overall programming and what impact of those changes might have on overall satisfaction and same concept on the [00:10:00] employee side is we're much more focused there on turnover.

Thank you and last Steve. Thank you, Amber, and sorry for being a little late. I clicked the wrong link. I very much appreciate being a part of this. And I'm Steve Micah. I am the head of deployment strategy at SkyPoint and we very much look at AI as a data product. 1st, we see a lot of common themes and senior care and senior housing prominently.

The lack of data unification, the true inability to get a holistic view of all the data at your fingertips, there's a lot of siloed data sources and inability to get that unified view. So we really start with our kind of journey to generative AI with data first, cleaning up your data and really bringing together that single source of truth that you can then layer traditional analytics tools on top of, as well as generative AI, really looking to generative AI as a human in the loop.

To support caregivers, to support leaders, to have quicker access to data, better understanding of internal data at their fingertips that employ them to [00:11:00] spend more face time with employees, spend more time with residents and really improve that caregiving and employee experience. All right. Thank you so much for introductions from everyone.

So if you showed up a little bit late, we're going to do a couple of questions. We're going to do some round robin. I have some prepared questions I'm going to read, but please feel free to pop your questions in the chat as we go along. And we'll be answering audience questions at the end. So Steve, first question I have for you, and this is a question I hear a lot when we're talking about AI.

So I'm really curious to get your input on this one, but. How can we better address the concerns and issues facing frontline senior living staff, utilizing AI? And maybe you can talk a little bit about people's fears that maybe this might take away jobs or things like that. Yeah. And that's definitely a common question that's thrown around.

I go to a lot of AI user groups and just beyond the senior living industry, all up the common question is, fear of losing jobs. And I think there's a couple of interesting factors at play in senior [00:12:00] living that make that less of a concern, you know, primarily that of employee retention already being an issue and also that average age of caregivers being on the higher end.

What we see on the ground is a lot of complications using the multiple different platforms expected to use at all the senior living facilities. What we really want to look to AI to better help those folks on the ground, deliver care by spending way less time with administrative and operational tasks.

Less time looking up information, less time as data entry specialists, much more time with face to face experiences. And I think that in the current state of what we're providing and looking at is generative AI is truly to provide that human in the loop to support that quicker access to data. And I think that's truly going to help both the resident experience and the employee experience.

We should not be living in a day where you have to access 4 different systems for your HR, your CRM. You should be able to go to 1 place and access all your data and leverage common language to ask those questions. And that's the other side. We're looking at it is as I mentioned, a lot of [00:13:00] the times I hear caregivers feeling like they're almost data entry specialists in their day to day lives.

We need to have much more easy to use. Platforms that allow you to use natural language to both ask questions and, track meeting notes. And a lot of the AI tools out there, I know a lot of people have probably seen the news around ChatGPT 4. 0 and the kind of creepy voice that they decided to go with.

But in the long run, what we're really doing here is the ability to, track with audio and leverage AI to ingest that and, easily get notes. Again, spend less time entering data in yourself and more time leveraging tools. For that increased face to face time, and I think that's what everybody in the industry is really wanting to look to towards in terms of a better employee experience, a better resident experience.

And before I move on to the next question, I'm just going to ask you as a follow up to that, if you can just in a minute or less, can you just give a really specific example of like, how would this impact like a nurse or a CNA on a daily basis? Yeah, so specifically, a lot of the tools we're using even looking up state regs or looking up policies, procedures, [00:14:00] looking up patient information in a secure platform.

Common issues you'll have with publicly available generative AI tools is that lack of HIPAA compliance, lack of PHI. Safety and security when you're leveraging a tool like sky point, you can have confidence that when you're entering and receiving patient information, resident information that has done so securely.

And again, last time, clicking through reports, clicking through screens, just get answer that get that answer very quickly using common language to ask the question. Great. Thank you. All right, Jonathan. Next question is for you. And this is such a cool question that I think people will be interested in hearing the answer to, but what makes your robotic companions ideal for senior living settings.

Thank you. That is a really cool question. That's at the heart of it. Why introduce something in a setting that could detract, right? Or take away because we already know there are a lot of stressors as is. So fundamental to this is I think a theme that I see running through here. Making the burden or easing the burden on the [00:15:00] care staff in performing their duties.

And I can't think of a better place to start than at the point of care. 1 of the, I'll give you a concrete example of how we see that unfold. We have a follow me feature. As a nurse is doing her rounds or has rounds, comes into a resident's suite, begins an assessment, and speaks into CC.

The findings, or this is the verbal report that would end up having to be transcribed and eventually. After a lot of administrative activities put into the HR system and updates. In the environment, we're talking about. Our CC will follow the nurse, go into the room, hear the dictation, hear the words spoken, the conversational activity transcribes that we use algorithms to create.

The necessary parsing and putting the data where it should be. And then pushing that off to an EHR that pushing off to an EHR, as I'm sure Steve can [00:16:00] attest, many can attest. Is not an easy task, and it's, there are battlegrounds between the HRS and there's walls set up for purposes, right?

They want you to, be totally involved in their environment as much as possible. And that does pose a challenge if you're trying to create an openness, right? But there are ways to do that. There are companies like sky point and others. And it's exciting that those walls are coming down, but what you're getting with that care worker, the nurse now does not have to go back to her office, transcribe her notes, put it into.

And by the way, all of this is happening in a very dynamic. Environment where there's lots of interruptions, things get rescaled in terms of what needs to be done when it's very hectic and dynamic. Because she's spoken out, or he's spoken out the assessment, and we created the report that can be pushed to the EHR, can be adjusted if need be, but our track record is about 98 percent accurate in terms of the text, [00:17:00] getting in the right categories, like if it's pharmaceutical or medication based, general awareness, wellness, et cetera.

And that process saves at least 3 hours. Of a nurse's day, and so we're talking a robotic companion that goes around with the nurse and that's only one area. We have a an array of biometric sensors that are going to ambiently take data from the resident as part of the protocol for the care.

That can also be appended to this update. We have a 3D or rather a a facial recognition cameras and other validation can be utilized for consuming, for validating that the resident took the meds when they said they would. Things like that, so there's a variety of different uses of this.

That will help the care setting the caregiver, and I think as well, increase the quality of understanding the care. Situation with that resident, that patient. And it can be in the home as well. Just monitoring a fall risk individual, the camera that we're [00:18:00] utilizing has capabilities. So we can see if the gates changing, if there's a posture that looks very unstable and then create an alert to let staff know where and when and who all of that information.

So having the point of care tool there with the nurse, the care, the various caregivers I think is really the powerful, compelling reason we're seeing tremendous amount of response in the market. Attraction is increasing daily. I think it's a good word to use now accurate word because this is a big problem.

We don't have enough people, right? And we have a tremendous amount of burden put on the people we have. And so we're trying to assist that. Yeah I really love what you and Steve both just commented on because I, as Steve said, there's this burden of the administration side that technology has placed on everybody, especially on caregivers and it's been building and building for years and I feel like the technology is now shifting that to the point where we're [00:19:00] able to remove some of that burden and make some of these workflows and day to day processes, just more efficient using this technology.

So exciting to hear about that from both of you, Jessica, we're going to shift the focus a little bit. So we're going to talk about some metrics and some outcomes. So we're using this technology. We're putting it in. Let's talk a little bit about what kind of metrics do you think we can get out of AI enhanced insights that would have the most impact for communities.

Yeah, no. So I'm sure everyone or the majority of people on this call are all here. You might be in leadership conversations where you're saying we need to when you're looking at your quarterly metrics, what's our overall QM score? What are our, what's our data around UTIs, our data around falls with injury or pressure injuries, and how can we get better in these areas?

What tools are out there, which is probably why the majority of you are on this call. And that's truly at the heart of what we do by utilizing remote patient monitoring, everyone on [00:20:00] every single speaker you're going to hear from today is going to touch on the staffing crisis that is in this country and how we can help people in their operations, but also how we can truly benefit your metrics.

I was really pleased after having worked with a lot of big gorilla pharmaceutical or medical device companies. I always, we always had data, right? And that was something that I expressed to somatics that we really need. I need actionable data to show and validate that remote patient monitoring that travels around with the person that it's impactful.

We do have that data. We're excited about that. We did a clinical study with the University of Pennsylvania in the Wharton School of Business. As well as we did it in a, it was called Catholic senior housing in Pennsylvania. So we looked at a hundred patients in various levels of care.

So sub acute, independent living. We had them wear bands and we looked at their metrics. Six months prior to initiating the use [00:21:00] of a just passive wearable band that's enhanced with AI and insights around all this data that we're gathering from people. And then what we did was we looked at their metrics six months after.

And the numbers, and I can share them, should anyone want to see the paper, I'd be happy to share it with you. But the numbers are impactful. We were able to reduce UTIs by 52%. We were able to reduce falls with injury by 42, 40 2%, with falls with injury, 17% drop in 30 day readmissions.

These are all things that you're most likely very interested in and our metrics that you're analyzing every day. And I think that one of the key things though, that I talk about is that putting a wearable on someone's wrist. Isn't going to get you those results. What truly gets you those results are two things.

The AI that we apply to the data that we're cap, that we're passively capturing. So the nice thing about it is that you're [00:22:00] not requiring nurses to take episodic readings. They don't have the time for that, nor do where do they log it, right? All these questions. It's doing it automatically. It's syncing it in automatically.

But what the AI then that we're applying is doing is looking at all these thousands of data points every day, and it's identifying abnormalities and patterns. Predictively. That word is so important. It's how can we prevent these things from occurring? So us giving, looking at hydration, looking at nighttime waking, walking episodes to give a predictive risk or alert around UTI risk.

That's number one is giving that alert. That's what the A. I does. But the second piece of that is ensuring that we were and we do this. It's semantics, but or any other company. I can talk about that, too. But how we partner with who's looking at the data and managing it right to help you operationalize.

Because if. If nobody communicates that to the resident or nothing happens to it, you're [00:23:00] not going to see those effects and metrics. So it's really important, I think, that you look at all of it holistically. Yes, you can see what AI does, but it's also how do we put it into practice and that we we help with.

So we're excited about what the AI and the insights can do by making it easy and making it truly impactful with some real clinical data. Thanks, Jessica. I love that you share that. As I think Sanjeev mentioned earlier, AI is such a buzzword. We're hearing so much about it. We wrote a white paper about it, but to actually hear you speak to it and how it's actually changing lives is just really impactful.

Okay, Ryan, I got a question for you next. So let's talk a little bit about the resident experience. So how can AI be used to enhance and increase resident engagement? Yeah. So I think, for a while now, I'm assuming you're using some sort of software platform for engagement. You're collecting a ton of data.

And a lot of great stuff is in there. And I think a challenge that has everyone's alluded to is that staff don't have the time to be [00:24:00] data analysts. They don't have the time to go through and look at the trends or identify opportunities to it. Improve the experience. And so that's where a I can be very helpful.

In being essentially your data analyst. If you think about your population in a community at any one point in time. The, what's relevant, what's interesting really depends on the makeup, the complex makeup of people in there at that exact moment. And one exciting way we're using AI is to look through all of the different, unique interests, likes, dislikes, what people have gone through in the past, really anything that's social, nonclinical to identify really specifically, here are the five things you can add to your programming.

That's the most relevant to the most people is probably get the best attendance and try to make those predicted insights. To say, you add this program, you might increase participation by X percent. And that's really a thing where people have had that data for a while and probably couldn't do that manually, but [00:25:00] this.

It's really does it for you gives you really specific action items as to what to do using the generative component, which is great for summarization for taking complexity and synthesizing into kind of a written text that's digestible by the average person. And then letting the staff use that and leverage it really easily in their day to day.

The second piece, too, is even inter residents. If you think about someone is moving in or even coming on a tour of a community. The most important thing is helping them make those connections as quickly as possible in in the community, there's people talk about the back door.

They left the 1st, 30 days. Someone's not settled. They might move out, help them make that connection, find someone in the community. Using AI to identify who might be compatible who share similar backgrounds and interests, and let's introduce them to each other. Let's start helping them make those connections as quickly as possible.

And so that's really what gets me excited. The [00:26:00] ability to just take all the complexity and then leverage our experience in engagement. To really take and help you take your programming to the next level. Yeah, that's really exciting to think about. I think a lot of times we're thinking about AI from the staffing perspective, but to think about the residents actually being able to take advantage of this technology directly is pretty exciting.

And if anybody hasn't seen the AI tools that are in icon, I got a demo of it recently. It's pretty cool stuff. So definitely check that out. If you haven't so far. All right, Sanjeev. I have a question for you. This is probably a question. A lot of people in the audience are wondering about. I know I've been asked this by our clients specifically.

So the question is, how do you overcome data privacy with your platform? That's a great question, Amber. And oddly enough, that's probably the 1st question I always get asked before we even get into any sort of AI solution or robotics. But, before I jump into addressing this concern, I do want to bring to light.

[00:27:00] Why I think this is such a grave concern, and it's only going to get more and more brought to, the the spotlight so I systems can digest and analyze exponentially more data than your traditional legacy systems. So there's an increased risk of personal data exposure.

And I think someone mentioned predictive analytics, for example, uses like pattern recognition and predictive modeling, and all of this requires data. And, the algorithms we're building at HelloGuard and vCare really can infer things like personal behavior preferences, passively learning along the way, proactively making care plan recommendations as needed.

Clearly, with all this data that's involved in all of this brings to light concerns about security and HIPAA. Specifically and I think I read the other day that the number 1 biggest concern with adoption when it comes to the C suite is the ability to handle data, privacy and security when it comes to and there's a lot of [00:28:00] fear behind it.

Rightfully and with all the benefits of AI there's some bad players. I think we've all seen the news where healthcare and senior living have been held ransom for, data that data breaches that obviously is not a good outcome that anyone wants.

So there, we're seeing an increased investment in cybersecurity and HIPAA protection. It's almost like we're in an age where AI is fighting against itself. And we're seeing that happen right in front of our eyes. And the more advanced AI gets, The higher the investment in cyber security and data protection, and we're already seeing that rapid rise in cyber security companies combating this issue and it's going to continue to evolve as we move forward.

But when it comes specifically to privacy and HIPAA, we are generally talking about something called P. H. I. or patient sensitive data. And we had hello guard and be care, As a company, we conform to strict security standards both on the edge where a lot [00:29:00] of our applications are running as well as in the hybrid cloud environment where most of the processing occurs.

So if we take a specific scenario at HelloGuard and vCare, we require all of our app partners running on the robot to conform to these HIPAA and SOC 2 standards. And the way we do this is we de identify or encrypt the data that's captured at the point of care. And, before it's sent to the HR systems in the cloud.

So if someone were to hack us, for instance, they would see gibberish. They really wouldn't see any data. Hybrid clouds, such as AWS and Microsoft Azure are inherently protected. By cyber security and HIPAA protocols as well. And those are the clouds that we use.

So this is where most of the processing of the collected data occurs. So to summarize all of this, there's really no data stored on our robots. Any data collected is encrypted before it's processed and almost all of the processing and retrieval of data is done in a secure and protected cloud environment.

So that's [00:30:00] how we overcome some of these concerns.

Sorry, I clicked on the wrong box trying to meet myself. Thanks for that. And I'm, I may have some follow up questions for you later on governance and policies and things like that. But I think that's a question we'll get to a little bit later. Steve, I'm going to circle back to you. What are you witnessing with operators that have actively deployed AI solutions at their communities?

Some specific use cases, impact potential if you can share a little bit more around that. Absolutely. Thanks, Amber. I'll be honest, and a lot of operators that we're working with, there's a kind of ground layer, really building a foundation that happens early on. And that's creating that unified data analytics platform, bringing all those different data sources together.

Jonathan previously mentioned the EHR gorillas that we often have to wrestle with that 1st layer is really bringing that data together. And then being able to leverage generative AI and traditional analytics tools to get that kind of holistic view of the data. That's already at your [00:31:00] fingertips, but you're currently siloed.

So many of our clients live in this world where they go to their HR, they go to their CRM, they go to their finance application and have to look in those kind of siloed contexts at their data. The 1st layer, there's a lot of reconciliation need to be done. We've helped capture a lot of revenue just from that early stage kind of misunderstandings between different platforms and how even you track occupancy or move ins move outs within different facilities.

But in terms of generative a lot of the use cases we're seeing truly are that human in a loop quicker access to data when it comes to, hey, check out what's the insurance details of a certain resident. A lot of finance information, a lot of sales and marketing, just quicker access to those data points instead of looking at a report for everything.

And we're also seeing a ton, especially with operators operating in multiple states of that regulatory review, being able to look up internal compliance measures, be able to compare those against state regulations and do so in a really quickly quick manner. Ensuring your internal compliance and running the gamut from accessing internal data to [00:32:00] access accessing corpuses of documentation, knowledge management, another popular tool that we started to deploy our resident facing, really help capturing.

What residents are doing in terms of activities help suggesting other activities to them, giving them an opportunity to interact with a lot of the policies and engagement opportunities available at different facilities. And I think 1 of the really cool features that both your employee facing tools and resident facing tools allow for you is to really gauge.

What questions are being asked and help shaping your services, your offerings, and the way that you interact with both employees and residents through that process. The kind of telemetry you get when you see the way employees want to consume data, seeing the questions and the requests being asked from individual residents really helps shape your services and has an added benefit of help fine tuning the models so that large language model can really understand the context of your industry and your facility a little bit better.

Thank you Sanjeev coming back to you. I [00:33:00] again, this is another question that I know I've had clients come to me with. I've had clients say, this technology is great and it's exciting, but we still have mandates. We have certain regulations that we have to deal with. So how do you overcome that in certain states?

That's a great question, Amber and, some of this is really focused around minimum staffing requirements for nursing homes that participate in Medicare and Medicaid. And like you rightfully said, it is straight driven. It's not federal. And I think it was proposed in September that the final rule will actually require nursing homes to provide a minimum of 3 and a half hours of nursing care per resident day.

And that includes things like, half an hour of care from a registered nurse for resident day, and at least 2 and a half hours of care from a nurse aid for resident day and so on and so forth going to have things like 24 by 7 onsite are in services. Coming back to the question, how do we overcome this?

Ruling and how do we apply our robotic solutions to this. [00:34:00] So really these mandates don't overcome the reality of what exists today in communities. And the reality is that you have overburden nurses and you have very costly staffing agencies out there. And I don't think anyone is new to this concept of, agency rates and availability and turnaround times given the severe shortage of nurses.

I think I was reading the other day. Some nursing schools are trying to turn out that, nurses even faster, taking like a 2 year program and kind of condense it into 9 months. I don't know what, what that does to the quality of the education that they're getting, but, we just feel like our solution provides an alternative to what's out there today, which isn't great.

And it's really hurting the operators. We're simply offering that alternative not to replace nurses. But to be that force multiplier or that supplement to the nurses the biggest problem that hello guard is solved is the burnout and the ability to alleviate [00:35:00] that burden on the nurses through verifiable data that we've seen in the communities.

If you rewind back 20, 30 years a nurse had to remember 10 things, maybe 20 things in today's day and age, post pandemic, they may have to remember 100 things or maybe 200 things, right? You almost need a checklist just to remember, what you need to do as a nurse.

And the staffing mandates don't change these problems, these prevalent problems in any significant way. If anything, they actually accelerate it or make it worse. Hello, garden, be care, are there really to provide that relief to existing and new staff by automating those non direct care related tasks.

Things like deliveries of medication, rounding, dictation, med passing. There's, I can keep going on and on, but, these tasks typically take up, 30 to 40 percent of a nurse's day. So when you talk. Nurse, mandates of 3 and a half hours of a nursing care per resident day.

You're talking like, half of their shift, [00:36:00] right? We're basically automating half of their shift. So that relief, really allows the nurse to be more productive. Reduces attrition make some happier, obviously, happier employees mean happier residents, right? We all know that. And that's what we're doing, right?

We're not replacing staff, but we're actually helping them be happier, be more productive. Reduce some of the the burnout and really make them more productive. Thanks for that Sanjeev. I know we have a lot of audience questions coming in, so I'm going to ask one more prepared question and it's going to be both for Ryan and Jessica from different perspectives.

And then we're going to jump to the audience questions after that. These questions are similar. They're basically around how can we approach conversations about using AI? So Ryan, I'm going to ask you from the resident perspective, and I think probably residents board members could probably be similar if they're skeptical or they're concerned about the use of AI technology in their community.

And then after Ryan answers, Jessica, I'm going to have you answer that from [00:37:00] speaking to more of the C level at the community. So Ryan, I'll get started with you. Yeah, I think it really comes down to a lack of understanding. I think a I, for whatever reason, being in the news as much as has been has gotten somewhat of a bad or scary reputation.

We're talking about a little bit earlier on the staff side. And it's really just about education and informing the resident. Lot of residents are surprised. And when we talked to them to learn that they're actually already using a I and a lot of different parts of their lives.

If they're getting recommendations through Netflix, there's basic, specialized a I focused on that using it already. And so it's talking more about it from the perspective of the benefits of the technology and not necessarily even leaning into the shiny AI portion of it. It's a lot more about, this is going to make your life much easier, or it's going to make your experience much better.

That kind of [00:38:00] conversation and just having that conversation. I think it's super impactful. And I think, unfortunately, due to just preconceived notions of certain stereotypes. A lot of times those conversations aren't had because we just don't think that for whatever reason, there's going to be that kind of understanding.

And so have the conversation. It's super important. And you will be surprised at the impact it will have in changing perceptions. And, I agree wholeheartedly. I think communicating to the residents that so they understand what it is, right? No matter what form of AI, whether it's a wearable or any of these other platforms, it's just that if they understand, I think their level of anxiety comes down.

But one of the biggest challenges that I saw immediately when I came to semantics was that, A lot of people don't question, they want to use it. You guys are all on this call because you're interested in using it. It's how do I do it? How do we actually put this into practice when I have all of these other barriers that I'm dealing with on a day to day basis?

My [00:39:00] role in, in terms of business growth for Somatics has been completely reliant upon the strategic partnerships that we have formed with management companies. Basically, we have companies all over the country that do remote patient monitoring management, chronic care management, to where you can bring a solution like a remote patient monitoring wearable, communicate the benefits such as hydration tracking, vitals tracking to your residents to provide them with a peace of mind.

It allows you to market the use of it, which is what, when people are choosing a community that they want to live in, sometimes that can be very attractive to people. It shows that you're going above and beyond, but we come along and we can bring it at no cost to you because now we've partnered with groups.

That are billing Medicare for the service because this is completely reimbursable through Medicare and you don't have any out of pocket costs. You're benefiting from the metrics. You're benefiting from the monitoring. So it's really we've pivoted into [00:40:00] forming strategic partnerships to bring the solution to you.

To make it easy for you so your staff doesn't have one more thing. They have to do one more thing. They have to learn one more thing. They have to manage and your residents can benefit. So that's been a key part of our growth and the ability to get it out there in the market. So it's been helpful for us.

Thanks. Okay, I'm going to I'm going to go through a couple audience questions, and then I do have a couple more to follow up with if we have enough time at the end. Jonathan, this is a question for you. I think you partially answered it earlier, but because you said the transcription accuracy is very high, but do you have a way to verify and validate that transcribed audio?

Yeah, the workflow is very simple. The text is captured at the robotic. Point and then that text gets transferred once the report is completed, the person presses, the process. What happens is we take that audio. [00:41:00] Transcribed in a text in through the cloud is where we process. Using going against a large language model, and it's been tuned.

It's not. Very important to I think this is a challenge. Transcribed Within the AI world, depending on the model that we're working against, the processing time can be incredibly long and very unproductive. So we have a large language model focused on the content that you would have. We go very deep in the nursing care world with terminologies, medications, et cetera.

So we process against that. Model and come back to the robot presenting the report based on the data in the proper categories. And that the system learns it's generative. So it's learning. How do we respond? Because the. A nurse has the opportunity to make any corrections or edits. And our results have been in the 9597 and [00:42:00] after.

A period of use with an individual, the system's learning. So you have a unique log in. We also with Tammy or with CC have a facial recognition camera as another means of validating the user. So the processing is against the model. The validation is against, um, the individual who's taking the notes.

The nurse is looking at what came back and can adjust it. And the experience that we get when people see about 95, 97 percent of what they said is put in formatted in a, in the report that they're going to need to create anyway. That's the validation, right? The user. And the system learns the more often it does that.

Is that does that help? Explain. Yeah, I think it does for me. You guys can put in the chat. I know that we've been using the zoom transcription services and it is really accurate. It's scary accurate actually. So it's really interesting how this technology has continued to evolve to just become more and more [00:43:00] accurate than it used to be in the past.

I think it's a question of tuning models to fit situations. It's think about having a garage with. Everything like a tractor trailer, a fast race car. You don't want to have one vehicle trying to do everything. That runs in tremendous issues with performance. So we're very sensitive to that experience.

Thanks. This question doesn't say specifically who it's for but Jessica I think I'm going to direct it to you because this is something else I'm also curious about because I've had clients ask, how do you. Okay. Monitor your A. I. Outputs. And I think what the question means is who's checking all this data and are you potentially liable if you're not responding to me?

Yeah, so so just how I just mentioned sometimes it's oh, my gosh, I don't want to be liable. This data comes through and we don't act on it. So for in those instances, there's 2 ways. One, a lot of our like independent living communities, they just have a simple [00:44:00] waiver to say, Hey, we're offering this to you through the community, but we're not liable.

It's just a simple consent form. We have plenty of examples of them for the communities that are like, listen, we really want to market this, but we just do not have the legs to be able to Have anything to do with it. That's when I bring in my remote patient monitoring chronic care management partners.

They come in. They literally operationalize the whole thing. It's so simple because all people are doing are wearing a band on their wrist. There's no other infrastructure involved. There's no cameras sensors that it's the community itself literally has zero cost. Because it's reimbursable through Medicare.

So the management company will build Medicare. They're getting paid. They'll build Medicare for managing it. But then they're the ones who are establishing it managing it. And I think 1 more thing to note is that just because someone's monitoring, someone's remote patient monitoring or chronic care management doesn't make them that person's primary care provider or their specialist.

It doesn't replace [00:45:00] that at all. It's just simply monitoring people. That's it. all. That no matter where they live at what area of care. So we do have some communities that are using it and an assisted sub acute type of level, or some people who want to and we have partnerships with groups that will also do that.

Depending upon the need, I assess that when I meet a group, just say, what are your capabilities? What are your needs? And what helps to fit the best? But that's a way that doesn't create any liability for the community. It offers the benefits. And it's not that intimidating for residents to be able to bring it on.

Great. Thanks for that. Okay. So this next question is again, not specific to anyone, but I think Ryan, I'm going to give you the first chance to answer it. And if anybody else wants to join in, but any specifics on AI events or activities for communities. Is it events around AI for communities or is it AI using it [00:46:00] for events like what we're doing with our platform?

Yeah, I think looking at, there's a little bit more detail from Michelle. Just, are there events, activities like trivia, storytelling, things like that that AI could help support? Absolutely. So that's exactly what we're doing. And we're actually going even a step further. So not only will we, use the AI to go through everyone in your population and say, here's five activities.

You can implement, we'll give you short plans as to what you, how to deliver that, and then even tell you any certain flags, like X person, be cautious because of this mobility issue they have, or here's an adaptation that you might have to make to the activity because this person has poor vision impairment, and then I'll give you suggestions as to what.

Adaptations can be made to accommodate that person. So it's even going to that next year now. And so we're working on really standardizing that and making sure obviously it works in every context, but absolutely. It's a great use case [00:47:00] for great. Thanks. I'm Sanjeev. This question is for you. How do residents respond to robots being in the community?

I want to answer that, but I also want to answer the previous question. Amber, we've made it very easy for people to adopt in the community. And there's simple ways to do it. So we've integrated chat with our robots, for instance. So you see a little smiley face and you can speak to it just like you would on your phone, right?

But it's very simple and easy but in terms of And we've also done educational series For example, we partnered with MIT and their scratch program to allow people of any age to learn how to code using no code language How cool is that on a robot and make it do things, right? Obviously this could have, implications in K through 12, but it can also be used like in an activity session with an activities director.

But going back to your question about, how safe do people feel with our robots? The robots that we deploy in the communities are basically iPads on wheels. If you're comfortable using an [00:48:00] iPad on wheels, then, and you're comfortable with Alexa, then you're going to be comfortable with our robots.

They're not, that big, they're 3 feet tall. They weigh 35 pounds. They've got 16 sensors on it. Very easy on the eye. People start dancing around it because it's so cute. It looks like a little E. T. right? So that's the easiest way to explain it. And it's very non threatening very easy to interact with, and very easy to integrate it because it comes with an SDK kit, a software development kit.

It's really easy to integrate it. Into any existing operation. Thanks. Yeah, and I've heard the same thing. I've heard that residents get really excited about the robots. They like to name them and even sometimes brag about having them at their community. Right. Steve, I'm going to ask you a question.

This is my own question. So hopefully you're ready to answer it. But I think SkyPoint is such a cool solution. I tell our clients about it all the time. But I think some of the struggle and maybe people listening to this or who've read our white paper, they're like. AI sounds really amazing, we're still tracking [00:49:00] some of our data in spreadsheets, or we feel like we're down here and AI is way up here.

So how do they get started? What's that first step to start using AI in like a simple way? And how do they actually get to, to be able to fully utilize this technology? If maybe they feel that their technology culture is a little bit further behind. That's a great question, Amber. And let's be honest.

That's something that we see often in the industry. There's a lot of tech that accumulated from having all these different platforms and that lack of true kind of unifying force, and that's why I think what SkyPoint is doing has been so impactful and driving so much value because we can really be at several layers of your data journey.

We can be that base layer. We have a several clients that we literally just ported off of that world where. They're looking at PCC for their EHR data. They're looking at Yardy for some other, operational data. They're not able to get that true view. So we're ingesting all those data sources together and getting you off of spreadsheets, getting you onto unified analytics, be it BI tool or leveraging AI to start asking some of those questions.

Cause the other [00:50:00] thing that we're finding in with some of our partners that are a lot more advanced already have a lot of BI tools employed, might have a data warehouse that's ingesting all their different data sources. Is that there are all these points solutions that can also be deployed and reduce the need for report for everything.

How much time do we spend paging through different Excel workbooks or drilling down to just get that one simple data point that we wanted to get 15, 30 seconds ago. So you can save development time from your BA team, building all these reports. You can also get that time to value, just accessing that single data point that you needed more quickly.

So yeah, to summarize, SkyPoint can really meet you at every phase of your journey. We can be your data architecture. We can also just be a part of your AI acceleration path. All right. Great. Thank you. Jonathan, I'm going to ask you a question and we'll see how long this may be our final question.

And I'm sure this is again, something everybody is thinking about. So I'm going to talk to you about ROI. So how do you calculate ROI for your solution or any general advice you have [00:51:00] for calculating ROI for any of these types of solutions? I appreciate the question. And I actually sat on both sides of the table.

I owned a memory care community and I had to look at technology and what makes sense and along with many other things. So essentially ROI calculation is what do we do today? How much does it cost us to do that today? And then what can we do different and validate that we can do it and validate that we're capturing what we expected, so that process to do that is collaborative.

And ideally, you want to have, and this is how we're getting engaged with our opportunities where we lay that out 1st. There's so many capabilities that we have. It's almost trying to cost justify why you want to buy a phone, right? There's so many ways that you can say, if that if I had a phone, I could do this out of the other thing.

So we put construct around prioritization of areas that we're going to look at. So that process to determine ROI. It's it's. I'd say it's not very glamorous, but it's the [00:52:00] way it is, right? You look at, you walk in the shoes of the folks in the care side, and it's also multidimensional, meaning it's the care staff, it's the administration, it's the corporate side, so they all have views and aspects of what they're looking at.

And that's how we create the ROI model and determine the batting order, if you will, on how we would do rollout and feedback and monitoring. Yeah, and I think 1 thing we've heard over and over from all of you on the call today is how much time is being saved with a lot of this, these tools and also just how much more data you're getting to just provide better care, better experiences for both staff and residents.

It is an opportunity to rethink processes to look at implementing. We're talking not just technology. We're talking about an introduction of something in a very dynamic and stressful situation or scenario. It's so important. It kind of ties into the 2nd thing about balancing [00:53:00] how this gets introduced.

And so we have an adoption. We use there's 3 faces. There's the introduction of what it is and to sort out. Then the adoption phase, which is we determine what are the areas we want to tackle. So we begin the process of introducing CC into the environment. We have a great hands on boarding. Think about bringing on a new employee.

CC is like that, right? So there's a onboarding process. And then we have the execution follow up. And, validation and as invariably will happen care staff. Somebody's going to say, hey, what about doing this? For example, we can do the med pass piece. That's. Very routine for residents, they may want to know more about that because there's a certain aspect will really save some time for their day.

So we're going to be responsive to that. It's setting up that dialogue so that we can be attuned to the clients needs, but adoption. Acceptance and then ongoing, refinement adaption are adopting into [00:54:00] new areas or adding new areas of capability. But having those 3 elements in place are so important.

It's not just about the return on investment, right? That's a metric. Yes, definitely. But it's about satisfaction of the staff. It's about customer or client or resident, a patient satisfaction, right? Responsiveness. And ideally, we'd like folks to think that we are really helping everybody out. We have a wellness component.

So all of our interactions, we have a model that gauges the type of responses. And the idea is to create that sense that when I've left my time with Cece, I feel good about, or I have a clearer direction, or I understand areas that I need to get more information about, but it's not about it's overwhelming.

It's about there's a way forward, we're in this together and the difference is Cece has a tremendous Source of information through the data, like through accessing the various things. You know that Steve talked about the answers are there. It's just how to make it easy to come together at that point of care in that very [00:55:00] moment so that we give the best possible outcome for the care staff and for the residents.

Yeah, and just to add to that, I think even to take it up another level, this is about differentiation for your community. And as a provider, this is the direction that the world is going. And how quickly are you going to get there? Are you going to be an early adopter in the middle? Or are you going to be behind?

Because eventually residents, staff, family members, everyone's going to be looking to move into communities that are doing this, these types of things with technology. So it's exciting. I always say senior living technology is the most exciting technology field out there today. We were at the end of our time.

This has been really fun to do a live podcast. It was our first one. I want to thank all of our panelists. I want to thank our audience. 

You guys had some really great questions. You can find us online at RaisingTechPodcast. com where you can see all of our episodes and contact us to provide feedback or submit an episode idea. We are on social media everywhere at Raising Tech Podcast. If you enjoy [00:56:00] Raising Tech, please leave us a review and share with a friend. Music is an original production by Tim Resig, one of our very own Parasol Alliance employees.

As always, thank you for listening.