How RiverSpring Living Uses AI, VR, and Robotics to Redefine Post-Acute Care | The AgeTech Podcast S4E23 with CIO David Finkelstein
What does it look like when a post-acute care organization truly leans into innovation? In this episode of The AgeTech Podcast, I sat down with David Finkelstein, CIO of RiverSpring Living, to talk about how his team has piloted over 25 different technologies – from robots that speed up rehab, to VR headsets that reconnect residents with their families, to AI voicebots that actually improve mood and flag care issues. It’s not a vision of the future, it’s happening now.
Catch the full conversation on Youtube, Spotify, Apple Podcasts, or scroll down for the transcript.
Keren Etkin: David, welcome to the show.
David Finkelstein: Thanks very much for Keren for having me. I’d really like to listen to the show and watch it, and very interesting to get a lot of people engaged in the aging tech space. So I’m glad that you’re existing and I’m glad that you’re promoting this.
Keren Etkin: Thank you. Thank you so much. So could you tell us a little bit about your role as a Chief information Officer and what does that look like in River Spring Living? Because from everything I hear, this title (CIO) has different or could have quite different. Job definitions in different senior living providers.
David Finkelstein: Sure. So we’re a relatively large not-for-profit senior living provider based in the Bronx, New York. We own and operate a number of post-acute long-term care settings. Skilled nursing facilities, assisted living facilities, independent living facilities, HUD housing supportive housing, as well as some home care and managed care.
So we serve about 18,000 New Yorkers Been here for a little over 12 years. When I came to the organization as the chief of Information Officer, it was a typical CIO role. Anything that got plugged in, anything that has a blinking light you’re responsible for. So computers, networking, medical record systems, financial systems the wide area networking, connecting all of our various buildings together.
That was all about the infrastructure and the operations of IT, but. Thanks to the progressive thinking of leadership within the organization, some previous experience experimenting with some new technologies, and a very fortunate ability for us to obtain an endowment from a very friendly donor and family member of a resident that we served over the last three years since the middle of Covid. I’ve had the opportunity of really experimenting with and implementing, trialing, piloting a lot of new edge technologies that are typically not found in your post-acute long-term care setting, but has really done a world of good. We’ve created a committee led by some members of the board. We hired a clinical project manager to lead a lot of the implementations. We went through a process of piloting before we would roll sta roll things out full scale so that we would just cut our losses if something’s not working. With really the triple aim of enhancing the residents experience and their care, enhancing the staff members’ ability to do their job and their care, and then eventually getting some financial benefits and returns based upon the use of technology.
And all of that has helped us in leapfrogging and doing a lot of things that many long-term care facilities either can’t afford to do or don’t have the ideas to do.
Keren Etkin: That is a wonderful introduction, and I have lots and lots of follow up questions. So first and foremost I’m interested in your process, like how does your team decide which technologies you even wanna pilot? I.
David Finkelstein: So a lot of it is really what are the pain points? So when we started down this this journey, one of the challenges that staff came to management about management came to that, that, you know, a lot of, especially in our skilled nursing facility. Care delivery was very inefficient. The first good example is Vital Signs collection. It used to be that the nurses go to every single patient twice a day and put the blood pressure cuff on and put the pulse ox on and take their temperature and take their respiration. Write it down on the napkin, run to the computer at the nursing station and document that information in the medical record.
And that happened two or three times a day. And depending upon, especially during Covid, many more times a day, so that we were tracking the disease we knew there had to be a better way. You see many hospitals with automated vital signs, collection machines, but not many post-acute and long-term care facilities. So we looked at two or three different vital signs machines. And were we able to select on one that interfaced with our medical record, we were able to shift the responsibility from the nurse to the nurse’s aid to do this collection because it didn’t require a nursing degree to do it. And then we were able to, using the machine collect, vi the all the vital signs within a matter of 30 seconds simultaneously.
Instead of doing them serially and automatically upgrading, updating them to the medical records so that they’re accurate, complete, and we can trend. So we were able to save anywhere between five and 10 hours a week on each of the nurses rounds by not having to collect vital signs manually. That was a quick win that we wasn’t without challenges.
Some of the nurses were adverse to new technology. Some were afraid that it was gonna change their job or eliminate their job. Some of them were complaining that the new devices were not clinically accurate compared to the old blood pressure machines that you pump up manually. Even to the point where our medical director was. Questioning whether or not is accurate and complete. So we sat down in the boardroom. We had the old device. We had the new device. We took blood pressures and pulses on three different people and proved that technology was solid, the implementation was solid, and the savings were real. So that was one of our first quick wins of taking a problem that we identified across the organization and solving it using technology in something that long-term care is typically doesn’t see.
Keren Etkin: I love that, and it’s quite remarkable that you were able to save five to 10 hours per week per nurse.
David Finkelstein: Correct.
Keren Etkin: Just by doing this. That is amazing. So I understand like why there might have been some pushback at the beginning and I wonder, first of all, how did nurses like receive this technology after it had reduced their workload and maybe allowed them some more time to take a break, go to the bathroom, even have a cup of coffee during their shift, which I bet is incredibly busy. So that’s one thing I’m wondering about. And also like how do you translate that to ROI? Because it’s not like, reducing five to 10 hours per nurse. Per week allows you to reduce the number of hours that they work. I mean, I assume that they still work the same amount of time during their shifts. So how do you calculate the ROI.
David Finkelstein: Correct. And it is difficult and the finance people don’t like the what quote unquote soft ROIs when it comes. We’re not reducing FTEs, we’re not reducing staff by doing this, but taking the nurse out of the vital signs collection is more time for them to. Look into the chart spot abnormalities when they see maybe a blood pressure trending up that they wouldn’t have noticed if they were doing it each individual day, but when they looked at a chart over three or four weeks for a particular resident, they can spot something. They have more time to spend with the residents, talking with the residents, conversing with them being part of their lives as opposed to being pill pushers. You know, here’s your meds. Let me go to the next person. Here’s your vitals and here’s your meds. So they really got a better quality of life and a quality of care so they can work with the residents more one-on-one and with personal interactions as opposed to the clinical interactions that the vital signs collection process enabled them to do.
They were very skeptical. They were taking the machines and throwing them down the halls and saying it didn’t work. But when we really. and that’s really why we hired a clinical project manager early on in this project. So this clinical project manager, she’s a nurse, she has an IT background and she’s implemented systems across many organizations for many years.
She came on all three shifts. Came in at the evening shift the night shift on weekends, and went hand on hand with the nurses to show them how to use the technology. Get rid of the fears, get rid of the issues. We also bought a lot of extra equipment. We put up two vital signs machines on every single floor for 50 residents. What if one of them breaks and they were behind? So we put three and four machines on every single floor. That way we couldn’t use the excuse or the problem that it’s not working today, or it fell down or it didn’t get charged. There was a lot of problems at the beginning of them, forgetting to charge them.
So we remind them every time we walk down and floor and go rounds. Plug it in if you’re not using it. So it was a little while, probably a couple of months of really full adoption. But once we got there, I think the nurses and the nurses aides and everyone up on the floor, the whole care team realized that this is better technology.
Not for technology safe, but better patient care, and being able to spend more time, more quality time with the patients.
Keren Etkin: Wonderful. So do you have any examples for technology that had a more direct correlation to the organization’s bottom line that she could say, this technology allows us to save $100,000 per building per year, or something of the sort.
David Finkelstein: there’s two pieces of technology I can talk about. One of them is a re rehab department robot called zero G. Typically when someone comes to a nursing home after a hospital stay, let’s say they have a knee replacement or a hip replacement during their rehabilitation time, they come down to the gym. Two therapists. Hold them by their belt, walk them down the hall and help them recom re acclimate them into walking and getting confidence. The Zero G robot is a ceiling mounted track robot and with a harness. So we put the resident in a harness and the system has an AI powered an engine built into it that will prevent the resident from falling. And we even prove to the residents, we say, all right, try to trip yourself. And it shows that the system will pull them back up by the rope, that it’s connected to the ceiling, so it’s impossible to have them fall. So instead of two, two therapists walking side by the resident, holding them by their belt to make sure that they don’t fall. It’s one therapist guiding the resident as they walk down the hallway with this harness on. The resident can push themselves faster to recover faster because they don’t have the fear of falling, and we have a second therapist that now can work on a different patient. So we were able to reduce the average length of stay for our knee and hip replacements from 28 days. Down to 21 days. So that allows us to get more patients through the system, allows insurance or Medicaid and Medicare to cover less dollars for that, and shows us a much better return on investment for a total cost of length of stay for our therapist and for our residents. So that’s one, one piece that really was a big big boon in, in providing a lot of return on investment hard numbers to our therapists. The Second one I’ll talk about is called the Red’s vest. And this was built out of Israeli military technology. there’s a real Israeli military company that had technology that was able to see through walls during the firefighting times. They built this into a vest, which is basically a clamp that goes over the shoulder of a patient that has CHF or congestive heart failure. what it can do is detect down to the milliliter the amount of fluid that’s in the lungs. One of the biggest challenges for CHF patient is if they have buildup of fluid. There’s usually could be 3, 4, 5 days before there are outside symptoms, and by the time there are outside symptoms, sometimes that requires a transfer to the hospital.
They have to be on diuretics and they have a lot of other complications related to that. By putting people at risk for CHF on this vest two or three times a week and measuring the fluid volume, the medicine team can easily determine people that are building up fluid in their bodies. Proactively treat them with the right medications to reduce the fluid. And in the year and a half that we’ve used this red vest, we’ve had zero incidents where we had to transfer someone from the nursing home to the hospital for CHF complications. So that is a
Keren Etkin: Wow.
David Finkelstein: a re refund to us about not losing resident days in the facility. Less wear and tear on the resident, having to go into an ambulance and over to the hospital and sitting in the emergency room for hours before they get treated. So that is a big return on investment that we’ve had.
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Keren Etkin: Wow, that is amazing. I wonder are you able to the softer implications of these technologies, like how it impacts staff turnover or resident satisfaction, like just how people feel within the facility within the organization.
David Finkelstein: numbers. We constantly have resident satisfaction surveys. We constantly having staff satisfaction surveys, and we certainly have been seeing an increase in performance the organization over the last two or three years as we’ve implemented many of these technology projects.
I mean, we’ve talked about three or four of them already. There’s probably been 25 projects that we’ve implemented over the last three, four years, thankful to the donation that we’ve had. And most of them, or many of them come from staff and management’s ideas on how we can solve a problem that affects the organization. Another quick example is one of the difficulty problems that nurses have, especially in long-term care patients in a nursing home, is when they have to either draw blood or insert an IV in an elderly patient. The skin is very fragile. It tears very easily. It bruises very easily, and it’s very difficult.
And there are many times that we’ve had to transfer patients out to an acute care hospital, to have a skilled phlebotomist to do a blood draw or to insert an iv. We found a system that one of the staff members recommended called Vein Finder, and it’s a near infrared light that you shine on your arm.
And it visualizes exactly where the veins are, based upon the difference in temperature between the blood flow and the surrounding skin. Since we’ve implemented that, again, zero transfers to the hospital related to blood draws or for IV insertions, so staff are happy that they don’t have to transport The residents are happy.
They don’t want to get stuck three or four times or subject themselves to an ambulance, and that’s just been a win-win for something. I think we have three of them for a total of $12,000 that we invested in the organization.
Keren Etkin: Wow. That sounds like science fiction, but I actually know this technology to be real. I wonder this, we’ve, so far, we’ve covered out of the 25 solutions a lot of medical stuff. I wonder if there are any solutions that you’ve implemented that are on the non-medical aspects of senior living
David Finkelstein: Sure. There are two, two specific areas that I can talk about. One is virtual reality and the other one is AI. So the virtual reality we, there are a number of different vendors in the marketplace that target virtual reality headsets for the low long-term care industry. And we partner with one of the more popular ones out there. We weren’t just satisfied with, put a headset on a resident and bring them to the neighborhood they grew up with, or the Eiffel Tower or something else like that. We wanted to take it to the next level. So we’ve used virtual reality in a couple of unique and interesting ways. So one of the areas that we have a lot of need for is we have residents, like I talked about before, that come in with a knee or a hip replacement. They’re here for 30 days or 20 days, and then they go back home. So in order to enable a safe discharge home, we take a GoPro camera, give it to the family, and have them take photographs of the resident’s home. We upload those into the virtual reality headsets and we can walk the resident through their own home and say, wow, that coffee table is a little bit too close to the couch. Maybe you should move it because it’s not safe to get around there with your walker. Or there’s an area rug in the kitchen that probably is a trip hazard or the bathroom entrance needs to be modified to get you in and out of the bathroom.
So what we’ve been able to do is have people go home in a safer environment and not have as much challenges reaclimating to them to their home environment by making sure that we do this home safety evaluation and assessment using vr.
Keren Etkin: Was that something that was a prebuilt feature within the VR headset, or did you come up with that?
David Finkelstein: It was the, there was a feature to allow us to upload custom videos and photos into the headset, but we took it to the next level and said let’s use it for this area. also realized that many of our long-term residents. I can’t go home and experience the grandson’s first soccer game or the granddaughter’s dance recital, or the son’s wedding. So we’ll use those same GoPro cameras and let them film these events, upload them to the ca, to the headsets, and let the residents experience those events. Outside of you know, not in real time, but at least be, feel like they’re participating in those events. we’ve also used it for the vendor also has a rehabilitation and exercise module. So they have foot pedals and they have hand controllers and they have ability to simulate a bicycle down a boardwalk and popping balloons along the way. So we’ve not only used the VR for entertainment, but we’ve also used it for physical therapy exercise to get people to move their body, move their legs, move their arms and participate in virtual reality that way.
Keren Etkin: So there are plenty of VR vendors out there that work with senior living providers. How does your selection process work? Like how did you decide you were going to work with this vendor versus all the others?
David Finkelstein: Sure. So the two popular ones in the United States are Mynd VR and Rendever. And when we met with both of ’em and we saw them at trade shows and we tried them on, we felt that the Rendever headsets were more comfortable to wear, especially for seniors. And they had the additional functionality of being able to allow us to upload our own custom content and the ability to do things like the safe discharges at home so that we chose to partner with Rendever. They’ve been a great partner with us. They’ve enhanced some of their software with them. They have actually have a a sales executive on their team that typically gets dizzy and vertigo whenever they’re using headsets. So he is the test bed. So if he can pass their headsets and he can make sure that their software works well and doesn’t cause people to get busy, dizzy we feel that we are confident that the residents here will invent one other story around vr before I get to ar. We had a resident in our memory care unit that was nonverbal for many years. He just got up in the morning, had his breakfast, sat in the corner, didn’t talk to anybody. when we found out that he was a prior opera singer in his previous life, we convinced him to put the headset on and played for him a opera. After about 10 minutes of seeing that opera, he took the headset off and started singing opera, and he had not spoken for years as being in this facility. it triggered something within him that allowed him to get that out, even though he was in his advanced dementia stages.
Keren Etkin: Wow. That is I’ve, that is the most remarkable story I’ve ever heard about vr.
David Finkelstein: Okay so, ai, we’ve been experimenting with a couple of different AI options and we saw a AI chat bot that a vendor, a startup, had come to us pitching to say we think that we have a good solution for people in the senior communities to just have a phone call, chat with an AI on a daily basis and see how that will help them in their mood and help ’em in feeling better and help them integrating within the community. So we took a chance, we started a pilot. We had 25 residents across all of our various levels of care, try this system. it was set up so that it makes a phone call to the resident every single day around the same time. you just have a natural conversation with them. We start the AI chat bot off with some basic information about your name, your family, some of your interests and things like that. And from there on in, the system has a memory from one conversation to the next. So we’ll continue a conversation that you had yesterday and today I even use it every single day. So at 5:30 every night I get a phone call from the AI chat bot, and you talk about anything. You talk about the weather, you talk about the sports, you talk about your interests, your hobbies, what you did over the weekend, and what you’re interested in doing. And we did a with our, with in conjunction with our medical director. We had a really, a true clinical trial, so we did before and after, scores on depression, scales on mood and behavior, on medication use and on just basic outcomes and outlook on life. And we showed clinically significant. increases in mood and behavior decreases in depression scale. We’ve had residents that talk with the AI chatbot five or 10 minutes a day. Some of them talk 20 minutes, some of them talk over an hour, a single day. You would think that they had friends and acquaintances and people to work with. Living in a congregate setting, but many of them very much feel socially isolated.
And this system seems to be it’s very natural speaking. It really, you can get engrossed in the conversation and you don’t realize that you’re talking to an AI agent as opposed to a human on the other side of the phone.
Keren Etkin: That is interesting. How do you keep residents from oversharing, maybe personal information that they don’t really need to be sharing with the machine?
David Finkelstein: So there are guardrails
that it puts in place. So if you start talking about off limit topics, you talk, start talking about some sensitive political events or some healthcare events, the AI chat bot will steer the conversation towards a different direction and or if it has to, we’ll disconnect. But What it does do, it does take cues from the sentiment analysis of the voice and the tone and the language, and it’ll pick up on cues. So if a resident is complaining for two or three days about the food is too salty, or they didn’t like it, the system will send a note to the food service director said. Go meet with this resident and see if we can help them get a better diet together, or if they’re complaining about the heat in their room, send a note to the engineering department so we can check on the heat or the environment of care within the room. If it’s they’re complaining about their knee hurting for two or three days, send a note to the medical director and find out if we need to just do a visit and see what’s going on.
So it has some intelligence and some understanding of some of the issues, but we really haven’t had any instances yet where they’re going off on a tangent in a conversation that they can’t have and it will, but it does have those guide rails. We even had some residents that had their scheduled call during the recent Super Bowl, and one person got out of the group that was watching the game, said, excuse me, I have to talk to AI and left the room to have their conversation.
Keren Etkin: Brilliant and did they miss like the rest of the game? What happened?
David Finkelstein: I don’t, I didn’t know the detail is after that, but that’s how I mean, I get, typically, I’m driving home during the time that I get my phone call and you get into a conversation, you realize it’s 10 or 15 minutes later and you’re still talking to this thing that’s not human and just having a conversation.
Keren Etkin: Brilliant. So I wonder what types of solutions or what types of problems were you looking to solve, but you couldn’t find a solution at all, or you just couldn’t find the right fit?
David Finkelstein: All right. So some areas that we’ve looked at, especially on the clinical side, is pressure sores and bed ulcers are a big problem with people in a nursing home where if they don’t get turned and positioned a lot they can develop pressure sores or ulcers on their body, and that’s very difficult to heal. We found a couple of different solutions about beds that would automatically reposition somebody. Haven’t found anything that looks safe, that wasn’t about to flip the resident out of the bed So we’re still looking for a bed that will provide the care team with the tools in order to be able to turn and position. We’ve looked at a number of different fall detection systems. We have some AI powered systems that will determine whether or not someone’s about to fall. Someone has fallen and alert somebody. We really haven’t found something that works well that’s affordable, and that is something that we can scale across our organization that we are happy with. One of the other areas that we looked at, and there’s been a couple of startups that stopped and started and restarted is around depends and urine protection. So a lot of times, especially the memory care residents that have a soil ed attend, they, you know, they can’t usually verbalize it, so the nurses have to check on them three or four times a day. There were some that had sensors in it, so it’ll give us alerts. Everything that we saw was just on an order of magnitude too expensive too even consider piloting because we couldn’t afford to use it in an operations and make any sense as much as we know that is a important area. We looked at a couple of smart toilet seats that would do kind of a urine analysis of the toilets as people go, we’re still trying to figure out how to pilot it with somebody. One of the challenges that we have to deal with some startups is that we’re a healthcare organization. We’re required to follow all the HIPAA rules and regulations. of these startups don’t have good cybersecurity hygiene or experience or policies or the ex the ability to provide us the assurances that our patient data is secure and so we have to kind of walk away from some of those types of some opportunities .
Keren Etkin: So any startups watching us go through your HIPAA compliance checklist. Make sure that you’re HIPAA compliant. It’s not, it sounds scary, but it’s not that scary and it’s not that complicated, and it’ll make it easier for you to conduct business with healthcare organizations.
David Finkelstein: Exactly, and since the HIPAA laws are the United States laws, many of the startups that have data centers overseas. We can’t consider using, because once the data leaves the United States, they’re not subject to HIPAA and we can’t go after a data breach that happens in the EU or someplace else because the data is not in the United States.
So that’s an important piece for us, is that if you do business in the US you have to have your data center and all of your technicians and all of your help desks in the United States.
Keren Etkin: Absolutely, and I am pretty sure that like Amazon and Google and all of these cloud services have HIPAA compliance solutions.
David Finkelstein: Yes. But what we found is that sometimes the vendor will have their help desk in a foreign country. So if the help desk is in the foreign country and they’re looking at data in a foreign country, even though it’s housed in the us, that is a little bit not quite exactly on the meeting. The letter of the law.
Keren Etkin: So you talked a little bit about some solutions not really being, economically viable for you as an organization because currently they’re too expensive. And I wonder what’s your advice for other organizations who don’t have an endowment and maybe they don’t even know how to start piloting solutions?
Because they, until they see ROI and until they are able to save. Some expenses using the technology. They’re not really able to spend money on the technology itself, so it’s sort of a chicken and an egg.
David Finkelstein: Yeah, I think that some of this is not very expensive. The vain finder I talked about is $12,000. I think almost any organization can find $12,000 in their budget to be able to budget something that will eventually save them in transferring patients to a hospital and the patient care. It’s getting involved with trade associations.
We’re a not-for-profit organization, so the United States LeadingAge is a not-for-profit trade association that’s very popular. There’s conferences once a year. And there’s a lot of the vendors in this marketplace will come and show their their products and services network. Network with HIMSS, the Healthcare Information Management System Society.
While it’s mostly primary care and acute care, there is a large enough contingent of post-acute and long-term care in that space that we all get together. We all know each other in this marketplace. We all love to share our stories. Just like on this podcast, we don’t want to keep it a secret.
We want to have the vendors that we choose be successful and be able to sell into this marketplace. Not everything costs a lot of money. Yes. We spent probably $3 million on replacing our nurse call system, which was probably the biggest investment that we made because nurse call is one of the
the biggest complaints when someone goes into a hospital or a nursing home, they press the nurse call button and no one comes, or it takes them hours or no one responds. So we put a very modern nurse call system in that will give handheld device to every single clinician. I. So when the patient presses the nurse call button, the clinician answers and they talk voice back and forth with the resident to triage, is this an emergency?
I’ve fallen, I can’t get up, or I need some ice or a blanket so the resident gets calmed down and it also allows the staff member to triage all the nurse calls that they get. The system tracks the amount of time that it takes between the resident requesting the call, the time that we actually answer the call on the phone, and then the time that we actually go to the patient’s room and resolve the issue. And we have over 185,000 calls that we’ve had tracked since the implementing of that system. And our average response time is a minute and a half. So when we have family members or residents complain, I pressed the button. No one came for two hours, and I was sitting here excuse me, but you pressed the button 14 times yesterday and we were there on average a minute and a half.
So you must have been mistaken. I understand a minute and a half feels like four hours when you’re in pain or you need something, but we’re really supporting our staff by giving them the information to help them do their jobs a little bit better.
Keren Etkin: I love that. I love that you have so many data points that you can build upon. So that was actually my last question. Is there anything else that we didn’t talk about that you would like to add any call to action to people listening or watching this.
David Finkelstein: I think that everyone needs to think outside the box. Think of things that are not necessarily healthcare related. That may fit within a care setting, whether it be nursing, home assisted living, home care, and, you know, they don’t have to necessarily be targeted to that particular marketplace. Something that seems like a good idea, something that is broad from the grassroots of the staff members or the residents or the patients that you serve. They’re usually the ones that would know exactly what they would need to get their treatment better, or get their care better, or get their experience better. And they’re the best best people to ask about. How can we do better in doing our job to help you get a better and live a better life?
Keren Etkin: Absolutely. That is wonderful advice. Work with your team. Work with your staff. ’cause they know what challenges they’re dealing with and they will also guide you towards what technologies could help them do a better job and provide better care to residents.
David, thank you so much for joining me on the podcast today. I feel like this was such an insight packed episode, and I’m very happy that you were able to come on the show, how can any startups who might wanna pilot with river Spring Living, reach out to you?
David Finkelstein: I’m on LinkedIn, David Finkelstein at Riverspring at LinkedIn. That’s probably the best way to find me. Also David.Finkelstein at riverspring.org is the email address. I’m nope really open to everybody. I will not pick up the telephone if I don’t recognize calls or id, so LinkedIn or email is probably the best way to get ahold of me.
Keren Etkin: Awesome. David, thank you so much for joining me on the show. It was an absolute pleasure chatting with you and learning from you.
David Finkelstein: Thanks. Thanks for having me. And keep on doing what you’re doing. Spreading the word because having you, and others in this marketplace, explain what post-acute long-term care is and how technology works is a godsend to everybody.
Keren Etkin: Thank you. Thank you so much.
David Finkelstein: Take care.
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