Outcomes Rocket_Victor Wang: this mp3 audio file was automatically transcribed by Sonix with the best speech-to-text algorithms. This transcript may contain errors.
Saul Marquez:
Hey everybody! Saul Marquez with the Outcomes Rocket, and we are here at the HLTH event in Las Vegas at the Venetian. I am so excited to host yet another amazing healthcare leader. His name is Victor Wang. You guys know him, he’s been on the podcast a couple of times already and he’s a founder and CEO of Care.Coach, a San Francisco Bay startup, scaling conversationally driven relationships and helping health insurers to drive clinical and cost outcomes while improving the member experience. They are funded by investors, including Startup Health and AARP, as well as US Congress and National Institutes of Health. Victor, it’s so great to see you again. Thanks for joining us.
Victor Wang:
Yeah, thanks for having me again, Saul.
Saul Marquez:
So, you know, it’s been a while and so I think it’s worth level setting. Help the listeners understand more about Care.Coach.
Victor Wang:
Yeah, so we coach people to improve self-care digitally. That’s why the dot is very important.
Saul Marquez:
Yeah.
Victor Wang:
So there’s a digital avatar that’s kind of in the home of the member and talking with them day to day, greeting them in the morning, doing evening prayers, reminiscing with people about the kids, actively listening as they complain about their kids not picking up their phone call. So we build this relationship and it’s on top of this relationship that we do the coaching, that’s why it’s so effective.
Saul Marquez:
That’s great, and so the digital avatar, I think it’s worth diving into that a little bit more. So it’s like a little robot, right?
Victor Wang:
It’s on a screen, so I guess I wouldn’t really call it a robot. It’s like a, on a tablet that we provide and it looks like a little dog or a cat because why not?
Saul Marquez:
Yeah, I think it’s a really cool-looking digital avatar. And so talk to us about how that relationship is formed and how your platform differs from other platforms in helping get engagement, you know, medication adherence, and so on.
Victor Wang:
Yeah, as far as I know, we’re still the only 24/7 digital relationship in the home that’s actually staffed 24/7 by real people around the world. So when I started the company back in 2012, the original goal was just to solve senior loneliness, and I realized that conversational AI wasn’t really there, and really you need real people to build real relationships with other real people. So we ended up hiring a bunch of people in the Philippines for English, Latin American countries for Spanish, very good culture fit for aging care. And I have like this great respect for older adults and just very supportive and caring culture, and we have them staff this little dog or cat avatar. And so we’re able to engage in all these conversations that really only real people can engage in. So we’re able to build trust and day-to-day relationships and conversations and build a nudge people to take better care of themselves, take their medications, do their PT exercises, and so on. Much better than getting a push notification or trying to follow your care plan for your seven chronic conditions all on your own.
Saul Marquez:
Yeah, Victor, I love that. And so your team, the team that’s staffing the robot. I keep calling it a robot.
Victor Wang:
It’s an avatar.
Saul Marquez:
It’s called an avatar, let’s call it an avatar. A screen with the little dog, it’s so cute. We’re going to put a link in the show notes so you guys could see what it looks like. But, so they’re having these conversations, they’re establishing a relationship. And how many lives are you guys working with now?
Victor Wang:
We’re in the thousands now. And you know, if you’re in the Bay Area talking about companies like Facebook or something like that, that doesn’t sound like a huge number, but historically we’ve focused on hyper-complex individuals. So, for example, we got started in health insurance through PACE, our program of all-inclusive care for the elderly. So if anybody has an older loved one, you should look into that, it’s a really amazing program. They take people who are older and low income, so Medicare and Medicaid funding pooled together and an average pace participant has 7.8 chronic conditions and is skilled nursing eligible. So we focus on hyper complexity, so even though like a couple of thousand people, it can account for a lot of healthcare costs.
Saul Marquez:
Oh, totally!
Victor Wang:
That’s like $70,000 a year is pretty typical in PACE.
Saul Marquez:
Yeah, that’s huge. And the numbers are something like 80% of the spend comes from 5% of the sickest. And so if you’re focused on those people, the ROI to the system, let alone the value to the person receiving the care is huge. No, I’m glad you went there, you know, so we’ve been talking a lot about tech-quity, equity in healthcare. And so this, this product and service seems like a really great example of that.
Victor Wang:
Yeah, I find it really rewarding to work with the payers because, you know, we do sell direct to consumers. If somebody like needs this for their mom or dad or something like that and just hit us up, we definitely got Care.Coach, but for the most part, we go through the health plan and we’re able to help people that don’t have a son or a daughter Googling solutions for them. And even if they did, like, maybe their family wouldn’t be able to afford privately paying for a solution like ours. So it’s really rewarding to be able to reach people that they’re actually on their own, literally in their life, and we’re there for them and our avatar becomes their friend. And those people would be unreachable if we didn’t work through the payer.
Saul Marquez:
Totally, yeah, and you mentioned loneliness, and I want to get into outcomes in a second. So, you know, we’ve been sharing a lot about, hey, you know, we’re tackling a lot of problems in healthcare. Oftentimes, they are symptoms of the root cause, and loneliness seems to be one of those root causes. So talk to us about why you decided to focus there.
Victor Wang:
Well, you know, I was at MIT doing telepresence operations research, and they put me on a clinical trial about how fatigue affects astronauts’ performance, controlling the robot arm in the space station. So I had to do a bunch of background reading on clinical trials and things like that, and I came across a paper about how loneliness is a big problem for the space program. And then a pang of irony hit me, sitting in this lab working on telepresence and teleoperation, and loneliness is a big problem for these astronauts up in space. And I realized that here on Earth my grandmother in Taiwan has been living by herself, and, you know, this loneliness kind of, we could see how it affected her motivation to recover after a fall, for example. And it was just like, oh, I think I can probably apply this concept of teleoperation and telepresence to solve a really big problem for millions of people here on Earth.
Saul Marquez:
Amazing, that sounds so cool. So let’s talk about outcomes. Any new outcomes to report?
Victor Wang:
Yeah, so we’ve, you know, since a long time back we’ve been publishing research about how we reduce loneliness. For example, Stanford has a paper in JMIR about how we’ve reduced loneliness by three times more than a daily visit from a nursing student to socialize. That reduces loneliness, and our avatar at the bedside reduces loneliness three times more than that. And then we’ve gone on with our health insurers to kind of drive more close to the dollar-type outcomes. And at this point, we’re able to show, for example, with one of our customers $400 PMPM cost savings, so per member per month cost reduction of $400, and this is on a somewhat risk elevated population. We use machine learning to predict who in the plan would cost the most in a way that we could coach and prevent. So this is in a population that averages $1700 to $1800 per member, per month medical costs. We’re able to save $400 off of that.
Saul Marquez:
Well, the numbers speak for themselves. I think it’s a solution worth exploring for anybody looking at care for the elderly, Medicare Advantage type of play here.
Victor Wang:
Right, exactly.
Saul Marquez:
So what else is new in the payer insurer space?
Victor Wang:
Yeah, so Medicare Advantage is, a lot of interesting stuff going on ….
Saul Marquez:
A lot of innovation.
Victor Wang:
Yeah, yeah, and there’s also a lot of pressure. So what happened recently is, you may know that in Medicare Advantage there’s these things called star ratings that are very, very important, almost like stars for like a Yelp score for a restaurant. And the way it works in Medicare Advantage is if you have five stars, the government actually incentivizes or kind of like nudges people to go to your plan, which means if you’re not five stars, the government nudges people to leave your plan and go to your competitor’s plan. And things were kind of lax because of COVID, but now they’re kind of stringently evaluating all the plans now. So what’s happening is member experience is becoming very, very important. And, you know, there’s a survey that goes out and it asks the members like, how would you rate your health insurer on a scale of 1 to 10? How would you rate your healthcare on a scale of 1 to 10? And so this is what we’re able to influence actually through our services as we build this conversational relationship and trust day to day that would otherwise be very difficult for a health insurer to develop. You know, like people normally have a much tighter relationship with their healthcare provider or their doctor, and really nothing beats the relationship with the avatar.
Saul Marquez:
Yeah, no, that’s great, you know, and this is a common theme, patient experience, patient experience, patient experience. And Medicare Advantage is no different, in fact, it sounds like it’s even more stringent and more important for plans to consider ways to engage patients, get beyond that episodic care type of model, and continuously kind of follow them through the journey, create trust.
Victor Wang:
Yeah, our NPS score, last we surveyed was plus 81 with a margin of error of 4.
Saul Marquez:
So that’s pretty good.
Victor Wang:
Well, statistically, significantly, world-class, according to Bain.
Saul Marquez:
So that, again, the numbers speak for themselves. So how about on the technology side of things? Anything new on that side?
Victor Wang:
Yeah, so what we really want to do, especially, you know, there’s 30 plus million Medicare Advantage members these days, and we want to help a lot of people. It’s our mission these days at Care.Coach to improve the health and well-being of millions of people by 2027. So in order to do that, you know, this would be a lot of people we’d have to hire in the Philippines or Latin American countries to staff the avatar. And so what we’re doing is there’s very exciting technologies that has only become available in the last couple of years, and you see it in the news around like generative art. So you like, ask for a photo or a painting and the eye produces it, artists are getting worried for their jobs. It’s kind of all the rage in social media because it’s very easy to consume, you see a funny painting or an interesting painting and share it, but that foundational technology is extremely powerful for other purposes as well. So we’re using it for conversation now, and what happens is we have over a million conversations per year through our avatars these days. And it turns out that that data, all of these recorded conversations are very important to fine-tune this foundational technology to be able to do, to be able to conduct these types of empathic, intelligent conversations with people. So we have a new product that we’re building that’s going to launch soon called Care.Coach Fera, which is our conversational AI that’s generative and based on all of our unique training data. So you’ll probably hear about it more early next year.
Saul Marquez:
And so you’re taking all of these conversations and now you’re going to apply a layer of analytics intelligence to provide insights, is that what I’m hearing you say?
Victor Wang:
We already do that to predict who should get our avatar or our video visits product. And then what happens is, so far, like historically, we focused on, say, the top 20% that account for 80% of healthcare costs. But then if you’re a big Medicare Advantage plan, you need to affect or engage or build trust with your total population. So it’s not just about clinical improvement or cost savings in this hyper-complex population, you need to address everybody so that when these surveys go out, you have a tighter relationship with your population. So Fera is our autonomous or AI-driven much, much cheaper solution to building these conversationally driven relationships with the 80% of the population that actually don’t cost that much, but you still want to build trust and a great experience with them.
Saul Marquez:
That’s great. Well, great use of tech to help some of the patients out there with the greatest need. Victor, love what you’re up to. What call-out would you leave our listeners with today as they consider ways that they could improve their outcomes and do better for their patients?
Victor Wang:
Want to listen to them, I guess.
Saul Marquez:
That’s a good one.
Victor Wang:
We’ll make a lot of assumptions, but, yeah.
Saul Marquez:
I love that, yeah, and a good way to listen is through conversation. So, you know, it’s funny, we were having a conversation with a couple of other guests during the meeting and they talked about the importance of the feedback loop and pipeline businesses versus platform businesses, and the difference being on a platform business, you listen and you iterate.
Victor Wang:
Oh, well, Saul, we’re building a platform here at Care.Coach, so.
Saul Marquez:
So folks, check them out. We’ll leave the links for ways to get in touch with Victor and his team and the show notes. Victor, thank you so much for being with us today.
Victor Wang:
Yeah, thank you, Saul.
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