Blending data and coaching can be the key to sustainable behavior change.
In this episode of Bite the Orange, Ravi Komatireddy, Founder and CEO of Daytona Health, discusses combining precision medicine with behavior change through coaching in digital health. He emphasizes the need for more than just data from wearable devices to drive meaningful behavior change and address chronic lifestyle-related diseases. He created Daytona Health, an integrated platform that guides people toward better lifestyle decisions, as he believes coaching is the missing piece in digital health, helping individuals build self-efficacy and sustain long-term behavior change. He and Manny discuss the business’ scalability, with plans to train an AI system to enhance engagement and deliver persuasive messaging, and its pricing, aiming to make the program accessible to a broader population while emphasizing the commitment and psychological impact of financial investment in driving results.
Tune in to learn about Daytona Health’s mission to make the most out of precision medicine and behavioral science!
FULL EPISODE
BTO_Ravi Komatireddy: Audio automatically transcribed by Sonix
BTO_Ravi Komatireddy: this mp3 audio file was automatically transcribed by Sonix with the best speech-to-text algorithms. This transcript may contain errors.
Emmanuel Fombu:
Welcome to Bite the Orange. Through our conversations, we create a roadmap for the future of health with the most impactful leaders in the space. This is your host, Dr. Manny Fombu. Let's make the future of healthcare a reality together.
Emmanuel Fombu:
Good morning, good afternoon, good evening, ladies and gentlemen. Welcome to another episode of Bite the Orange. And today, we have another special guest who also has a background as a clinician and has a fantastic company that he's running, and I'm sure we'll all learn from this today. So with that being said, welcome to the show, Doctor Ravi Komatireddy.
Ravi Komatireddy:
Thank you very much for having me on to let me share the vision here.
Emmanuel Fombu:
So welcome to the show. So I believe that your company is called Daytona Health. But before we get into that piece, for those that don't know Ravi, so tell us about yourself.
Ravi Komatireddy:
Yeah, that's right. So I'm an internal medicine-trained physician. I'm a kind of a redneck from the Midwest, originally went to undergrad in med school out there, did some work on the East Coast, also did my initial training on the East Coast, and then came to finish medical training on the West Coast at UCSD. In addition to kind of clinical practice, and after some time spent being an attending, I was one of the first digital health fellows with Eric Topol over at Scripps Research under the SAT essay grant. So this is a time in digital health's evolution that was very early, and I happened to be lucky enough to be selected for that fellowship, but also be in a community in San Diego that was a burgeoning place for technology and health and life sciences. So as you know, we have Qualcomm, and we have Scripps, and we have UCSD, and we have a lots of people who are interested in both the intersection of technology medicine and was able to partake and be right in the center of that Venn diagram very early. So that's my background there, and then went off to co-found and become chief medical officer of two other digital health startups, very early one called Luminata and another one called Reflection Health, so in the virtual physical therapy space and in the big data AI space.
Emmanuel Fombu:
Which is quite impressive for the background you have, Ravi, and for those that don't know, Allscripts is the place to go for all digital analytics and everything related. Myself, when I worked in clinical research, designing these wearables studies, Allscripts is where we went for guidance and support in interpreting our data, and, of course, Eric Topol is a legend in the field. And so it's an honor to speak to you, Ravi, and it's great to hear that piece of your background.
Ravi Komatireddy:
This is funny because it's one of those things you look back in your life, and when you're in it, you're like, I don't know where this is going or if this is going to be useful, and you just have faith, and you think we're going to make something cool here. And it was, just happened to be a great team of people, and that team is all now doing great things in digital health and in healthcare. So it was, I'm just lucky to be a part of it.
Emmanuel Fombu:
Definitely, I can't disagree with you anymore on that. I don't think there's more a place more respected than Scripps and the people that came out of that whole environment. I think you guys are the forefathers and leaders in this world of digital health. So anyone listening, we have a great partner and colleague, and guest on the show today. So with that being said, your current company is called Daytona. So how'd you come up with that name?
Ravi Komatireddy:
I wish I could tell you there were some very complicated reason why I came up with the name. Honestly, it sounds cool, and like the Ferrari, I like the watch and the beach and the race. But yeah, that's literally how I came up with the name, wasn't anything more complicated than that. Yeah, so Daytona, so I've been working on Daytona, the Midas of these ideas always are years before the actual company starts. And if you've been in startups long enough, you know that things are spinning around in people's heads and founders' heads for years based on their experience. The idea of creating a precision medicine combined with kind of a precision behavior change company started in 2014. We were trying to design a trial with wearables, and I remember writing this trial and including something around coaching in the middle of it. It was me and Dr. Evan Muse, another, right, cardiologist who came out of AllScripts as one of the other digital health fellows, and Evan and I were thinking about, we were worried. Our concern was, clearly these wearables are giving people access to incredible amounts of data and insight onto their bodies that wasn't available before, in a very cheap price, and that connected to your smartphone and so on and so forth, things that we're used to now. I was just concerned that the data alone wouldn't be enough to change behavior. And if you're in the medical field and if you're a person who's struggled to be on a health journey, I think we can all agree that behavior change is the holy grail of healthcare, and I believe it's the missing piece to digital health in general. So back in 2014, when we were thinking about this, I included some consultations in the trial protocol with health coaches. I don't even know what a health coach really was or what they did, but I knew they were important. I knew there was someone who had to take the data and help people apply it in a way that was persuasive and motivating. And I was thinking, That's what's gonna make the difference. We got laughed at with that trial, and literally no one believed that it would work, nor did we believe that it was going to be useful. Even though, even ten years ago, there was good data on coaching that was emerging out of the literature saying, Hey, this behavior change stuff is possible. It just takes the right team, the right tools, and the techniques. So I put that trial, filed it away in the mental library, and said there will be a time when I'm able to work on this, and that time was years later. So other things got in the way, other startups, other responsibilities, clinical practice, doing some work abroad, and everything like that, and then, I finally was able to return to this around 2018, 2019, and then thought, okay, by that time, remember now digital health tools are becoming more ubiquitous. The freaking Apple store has blood pressure cuffs. Have you ever told me that was going to happen 10, 15 years ago? I would have laughed at you. But everyone now is getting used to the idea of supercomputers in their pocket. The digital health movement is not a fringe movement now. It is actually pervasive in consumer health, and other health systems are all trying to figure out how to adopt it, but the same problem exists. It doesn't feel like the data itself is moving people's behaviors. And when it comes down to the diseases that we all care about, the ones that are most pervasive in our societies, cardiometabolic health, like we treat them as a cluster, right? Heart disease, stroke, diabetes, insulin resistance in general, hyperlipidemia, hypertension, these are diseases of lifestyle. If you look at the 2015 Lancet Global Burden of Disease Report, you'll see that 70% of these diseases, including some of these solid tumors, are related directly to the choices people make in sleep, exercise, nutrition, their mindset, how they manage stress and these social determinants who you hang out with, your relationships and things like that. Every year that goes by, Manny, there are more and more studies basically forming the foundation of what I just said. So we know this to be true, both scientifically, but also if you just ask a person off the street, you intuitively know it's true. So when I tell people your sleep and exercise and nutrition makes a big difference to whether you get disease or not, they're like, they look at me like I'm an idiot. They're like, Yeah, obviously. Why don't you know that? You're, are you a doctor? That's the kind of response all of us are probably used to. Everyone knows this. We're on the verge of a revolution, but just doesn't seem like these devices themselves and the data is moving people, except for a small percentage of people, they do get motivated by that. So to me, coaching was the answer. So this idea of trying to encapsulate and apply the science of behavior change into a structured program so that people could access it virtually using the right tools, the right team of people, which includes not just doctors, but also allied health professionals, that we need to pay more attention to dietitians, personal trainers, life coaches, executive coaches, health coaches, and using data from wearables and the other digital health tools and precision diagnostics to guide that journey. The thesis is, with Daytona, if we get to know you well enough, can we know exactly what behavior change techniques work on you so that we have the emotional levers to pull to help nudge, steer, and guide you toward better decisions in your lifestyle over the course of months to years? And does that make a difference in healthspan? And that's what Daytona is really about, healthspan, trying to avoid or prevent or even reverse some of these chronic diseases, and helping people live longer, but better. That's really what everyone wants from their healthcare system. Our healthcare system really isn't set up to do that. It's really great at cardiothoracic surgery. It's really great, it's stents. It's great at an incredible number of things which we should be proud of. But if we take an honest accounting of what we're not so good at, it's this part. And when think about it, it's like we need something like Daytona because when you think about the number of minutes in a year, it's like, what, 525,000 some-odd minutes. Like health is not happening in those minutes that you're in front of your doctor in the clinic. It's happening at all those other minutes where you spend 99% of your time at home and at work. It's when you wake up and decide what to eat. It's should I take that five-minute walk in the afternoon? Do I have time for that 30-minute cardio in zone two later this evening? All those choices that you're making, that's where you need to help people, so Daytona is that. So we're a consumer health platform that does precision medicine, but precision coaching, and that's super personalized, integrated, everything is in one platform in one place, all tools, techniques, and people, and it's, we take a very functional root-cause approach. So when people ask me, do I treat diabetes or do I treat hypertension, I just say yes, because we do the lifestyle changes that are evidence-based to treat all of it, and we've seen some amazing transformation. So, the good news of all this is behavior change is very possible, very doable. It just takes structure.
Emmanuel Fombu:
Which is quite incredible. I think everything you're saying, Ravi, is something that I strongly believe in, and I advocate for, right? I believe that today's healthcare, I wouldn't even call it healthcare, I think sick care, what you're saying is let's go from sick care to the business of healthcare. And if you are sick to the point where you need a stent, right, or you need some kind of procedure or surgical procedure, yes, that's what health systems are for, hospitals are for. But in between that period of time, let's improve your quality of life, right? Let's bring, like ... I think there's a piece where the doctor who's seeing ... patients are seeing now, whatever it's called, right? And the idea of having medicine outside of the four walls of the hospital, like coming to that patient and being fully engaged. With that being said, for myself in general, I'll tell you that I tried to get myself to go to the gym sometimes, right? But there's certain things that I know myself pretty well, some things that would push me to go on certain days or some things that would not push me because I'm unique, right, for me. So tell me, what kind of data do you go ahead collecting? So if I'm a consumer, I want to use your product. What do I need to provide to you that understand?
Ravi Komatireddy:
It's a very good question. So we do a little differently than what you may have heard before. So I'll talk about two sides of the coin. The first side is the precision medicine piece. So think about the diagnostics that would give us the higher resolution view, a very fine-grained photograph, if you will, of your physiology, your level of insulin resistance. We're planning on giving all of our new members this year a CGM for the first 30 days. We find it very useful psychologically, even those who are not diabetic, to give them an idea of how their food is triggering their glucose, insulin, kinetics, things like that. So we have a much finer view, we get a little bit more labs that would come in a typical panel. So again, give us help us calculate that risk of disease and those things better. Honestly, this side of the equation here is pretty standard and easy. It's not that complicated. We do, these are like tests and things that are available today that just give us that better view. For example, we also do a Dexa on people. It gives us an idea of subcutaneous versus visceral fat that wouldn't be available through skin ... testing and stuff like that. When you get done with these diagnostics, you have an idea of what your cardiometabolic risk is and where you stand and your current level of fitness and what you're eating, and how you're currently sleeping, and we use wearables to help measure some of those things as well. The second piece is much more interesting, and the first piece is interesting, and something that only could be done now when we were living in a society full of these devices and readily available technologies, and it's exciting, but the second piece is much more exciting. So now it's like we know what you should be doing and what your starting point is. How do we get people to actually do it? Like how do we get people to execute? That takes some very interesting types of data. The first type of data we get, we really have to figure out what people's whys are, the underlying motivating reasons for why they want to see behavior change or a difference in their health. So someone will typically start with something like, I'm going to lose weight, and we just go way deeper, and we go, why do you want to lose weight? And then the next question will be, you know, we'll use like the Toyota Five Whys as a starting point, and they'll say, well, no, there's a wedding coming up in three months, and I really want to look good in a dress for that. And we'll say, Who are you trying to impress in the dress? Like, why is it so important for you to impress? Anyway, this line of questioning, we continue that until we figure out what these base-level motivations are for people, and they're very unique and different for everybody. So when you say personalized, everyone's why is very different. And it depends on their background, on their goals, who they are in life, who they surround themselves with, and things like that. We actually take the time to find all those out. That's a really important piece. Once we find the why, now we have a pin that we can put in their motivation profile or a few pins to say these are really emotionally important. The second is we have to find out kind of their social circle and their environment. We send our coaches out to do a site visit with each of our new members, they actually spend two days with them. We want to see where you work, we want to see how you work, and we want to see where you live. We need to see what's in the fridge, what's in the pantry. If you're living with somebody, if you're married, we want to talk to your spouse. We need to see what kind of pets you have. When you see how you handle stress. We need to immerse ourselves in the science of you. What is it like to be you for 1 or 2 days? This site visit is incredibly useful. It's a great bonding experience for our team and the member, and they really feel like someone's got their back, but it lets us in in a way that's difficult to replace with any technology or virtual, right? But it's an important piece. The third piece of data we get is we've internalized and categorized different behavioral profiles and techniques that work on different people. What we're trying to do with all the data we've got so far is to create a profile that says, Manny is the kind of person who is very competitive, but maybe less collaborative, maybe very open to experience entrepreneurial, but also highly conscientious, so on and so forth. So we get all these personality attributes, some of it comes from testing, and we create we start piecing together behavioral profiles. So we've got your physiology, your defense mechanisms, your environment, your social circle, your deep whys, and then, we start figuring out which one of these types of techniques work best for you. For example, we have two members right now. One is very into data. She needs to see data in proof, and that kind of have that voice of a, already to understand that when she's doing exercise a certain way, that's super grounded. We have another member, very similar profile in terms of her socioeconomic status and things like that, but just doesn't respond to the data, she don’t really care. She cares more about collaboration. She feels like she wants to be a member, that she's working together with one of our coaching team, and that's more important than data. Knowing that difference is what allows us to interact and coach you well in a way that you respond to. So what we end up having from this analysis is a very unique coaching profile for each person, and then we execute that profile. So it usually takes some hours of video and also very specific types of interactions over text. And we use the wearables and repeat labs to track and assess whether you're doing the actual behaviors or not or whether you're progressing or not. The behaviors we coach are in sleep, exercise, nutrition, the obvious three. We also coach mindfulness, but the overarching kind of umbrella over all of this is mindset. And this is the thing that's incredibly important for people to understand when they're on a health journey, and they want to lose weight, or they want to get healthier or want to reverse their diabetes or avoid the future surgeries. What separates people who sustain long term behavior change, Manny, from the people who kind of yo-yo, plateau, or kind of a very unbalanced view, is their mindset is different, and the good news is mindset is trainable, and it takes about eight months to a year to really do this. And by mindset, I mean your consistent collection of beliefs and attitudes toward the world in situations, right? That's really what we're talking about, mindset. So we've seen people really transform. People who started as, I'm that fat woman, I'm the fat girl, always have been, and I have to go work out, to I'm the kind of person who's working on myself and uses every day as an opportunity to improve. That subtle difference in how people think about adversity, difficult things, and how they build their resilience, really, all that is adding up to building self-efficacy. And once people have self-efficacy, that's when they can sustain those behavior changes. They're starting to count things as small wins. So it really doesn't matter where you start from. You can start from 350 pounds and be, have type two diabetes and hypertension, and dyslipidemia, or you could be an athlete who's already pretty self-actualized, but you want to get your mile times faster. We help people build self-efficacy and guide them through those specific behaviors, through text and video, and we coach them and nudge them to do those behaviors, and sometimes you need nudges, sometimes you need just encouragement. So it's a mix of these different interactions, but they're all building toward mindset, and they're all directed by a team, and they're all directed by data, and we get that data from wearables and the rest of the digital health ecosystem. So it's one integrated platform to help train, educate, steer, nudge people toward better behaviors. And it takes time, but it does work.
Emmanuel Fombu:
It is quite fascinating the way you describe it and your passion for this, and it makes a lot of sense. What I really like about it is, up to this point, you haven't mentioned the word AI or blockchain or ChatGPT or like all these fancy terms that people tend to use in that particular space when it comes to innovation. It has that kind of human element as I listen to you talk about this particular piece of it. And so, with that being said, this is like a very niche, concierge kind of feels like hand-holding and guidance along the way. And so, the question becomes how scalable is this model, right? How many coaches do you have, correct?
Ravi Komatireddy:
Yeah, that's right. So now I'm going to start talking about AI, and ChatGPT, it's the perfect segue.
Emmanuel Fombu:
So I think it's important to understand the core of what it is that you're doing, right? It's not just about that. It's about this, right? There's the science behind it. ... You talk to us about that piece.
Ravi Komatireddy:
Yeah, that's right. So it's not just getting data, showing people dashboards, and sending them reminders to go for a walk or to meditate for five minutes. That won't work. And we know that won't work, right? Let me put it this way. The core piece of the company and everything I've described to you, describes a very nice concierge service, which is expensive, and it works, and blah blah, blah. But our goal, we'll work backwards from the vision. Our vision, and you ... dumb or ambitious, or both, but is literally, I want every single 16-year-old with a smartphone to have access to a coaching team like this. They start making better decisions from a very young age. That's the goal. So this can't just be coaching and precision medicine for rich people. That's not our goal at the company. But we're starting like Tesla, we just have to start with the model first before we are able to scale it and build the technology to get the electric future for everybody. To do that, what we've done so far with kind of our current coaching is we're starting to train our system to create the best virtual coaching system in the world, and that's what we're doing through machine learning. So essentially, use the best team, pioneer the right techniques, figure out what tools you need in the data you need, and then transfer that knowledge into a system that can help. The system we're building, it's an AI approach, is the more accurate way to say it. So the AI approach we're taking is going to help in two ways. One is it's going to be able to help us given some initial data we have, having enough patients initial data, it's going to be able to say, oh, you know what, I'm going to predict that you are sensitive to this and this behavior change technique. You're this kind of person, and you're going to this kind of plan we're going to auto-generate because it's going to work for you because I've seen a thousand examples of you before, and it's like, we can shortcut to that much better. What that helps us with is engagement. When people feel like we've understood them, they stick with us longer. That's what really engagement is, right? And engagement is one of the big problems of healthcare that we're that everyone's trying to solve. So that's our way out of it now is to transfer. We're very engaging now with humans, but how do we get to machines and get that done just a little bit faster and accurately? The funny thing about this, that's already been done in so many other fields, if you think about Blockbuster video, Netflix, remember in Blockbuster video, there used to be a dude who stood there and gave you the movie recommendations of the week. You don't need that anymore. Like Netflix and Amazon Prime have enough data on what people watch and who's watching, they can do some fancy math and figure out what you need, right? Amazon makes me buy stuff I don't even think I need on the first page because it knows what to put there. So this science of recommending the right things based on data from both parties is already done. We're just bringing that to consumer health and to coaching in general and behavior change, so that's one piece. So can we just get that system to figure out what coaching techniques work? That's to make it more personalized. The second piece is delivering it. There, I can say with having worked on AI things before and being in this digital health field for a long time, nothing will replace that one-hour video visit. There's nothing that will replace that. It just won't because people are flawed, people are human, and humans have flaws and quirks, and those quirks become very dependable and predictable, and that's what we like about people. That's where the interaction is from. We form really great bonds with our members. However, there are some of these interactions that are very bot-able, and that we're doing is training the system to understand how to deploy persuasive messaging in a way that's effective in our coaches. So we're essentially making health behavior change computable. So every time one of our coaches sends a message now, and it's constructed by that coach or one of the coaching team, we have a lot of metadata on that message. So the user may see a text come through Slack or a messaging app or something, but on our end, it's like there's 2X, the data on the specific captivate or the specific behavior change ... The specific parameters on why that coach created that message. We believe that using that missing data set can help augment these larger language models to become virtual coaching assistants that can help deliver some of these things. Our goal is never to trick ... an article on this thing published on my medium, or, I can send you a link, it's how the Turing test is dead, right? We don't need to convince people or fool them that machines are humans. I don't think that's the right way going forward, I think it's better to present this as, Look, you're signing on to something here for $50 a month. It's going to be the world's best coaching team. Your team is going to be comprised of humans and machines, they both care about you, they're both looking out for you, they're going to steer you in the right direction. That's the future to me, that's the way we get this to everybody. And as you can already see, one of the problems with, already emerging after just having out for two months ChatGPT and Bing and all these other these models, accuracy, factual accuracy, and the right tone is important, and getting that wrong can completely ruin the relationship, as it has right now for Bing. I hope they fix that, but I hope by the time this gets published, they're fixing that. But so we know that these technologies are inevitable, this is what's inevitably going to happen is we're going to have to use augment human labor. It's a matter of, we believe we have the right data set to turn these language models into the right types of assistant coaches that have the right tone can nudge people correctly and effectively. So that's what we're making a bet on that.
Emmanuel Fombu:
So with that being said, I love the philosophy so far. And personally, I'm willing to sign up for this because I think that's what I need. ... myself, I would like to bring it back on the show, of course, to get some additional feedback. So how's the pricing of this? How do you price this?
Ravi Komatireddy:
Our goal pricing for this eventually, to get to like our scalable model is to get this below $200 a month. That's really what I want to do. Now, there's a question here which I always get asked, I'm going to preempt you if you were thinking about it. So we're a direct-to-consumer company, and one of the questions I get asked a lot is, will insurance cover this and things like that? And I always say, what we've noticed, behavior change is intrinsically difficult. There's an activation energy that you need to start it. People have to be in the right stage of change. You can't force them. I'll tell you, in my experience, we get paid for outcomes. You don't change, we'll give you your money back, like we guarantee results. It's very different from traditional healthcare in that way. Secondly, I've noticed when you get your credit card out, it gets real. And that like psychological switch of when you're paying with your credit card number, almost like flips a switch in people's minds that, oh, this is real. Like, I better really do this. That is, what we found is critical to sticking to a program like this. So I think this always has to be consumer. I think it's psychologically important. I think it's like this intrinsic signal to yourself that you care about yourself, and caring about yourself is the first part of being healthy, and that's the price we're aiming for. Right now, it's much more expensive. It's in the several thousands a year, and what we do is we give it up a year membership minimum. I think Jocko Willink said on his podcast, something about failure, right? Something that really resonated with me, he said, Success and failure are both very slow processes, and so is getting healthy. If you've been insulin resistant, eating poorly, not exercising for years, doing metabolic damage, it's going to take some time to untangle your thinking patterns and get you back on the right track. There is no three-month quick fix. Although people see results much quicker than three months, our goal is to sustain the results, right, we're trying to do true, right, lifestyle change, not just yo-yo people with their weight. It takes a year. Right now, we're charging 15,000 for a year membership, and that includes, So what we did was, you pay that once, you don't pay for anything again, wearables, diagnostics, all the different coaching styles are all included. You have unlimited sessions. So it's like, hands off.
Emmanuel Fombu:
There's no price for being healthy. I'm sure if you get sick, it's more expensive, right? Your quality of life or how much it costs ... in the hospital. So I think it's actually not that expensive to actually, to commit to this and buy into a commitment to be healthy and have a much better quality of life going forward.
Ravi Komatireddy:
It is, and it is a commitment, right? I won't lie. It's definitely, for everybody right now, it's, be quite a stretch, right? That's a lot of money. But last time I checked, it's out-of-pocket costs for insulin per year or 16 grand. So it's which hard do you want to pick your hard, right? Which one do you want to try to afford? It's your surgeon. What's one night in the CCU? $6,000?
Emmanuel Fombu:
..., and then you don't get back to normal even after spending that very expensive, expensive hotel stay that you'll get back to normal. And, of course, as everything else, as we get more data, we get more people using this, and the technology evolves, this becomes cheaper over time. But I think for right now, there's no time to buy. You might not be around tomorrow. So I think it's something that is urgent. I don't think it's something that we should be passive about it. So I would encourage anyone listening that can afford to please join Daytona Health and Ravi on this mission. Myself, definitely want to commit to that because I think everything you described is exactly what I need on my side. Thanks a lot for working on this great effort, Ravi. Hopefully, we can get you on the show again soon, to see how things are going.
Ravi Komatireddy:
Absolutely. Thank you very much for letting us share the vision and talk about what we're doing. Really appreciate it.
Emmanuel Fombu:
Yeah, thank you, everyone. If you're listening to this, please join Ravi on his mission. I'll join myself. I would love to bring him back on in a few months to see how things are going, and I'll probably share my own progress as well. So thank you.
Ravi Komatireddy:
Yeah, that'd be great. Thanks.
Emmanuel Fombu:
Thank you for listening to Bite the Orange. If you want to change healthcare with us, please contact us at info@EmmanuelFombu.com or you can visit us at EmmanuelFombu.com or BiteTheOrange.com. If you liked this episode and want more information about us, you can also visit us at EmmanuelFombu.com.
Sonix is the world’s most advanced automated transcription, translation, and subtitling platform. Fast, accurate, and affordable.
Automatically convert your mp3 files to text (txt file), Microsoft Word (docx file), and SubRip Subtitle (srt file) in minutes.
Sonix has many features that you'd love including advanced search, automated subtitles, enterprise-grade admin tools, automated translation, and easily transcribe your Zoom meetings. Try Sonix for free today.
Ravi Komatireddy:
As founder and CEO of Daytona Health, Ravi is a Board-certified physician and former Founder and Chief Medical Officer who brings an innate curiosity, diversity of thought, and expansive domain knowledge coupled with 15 years of lessons learned to disrupt healthcare as we know it. At Daytona Health, he is championing innovative digital health initiatives and behavior modification systems that will help people achieve optimal HealthSpan using both technology and the human touch.
Ravi received his Bachelor of Science degree in Biochemistry and his MD degree from the University of Missouri-Columbia, and a Master of Science degree in Clinical and Translational Investigation from Scripps Research.
Things You’ll Learn:
70% of diseases such as heart disease, stroke, diabetes, and hypertension are directly related to lifestyle choices, including sleep, exercise, nutrition, stress management, and social determinants.
The integration of precision medicine, coaching, and data from wearables can create a personalized platform to guide individuals toward better lifestyle choices.
Mindset, including building self-efficacy and resilience, plays a significant role in sustaining behavior change.
Daytona Health plans to train an AI system to enhance engagement and deliver persuasive messaging, making health behavior change computable.
When it comes to pricing goals, Daytona aims to eventually offer the program below $200 a month, with a focus on direct-to-consumer access and a money-back guarantee if desired outcomes are not achieved.
Making a financial investment can have a psychological impact on a person's commitment to going through with what they signed up for and producing better results.