Data vs Chronic Conditions with Glen Tullman and Jennifer Schneider (Livongo Health) | Disrupt SF (Day 1)
3:10AM Sep 6, 2018
So we're going to hear now about how using data diagnostics and community to reframe treatment for chronic conditions like diabetes, we can actually have a real effect in the world. And to discuss this will be john Sheba from TechCrunch with Glen tullman and Jennifer Schneider from livongo health. Big round of applause. Come on, everybody likes.
Thank you all for sticking around for the afternoon panel. I am john Schieber and we have a wonderful session this afternoon where we're going to talk about some of the ways in which data diagnostics and community are involved in the treatment of chronic diseases as my consent earlier to help me out with this conversation. We have Glen tullman, Chief Executive Officer Officer of livongo health and Dr. Jenny Schneider, who is livongo Chief Medical Officer, thank you so much for being here. Appreciate it. So walk us through the livongo platform and how you're using this combination of data,
big data diagnostics and community to to treat what is initially diabetes. Right. That's the first element on the roadmap. Mm
hmm. Well, let
me let me start now. I asked Dr. Schneider to comment on it. But livongo is about empowering people with chronic conditions to live better and healthier lives. And the way we go about doing that is we want to make it easier for people to live better to live healthier. And so how do you do that? Well, you eliminate the hassles and you give them less, not more to do. So livongo starts with a connected glucose monitor. So that's a glue commoners. So if you have diabetes, where we're starting, you prick your finger to take a blood sample. And traditionally that was unconnected. So you would get a readout of what your blood sugar was. But then you didn't know what to do with it. And, you know, you had no way to kind of share that with other people, or get real time feedback. So the first innovation was a cellular glue commenter, which meant that you are always connected, and that information could be sent to the cloud, it could be analyzed and a lot of data science, and then you could get real time insights about what to do could also be shared with a community of other people, people who surround you, you know, friends, parents, sons, and daughters of elderly people, and the like, who could provide real time care. And last but not least, that information can be shared with physicians. So that's the general platform that we started with. And then we innovated from there. And Jenny, would you like to, I would
just add that we today we have three products and market we have livongo for diabetes, livongo for hypertension, and livongo for diabetes prevention? does
it all work off the same hardware platform? So it's the same like is it the only hardware devices the good commoner though, right? Or you, you can use that for everything or no. So
three different order to
measure blood pressure, for example, right commenter today would not be able to measure blood pressure. But the principles that Glenn has described those three principles of easy data collection, data analytics with nudges back, and then human services when somebody needs them are consistent across the three products. And so there are three discrete hardware products are selling for each of the different elements,
as you look at how to expand the business, what are some of the steps that you can take to sort of move beyond just the livongo platform? Are there ways to incorporate the services or data aspect of things into into other companies platform? Well, I
think that when we look at it, we look at if you if you think about someone who has diabetes, let's say type two diabetes, about 70% of those people also have hypertension, many of those people are struggling with weight issues, they may be having depression issues in the light. And so first and foremost, as a company principle, we look at the whole person and we say, what do we have to do to make it easier for the whole person to stay healthy, and, and we're starting with the person as opposed to as opposed to some outside third party who's going to fix it for them, we want to give them information that allows them to be healthier. So that's the first step Second, you drive that off of a single app, one place to go, whether it be one coach or the like, and then you use different connected devices. And you know, one innovation is just today a TechCrunch, we announced a relationship with the abbot Lieb re CGM or continuous glucose monitor. So rather having to prick your finger continuously, you could now put a patch on and you could actually get readings anytime you want that information. And that information would be shared up to the cloud. And then those nudges that Dr. Schneider referred to would be given back to you. So So I think we're continuously trying to innovate, to say, how can we make it easier for people to do less and still stay healthy and
it that's not a competing product or it's not going to Canada cannibalize the business that you have with your existing one kilometer why not so
our our business it's not only about hardware, our businesses an end to end solution to allow an empower people with chronic conditions to live better lives. And that includes a piece of the hardware, it includes really the data the analytics around personalizing the data, we get back to affect behavior change, and then the services arm as well. And so from a philosophy standpoint, the any, any device where we can easily collect data, that's great, that's great for the end user, for the member for the person with diabetes or hypertension. It's really the taking of that data and making it personalized that drives the behavior change. And that's where we spend a lot of our time and does that then extend into other types of devices as the sort of diagnostic tools on on smartphones or other smart watches. As those get more robust, you'll be able to sort of slide in and integrate with those platforms, as well as that the idea that's the idea. So the idea is today, if anything we can do to make data capture easy for a person with a chronic condition, whether it be a connected inhaler, a scale, oh, trout Activity Tracker, where someone doesn't have to Bluetooth Connect, download their data, anything we can do allows us to create an experience to take care of what Glenn described as the whole person. Now,
a lot of the the the sort of symptoms that your ailments that you're treating right now are sort of interconnected. Right, you mentioned that that died. Beatty's is sort of one of the connectors between hypertension and some of these other issues. Is there is there a way for you to move beyond the the the diabetes market and the ancillary conditions around it into other forms of chronic conditions or chronic illnesses? Is that on the roadmap?
Well, I think that is on the roadmap. And that's what Dr. Schneider talked about. So again, we see it as one continuum of someone staying healthy. So whether it's their diabetes, whether it's a weight management issue, whether it's depression, and you can see that someone might be depressed if they had diabetes, and hypertension, and every day they woke up, and they felt bad, that would, that would be depressing. So we can understand that. So again, the more that we can get those signals back to us, whatever the methodology is, it could be a connected scale, or what have you, then we can use that information, process it in the cloud, develop insights, and then share that back with so
what would be the next stop on the hardware roadmap for y'all if you are going to think about where how that extends beyond just the abbot partnership that you Yes,
so there's a lot of you think about in the industry today, a lot of hardware devices are manufactured in a way that's not maybe user friendly. So I think, you know, the idea around Bluetooth enablement is a step forward. But we all know that that doesn't work. So where we have been very successful in the glue commoner is through cellular enablement, right. So you don't have to actually configure it, you don't have to link it, it just happens, we automatically transmit the data. So we believe there's a trend in that market. There's a lot of other devices, tracking devices in other chronic conditions that are also moving to similar type of functionality. And with
those then be products that you would manufacturer yourself. I mean, like so much of hardware now is kind of commodities. So when you think about the ways in which you could expand even your own business, beyond the beyond the, the computer hardware and the other devices that you've you've developed for these other elements, what, what's next I my, I don't want to push too hard. But I'm going to push
I don't think it's pushing we we are happy to talk to just like our relationship with habit, we're happy to talk to anyone who has information to give us to allow us to, again, give the right nudges, make it easier for people to stay healthy. So that doesn't, we don't care where that information comes from. And we surely don't want to, and nor do we think of ourselves as in the device business. But that said, unfortunately, there aren't a lot of easy to use connected devices today for true clinical conditions. But so we've actually been forced to produce our own today. All right. And
and talk to me a little bit about the security element of all this because I would assume that there's an incredible amount of of concern around privacy and patient security that would go into transmitting this information over cellular and and the types of systems that you you have in place. How do you think about security? Okay,
well, I think security is look, we are using the highest standards for security, just like everyone in the industry, and we believe that people individuals ought to be in charge of their own information. So from that standpoint, I think we're doing everything we can to put the health consumer in charge of their information and protect that information. We do that across the board.
And because it's 2018, I'd be remiss if I didn't mention blockchain or crypto at least cryptocurrency at least once in a conversation. Is that something I mean, it really is sort of a foregone conclusion has to be done. But do y'all think about that as as an element of any sort of security suite or any sort of data stack that y'all might want to develop? Or is it is it sort of reinventing the wheel needlessly,
I think that Jenny is letting me handle these. I'm not really the technologist. But I think that, you know, from our standpoint, our technical people could talk about blockchain. But right now, it's not core to our offering. We think in the future. It may be, but we'll see.
All right. I'm just a bit of a housekeeping note. And I'm sorry, I didn't do this at the beginning of the session. My my Twitter is open. If anyone in the audience wants to I'd like to make this as interactive as possible. So if anyone in the audience has questions for my esteemed panelists, feel free to tweet at me. It's at J. Schieber, j. s. h. e. B as in boy, er, it will also keep the trolls that are mad about a post I wrote about the Justice Department off my feet well, so I won't get yelled at. Um. Which would be great. So again, that's Jay Schieber on Twitter. And I'm happy to field any questions and pose them to my panelists. But now I'm going to get back to questioning you. So, um, How many of y'all in the room actually, our health care or health tech entrepreneurs? Let's show of hands. So there are a fair few of y'all. Um, what advice would you give to companies or entrepreneurs that are starting up in healthcare right now in the health tech or medical device space. So
I'll start. So I think one of the items that we made an early bet on and that has been key to our success as a company has been to bet on the individual person, rather than on the health care ecosystem. First and foremost, does not mean ignore the healthcare ecosystem, it does mean if you want to improve health, allowing the individual person and really focusing and designing a product for the person with the condition is fundamental, I can give you some examples in the diabetes space, these people have often spent time saying, if I can only design something to get all the data to the doctor, I will make diabetes better. So I am a doc and I have type one. So I'm both patient and doctor well, and without it out the information that my endocrinologist sees when I spend time with him. And he's an amazing doctor two times a year for 20 minutes does not impact how my overall control is, is really the ability to drive the data back to me, and make those nudges and recommendations. So particularly for chronic conditions. And so designing a system to make sure my endocrinologist gets data does not impact my outcome. designing a system that allows me to see the data in an effective way to allow me to make behavioral changes to adjust along the way is highly impactful
when you think about this tension between sort of designing for the individual and designing for for a population, there's been a lot of talk around population health and using data diagnostics as as tools to sort of inform a broader and more automated healthcare environment as, as sort of constraints continued to, to build or pressures continue to build on the existing healthcare community. How do y'all think about that? And, and where do you position yourselves in within that debate,
I think it's, I think it's a little tricky. The Right now we are understand how valuable physicians and in particular endocrinologist are in the for people with diabetes. And let's start with diabetes. And yet there aren't enough for every person in the country to visit them on a regular basis. So we have to treat valuable resources is very valuable resources. And that means when people don't need to see their endocrinologist or their physician, we should make sure they get treatment in the appropriate environment, which may be home or wherever they are. So we think of using technology is to provide real time treatment for people with diabetes when and where they need it, and to personalize their treatment for them. So so I think that's really the future, the difference in the future that we're going to see, it's not about saying to someone go and see your physician more, it's about making sure that physicians are being appropriately paid, and saying the right patient at the right time, and keeping everyone else out of the physician's office. And as Dr. Dr. Schneider mentioned, if you saw your physicians five hours a year face to face, which is more than all but 1% of the people in the United States do and a lot less across the world, that would mean that 99.9% of the time you're on your own to manage your condition. So we know that people are going to have to learn to manage their own conditions. And it's a little bit of a turnaround, because we see the futures saying to people who have chronic conditions, we're going to give you the tools, but you have to learn to manage yourself. And that's really the future of healthcare. And yet, if you look at every other industry, what we found in every other industry is people want to self manage, if we give them the tools to do it, and they actually like it better. So
Dr. Where do you see the holes in the in the healthcare stack? Right now, if you were if you were an entrepreneur was starting a company right now? Yeah, what sort of what sort of spaces would you drive into? Or what sorts of things would you be looking for, as are identifying as opportunities?
And I do feel like I'm an entrepreneur. So it's a perfect question. And I feel like we're starting something being
fair. And so I I liked her where you were going with the question around population health, right? Because in the 70s, population health was what's the three things that you should advise for a population with very small slices, so cohort by disease, let's say hypertension, all people with hypertension are exactly the same, what are those three things that those people should do to improve overall health The world is really and scaling now in a way that we don't need general recommendations for large swaths of people. We have the ability with the data collection and the AI that's being deployed and other industries to bring that into health care, and really do micro level kind of recommend Asians and that's very different than, you know, the way the healthcare ecosystem is structured today. And so I think the healthcare ecosystem will reinvent itself, you need to starting to see more TV tele health visits electronic and you're doing personalization at Mass, right, because we can get in, collect data faster. But
one of the things that's been really interesting to me and, and I mean, fairness is a terrible example of this. But the, the push towards a more a more continuous diagnostics, right, where you are able as these these these tools, advanced to monitor your own your own health, eventually getting to the point, I hope where you can actually get sort of a casual blood test done, if you're paranoid like me, and are worried about having every disease under the sun, because I'm neurotic, then then that would be great. Like, I would be very happy with that. But there's a tension that I see and maybe I'm wrong about this between the notions that you can parse the harsh parts population health to find that sort of narrow sliver
of a treatment group versus like actually identifying individual treatments for for a single person am I am I misunderstanding what you're saying there? I could be
in fact, why don't we put a pin in that and I will just consider that me rambling and let's move on to another thing which is the i think i think though it's worth it's worth addressing and that is we believe that you can give someone individual recommendations and you know, cater to a set of one and yet still manage a population and that's the value of the technology and the reality is well Thera nose may have been make believe we have people who every day are getting real time blood samples right and real time information so whether they're standing on one of our scales that's connected from Verna cellular perspective, when they are using a blood pressure cuff that's connected or whether they're using a any kind of technology that's sending us real time information. They send it to the cloud, we're giving them real time information that relates to them. And yet, we're doing that at scale. And that's really the trick. You've never been able to do that before that at scale. And that's what we're able to do. So that's where the technology comes in. It's not technology for technology's sake. And I think in Silicon Valley, and a lot of cases, we invented the technology. And we said, how should we use it, right? Instead of saying, What's the problem, and we feel like, if our members are talking about the technology, we've actually failed, they should just say, this works magically, right now, just give you one example, somebody has a very high or dangerously low blood pressure, and they get a call within 60 seconds from one of our certified diabetes educators, 24 hours a day, seven days a week, 365 days a year anyway, in the world, and we say, Are you okay? How can you help? And people say things like, well, you call that the perfect time or That's unbelievable. I was just having low blood sugar reading. Of course, we know that because we have screens that light up that say that, but for them, it's magical. And they say that's exactly when I needed the call. Compare that to programs from large payers where they call people randomly and say, where your health coach, we're here to help. How can we help you we know you have hypertension, or we know you have diabetes? And in that case, people say, Why are you calling me why you interrupting my day? Why are you bothering me. And so that's the kind of population health management that doesn't work. But But this targeted and of one Technology Management actually does work. Speaking of large payers, our players coming into the healthcare space right now, I'd be remiss if I didn't mention Amazon and Berkshire Hathaway and the work that they're doing with I forget which bank right now, but one of them, um, how do you see yourselves fitting into the universe or the the sort of treatment paradigm or ideas that
that these folks are trying to craft around population now.
So I think that that Amazon and Berkshire Hathaway are two examples. And JPMorgan Chase, the other one, and the three of those organizations have fundamentally said, we don't think the existing system is working to take great care of our people, or to help us better manage costs. And so we're gonna have to do it ourselves. And the reality is, when that announcement was made, it wasn't like they had a grand plan. And they said, We don't have a grand plan. But we know somebody has to do something. And frankly, it has to be us, because no one else is doing it. So. So I think from that perspective, we see ourselves as fitting right into that. And it's no coincidence that Amazon and most the tech companies, and about half of the Fortune 100 are all customers of livongo today for hypertension, or weight management or diabetes. And the reason is, they're actually stepping outside of the existing system and saying, we have to try something different, because what we have isn't working. And we know that that all of those conditions are in fact becoming the most expensive part of healthcare today, when you
think about there's a massive market in the United States for for your services. But the it is a global problem, right, it doesn't just end at the US border, how do you think about internationalization? And and are there any any particular hurdles that that are specific to places like Germany, where the where, where the regulatory regime may be a little bit more stricter on privacy and security, then, yeah,
so there's a great opportunity worldwide for those of us that are empowering people with chronic conditions. And we won't stop just within the United States. And so we do think about those other markets, there are certainly differences. And I think through kind of the top list of hurdles, if you will, or opportunities, they include things such as regulatory clearance for devices, as we start to think Glenn had talked about, we're willing to take in data from anywhere, right? So started to figure out how can we work within those countries, those environments where there's data ingested, that's already been clear been cleared. The second is that a lot of what we're doing is around behavioral change is deeply understanding the person, it's not just the health part. It's not just the blood pressure, it's not just the weight, it's understanding what is the motivation. And so to do that, that requires deep cultural understanding different foods, different forms of communication, not just language, but how you say it within a specific language. So it takes some more work to really nail that there's a lot that we're learning along the way to allow us and enable us to be able to do that. So we're able to, at the front start to cluster people, you look like person in a year ago, these things seem to work to change your behavior to do B, or C, or D. And so we're learning a lot in that process. And there's some translation components as well,
let me just add something because Dr. Schneider and part runs our data sciences group. And, and I believe that we're not far and probably if you look at our spending today are spent on software development is probably not too far different from our stand on data science. And that's because given the amount of data, we have now, the largest real time database of diabetes information in the world, for example, that information holds the key to how different people react and respond to different kinds of nudges, to different kinds of treatments and the light. So when we think about this, you know, I went to a major self insured employer recently, and I had a list of 126 people. And I said, these people have a 92%
chance of being hospitalized or probability of being hospitalized in the next 30 days, if we don't intervene. Why? Because we could tell from the information we had that they were either using their insulin wrong, or they were not eating enough for, there were some major issue that was causing them dramatic highs and lows that would cause them to have seizures. So that ability to predict what's going to happen and then prescribe certain actions. And it's not always meds, it could be a diet, it could be changing work and stress. It could be different kinds of exercise regimens. So predict what's going to happen, prescribe some kind of action and then prevent what would have happened is really, we think the future of healthcare and I think with that, then it's a good place to end it. I obviously there's there's incredible potential for persistent diagnostics to transform the health care system at a human scale while working at the the internet scale as well. And thank you so much for this hallucinating sort of vision window
into that vision of the future. Thank you. Thank y'all for paying attention.