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Caregivers and Home Care with Seth Sternberg, CEO and Co-founder at Honor Technology

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Manage episode 352867203 series 2980364
İçerik GE HealthCare Command Center and Jeff Terry @ GE HealthCare Command Center tarafından sağlanmıştır. Bölümler, grafikler ve podcast açıklamaları dahil tüm podcast içeriği doğrudan GE HealthCare Command Center and Jeff Terry @ GE HealthCare Command Center veya podcast platform ortağı tarafından yüklenir ve sağlanır. Birinin telif hakkıyla korunan çalışmanızı izniniz olmadan kullandığını düşünüyorsanız burada https://tr.player.fm/legal özetlenen süreci takip edebilirsiniz.

(00:16) Helping older adults age in place
(01:07) Understand care professionals perspective
(01:42) How Honor provides non-medical home care
(02:13) Partnering with hospital-at-home providers
(03:32) Technology to aggregate care pros and provide transparency
(05:28) Improving care pro performance
(07:59) Extensive data on care pros and clients in the home
(10:36) Integrating with health systems' EMRs
(12:48) Machine learning to reduce care pro call-offs
(15:09) Respect and schedule flexibility
(18:39) Improving predictive algorithms
(20:26) Lower turnover and higher satisfaction
(21:13) Care pro satisfaction is feeling respected
(22:01) Schedule flexibility
(23:07) Honor's mission to honor care pros

Seth Sternberg and his team at Honor are committed to changing the aging experience. For them, that starts with caring for the people who provide care for older adults – the Care Pros. Listen as Seth explains how they use technology to respect and support home health caregivers. It’s a strategy that works -- Honor is consistently retaining employees for years in an industry with notoriously high turnover rates.

Jeff:
Hello and welcome. I'm Jeff Terry. Delighted to be joined today by Seth Sternberg, who's the CEO and co-founder of Honor Technology. Hi, Seth.
Seth Sternberg:
Hey, how are you doing, Jeff?
Jeff:
Wonderful. Great to be with you. I think a great place to open is where we were sort of just hit chatting offline, which is something that we have in common is between our firms and I think ourselves personally is a real appreciation and commitment to serving caregivers, which I think is what motivates you. So please talk about your mission as a company and caregivers in general.
Seth Sternberg:
Yeah, so we started a company to literally try to transform the way society cares for older adults. And as we unpacked that and kind of narrow that down, we said, "Well, let's really focus in on helping mom and dad stay in their homes as they age." It's too broad to transform everything up front. You have to pick a smaller slice to try to work on first.
And so then we looked at all the various ways to potentially do that. And we found this space called Home Care where what Bureau of Labor Statistic calls personal care aids, goes into homes of older adults and helps them with things like getting out of bed or getting food or getting dressed. And these are called Activities of Daily Living or ADLs. And so the way this service is delivered, it's a huge industry, it's an 85 billion dollar industry, is these personal cares get hired by local agencies. It's super fragmented, and they go into the homes of the adults and help them kind of individually one-to-one.
And so what we did is we went and interviewed about 50 of these folks at the Starbucks in Sacramento, California, and then at another Starbucks in Phoenix, Arizona. And a couple of things came out from those conversations, but the most poignant one was this person who said, "Look, I'm called unskilled to my face, treated like crap by the families, by the agencies, but I'm a professional, and I want to be treated like one. And that's how I act. That's how I see myself." And so that's actually where the term Care Pro or care professional came from. We said, "Okay, if these truly are professionals and let's call these caregivers what they see themselves as and what they really are, which is professionals. Call them care professionals." And then we coin the term really quickly thereafter, care for the Care Pros. And we've really built the company on that notion. And what it is if we do a good job caring for the Care Pros and put them in a better place into their own lives, then they can in turn do a better job caring for our customers, the older adults and then often their children.
Jeff:
This is great. Can I just, because I'm thinking of many in our audience who this will be super interesting, but we'll use some of these terms a little differently. So I want to make sure that we're all tracking. So the focus of your firm is on Care Pros who are home nursing and home care providers who go into homes and do that ADL work which is a great and important form of care giver. And so the focus of Honor, initially at least, is to serve those Care Pros, that type of caregiver. Is that right?
Seth Sternberg:
Well I think that our customers think that our mission is to care for older adults, and very specifically let's provide them better home care than they've been able to get elsewhere because we can actually go to scale. We have a whole bunch of technology that allows us to aggregate up a thousand Care Pros in a market. And so therefore we're much more likely to have the right Care Pro for your mom. And then your Care Pro's going to have much better, more modern tools so that they do a better job following a very clear care plan. You, the son or daughter who's helping take care of your mom, are going to get a lot of transparency in our app that's going to show you who's going to mom's home, what are the notes that they took, how the wellness check go, what did they did do while they were there? So I think our clients think of us as home care and they think of us as, hey, I'm hiring Honor or Home Instead, which we also own, in order to care for my mom or dad. But the background reality of how to deliver that service really, really well is actually the focus in your efforts. We as a firm focus in our efforts on caring for the Care Pros, our employees.
Jeff:
Which translates into better care for the end customer, for mom and dad at home. But that's really the focus of your approach that-
Seth Sternberg:
Exactly.
Jeff:
That makes great sense, thank you.
Seth Sternberg:
Yeah, and we build a lot of really cool technology, and I'd say about 70% of the budget goes to features that are about affecting Care Pro performance or behavior or job type. And usually it's like how do we give the Care Pro an even better job that's even more perfect for either their desires or their skills so that they will then perform better? Because we're not only giving them the right tools to perform well, but we're also putting them in the right environment for them. So often people miss it. Look, professionals do well when they're in the job that they're naturally good at.
Jeff:
Even Michael Jordan wasn't a great baseball player, right?
Seth Sternberg:
Exactly. Yeah. It's the same thing for the Care Pros. So if we recognize, look, you're going to be the best in this kind of job, that's the kind of job therefore we should offer up to you, that means that they'll perform better. And there are lots of other pieces to it I could take you through, but it's a huge focus of ours.
Jeff:
That's great. Another question maybe you might want to comment on is another growing area is Hospital at Home, but that's different than the kind of in-home care at least that we're talking about so far. Talk about that, please.
Seth Sternberg:
Yeah, so we provide what people refer to as non-medical home care or ADL supports home care. So we're basically doing everything up to piercing the skin. So we're doing help people get out of bed, help people with bathing, toileting, lifting and transferring, up to late-stage dementia, light wound care. So we're doing kind of right up to the bloody edge of things that become healthcare services that are reimbursed by either commercial insurance or the government. But we're usually private pay.
And then the other big difference is we're usually in an average home for, call it, 20 to 30 hours a week. So when we're serving someone, we're serving them in a really, really deep way as opposed to Home Health or Hospice, which will tend to pop in for 30 or 45 minutes and pop out. They did the thing. They changed the IV, or...
And then you asked about Hospital at Home. So we actually have partnered with Hospital at Home companies, and the way that we've done that is when we have a customer who may benefit from Hospital at Home, we will give them a call and bring them in. And the reason we're doing that is we want to help that person stay at home. That's a big part of what we do is help people stay at home. We do not provide Hospital at Home ourselves, but we have relationships with so many clients. We're the largest network in the United States by multiple. Largest network in the world by a multiple. So we have so many clients that we see people who have clear medical needs, and then we can get in touch with those providers and bring them into our network.
Jeff:
That makes total sense. So are you then, because clearly you're a partner too, in many cases you would be the discharge disposition of an inpatient, whether it's Hospital at Home or in a typical acute environment. And so you must partner with all the name brand hospital systems, or many of them, to make those transitions easy.
Seth Sternberg:
So that's a big part. When you look at where our customers come from, a big part that they do come from is some kind of acute setting. It might be a hospital discharge, it might actually be ER diversion. It can be something subacute, it can be I've been in a nursing home or a rehab for X amount of time and now I'm discharging to home. I need help. So that is one of the places that customers come from.
Jeff:
Sure. Many sources I'm sure, but just much of our audience is of hospital-oriented. So just to make that connection. And the work that you're describing, and thank you for clarifying it and helpful to me for sure to get my arms around it, is some of the most compassionate and important. Everybody needs and we're all going to need at some point. To your point about caring for the people doing that vital work certainly resonates with me.
Seth Sternberg:
And I think also when you're in the healthcare system, you know how important all the other stuff is. You know how important it is that the discharge home goes smoothly. Was the DME there? Was the food there? Were the meds there? Did this person get discharged into an environment that's extraordinarily likely to create a bounce back or not?
And so a big part of what we focus on is just ensuring that people are in a really good situation in their home when they get home from whatever acute setting that they're in. But then we're caring for people for years as well. And so when we're caring for those people for years, we also kind of send people the other way. It's like, "Hey, they're at home but they need some kind of healthcare service, and so let's make sure that we line them up appropriately." So we kind of flow in and out of the healthcare ecosystem and we partner with it closely, but we don't provide it directly ourselves. And that's actually intentional.
Jeff:
And may I ask, it sounds like you've got a pretty sophisticated app that serves your Care Pros and probably also your customers.
Seth Sternberg:
Yeah.
Jeff:
May I ask, do you do integrations with the health systems EMR ever, or how does that work?
Seth Sternberg:
Yeah, so we've done some light stuff in the past. They used this protocol called HL7. Some of your audience, maybe you know what HL7 is. So we've done some really light integrations in the past where we've passed a [inaudible 00:10:12] HL7 files, but we haven't done a deep integration into someone's EMR. It's something that we could do, but to be blunt, the volume would have to be really high. And so it would have to be, to get us to do that kind of technology work, it would just have to be a lot of volume.
Jeff:
And it may in the end be certain target integrations. I'm thinking of our software, we'll make it visual to the care team. Is the DME ordered in time, and is it there yet? And maybe some of those very targeted messages might be worth it that we could find a way to make it really easy to do.
Seth Sternberg:
So there's this alternate concept, and this is a platform that we actually have built, which is giving people a dashboard where they can see kind of status of what is the care that someone's getting or what's a care plan or whatnot. And that's available right now to two different kind of actors in our ecosystem or in our network if you will. Both kind of agencies that we partner with and then also the families. So there's already kind of a really robust set of tools that enable people to be able to track the care and situation of our end recipient of care-
Jeff:
Perfect.
Seth Sternberg:
-should they appropriately need that information.
Jeff:
So we talked about some of the things you're doing and might do. If you don't mind sharing, what are some of your development priorities? Where are you taking this? Where is this concept going?
Seth Sternberg:
So the thing that's really interesting is, we probably see more in the home and record all of it. Our roots are very technology and then we got into this, hey let's care for our parents and quickly learned the care and healthcare ecosystem. And so with those roots we recognized early on, look, when we're in the home for, call it 30 hours a week, we know almost everything. We know what the refrigerator looks like. We know the state of the bathroom. We know what meds are being taken. We know what food is being eaten. We ask people every day, every time we see them, "What's your state of mind? Are you happy or sad? How many bowel movements have you had in the last 24 hours? How many meals have you had in the last 24 hours? Let's talk about your sleep." We call this a wellness check.
So with all of this data collection, there's very interesting things you can do to link that person that we're caring for into both the broader kind of retail and consumer ecosystem, and also more appropriately into the healthcare system. And both are areas that we're pretty focused on. So in the broader retail ecosystem, I start thinking about if you're 80 years old, and you are in a chair, and it's hard for you to get up and move around, it's actually really hard to use Amazon. Not because you can't use Amazon's app, but because it's hard to get the box that arrives at the front door. It's hard to use the box cutter to open the box. It's hard to distribute the contents.
Jeff:
Yeah.
Seth Sternberg:
We can make that so easy, because we know the milk is low. We know that light bulb burned out, and so let's take care of that automatically and ensure that our Care Pro when they're in the home knows, hey the box just arrived from whoever, Amazon or Walmart, and let's go ahead and replace that light bulb.
And at the same time we can know a lot about what someone's kind of current condition is. And like I said, if it's appropriate for them to then start to seek or go talk to their medical provider. So that's another really interesting area for us.
Almost all of the features that we build are based on this data and watching this data, and it's almost always machine learning that's doing the heavy lifting. So an example would be, let's talk about the workforce for a second. Anyone who's a provider of care, they have a workforce that's providing the care, and their workforce has some kind of performance statistics that they look at over time. One performance statistic a lot of people look at is call offs. It's how often does do my care providers call me and say, "Hey I'm not coming."
Jeff:
Not work as scheduled.
Seth Sternberg:
Yeah, exactly. Not work as scheduled. Exactly. So we zeroed in on that problem. This is just one example and we said, "Hey, we want to get the call off rate down." And what we first did is we showed the machine all the data associated that we collect: GPS track logs, and care plan track logs, and scroll data on the app and the phone, and seconds viewing a page, and ratings customers are giving Care Pros, and ratings Care Pros are giving customers, like everything.
Jeff:
That's great.
Seth Sternberg:
We said, "Here's all the data around when there is a call off. Here's all the data when there is not a call off. Can you, the machine, figure out the pattern. Can you tell me what are the relevant-"
Jeff:
What did you find?
Seth Sternberg:
So the biggest one by far is actually distance from where the Care Pro lives to the client. That's a really big deal. The second one, which is super interesting, is the Care Pro will often say, "Yes, I'll take this job that's not perfect along a lot of dimensions," because they need a new job reasonably quickly, but in their heads they're taking it temporarily. And so it's kind of like I really need work right now. This is not great. Not just because of distance, but maybe so we've done another ML work that looks at the hours and type of work Care Pros want to work. And it turns out that you can kind of say, "Hey, you are a generalist. You are a nine to five. You are an overnight. You are a backfill." When you do the ML work on how [inaudible 00:16:04].
Jeff:
Clustering those behavior. I bet. I believe that.
Seth Sternberg:
It's behavioral life circumstance. Those are the four big buckets that people end up falling into. So someone who's an overnight might take a nine to five during the day because they lost a customer, the customer passed away, or moved to a facility.
Jeff:
So by understanding that you were then able to try to make matches differently to reduce those likelihoods. Is that...
Seth Sternberg:
Exactly. And so what we started doing is saying, "You know what? Since we now know that you're probably choosing this customer not because they're really great for you, but because you probably need to fill in, we're going to actually direct you to a different kind of job that is designed for fill in."
So what we ended up doing is we designed an area in the app that was literally the fill-in section. So it's like, if you just lost a customer because they moved into a facility or passed away or whatever, go to this tab over here. And in fact you might be able to fill in with lots of different shifts where there's a call-off that we have to back fill, or a new customer we're just spinning up or whatnot, or a condition changed and you're more appropriate for that condition change. But then keep watching this one over here and in fact we'll send you the machine, we'll send you automated notifications when a new customer pops up who's really like a direct hit.
Jeff:
That Meets your profile. Yeah.
Seth Sternberg:
Yes, exactly. So...
Jeff:
That makes a ton of sense, and I can see how it's good for the Care Pro, it's good for the customer, it's good for the cost of the system, it's good for everybody.
Seth Sternberg:
Yes, exactly. Everybody wins.
Jeff:
Can I come back to something that you touched on that I think is super interesting too is what you described, and the kind of information that your team's routinely capture would be roughly equivalent to a lot of what is considered nursing documentation in an inpatient environment. There are several deterioration scores that predict future clinical trajectories, like the Rothman Index, that call it 10 years ago, got a lot better when they started incorporating turning nursing notes into structured data and incorporating that into algorithms as opposed to just vitals and signs and labs and so forth. And it seems to me then you probably already thought about this. So I guess how are you thinking about turning those? It seems like you're sitting on something that could be really useful.
Seth Sternberg:
So we have that data, and actually importantly, you just said something that's really interesting. You said turning the unstructured data into structured data. You could actually take that a step further and you could say, "What if we went to observe data versus reported data?" So if your technology is embedded deeply enough in the use of the system, the technology can capture a lot of the data, kind of [inaudible 00:18:52].
Jeff:
Absolutely. Yeah. By one way or another, by turning things into sensors, by using natural language processing, by going to check boxes, lots of ways. But in the end, the net of that has been the ability to incorporate into an algorithm a signal that 10 years ago couldn't be incorporated.
Seth Sternberg:
Exactly. It's like a much more reliable signal that you have.
Jeff:
And it turned out, and the reason I always remember those, because it turned out that nursing documentation, which is exactly analogous to the kind of things, those were a game changer in the accuracy of those algorithms.
Seth Sternberg:
Yep, yep. Exactly. So [inaudible 00:19:24].
Jeff:
Are you guys thinking about it? I assume you're considering ways to use your data.
Seth Sternberg:
Definitely an interesting area for us. I have nothing to talk about there.
Jeff:
Okay, fair enough. We'll look forward to reading about that from you.
Seth Sternberg:
We have a lot of that data, and you would think that we could process it in interesting ways.
Jeff:
Let me ask you one last thing then, which you kind of started with, we've alluded to a few times, but I'd love to hear the sort of other end of the rainbow, which is you've put a lot of work and thought into how do we make it easier for Care Pros to do this work and so forth. What's been the reaction, the feedback of Care Pros from sort of experiencing how you serve them?
Seth Sternberg:
So we literally operated about half the turn rate of the industry. That's probably the headline stat. And then when you do our satisfaction scores with Care Pros at various market by market. We operate in lots of markets and states throughout the country and then Western Europe. But when you do the satisfaction scores about 80, mid eighties are usually satisfied or better, which is really awesome for this workforce. So we're really happy about that. We just looked at this one cohort, it was interesting, we analyzed them. 76 Care Pros came in from this one cohort back in 2019, pre-pandemic. And 40 of them are still with us today. Three years later, through a pandemic, in an industry that has average 80% annual turn, and over half are still here. And that's amazing. So the statistics kind of speak for themselves.
Now the question's why? And we've talked about, let's deliver to the Care Pros a professional experience, blah blah blah. But we actually have done the statistical analysis on what truly makes a happy Care Pro. And it turns out that the number one thing they care about is what they call respect. And this is the number one statistical correlate with I'm happy and I'm satisfied. And what they call respect when you break it down is things like, did you pay me what you said you would pay me? Did you pay me on time? Did you put me into an environment where my skills are appropriate? Do you guilt trip me? That's a big one. Do you guilt trip me into working with customers that I don't actually want to work with? Come on Janet, can't you take this shift? I know it's Christmas Eve, but I did that favor for you. They hate that. So that is the number one statistical correlate.
And then the number two statistical correlate is hours availability. So if I have two customers, 20 hours each, and one of them moves to a facility next week, did I just lose 50% of my income? Or is your system large enough in design such that no, no I can actually backfill the majority or even more than what I was working so that I don't lose that income. That's a big one.
But then the other one is not presupposing that we know exactly which customers and exactly which time slots that Care Pro wants to work in. And it turns out you don't even want to ask the Care Pro directly when they work. The data, they tell you, I don't want to work on Saturdays. Very frequently you will find they will actually violate what they said same day, and rather you go to inferred data where you watch their behavior and then you see, oh okay, you would work on Saturdays if it's within this geographic band or within these times or whatever. So if you deliver a system to Care Pros that lets them work on their schedule as they want, that's also really huge. So those are the two kind of clear correlates with a happy Care Pro who retains.
Jeff:
Super interesting and clear. And I'm curious, is that emphasis on respect, is that part of why the name of the firm is Honor?
Seth Sternberg:
Yeah, so when we started the company, this is 2014, we hired a naming firm. There were so many names that they went through, and I just kept not liking any of them. And we had gotten to the point where my co-founders were like, "Seth, you're screwing the company up, because we don't know what to [inaudible 00:23:26] base at this point. You're slowing down coding, because we don't have a name." And so one night I literally pulled out a thesaurus and just started going through lots of word associations, and I saw honor and I was like in isolation that's pretty bold, but the whole point of the company is honor the Care Pros, and honor the clients, the older adults. It is actually what we're about. And we're trying to do that better than anyone has ever done it before. Honor felt appropriate. So then I went to the team and I was like, "Hey, let's mock up Honor." So we mocked it up and looked at it, and it felt really good, and that's where it came from.
Jeff:
Makes a lot of sense. And yeah, honoring caregivers, certainly something we can get behind. Congratulations to you and maybe we'll leave it there. Thanks for joining and chatting, Seth.
Seth Sternberg:
Awesome. Thanks for having me, Jeff.
Jeff:
You bet, man. Really enjoyed it. Thanks very much to our audience. Well, that will close the podcast.

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Artwork
iconPaylaş
 
Manage episode 352867203 series 2980364
İçerik GE HealthCare Command Center and Jeff Terry @ GE HealthCare Command Center tarafından sağlanmıştır. Bölümler, grafikler ve podcast açıklamaları dahil tüm podcast içeriği doğrudan GE HealthCare Command Center and Jeff Terry @ GE HealthCare Command Center veya podcast platform ortağı tarafından yüklenir ve sağlanır. Birinin telif hakkıyla korunan çalışmanızı izniniz olmadan kullandığını düşünüyorsanız burada https://tr.player.fm/legal özetlenen süreci takip edebilirsiniz.

(00:16) Helping older adults age in place
(01:07) Understand care professionals perspective
(01:42) How Honor provides non-medical home care
(02:13) Partnering with hospital-at-home providers
(03:32) Technology to aggregate care pros and provide transparency
(05:28) Improving care pro performance
(07:59) Extensive data on care pros and clients in the home
(10:36) Integrating with health systems' EMRs
(12:48) Machine learning to reduce care pro call-offs
(15:09) Respect and schedule flexibility
(18:39) Improving predictive algorithms
(20:26) Lower turnover and higher satisfaction
(21:13) Care pro satisfaction is feeling respected
(22:01) Schedule flexibility
(23:07) Honor's mission to honor care pros

Seth Sternberg and his team at Honor are committed to changing the aging experience. For them, that starts with caring for the people who provide care for older adults – the Care Pros. Listen as Seth explains how they use technology to respect and support home health caregivers. It’s a strategy that works -- Honor is consistently retaining employees for years in an industry with notoriously high turnover rates.

Jeff:
Hello and welcome. I'm Jeff Terry. Delighted to be joined today by Seth Sternberg, who's the CEO and co-founder of Honor Technology. Hi, Seth.
Seth Sternberg:
Hey, how are you doing, Jeff?
Jeff:
Wonderful. Great to be with you. I think a great place to open is where we were sort of just hit chatting offline, which is something that we have in common is between our firms and I think ourselves personally is a real appreciation and commitment to serving caregivers, which I think is what motivates you. So please talk about your mission as a company and caregivers in general.
Seth Sternberg:
Yeah, so we started a company to literally try to transform the way society cares for older adults. And as we unpacked that and kind of narrow that down, we said, "Well, let's really focus in on helping mom and dad stay in their homes as they age." It's too broad to transform everything up front. You have to pick a smaller slice to try to work on first.
And so then we looked at all the various ways to potentially do that. And we found this space called Home Care where what Bureau of Labor Statistic calls personal care aids, goes into homes of older adults and helps them with things like getting out of bed or getting food or getting dressed. And these are called Activities of Daily Living or ADLs. And so the way this service is delivered, it's a huge industry, it's an 85 billion dollar industry, is these personal cares get hired by local agencies. It's super fragmented, and they go into the homes of the adults and help them kind of individually one-to-one.
And so what we did is we went and interviewed about 50 of these folks at the Starbucks in Sacramento, California, and then at another Starbucks in Phoenix, Arizona. And a couple of things came out from those conversations, but the most poignant one was this person who said, "Look, I'm called unskilled to my face, treated like crap by the families, by the agencies, but I'm a professional, and I want to be treated like one. And that's how I act. That's how I see myself." And so that's actually where the term Care Pro or care professional came from. We said, "Okay, if these truly are professionals and let's call these caregivers what they see themselves as and what they really are, which is professionals. Call them care professionals." And then we coin the term really quickly thereafter, care for the Care Pros. And we've really built the company on that notion. And what it is if we do a good job caring for the Care Pros and put them in a better place into their own lives, then they can in turn do a better job caring for our customers, the older adults and then often their children.
Jeff:
This is great. Can I just, because I'm thinking of many in our audience who this will be super interesting, but we'll use some of these terms a little differently. So I want to make sure that we're all tracking. So the focus of your firm is on Care Pros who are home nursing and home care providers who go into homes and do that ADL work which is a great and important form of care giver. And so the focus of Honor, initially at least, is to serve those Care Pros, that type of caregiver. Is that right?
Seth Sternberg:
Well I think that our customers think that our mission is to care for older adults, and very specifically let's provide them better home care than they've been able to get elsewhere because we can actually go to scale. We have a whole bunch of technology that allows us to aggregate up a thousand Care Pros in a market. And so therefore we're much more likely to have the right Care Pro for your mom. And then your Care Pro's going to have much better, more modern tools so that they do a better job following a very clear care plan. You, the son or daughter who's helping take care of your mom, are going to get a lot of transparency in our app that's going to show you who's going to mom's home, what are the notes that they took, how the wellness check go, what did they did do while they were there? So I think our clients think of us as home care and they think of us as, hey, I'm hiring Honor or Home Instead, which we also own, in order to care for my mom or dad. But the background reality of how to deliver that service really, really well is actually the focus in your efforts. We as a firm focus in our efforts on caring for the Care Pros, our employees.
Jeff:
Which translates into better care for the end customer, for mom and dad at home. But that's really the focus of your approach that-
Seth Sternberg:
Exactly.
Jeff:
That makes great sense, thank you.
Seth Sternberg:
Yeah, and we build a lot of really cool technology, and I'd say about 70% of the budget goes to features that are about affecting Care Pro performance or behavior or job type. And usually it's like how do we give the Care Pro an even better job that's even more perfect for either their desires or their skills so that they will then perform better? Because we're not only giving them the right tools to perform well, but we're also putting them in the right environment for them. So often people miss it. Look, professionals do well when they're in the job that they're naturally good at.
Jeff:
Even Michael Jordan wasn't a great baseball player, right?
Seth Sternberg:
Exactly. Yeah. It's the same thing for the Care Pros. So if we recognize, look, you're going to be the best in this kind of job, that's the kind of job therefore we should offer up to you, that means that they'll perform better. And there are lots of other pieces to it I could take you through, but it's a huge focus of ours.
Jeff:
That's great. Another question maybe you might want to comment on is another growing area is Hospital at Home, but that's different than the kind of in-home care at least that we're talking about so far. Talk about that, please.
Seth Sternberg:
Yeah, so we provide what people refer to as non-medical home care or ADL supports home care. So we're basically doing everything up to piercing the skin. So we're doing help people get out of bed, help people with bathing, toileting, lifting and transferring, up to late-stage dementia, light wound care. So we're doing kind of right up to the bloody edge of things that become healthcare services that are reimbursed by either commercial insurance or the government. But we're usually private pay.
And then the other big difference is we're usually in an average home for, call it, 20 to 30 hours a week. So when we're serving someone, we're serving them in a really, really deep way as opposed to Home Health or Hospice, which will tend to pop in for 30 or 45 minutes and pop out. They did the thing. They changed the IV, or...
And then you asked about Hospital at Home. So we actually have partnered with Hospital at Home companies, and the way that we've done that is when we have a customer who may benefit from Hospital at Home, we will give them a call and bring them in. And the reason we're doing that is we want to help that person stay at home. That's a big part of what we do is help people stay at home. We do not provide Hospital at Home ourselves, but we have relationships with so many clients. We're the largest network in the United States by multiple. Largest network in the world by a multiple. So we have so many clients that we see people who have clear medical needs, and then we can get in touch with those providers and bring them into our network.
Jeff:
That makes total sense. So are you then, because clearly you're a partner too, in many cases you would be the discharge disposition of an inpatient, whether it's Hospital at Home or in a typical acute environment. And so you must partner with all the name brand hospital systems, or many of them, to make those transitions easy.
Seth Sternberg:
So that's a big part. When you look at where our customers come from, a big part that they do come from is some kind of acute setting. It might be a hospital discharge, it might actually be ER diversion. It can be something subacute, it can be I've been in a nursing home or a rehab for X amount of time and now I'm discharging to home. I need help. So that is one of the places that customers come from.
Jeff:
Sure. Many sources I'm sure, but just much of our audience is of hospital-oriented. So just to make that connection. And the work that you're describing, and thank you for clarifying it and helpful to me for sure to get my arms around it, is some of the most compassionate and important. Everybody needs and we're all going to need at some point. To your point about caring for the people doing that vital work certainly resonates with me.
Seth Sternberg:
And I think also when you're in the healthcare system, you know how important all the other stuff is. You know how important it is that the discharge home goes smoothly. Was the DME there? Was the food there? Were the meds there? Did this person get discharged into an environment that's extraordinarily likely to create a bounce back or not?
And so a big part of what we focus on is just ensuring that people are in a really good situation in their home when they get home from whatever acute setting that they're in. But then we're caring for people for years as well. And so when we're caring for those people for years, we also kind of send people the other way. It's like, "Hey, they're at home but they need some kind of healthcare service, and so let's make sure that we line them up appropriately." So we kind of flow in and out of the healthcare ecosystem and we partner with it closely, but we don't provide it directly ourselves. And that's actually intentional.
Jeff:
And may I ask, it sounds like you've got a pretty sophisticated app that serves your Care Pros and probably also your customers.
Seth Sternberg:
Yeah.
Jeff:
May I ask, do you do integrations with the health systems EMR ever, or how does that work?
Seth Sternberg:
Yeah, so we've done some light stuff in the past. They used this protocol called HL7. Some of your audience, maybe you know what HL7 is. So we've done some really light integrations in the past where we've passed a [inaudible 00:10:12] HL7 files, but we haven't done a deep integration into someone's EMR. It's something that we could do, but to be blunt, the volume would have to be really high. And so it would have to be, to get us to do that kind of technology work, it would just have to be a lot of volume.
Jeff:
And it may in the end be certain target integrations. I'm thinking of our software, we'll make it visual to the care team. Is the DME ordered in time, and is it there yet? And maybe some of those very targeted messages might be worth it that we could find a way to make it really easy to do.
Seth Sternberg:
So there's this alternate concept, and this is a platform that we actually have built, which is giving people a dashboard where they can see kind of status of what is the care that someone's getting or what's a care plan or whatnot. And that's available right now to two different kind of actors in our ecosystem or in our network if you will. Both kind of agencies that we partner with and then also the families. So there's already kind of a really robust set of tools that enable people to be able to track the care and situation of our end recipient of care-
Jeff:
Perfect.
Seth Sternberg:
-should they appropriately need that information.
Jeff:
So we talked about some of the things you're doing and might do. If you don't mind sharing, what are some of your development priorities? Where are you taking this? Where is this concept going?
Seth Sternberg:
So the thing that's really interesting is, we probably see more in the home and record all of it. Our roots are very technology and then we got into this, hey let's care for our parents and quickly learned the care and healthcare ecosystem. And so with those roots we recognized early on, look, when we're in the home for, call it 30 hours a week, we know almost everything. We know what the refrigerator looks like. We know the state of the bathroom. We know what meds are being taken. We know what food is being eaten. We ask people every day, every time we see them, "What's your state of mind? Are you happy or sad? How many bowel movements have you had in the last 24 hours? How many meals have you had in the last 24 hours? Let's talk about your sleep." We call this a wellness check.
So with all of this data collection, there's very interesting things you can do to link that person that we're caring for into both the broader kind of retail and consumer ecosystem, and also more appropriately into the healthcare system. And both are areas that we're pretty focused on. So in the broader retail ecosystem, I start thinking about if you're 80 years old, and you are in a chair, and it's hard for you to get up and move around, it's actually really hard to use Amazon. Not because you can't use Amazon's app, but because it's hard to get the box that arrives at the front door. It's hard to use the box cutter to open the box. It's hard to distribute the contents.
Jeff:
Yeah.
Seth Sternberg:
We can make that so easy, because we know the milk is low. We know that light bulb burned out, and so let's take care of that automatically and ensure that our Care Pro when they're in the home knows, hey the box just arrived from whoever, Amazon or Walmart, and let's go ahead and replace that light bulb.
And at the same time we can know a lot about what someone's kind of current condition is. And like I said, if it's appropriate for them to then start to seek or go talk to their medical provider. So that's another really interesting area for us.
Almost all of the features that we build are based on this data and watching this data, and it's almost always machine learning that's doing the heavy lifting. So an example would be, let's talk about the workforce for a second. Anyone who's a provider of care, they have a workforce that's providing the care, and their workforce has some kind of performance statistics that they look at over time. One performance statistic a lot of people look at is call offs. It's how often does do my care providers call me and say, "Hey I'm not coming."
Jeff:
Not work as scheduled.
Seth Sternberg:
Yeah, exactly. Not work as scheduled. Exactly. So we zeroed in on that problem. This is just one example and we said, "Hey, we want to get the call off rate down." And what we first did is we showed the machine all the data associated that we collect: GPS track logs, and care plan track logs, and scroll data on the app and the phone, and seconds viewing a page, and ratings customers are giving Care Pros, and ratings Care Pros are giving customers, like everything.
Jeff:
That's great.
Seth Sternberg:
We said, "Here's all the data around when there is a call off. Here's all the data when there is not a call off. Can you, the machine, figure out the pattern. Can you tell me what are the relevant-"
Jeff:
What did you find?
Seth Sternberg:
So the biggest one by far is actually distance from where the Care Pro lives to the client. That's a really big deal. The second one, which is super interesting, is the Care Pro will often say, "Yes, I'll take this job that's not perfect along a lot of dimensions," because they need a new job reasonably quickly, but in their heads they're taking it temporarily. And so it's kind of like I really need work right now. This is not great. Not just because of distance, but maybe so we've done another ML work that looks at the hours and type of work Care Pros want to work. And it turns out that you can kind of say, "Hey, you are a generalist. You are a nine to five. You are an overnight. You are a backfill." When you do the ML work on how [inaudible 00:16:04].
Jeff:
Clustering those behavior. I bet. I believe that.
Seth Sternberg:
It's behavioral life circumstance. Those are the four big buckets that people end up falling into. So someone who's an overnight might take a nine to five during the day because they lost a customer, the customer passed away, or moved to a facility.
Jeff:
So by understanding that you were then able to try to make matches differently to reduce those likelihoods. Is that...
Seth Sternberg:
Exactly. And so what we started doing is saying, "You know what? Since we now know that you're probably choosing this customer not because they're really great for you, but because you probably need to fill in, we're going to actually direct you to a different kind of job that is designed for fill in."
So what we ended up doing is we designed an area in the app that was literally the fill-in section. So it's like, if you just lost a customer because they moved into a facility or passed away or whatever, go to this tab over here. And in fact you might be able to fill in with lots of different shifts where there's a call-off that we have to back fill, or a new customer we're just spinning up or whatnot, or a condition changed and you're more appropriate for that condition change. But then keep watching this one over here and in fact we'll send you the machine, we'll send you automated notifications when a new customer pops up who's really like a direct hit.
Jeff:
That Meets your profile. Yeah.
Seth Sternberg:
Yes, exactly. So...
Jeff:
That makes a ton of sense, and I can see how it's good for the Care Pro, it's good for the customer, it's good for the cost of the system, it's good for everybody.
Seth Sternberg:
Yes, exactly. Everybody wins.
Jeff:
Can I come back to something that you touched on that I think is super interesting too is what you described, and the kind of information that your team's routinely capture would be roughly equivalent to a lot of what is considered nursing documentation in an inpatient environment. There are several deterioration scores that predict future clinical trajectories, like the Rothman Index, that call it 10 years ago, got a lot better when they started incorporating turning nursing notes into structured data and incorporating that into algorithms as opposed to just vitals and signs and labs and so forth. And it seems to me then you probably already thought about this. So I guess how are you thinking about turning those? It seems like you're sitting on something that could be really useful.
Seth Sternberg:
So we have that data, and actually importantly, you just said something that's really interesting. You said turning the unstructured data into structured data. You could actually take that a step further and you could say, "What if we went to observe data versus reported data?" So if your technology is embedded deeply enough in the use of the system, the technology can capture a lot of the data, kind of [inaudible 00:18:52].
Jeff:
Absolutely. Yeah. By one way or another, by turning things into sensors, by using natural language processing, by going to check boxes, lots of ways. But in the end, the net of that has been the ability to incorporate into an algorithm a signal that 10 years ago couldn't be incorporated.
Seth Sternberg:
Exactly. It's like a much more reliable signal that you have.
Jeff:
And it turned out, and the reason I always remember those, because it turned out that nursing documentation, which is exactly analogous to the kind of things, those were a game changer in the accuracy of those algorithms.
Seth Sternberg:
Yep, yep. Exactly. So [inaudible 00:19:24].
Jeff:
Are you guys thinking about it? I assume you're considering ways to use your data.
Seth Sternberg:
Definitely an interesting area for us. I have nothing to talk about there.
Jeff:
Okay, fair enough. We'll look forward to reading about that from you.
Seth Sternberg:
We have a lot of that data, and you would think that we could process it in interesting ways.
Jeff:
Let me ask you one last thing then, which you kind of started with, we've alluded to a few times, but I'd love to hear the sort of other end of the rainbow, which is you've put a lot of work and thought into how do we make it easier for Care Pros to do this work and so forth. What's been the reaction, the feedback of Care Pros from sort of experiencing how you serve them?
Seth Sternberg:
So we literally operated about half the turn rate of the industry. That's probably the headline stat. And then when you do our satisfaction scores with Care Pros at various market by market. We operate in lots of markets and states throughout the country and then Western Europe. But when you do the satisfaction scores about 80, mid eighties are usually satisfied or better, which is really awesome for this workforce. So we're really happy about that. We just looked at this one cohort, it was interesting, we analyzed them. 76 Care Pros came in from this one cohort back in 2019, pre-pandemic. And 40 of them are still with us today. Three years later, through a pandemic, in an industry that has average 80% annual turn, and over half are still here. And that's amazing. So the statistics kind of speak for themselves.
Now the question's why? And we've talked about, let's deliver to the Care Pros a professional experience, blah blah blah. But we actually have done the statistical analysis on what truly makes a happy Care Pro. And it turns out that the number one thing they care about is what they call respect. And this is the number one statistical correlate with I'm happy and I'm satisfied. And what they call respect when you break it down is things like, did you pay me what you said you would pay me? Did you pay me on time? Did you put me into an environment where my skills are appropriate? Do you guilt trip me? That's a big one. Do you guilt trip me into working with customers that I don't actually want to work with? Come on Janet, can't you take this shift? I know it's Christmas Eve, but I did that favor for you. They hate that. So that is the number one statistical correlate.
And then the number two statistical correlate is hours availability. So if I have two customers, 20 hours each, and one of them moves to a facility next week, did I just lose 50% of my income? Or is your system large enough in design such that no, no I can actually backfill the majority or even more than what I was working so that I don't lose that income. That's a big one.
But then the other one is not presupposing that we know exactly which customers and exactly which time slots that Care Pro wants to work in. And it turns out you don't even want to ask the Care Pro directly when they work. The data, they tell you, I don't want to work on Saturdays. Very frequently you will find they will actually violate what they said same day, and rather you go to inferred data where you watch their behavior and then you see, oh okay, you would work on Saturdays if it's within this geographic band or within these times or whatever. So if you deliver a system to Care Pros that lets them work on their schedule as they want, that's also really huge. So those are the two kind of clear correlates with a happy Care Pro who retains.
Jeff:
Super interesting and clear. And I'm curious, is that emphasis on respect, is that part of why the name of the firm is Honor?
Seth Sternberg:
Yeah, so when we started the company, this is 2014, we hired a naming firm. There were so many names that they went through, and I just kept not liking any of them. And we had gotten to the point where my co-founders were like, "Seth, you're screwing the company up, because we don't know what to [inaudible 00:23:26] base at this point. You're slowing down coding, because we don't have a name." And so one night I literally pulled out a thesaurus and just started going through lots of word associations, and I saw honor and I was like in isolation that's pretty bold, but the whole point of the company is honor the Care Pros, and honor the clients, the older adults. It is actually what we're about. And we're trying to do that better than anyone has ever done it before. Honor felt appropriate. So then I went to the team and I was like, "Hey, let's mock up Honor." So we mocked it up and looked at it, and it felt really good, and that's where it came from.
Jeff:
Makes a lot of sense. And yeah, honoring caregivers, certainly something we can get behind. Congratulations to you and maybe we'll leave it there. Thanks for joining and chatting, Seth.
Seth Sternberg:
Awesome. Thanks for having me, Jeff.
Jeff:
You bet, man. Really enjoyed it. Thanks very much to our audience. Well, that will close the podcast.

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