Category: Artificial Intelligence

Why Evolving Medical School Training Will Improve Healthcare with Dr. King Li, Inaugural Dean at Carle Illinois College of Medicine, University of Illinois at Urbana-Champaign

Hey Outcomes Rocket friends, thanks for tuning in to the podcast once again. As a leader in health care, you have big ideas great products, a story to tell, and are looking for ways to improve your reach and scale your business. However there's one tiny problem. Health care is tough to navigate and the typical sales cycle is low. That's why you should consider starting your own podcast as part of your sales and marketing strategy. At the Outcomes Rocket, I've been able to reach thousands of people every single month that I wouldn't have otherwise been able to reach if I had not started my podcast. Having this organic reach enables me to get the feedback necessary to create a podcast that delivers value that you are looking for. And the same thing goes if you start a podcast for what you could learn from your customers. The best thing about podcasting in healthcare is that we are currently at the ground level, meaning that the number of people in healthcare listening to podcasts is small but growing rapidly. I put together a free checklist for you to check out the steps on what it takes to create your own podcast. You could find that at outcomesrocket.health/podcast. Check it out today and find a new way to leverage the sales, marketing and outcomes of your business. That's outcomesrocket.health/podcast.

: Welcome back once again to the Outcomes Rocket podcast where we chat with today's most successful and inspiring health leaders. Today I have the amazing Dr. King Li. He's the Inaugural Dean at Carle Illinois College of Medicine, University of Illinois at Urbana-Champaign. Dr. Li's experience includes research, clinical, educational, and entrepreneurial roles at the NIH Clinical Center and Stanford University as well as Wake Forest in Houston Methodist Hospital. He studied physiology and biochemistry at the University of Toronto earned a medical degree from Toronto and an MBA from San Jose State University. He's been widely recognized by the Association of University radiologists in 2018 and he's received several awards in innovation and leadership. This award in particular recognizes a visionary who's made significant contributions to advancing radiology research, innovation, leadership, mentorship and growth of the RRAA - that's the Radiology Research Alliance. He's brought together all of these wonderful experiences and expertise to start the Carle Illinois College of Medicine. So I'm excited to dive into Dr. Lee's experience and then also talk more about the exciting projects that they have going on there so. King welcome to the podcast.

: Saul, thank you for having me.

: It is a pleasure. So is there anything in the bio that I left out that maybe you want the listeners to know about?

: Yes I think I am also inventor. I have 17 inventions already. Also some entrepreneurial experience studying about tech companies. So you know that aspect also strengthened my experience in putting this new college to work.

: That's fascinating. I didn't know you were an inventor as well. And and so this makes a lot of sense. You know why you're the Dean there but for the listeners that don't know maybe it would serve to give them a nice introduction about this school of medicine that you guys founded in Champaigne.

: So the Carle Illinois College of Medicine is the world's first engineering focus college or medicine. So what is engineering focused college of medicine. So fundamentally we're actually combining Engineering and Medicine in teaching students. So we actually start by selecting students who have quantitative science background in addition to the medical requirements so that at a time they come in we can actually use a curriculum that actually leverages engineering principles and technology to actually teach medicine. So there are many schools for us that have actually layered engineering on top of medicine. We're not layering. We're actually combining so that they learn medicine they learn it through the lens of engineer and also through the lens of basic scientists. So we actually have four pillars in our education. So traditionally is just clinical sciences and basic sciences. We did it to this engineering and also humanities. That's the fundamental difference between our school and the College of Medicine.

: It's super interesting King How you guys made a decision a conscious decision to do this and put together a program a facility all focused toward this especially now and in the realm where technology just keeps getting better and cheaper. And so I think the need is going to be there for physicians that have that engineering talent. I'm curious though, what made you decide to get into medicine to begin with?

: Well so I've always been interested in the quantitative sciences and I was debating between hardcore science engineering or medicine. I learned that in medicine you can actually combine all of those. So to me that also gives a possibility of helping people. So to me that was a no brainer to get into medicine at that time.

: That's really interesting. So we're at the forefront of a lot of new things in health we got value based care, we've got new treatments for oncology, digital health. Out of all the the soup of new things and buzzwords King, What would you say a hot topic that needs to be on every medical leaders agenda today and how are you guys addressing it there at the school?

: Right so I think the one thing that people stick in technology and medicine is the really technology should be used to strengthen humanistic aspects of medicine rather than to distance the healthcare providers from the patients or actually not just patients but anyone that they tick off whether they're sick healthy. In our world we actually want to emphasize rebuilding relationships using technology so they include human to human relationships, human to machine relationships and machine to machine relationships. I think that's the hot topic how to actually leverage technology to enhance relationships is a topic that we focus on a lot.

: So what would you say an example of how you and your organization approach that? This how tech can can enhance relationships?

: So for instance right so if you walk into a doctor's office today versus walking into a doctor's office 30 years ago.

: Yes.

: You find that most of the technologies that doctors use today in the office has not changed, right? See the stethoscope that was invented 200 years ago or telescope the instrument that doctors look into years of patients with was invented 180 years ago. And this technology's actually low fidelity and they also low efficiency. Why. Because they tie in four different processes into one. So data acquisition. So the doctor has to listen and acquire data using their own years rate which is as we all age of her daddy goes down. Yeah second is it data analysis, right? That too actually requires the brain of a weltering person the right to actually analyze data is not recorded. So it has to be processed instantly. Right. Then you have to have decision making right. So you have to combine the data analysis with added data to come up with the decision and then counseling. Right. So that doctor has to decide on a course of action in the end and hopefully get the consent of the patients and proceed with the course of treatment. So you can see all four processes are tied to the most highly paid person in the food chain right.

: Yes.

: If we can't divide up the processes and use an instrument to have higher fidelity that can actually record the sound and record the waveforms and the second step data analysis can be using artificial intelligence assisted analysis and the gift that decisions support to the physicians and actually we can now combine that data with all the other data from the clinical records and elsewhere to give that doctor the best decision support. And then all this can be done separately from where the doctors sit. So theoretically it can be done remotely and this data and the decisions report can then be sent to the doctor. The doctor can then write make a decision and then talk to the patients remotely so he can see how by leveraging that type of technology we can increase the efficiency and quality of healthcare and also make it lower cost and more accessible to patients.

: That's a really great breakdown and a good example from a very basic physical to your physician. I didn't realize these instruments were that old 180 years old on the ah...

: That's why you know we're still used as status almost as a symbol of the physician right. That's interesting that we haven't really improved that instrument until most recently.

: Very interesting. Some of these things oftentimes go unquestioned listeners we gotta start questioning even the most fundamental things in what we do. It could be those minor shifts that could lead to large scale outcomes improvement and new business models. As you look to approach these two things in healthcare it's really important to King's point. Dr. Lee can you give the listeners an example of how you and your organization have created results with this new campus?

: Absolutely. So the first thing that we need to do is to actually fundamentally read them the curriculum. So to do that we actually in each of the courses we have three course directors. Basic science, one from clinical science and one from engineering. And their purpose is to make sure that the curriculum integrates all those disciplines. And we also have humanities professors that actually look through the threat to make sure that the social aspects, the humanistic aspects of medicine is incorporated in the curriculum and the curriculum is through active learning in the pre-clinicial years. That means that instead of hearing lectures. So the students are divided up into groups of eight and we give them cases for down to solve. And during the case solving process they will learn to use a different knowledge base including engineering basic science, clinical science. We can also set up cases where they learn to write the practical social and humanistic aspects. For example imagine you have a heart disease patients coming in and the patient doesn't even have money to fill the prescription. So just writing a prescription doesn't help that patient. So you give the patients support to the group and they can look up the potential support system that can help the patient right. So that gives them more training than just learning to prescribe the correct medicine.

: That's great. Yep. And so tying up this I think it's fascinating that you guys have put together this system within the organization. You know the science, the clinical science, the engineering and then the humanities I really think that that really captures nicely all the elements of medicine and it's great that you're giving students the opportunity to start early on in their career with this. One of the things that that has come up in discussions with other healthcare leaders I've had several chief medical officers on the podcast they've said Our students are not learning how to be leaders. And one of the deficiencies unfortunately as we seek to make physicians leaders of large ideations is leadership skills. Is your campus doing anything to hold the leadership skills of these people?

: Absolutely. So in the critical years we want to really stimulate curiosity and creativity in our students. So for every critical rotation our students are required to come up with a new idea to change things. You call them your projects and you help them. We actually have engineering rounds so in clinical rotations right the students do rounds with the clinical professors. But in addition to the clinical professors we have engineering professors going two rounds with our students. The idea is that our students are young and they are curious they will look at the way we do things and they will challenge the way we do things and come up with potential ideas of changing things right. So do we have some ideas around with both a clinical professor and also the engineer and professor to see whether those ideas are actually feasible or have anyone thought of them before. Have they done before. Each rotation there will be a new and through the idea projects one will be selected to be there Capstone projects in the capstone projects. They will be the leader of a team of artists that they select from campus. For example you can't have a business school and you can have engineering students you can even design student right. So they would lead the team to turn the idea into a prototype so they would learn the actual leadership skills in leading a multidisciplinary team. I think from ideas to a prototype.

: That's great. Sounds like you guys have captured a lot of the things that have been lacking in traditional medical schools today and that's it's pretty exciting to hear that you've put it all together as part of a capstone project sort of from the beginning just teaching them to question, teaching them to question convention.

: Yes I think there are four qualities, ee call them the four Cs that we emphasize.

: Okay.

: Right. The first is compassion training doctors. Second is competence. Those two are quite common in the medical school values. But the last two Cs are quite uncommon that is curiosity and creativity. So the idea that in most medical education we're learning the so-called standard practice. So we were taught when we were going through medical school to learn the standard of practice almost never question right. Why we practice the way we practice. But for our students we encourage them to actually question, to ask the question why. Typically we educate students to ask right - what, when, and how and not why. So our students will be encouraged to ask the question why. Why are we doing this? Why are we treating this patient this way? Right. So that is fundamentally different.

: Yeah. It's that creativity and just understanding the why behind it. Whereas before they didn't Yeah you know I had I don't know if you know or Arlen Mayers he's the guy that started society of physician entrepreneurs.

: Yeah.

: Yes. You know he comes to mind and I was at a meeting and he was very passionate about these two pillars you know creativity and just being able to be curious and to your point, Dr. Li it's just I think it's such a wonderful thing to focus on. And the best organizations know how to keep things simple. And you guys have definitely done that with these two pillars to really capture this this much needed skill in physicians today. So congratulations for being able to boil it down to just those two pillars.

: Thank you.

: So what would you say King is one of the things that during the inception of this school and everything that you guys did what was a setback that you guys had that you learned a lot from that you want to share with the listeners?

: So one of the things that we were actually trying to do to actually finance the actual medical school was fundraising.

: Yes.

: So we were actually behind in our fundraising and the target set for our fundraising goal was very high. So there was a setback that we experience but luckily the university has come up with the support that is needed to give us all the resources that is needed to make the medical school very successful. Clearly we are continuing to raise money and very actively actually. But that was a mistake that was made to actually set the fundraising target very high in the beginning.

: And so you'd think it would have been better said a little bit lower?

: Or actually not use it as a major pillar in the beginning for funding Medical's enterprise.

: Got it. Got it as sort of as a requirement to make it happen.

: Yes.

: Gotcha gotcha. OK. Because obviously hey it's not cheap to run a medical school and just being able to not make it a requirement and finding creative ways like you guys did with the university to make it happen.

: Yes. So we have many ways of making it very efficient. So for example instead of hiring a lot of full time faculties the major advantage for us is we are within a large comprehensive university so most of our faculty is actually part time from other colleges. In fact we have faculty from 10 different colleges. It is a huge advantage because imagine. Right. Who can really teach behavioral change and marketing professor from business. So we actually have professors from liberal arts and sciences, engineering, business you name it all the way to fine arts. So that's why we can be a lot more efficient financially and also it builds in from the beginning the disciplinary nature of how Education Research. And so on.

: Fascinating. Well congrats on being able to make that happen. Kane you've had a fruitful career. What would you say out of all the things that you've done is one of the proudest medical leadership experiences you've had to date? It could be on the business side it could be on the practitioner side, what would you say?

: I would say definitely the current job right. The inaugural dean of the Carle Illinois College of Medicine is clearly the most impactful job I've ever had. Because can be seeing the turning point in not just a medical education. The delivery of healthcare in the world. And you really look at health care right at a time when major changes are required. So the costs of health care in this country is already about 18 percent of GDP. Aging population. Right. We have a urgent time to find solutions that can improve the quality decrease cost increase access ability and increase equity in health care. And we believe that technology and engineering can bring solutions that can help healthcare to move in that direction. We let the people who actually are trained specifically to do it. And so our school is targeted to that purpose and that can be a turning point in our group. Dean that this fantastic mission is clearly the most impactful job ever had.

: That's outstanding congratulations on that and listeners if you're looking for a school that is at the forefront of getting things done in the new age of medicine. You guys definitely have to check it out. We'll leave a link for the school as well as the best way to get a hold of the folks over there here at toward the end of the podcast which we're getting close to. So Li, getting close to the end. Let's pretend you and I are building a medical leadership course and what it takes to be successful in the business of medicine - The 101 of Dr. King Li. We're going to build a syllabus with four questions that are lightning round style followed by a book that you recommend to the listeners. You ready?

: Yes.

: All right. What's the best way to improve healthcare outcomes?

: As I mentioned earlier is rebuilding relationships. We have to look at how to rebuild a patient doctor relationships currently around you only see a doctor once a year or even less when you are healthy and then use suddenly I have to see them. Often when you get sick they really don't know you as a person by the way that we build relationships. Very different from the family doctors that West portray. Right. Many years ago. Right. Dr. Marcus Welby that actually watch when I was a kid. So the way to use technology to rebuild relationship is look at how for example I get contact my grandkids in California or I can Skype with them. And so on. How can we actually build relationships again so that doctors and patients actually feel like they really didn't know each other so that important important. Also rebuilding a network of support systems that doctors know about not just the patient people who are around the family their friends and so on. Right. And then the second is so called person to machine relationships. Currently the doctors have a hyper now rate because electronic health records really require doctors to enter a lot of data that is actually draining energy instead of putting it into patient care actually pulling it into capturing data. So that needs to change. And lastly machine relationships. Imagine you have one electronic health care record not talking to an electronic health record right patients actually carrying this from one doctor to another. Now what needs to change also. So rebuilding relationships fundamentally, leveraging technology but not to decrease the humanistic aspect but increased a humanistic aspect is the most important and the best way to improve healthcare outcomes.

: And what would you say the biggest mistake or pitfall to avoid is?

: The resistance to change is the major barrier right. For example we as doctors are used to patients coming to see us now. But before the industrial revolution, doctors used to go and see the patients.

: Right.

: In their home. So imagine you're 83 year old, living alone. It's snowing outside the closest doctor is 35 miles away and you're sick. You have to drive to the doctor or you have to call an ambulance to transport you right. That's highly inefficient and not accessible. So how do we leverage technology to fundamentally change bring high quality health care to sick people where they are inside too. That's right. Well imagine the day when you can actually use Alexa to take their medical history.

: Love that.

: Then a drone would send the right equipment to do the data collection. Using artificial intelligence and then the doctors remotely can come up and say so and so. I thoink you have pneumonia. It's not so bad. You have to go to the hospital. So the next drone coming in would take the drugs to you. Right. This is how you take them. You have any questions you can call me anytime. And by the way you can't put all those instruments under drone and then flies back to where we are so that way you can take high quality medicine to where patients are right. That's not a pipe dream right. It can be done using even current technology. So those are some fundamental changes that doctors have to that too. Right.

: Absolutely. And that's a great way of focusing on and where things could be. What would you say your favorite book that you'd like to recommend to the listeners is?

: The book that I like the most recent reading is called Cancer the Emperor of all Melodies. He's Siddhartha Mukherjee is a winning book and it's not just talk about cancer. It actually went back into the history of how medicine, modern medicine, the concept of modern medicine get to the point that we are right. So it really opens the eyes as to why we feel that modern medicine can cure everything. If you are obese you want to take a pill and get it working your cure rate. That type of stuff is actually stand from the biggest success in modern medical history which is dealing with infectious disease right. You find a very specific course of the disease. It give a very specific treatment the right antibiotic and then your cure. What it's the biggest success in modern medical history. And we now have the mindset that everything is like that right we called deterministic for example give you are most likely to get sick. The randomized x you get cure right. Most diseases that will deal with today chronic right. So for example heart disease, diabetes and so on. And there is no magic cure. There's no single right treatment right. A lot of it is actually related to lifestyle. Everyone knows if you eat well, exercise well you have lower chance of getting a lot of those chronic diseases. How come we are not enabled to change behavior. Right. Because doctors are not trained to change behavior. Right. We are used to writing prescriptions in the concept of infectious disease but in the new world right where we're trying to actually do preventive care prevent this from happening. That goes to another core problem that we have this our biomarkers are too late. For example I can keep checking your blood pressure. By the time your prep pressure is high is actually late. I can keep checking your kidney functions by the time the kidney functions appears abnormal in the lab tests really have lost a lot of your kidney function. So how do we actually give very good predictive value of when you will be in 30 years and help you change your lifestyle right to prevent diseases from happening. Where does that data come from. Right that data actually doesn't come from measuring the the blood pressure, blood sugar, and so on. Actually measuring what you are doing is icing eating the right food and so on and that data actually sets in a lot of digital transactions, digital transaction become the norm. All that data is actually available. What food are you eating? Are you going to the gym with a cell phone in your pocket, theoretically we can trap where you have been. Have you been running? Have you been going to the park? You've been sitting there watching TV. Right so. So in that new world right. How do we actually leverage that data will it give us much better readout of what we call the risk. So again most people think that the CCS so-called deterministic. That means there is a cost right. And then you know it's definitely the result just like if I hit you right with my fist and your face you get traumatized. Deterministic medicine. Most diseases with deal if are not deterministic stochastic yes say not everyone smokes will get cancer for example lung cancer. Not everyone who don't smoke will not get lung cancer. So isn't it increased the risk, decreased risk. The whole mentality of dealing with stochastic diseases versus deterministic diseases is very different and that mindset is not naturally dear for both the practitioners and also patients.

: Fascinating and like a good professor you've left us with a lot of questions to ponder. You've left us in a good place. Dr. Li. Before we conclude our love if you could just share a closing thought and then the best place where the listeners could get in touch with or follow you.

: Well the closing thought is I think we have a lot of young people with the right mindset that is willing to actually put the energy in helping the healthcare system to perform better make it higher or lower costs and more accessible and equitable. And the way we can help is actually unleash the potential and make them more successful. And best way to do that is really fundamentally changing education system. So.

: You're doing just that.

: Yes.

: And so am excited to see your work continue there. Dr. Li. What would be the best place for the listeners to get in touch with or follow your work?

: Yes. We have a website. If you just google Carle Illinois College of Medicine you get to a website. We have a lot of updated news and so on. So you can actually follow the progress or if you want to get in touch with me personally my email is kingli@illinois.edu and I would welcome the opportunity to communicate with anyone who is interested in what we're doing.

: Thank you so much, King and folks I'll put all of the links that Keen's shared Dr. Lee shared on on the show notes you could find those at outcomesrocket.health/kingli you're going to find that there. His email, a link to the new school and the book that he recommended as well as the full transcript of our discussion today so King really appreciate your time and your insights today.

: Thank you very much for giving me a chance to share my thoughts with the audience.

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Recommended Book:

The Emperor of All Maladies: A Biography of Cancer

Best Way to Contact King:

kingli@illinois.edu

Mentioned Link:

https://medicine.illinois.edu/

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https://outcomesrocket.health/podcast

Solving a $150 Billion Dollar Problem with Machine Learning with Benjamin Fels, Founder and CEO at macro-eyes

Solving a $50 Billion Dollar Problem with Machine Learning with Benjamin Fels, Founder and CEO at macro-eyes

: Welcome back once again to the outcomes rocket podcast where we reach out with today's most successful and inspiring health leaders. Today I have Benjamin Fels as a guest. He's the founder and CEO at Macro-eyes. He leads teams that innovate and build systems that recognize predictive patterns and macro-eyes, they use machine learning to increase access to care. Their live clinical product and a two leading academic medical center institutions they develop supply chain analytics product for one of the largest value based healthcare systems in the U.S.. Today it's super important that we find ways to apply artificial intelligence and machine learning to healthcare. Because let's face it we're not able to scale the number of patients that need care with a number of providers that can give it. And so that's why that'd be so timely to have Benjamín on the podcast today to talk to us a little bit about what they do it macro-eyes as well as the concept of machine learning and how we can apply it in healthcare so Benjamin. It's a pleasure to have you on the podcast sir.

: Thank you. The pleasure's mine.

: So Benjamin did I leave anything out in your intro that maybe you wanted to have the listeners know more about.

: No no just kidding. That's not I. I don't love talking about myself. So maybe some other pieces of the backstory of Macro-eyes as a company or from my own history of working with my friends will sort of come out through this conversation. So I'd love to just dive into it.

: Beautiful Love that you open that loop there. And so you know before we do dive into that I'd love to hear what got you intrigued or interested in the medical sector to begin with.

: Well that's a good question because I didn't train as a doctor as a company we've been working in healthcare now since since 2014. But it's I bet it's a pretty unconventional route. So sort of go backwards in time here to answer that. So..

: All right.

: I've worked on what you could broadly call pattern recognition for many years and I believe in and I pretty sure that most of the people who are listening would agree with me that health care poses the most complex and at the same time most important problems in pattern recognition. This is where pattern recognition matters. So OK now let's go to sort of how I got to this point. So I graduated with a degree in the history of art and the way that I see the history of art as a series of exercises and pattern recognition how one artist perceives, reflects on, interacts with art that came before art from other places. And there's a way to see that transformation refraction of pattern. When I graduated college I then went to go work for a quantitative hedge fund first in Chicago then in London. My job was to predict patterns and data faster more accurately than our competitors. That was it. It was very clearly defined. I mean there's that great beauty in that in that clarity. I led teams that traded global markets 24 hours a day. I led teams also built autonomous agents so what I now know is called machine learning. So basically machines that looked at patterns and data in markets and looked for signals that we might have missed and acted upon. And financial markets as a whole are decades ahead of healthcare in terms of designing and implementing infrastructure for I guess what we could broadly call data driven decision making. So designing systems that learn as reality on the ground changes. So it's everything in financial markets is always responding reacting learning. There's a very powerful very heavily incentivized feedback loop there. Nothing is ever static. So essentially I left this hedge fund to found a company so that I could take this approach this mindset and a bit of new ideas for technology to where it is needed most. And we believe that's healthcare. And again this concept that. Pattern recognition the ability to detect patterns that are meaningful and large amounts of data where that is the most important is in both the delivery of care and the practice of care and I'll just speak a little bit about some of my colleagues in this company because it's certainly certainly not me doing this all on my own. So I found it with two other people a chief design officer and a chief AI officer. Maybe we'll get a little bit later in this conversation to why I think that mix is important. So Sebastian Cowper's and Sebastian is our chief design officer and he has had a really a career long commitment to thinking through how healthcare organizations can best use data. And this is from huge global pharmaceutical companies to one of the first personal health data dashboards which he designed for a company now more than 10 years ago and surprise our lead AI officers since read is a world renowned expert in large scale machine learning and optimization and a professor at MIT. So I hope I answered that question about sort of how how I got to healthcare.

: Absolutely. And you've now focused on this area. You've got a phenomenal executive leadership team there at your company. You're tackling Data in Healthcare and making insights so as it relates to that Benjamin, what would you say a hot topic that needs to be on every medical leaders agenda today and how are you guys approaching it?

: So I gave away this answer a bit already and I hope this is the answer that many other leaders in healthcare would come to but absolutely machine learning or AI and me and maybe to talk a little bit later about the distinction between those two. But again this is medicine is pattern recognition and the delivery of care should be pattern recognition at scale, at speed. And the thing that is so unique about healthcare as an industry is that it is unparalleled in the richness of the data that it holds that describes almost every one of us in incredible detail, meaningful clarity and no other domain has such an impact on human life and has this incredible picture of each one of us. And I mean all of us have experienced this for better or for worse every time we go to see a doctor or nurse. They spend a lot of time mentoring in data and speaking very, very, very broadly and I'm going to ruffle some feathers here. Very little of that data is effectively put to use to build what we could again say very broadly our learning systems for help very little of that data is learned from in a systematic structural way to personalize care to make care more efficient. And I see absolutely no reason why that should continue to be the case.

: Love your passion for this. Benjamin and I agree. You know a lot of the data that we shovel into EMR is stays shoveled into silos. That is not accessible by anybody outside of the system. Definitely a problem right. And so you guys work to offer this solution to health care. You've decided on the macro-eyes. So can you give us a little bit more detail about what macro-eyes is focused on and what's the problem what's the solution you guys are providing?

: Sure. So I'll tell you a little bit of the evolution of the company and also the problem that we're most focused on today. So we founded this company in 2014 and we spent a number of years refining and deploying core machine learning at a leading academic medical center in York City at Stanford at one of the largest health systems in the United States and at a number of federally qualified health centers across the country.

And what came out of this experience was a couple of a very robust technology for understanding patient behavior and understanding patient behavior multi-dimensional and what I mean by that is at many points in healthcare, the understanding of the patient is very or at least the classification of the patients is very limited. Fifteen year old male diabetic but there are hundreds if not thousands of other data points in dimensions which are going to inform both the care that is most appropriate for that patients and how we should think about risk and also opportunities and our expertise is that ability to build these very rich pictures of patients in time and the other important thing that came out of this experience largely focused on clinical decision support during these years were working with physicians, physicians scientists to answer clinical questions and from a business perspective probably the most important piece of this is that we we've got an understanding of healthcare as a business and as everybody listening here knows it's a very complicated business it's very difficult to to understand. And I think we got an understanding of the problems that are solvable and the problems that are less solvable particularly for a small company like ours and one of those problems that came to us again and again and again and from many different perspective this is really twofold. One schedules that don't work schedules that aren't predictable a day that a provider has which is chaotic. So it's a balance between having 10 patients in the waiting room all waiting for the same slot and other periods of the day where four of the five patients who were scheduled don't show up. So it's it's sort of feast or famine and there's a significant financial impact to that. There is a clinical impact that this is important to patients, it's important to administrators, it's important to physicians. Scheduling is really the front door to care. And our own response to that was to spend the last. Now more than a year developing and implementing and refining a product called Sybel and Sybel is software for intelligent patient schedule and what that means is that Sybel identifies when each patient is most likely to show for an appointment and uses that insight to build a better schedule, a schedule that is more predictable, a schedule that increases access to care and a schedule that reduces the number of times in the day when there are expensive gaps in the schedule and reduces those periods in the day when there are many patients waiting and waiting and waiting in the waiting room because they've all been booked for the same timeslot.

: That's fascinating and through the work that you've done you found that this is one of the biggest problems. And you're right it's definitely a huge issue. And so you've deployed a solution to help fight this problem. Intelligent scheduling.

: Yes. Yeah. And I want to emphasize and this is sort of one of the things that drives us as a company and so when all of us think about what machine learning, artificial intelligence, innovation in healthcare probably what comes to mind, Robots, self driving cars, things happening on Mars. And one of the strong beliefs in our company and that I really want to emphasize is that where innovation is both needed the most and has the greatest likelihood of actually making an impact are these issues at the very foundations. Of care issues that touch operations supply chain scheduling. Think of that as this is the roads and the airport of healthcare right. This is the core building blocks that when they don't work the whole system suffers. And when they work effectively now you have a base that you can build on and you can build something which is much more efficient. And we would argue also were personalized and enables both better access to care and more personalized care.

: And I love that you've focused your efforts in this very niche area that frankly a lot of health systems health executives I mean if you're listening to this you're probably like yeah I'm definitely struggling with this. It's a billion dollar problem. There's a big loss of revenue due to people not showing up to their appointments. And so I think it's interesting that you guys decided to just niche down to this particular pain point.

: Yeah and part of it has to do with again this from our perspective and this is what really, really exciting this is a problem that we believe is solvable. And again I'm gonna say maybe some some controversial things here but there are a number of issues in healthcare that particularly when you're new to healthcare as an entrepreneur and you look around and you see things that just don't make any sense. And if you're looking at that from an entrepreneurial mindset. These are why should start a company to address this and this and this and each one of these is maybe 50 billion dollar problem. But I think if you are humble and you observe carefully you start to notice that many of those issues you cannot solve them as an entrepreneur even if you are enormously successful because perhaps at some level they are the result of policy or they are the result of a certain structure that's in place. And you know we could argue whether that's a good structure or a bad structure but it's very often something that you cannot move even if you are immensely successful as a company. And what our job as a startup and as a startup that wants to make an immediate impact and I would argue that that's the job of every startup. Our job is to find those points in health care where we can affect change we can push the system towards operating better operating more efficiently giving greater access to care to patients because that's that's what we get excited about. Right we want to do something where we can have an impact.

: Absolutely. And listeners by the way if you're curious if Benjamin has has hooked you at this point which definitely probably has hit pause and go to gosibyl.com. You'll see a little quick video on what the software does for your scheduling. So it's G O S I B Y L.com. Check them out. They're definitely doing some very intriguing things to use A.I. to help you keep those patients in those slots that are scheduled for whether they show up or not. So this is fantastic work that you guys are up to here. Benjamin looks like you guys even received Grand Challenges exploration grant to deploy a version of it in East Africa by the Bill and Melinda Gates Foundation.

: Yeah that's really really exciting. So I'll talk a little bit about that. So we described here that this evolution. You know we we spent years in where we're up close to clinical questions. Our core technology has analyzed several million medical records and has learned from all of this and then out of this came this manifestation of that this product which uses insight into patient behavior to build a better schedule to better predict demand and to build better schedule so you can make best use of existing resources and offer the basis of that. We were awarded this very prestigious funding from the Bill and Melinda Gates Foundation and USA which is development and its government to design the first predictive supply chain for vaccines and at a certain level. And bear with me here as I as I explain this I see these really remarkable similarities. So our aim with this work is to increase the coverage so increase the number of children who can access vaccines and significantly cut the amount of vaccine wastage. And this is also a many many many many billion dollar a year problem. And it is also a problem which you can measure in terms of human lives just like in the United States where if you have to wait weeks and months to access care because the scheduling doesn't work and if you are particularly ill your illness will become far more grave with that period of time. So if a child is brought to a facility and they've run out of that vaccine that's an opportunity that you might lose forever. So our job is to analyze data which describes these different facilities and use that to predict exactly the right amount of each type of vaccine to be delivered to each clinic. No more and no less. Because if you deliver too many vaccines what happens is you're significantly increasing the likelihood that there will be wasted vaccines are very very fragile. They live in these delicate glass files they have to live uninterrupted in a very very narrow temperature range there just really easily breakable. You deliver too few vaccines to a facility and then you have this issue of people are coming traveling to this facility to be vaccinated and you have to turn them away. So this is really a case of get where you want to exactly nail demand, you want to get a perfect sense of how many people are going to show up if you can get that right. You can make best use of existing resources.

: Yeah you know it's super interesting project and talk about hypersensitive matter with the vaccines. I mean you guys are definitely doing some cool work Benjamin. Scheduling Vaccines is the Bill Melinda Gates Foundation. This is super cool stuff that is making an impact. So I feel like as health leaders, we often learn more from our setbacks than the things that we've done right. And if you could just share one of the setbacks that you guys had and much you learned from it to make you guys stronger?

: Sure. So I'll go again back in time to the beginning of this company. And our first customer was Stanford. And at the same time we were working with a leading academic medical center in New York City and in both at both institutions and in both cases these are these are world famous organizations. These are these are places that are at the very cutting edge of care and in both cases we're working with with brilliant physicians and physicians scientists and and I'm going to describe a bit sort of our again our our founding thesis and how we changed that idea but our basic concept again is that medicine is pattern recognition. So let's pretend here that I'm a patient and I walk into your office and you're a brilliant physician and you look at me and you look at my chart and clicking away your brain is this a version of what we call patient similarity. So where have I seen a patient like Benjamin before have I read in the literature about a case like this. As a colleague in the hallway mentioned you know I saw a patient three weeks ago with this this this and this and then that happened. And that is going to guide almost every point on the journey a pair prognosis diagnosis a notion of risk a notion of which medication to prescribe when. And our founding idea was let's bring scale and depth and muscle to this. This pattern recognition that the good doctors do and let's take it across every record that sits in that organization so they can get the best sense of when have we seen a patient like this before and what happens and what we underestimated. To a great degree is the extent to which physicians have been forced to deal with technology that asks an enormous amount of them and delivers almost nothing and because of that. Rightfully so. And I will support them the whole way here. Physicians are overwhelmingly wary of working with yet another piece of technology that will guide them during this complex process of clinical decision making and I think the other thing that we learned is that if we want to support that process of decision making we need to earn trust and that trust has to be built up incrementally slowly. It might take years to build that trust. Being inside that institution and we believe innovating and improving on the very foundations of care because the other thing that we like about the points where we have focused is that very often there are very clear metrics that you can present and you can point to the impact again and have a very clear way and that helps to build trust. So just to reiterate here I think that the big mistake we made is we thought well this is transformative technology. Of course physicians will want to use that and we just didn't understand enough about the day to day reality of what physicians have to do with technology and how how much they dislike that interaction. And again speaking very very broadly for all of us on the side of the table who are building technology for health care. This is something that we have to think very carefully about how do we gain that trust and how do we deal with a community of users who are skeptical and again rightfully so from the very beginning.

: And you've brought up some great points. And I've done over 400 interviews now and the topic of adoption you know and getting clinicians to adopt a technology you it just continues to resurface. And it sounds like after the journey of figuring that out you've really gotten a clear idea of how to you know number one address it and number two just meeting them where they are. And so what would you say the best way to do that is today. Have you guys done it. It's a problem for a lot of people.

: That's a good point. So I would say I mean part of our answer to that is we are trying to make that day of every physician better, easier and largely by working in the background. So our product Sibyl is not something that a physician necessarily will interact with. Now I've worked with many physicians who are extremely involved in scheduling because it impacts every second of their day and they have very strong opinions about how that schedule should be structured. But our job I think first and foremost from a physician perspective is to make their day predictable and I cannot overemphasize how important that is. So let's put aside for a second the financial actual impact. And again this is a hundred and fifty billion dollars a year are lost in the U.S. alone just scheduling that doesn't work. That's a big number that just so happens to be what I believe to be the global cost.

: I knows it was in the billions that it knows 150 billion it's High.

: This is more than what the world spends to care for patients with cancer. So we're we're talking big, big, big numbers here. And let's put that aside for a second and let's put aside the access to care piece and let's just think about how a physician goes through their day and imagine trying to be efficient. And imagine trying to do your best which is what every provider of care wants to do when if you have for instance five appointments scheduled for every day, you have no idea which patients are actually going to show up which means how do you prepare for that. Secondly that means if we back out from that how do you allocate additional resources when we should. What types of support when should which types of nurses be available. Which of the supply chain kick-in in winter certain goods necessary and just that feeling of going to work every day and not knowing how many people are going to walk through that door is very difficult to work with. And that's something that we learned an enormous amount about during this experience of deploying and working with different organizations and that one of the things that came up over and over and over and over again is that this is literally driving our providers crazy. In one of the things that they talk about all the time is just how destabilizing and difficult it is to do your job when you have no sense of what is going to happen in the next day, hour, two days. And the more predictable you make that schedule, the more in control of their day providers are the better they can prepare and the more efficient the whole system becomes.

: Love it. You definitely honed in in a big way. Benjamin so kudos for you and your team for being so hyper focused. It's definitely what's needed to move the needle in this space for sure. So within all of the things that you're doing today what would you say an exciting project or focus is for you.

: I'm very excited about these early deployments of civil just because every time we work with an organization we learn new things and this sounds cliche to say but it's absolutely true. I mean one of we recently sat with some schedulers in Alaska and they shared their scheduling care that is very complex in many levels. They're scheduling sequential care they're scheduling care oftentimes for a family because the distance traveled to the clinic is so great that maybe everybody is going to get in the car or try to see this physical therapist this occupational therapist on the same day. And so they have to find maybe four or five different types of appointments which are just certain order and balance that with the availability of providers. And they shared with us that this can take some 45 minutes to put together a schedule and we didn't build our software for that used case we didn't think about oh well this is going to save schedulers time. Our goal is to increase access to care for patients and build a schedule which maximizes utilization. But we realized well if we can cut that down to a minute for a scheduler that means the schedule will have more time and that means the scheduler could then spend his time her time in what we believe is the best use which is engaging directly with patients. So imagine that the scheduler could then pick up a phone and personally call the patients who they're the most concerned about not showing up and a personal phone call is so much more meaningful than getting a text message before moving an automated reminder or an e-mail. There's just as human beings we respond very strongly to human beings. And that's something that you can't do if you're spending 45 minutes to schedule an appointment.

: It's a great call out and the journey is exciting and Benjamin if people want to engage with your software if they're curious about it they're listening right now and you're like OK just tell me how I could get involved. Where do they go?

: They should definitely go to the website you just mentioned, gosibyl.com and send me a note. So my first name benjamin@micro-eyes.com, and I'd love to have a conversation.

: Love that. So folks the website. Benjamin's email. All those things. I'll have them for you here on the show notes. Just go to outcomesrocket.health/sibyl and sibyl is S I B Y L. So outcomesrocket.health/sibyl and you'll find a way to get a hold of Benjamin and get started with this phenomenal scheduling platform. Benjamin this has been a blast. Time flies when you're having fun. Would love if you could just share a closing thought and then the best place where the listeners could follow the work that you're doing.

: Well I think that if I could share a closing thought all a little bit more broadly to just sort of what we've observed with working with a number of health care organizations. Big, small and the lesson that I'd love to get across to health care leaders is embrace risk. So understand risk. Think about it carefully. But embrace the right type of risk. And there are very often opportunities to work with innovative companies like ours and we're certainly not the only one out there where the downside is very limited. But the upside is almost immeasurable and maybe I'm sort of putting back on my hat from when I used to trade derivatives but that's exactly the type of risk you want. Right. You know the worst that can happen here is nothing and that's it right. Yeah nothing collapses. No one gets fired. But the best that could happen here is transformative. Right it's a transformation of how we deliver care. And I would love to see more of that intelligent risk taking.

: I love that call out and folks I know we've we've talked a lot about Sibyl at gosibyl.com but also check out Benjamin's company macro-eyes macro-eyes.com. You'll see some of this thought process that he has shared. He's a thought leader in this space applying what he did with derivatives into health care. We're always trying to manage risk and I think it's a good opportunity for you learn the philosophy that him and his leadership team are leading with here. So check them out macro-eyes.com. But again you could get that link and all the rest just keep it simple. Go to outcomesrocket.health/sibyl, S I B Y L and you'll find everything there. Benjamin, truly appreciate the time you've carved out for us and we're excited for you and we're excited to stay in touch.

: Thank you. Thank you for a wonderful conversation.

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Demystifying Blockchain and AI in Healthcare with Sam De Brouwer, Cofounder, COO doc.ai

: Welcome back once again to the outcomes rocket podcast where we chat with today's most successful and inspiring health leaders. I have an amazing guest for you today. She is an outstanding contributor to Health Care focuses on the areas of artificial intelligence and block chain. You don't want to stick around. Her name is Sam. De Brouwer. She's a co-founder and chief operating officer at doc.ai,a block chain based AI platform that enables deep Learning computations on a quantified biology to develop personalized health insights and predictive models. She also cofounded Scanadu in 2011 where she served as V.P. of communications until 2016. They've got a fascinating device that has consumer facing mobile medical device that allows to read and understand outcome of a urine sample all through the mobile phone will be touching on some of her experience there. She's been involved in that even ICO's initial coin offerings. We're going to dive into what this very fascinating entrepreneur and health leaders up to. But I want to do is open up the microphones who are amazing guests Sam to fill in any of the gaps of the intro that I may have missed Sam. Welcome to the podcast.

: Thank you Saul, very very happy to be with you this morning and your listeners.

: It's a pleasure to have you Sam. Anything that you want to share that maybe I left that in your intro?

: No I think that's you to know is just that I've been just maybe that I'm being an entrepreneur in tech and science for the last 25 years. I moved to the U.S. in 2011 2012 to specifically moving to healthcare. Before that I've always been in the tech and science. I originally come from Europe more specifically from from France. I'm French.

: Fascinating and wonderful company. That's pretty far ahead and their health efforts so it's always great to have the international touch on the healthcare system. And Sam it's folks like you that that help us see things from a different light. So wondering what is it that got you into the medical sector to begin with.

: Sam Yeah well that's a that's a great question that's also very personal for me so I have two kids two boys and a pretty grown now but back in 2005 our youngest son has had a very severe accident.

: Oh my goodness.

: Very very severe brain trauma of brain injury. So he was in a coma. We spent a year in the hospital. And that was crazy. So back then we entered a journey that so many people enter. We chose we were so scared, we were powerless. We did not understand what was happening. I didn't know anything about health care. So the machines, the result,the language and I was coming from tech and science that was was so so I felt so powerless because I had no information no data I had nothing. And so I think what happened there for years with my husband, we kind of with cope with this situation and survive by becoming very analytical about the situation. Yes. And that was that's how it started really. And so I think you know with the rise of the smartphone then you know we were very much following what was happening. You know with sensors becoming cheaper and smaller and the rise of A.I. again. My husband Walter was also my co-founder for the last 25 years happens to have a background in artificial intelligence and so he went through the AI winter as we call it. But then he so is still the revival. So he's coming back and it's just connecting the dots and trying to do something that matters that can help us as a family and our son but also trying to help others and this is how it started really. And so you can see ignorance about the health care we need a lot of research. We knew a lot about the tech and the science and that's how it all started really.

: Wow. Sam thank you for sharing that very personal story. And you know the confusion, the just the helplessness that you feel when you're there at that point whether it be you or your or your loved one in your case and you decided to take the matters in your own hands using your science background and your husband using his AI background. Here you are now ten years later founding these companies to make a difference in your life but also in the life of the people that surround you. You've been in this for a decade now. Sam, what would you say is a hot topic that needs to be on leaders agenda today and how are you guys approaching it?

: Oh OK so a few things. Number one certainly artificial intelligence. I think that's what is happening right now. So number one when we started the very first company, we started using a lot of machine learning. There are a lot of things that human beings cannot do and you need to augment number one with this scale problem. So there are not enough doctors that's one so you really need. You need machine intelligence to be able to augment and capture older people who need it. But he's also in the entire chain. There are a lot of things a processing It can be reading colors to give a result or it can be processing data to have better models. All that has to be done by machines so certainly artificial intelligence is number one on my list. I think also what is very interesting what I'm seeing right now is healthcare that we did not really see before. So we've been talking about big data for a very long time and we have all been focusing on data. So healthcare happens to be an industry with a ton of data. What is happening is that I think everybody has been focusing on being able to share that data which has been difficult because this is not how the healthcare systems and industry has been designed for it has not been designed for the data are to be shared so pretty hard to you know be there. However what's happening right now is that there is not one industry on the planet that is not using artificial intelligence with the data to have better predictive models. It's the only way and we need to have better results, to be more efficient and to survive as a business. And I'm seeing that happening right now with the health care industry so a ton of data, The AI has become much much better. We also have the possibility to work with better data, structure data. We have learned a lot from there and I see the healthcare industry suddenly really trying to have new predictive models with that data and that that's a new element and that's very interesting for us and it doesn't matter if we're talking about payers or providers or I mean everybody wants to use that data in order to have better models otherwise the data become toxic. There's another thing that has happened recently. I've been working a lot in regulating environments and I kind of like that because regulation can be very difficult when you when you are an entrepreneur. However I think it can be a great source for innovation and we see that with the GDPR for example you know the new regulation coming from Euro, you that it's affecting US companies as well because data is global you know it has no frontier. And so that the GDPR is really pushing a new competition that is key I believe true progress in healthcare is to give people the data back and I think that's you know that idea of you know opting in consent that cannot be used anymore without people's consent. I think that's a great great sea change when it comes to healthcare because you see what I have learned my very very first impression when I was at the hospital with my son is that I didn't have access to my son's data and no one could give me access. And one thing I know as an entrepreneur. One thing I know having built companies and you know having dealing with technology all my life is that you cannot change the date of tomorrow if you don't know the day of today. And I think it really applies for patients and consumers as well. And so I'm very hopeful because today I think that if we are able to enable people to get their data I can be able to store them themselves and play. We need to make it smarter and you know keep on collecting and understanding it better. I think this is really a way for people to be able to change that data. But first they need to be able to collect it. So artificial intelligence certainly are very very high on the list.

: Sam you've offered some great great insight here listeners if you're understand today's data you're not going to be able to change tomorrow's data. Good friend of mine always says you got to be able to control the controllables and measure them. Sam give us a case scenario of a client or a type of customer that you work with. What problem do they present with them and how did you help them solve it?

: Yes so at doc.ai so we started 18 months ago. We are we are young starter and we've been building building building for the last 18 months. I am very lucky I have an exceptional team and very early on what we understood is that you know when it comes to artificial intelligence, everybody's trying to change behavior or change models. It's very important to understand that you cannot change if you cannot predict and in order to predict with the AI, you need to be able to collect the data so not real one. What our ecosystem allows people to do is simply to be able to collect all the medical data all around coming from all kind of BPIs those owns tools that we have been a lot of course medical records but also lab tests, blood test, urine test, gelati test, your environment will be expose mix, your microbiome information, your physiom, your phenom. So we have developed a system where people with their phone or their laptop can collect all that data in a very frictionless way and store it on their device on their own device that data like I'd spend before is structured so under the form of OMICS our bodies on 10 million of biomarkers and those biomarkers are structured under informal OMIC's and so those are biological field and that structure is very good for the AI. It's numbers, colons, rows. This is a very very good start. So that's number one. What we're doing right now so we are working with companies that are in these in search for new predictive models and those predictive models they can present different solutions or try to develop frameworks for it to see what AI could predict. So let me give you a few example that we are going to announce very soon by the way. So for example can an AI predict your risk for allergies, right. Can an AI predict the most optimal anti epileptic drug you take on the epilepsy problem. There are 26 anti epilepsy drugs. You can ask any neurologist, they will all tell you they were a lot of trial and error. They don't have any model they don't know what to give when they have patients and all of being epilepsy. They just try and see if it works. So this is not precise, right. So we also dealing with physician medicine. At the end of the day it's a fermentations problem. Something the machine can process much better and much faster than the doctor and by enabling people to collect all their OMICS data you also have a better idea from a machine perspective and from a medical perspective the UNICity that person based on her genome or other parameters so that's the kind of models we are talking about. This is what we are being on the platform.

: That's super fascinating Sam and gosh. I mean you put yourself in the shoes of the doctor and the patient and you've got 26 drug options for epilepsy. How do you make the best choice. I like to think of artificial intelligence as augmented intelligence. It's a platform that not only clinicians could use but patients could benefit from?

: Totally. So we have we will we really need everybody this is what I love about what we've been able to build so it's not only patients but it's also an end consumers, people who are just interested but also insurance companies, pharma, CROs, patients organization this is fascinating. I think that the fact that there are a few things we have done. You know I like to leverage on what the technology can offer us and there is a new technology, the blockchain it's not new. But I mean we can build on that so we'd be building on the blockchain in the public chain, the Ethereum. And so what it allows us to do really it allows us to do three things. Number one it allows via the smartphone tracks that you can program on the blockchain. It allows to write data matching depending on the problem that is broadcast on doc.ai that people called the data trial you know the question, "Can AI predict this or can AI predict that? You see the set of data that people can share with the project and that can be available for data scientists to build predictive models. So that's that's number one. Number two when you are a research sponsor, when you want to finance that research that as scientists you want to make sure that they reach the level of integrity in the data. You know we want to guarantee the provenance of the data which is exactly what the blockchain is doing again with a smart OnTrack because it's coming from different plats so on the blockchain on the smartphones Ican guarantee that, so the quality of that is that the integrity of good it and guaranteed.

: That's a fascinating application of Blackchain.

: Exactly. So that's that's very important. But I think for me one of the most important application that is very, very new and that I'm trying to explain. So thank you for giving me the floor today. That's on track for the financial transaction. So at the end of the day what we have built is a platform where we are considering that the medical data ease has value as financial value. So what we have done is we have put a financial value on every single biomarker in your body.

: Really.

: Yes. And then when the data matching happens when you want to participate in the data trial as a patient or consumer and you get financially rewarded for that. Right. And that's pretty interesting. So that's that's the third smartphone contract that does the financial transaction. And I find it very important for several reasons. I find it very important because I've always believed that people should own their data because it's ours. And also I think people should be financially rewarded when they generate that data and that data is used in the healthcare industry because after all that data already has a financial value we know that.

: Right.

: The only person that has been left out of the equation is the patient which is a pity because you want that patient to be engaged to be heard. And the last thing the last thing is in the U.S., The number one reason for personal bankruptcy is medical bills. I think that the block chain and the crypto world has this great opportunity to be able to rebalanced assymetry and it has the ethos of the open source movement and the features of the free market and that's the combination I think for healthcare. And it's very interesting.

: Folks. We've got Sam De Brouwer here talking about blockchain, AI. Her work at doc.ai. And she brought up a very important stat that two out of every three bankruptcies that happen are because of health care-related issues. So if you didn't catch what we just talked about hit the rewind button and replay it if you want to do that anyway. I think it's worth revisiting the value that she's provided here and her ideas. There's no doubt in my mind Sam, that you've been thinking about this for a long time and I'm very diligently.

: Yeah.

: So Sam can you give us an example of how you've used doc.ai to improve outcomes. Specific example?

: So we have very early as I said we are 18 months young startup so we have built the entire ecosystem. We have given access to our private data to about 500 people. We have a huge waiting lists all the testing went really well. We are actually pushing the public beta early summer so everybody can access. Yes. We have the IOS, via Apple and also the web up so online. It will be for screens free for people to connect at a time and place people own the data. We don't store anything it's on the phone. We are just an enabler. And we are about to announce our very first data . The RB has been approved and so on. So that's very exciting. So I don't know I don't I can't give you that kind of feedback. However there are a few value prob there from the patients perspective as well from the industry perspective where we see insurance is very high.

: Now for sure and totally get it right. I mean you guys are early on 18 months in but creating some major traction a waiting list for people that want to get involved. And there's no doubt that the appetite for us as leaders in health care for insights using these technologies is there. It's exciting. So congrats on and building it to this point and are excited to see where it goes from here.

: Yeah, will keep you posted Saul.

: Please do, please do. And so folks you could find out more about doc.ai at doc.ai. So Sam tell us about a time when you had a setback or failure what you learned from that moment?

: So that's hard to tell because that I had so many

: If you have to pick one of the many but you feel like okay this is the one thing.

: For all the founders out there entrepreneurs. I think it's very important very early on to embrace failure and to fail fast because it will be failure. That's a fact. So I think how they are. Me Really. And so to pick op one, they were all very learnful but one that is very very, I think timing. Don't wait for things which is very hard in health care by the way. that's a big dilemma, that's a big paradox but when you are dealing with innovation, you can't allow yourself to wait until everything is perfect. You have to iterate, you have to test, and iterate, test and iterate. And so when you know in the healthcare area arena it's really hard because there are a lot of things where you can't allow to make mistakes and you have to manage expectations even more than for any other software. So I mean we're dealing with a product that is with either force you can't have to dodge but that's tiny very hard. And I think have made some mistakes there and I just learn from it but there were so many so it's just it's just really hard.

: Now I get it I get it. Bottom line is just create, create, manage expectations and you're going to fail. Right? So just get over it, get over it and keep building right. I love it. Sam what's one of your proudest medical leadership experiences that you've experienced to date?

: So I think for me also my first medical company, device companies is Scanadu so clearly I think, one of my proudest moment is how we have been able to innovate and comply at the same time she's really really hard and how we've been able to develop that great relationship with EDI to understand what the regulator was expecting from us and what we were supposed to do and being able to build a road map together. I have been with them and it was really was really phenomenal so it's not easy dealing with the regulator but once you get that, it's something to be proud of because you know maintaining law complying is certainly not easy but it's so worth it. So once we do we create such a momentum for your team for the people who support you it's like opening a door that was not open before. So it feel special really.

: For sure and I understand that you guys were finally able to get 5, 10k clearance for the product.

: Yeah and so did my first company to U.S. Scanadu, just teceive it's 5, 10k clearance for the urine test. So it's one minute urine test, home-based. It's fantastic so well what we've done is we've put all these CTPs on one platform for leukocyte, nutrite, glocous, ketone and protein and you just dip that puddle in the car for you at phone and you wait one minute and it's now on your phone you take a picture of the panel and he tweaks car a change in real time between your phone and in the crowd. And it's parameter is given you a number so you can imagine for conditions such as pre eclempsia during pregnancy. You need to test yourself sample times a week for positional diabetes. There are many things really can you can follow up. And of course it's easy enough to hire a urine test reduce one minutes at a fraction of the cost of what the urine tests today. So I think for patients as well as for clinical research, the true application of artificial intelligence and do in terms of helping people, reducing the time, reducing the cost and of course when you've seen the margin for error because the machine reads numbers, alot of reading the color change only when your eyesight can be predictable. Not really quantifiable unless you go to Elaso.

: Yeah that's awesome. What happens if there is like a pink film over the camera. Are there controls that would show kind of hey the cameras now properly calibrated.

: Yeah yeah they are a few mechanismand you can imagine that with the yeah that's something also you have to do from a safety perspective. So number one the paddle has a QR code to verify the validity of the paddle because you can only use it once. If the paddle is not valid anymore you can't accuse it so the camera mean the algorithm recognizes that is been really hard to develop that algorithm being able to performing all those looks corridors, light corridors and if there are any elements disturbing the algorithm which will tell you that you have to redo it or take a your paddle or change on time that he cannot actually. But it took a long time. Because t was so into that operating in different light corridors and having central and corrected. That's a pretty heavy job.

: Fascinating folks the products is called Scanadu. The company is called Scanadu, Sam is part of that one as well. Go to links to doc.ai and Scanadu do and other things that we've talked about AI and block chain here. The transcript everything's going to be shown notes. What would you say. An exciting project within do.ai is today Sam?

: Oh we have a few but the first data tools are coming.

: That's amazing.

: It's just huge. So what is so exciting is the amount of people reaching out to us companies and yeah, we to know where do we sign. This exactly what we've been looking for. I think the 21st century there are few things we have to do differently when it comes to data when it comes to the model when it comes to the ownership when it comes to the inside so much we can do. But there's still a lot of work but at the end if you have the right ecosystem where everybody can work together it's an extra layer. I'm kind of exciting because as I said I think that we've been trying. There are many companies that have been trying to build models based on the data sharing and speed again. Healthcare is not be designed for that. So it's kind of art. However having that extra layer where you enable people to reclaim the medical data. We are always the eyes and becoming the seventh guardians of that data and being able to see a value of that data being able to see that in real time, it its completeness, in its do it but also its real world data and to see the value for third parties so that you can you know get more predictive insights for yourself but also how accurate research I think it's an equation that really works for everybody for all the pieces, the patients and providers the payers the people. So I think, yeah there's something in that model that is really I I'm super excited I don't I don't sleep that muchly. I have to go.

: There's no doubt you guys are and some wonderful things over there folks. The executive team over at Dach has some of the biggest brains in the business. Walter who is Sam's husband Sam and Jeremy Howard's work in over there, Alan Green. Check them out. They're definitely a company to follow. They are making some really fascinating splashes in our industry. Sam we're getting to the end here. We've got four questions lightening round style. It's the 101 with Sam De Brouwer on how to be successful with AI and health care. And then we're going to follow it with a book that you recommend to the listeners and then your closing thoughts. You ready?

: Yeah.

: All right. What's the best way to improve health care outcomes with A.I.?

: Oh it's to enable people to own their data and Souths.

: What's the biggest mistake or pitfall to avoid?

: To believe that to share the data within the existing healthcare system is possible. It's just not. It's not designed for that.

: Love that. How do you stay relevant as an organization despite constant change?

: Well we are a startup in Silicon Valley. The technology is AI, so by default who we are.

: I mean yeah as I said we are filling a little bit every day in order to major in order to book major successful.

: What's an area of focus should drive everything in a health organization?

: Oh I think the way I look at it but explanation so I think I explained what I mean for that the value of the data of real world data for the people who generate it?

: What book would you recommend to the listeners, Sam?

: So my latest book is, "Skin in the game from Nicholas Tayeb. He also wrote Antifragile, and Black Swan that spoke to me DPD. I'm an entrepreneur. And so every time I do something I have my Skin in the Game. I'm also a caregiver for my son I was 19 years old today. Now he's doing much better. Isn't it Chinese fantastic. He's a..

: So great to hear.

: So what I do with health care is also because I have my skin in the game because my son has this skin in the game so when you have your skin in the game, winning of things is slightly different.

: Totally agree with you Sam. Folks you could find all the transcript notes show notes and links to the things that we've talked about. Just go to outcomesrocket.health/docai, you can find all that there. Sam before we conclude I'd love if you could just share a closing thought and then the best place where the listeners could get in touch with you or follow you.

: Sure. So my niece and my last in the woods. Health care is really hard. I know so many people tried and are still trying. And I think deep deep inside we are all human beings and we want to do good. We finally have tools that might enable us to create some change. So do not despair. Let's keep moving. Let's move forward and let's try to make it happen. And if we can move the needle a little bit every time it's huge because we are talking about health care. We're not talking about you know small stuff and you can email me directly. I'm just going to keep my name address which samsm@doc.ai. Happy to take your e-mails and answer.

: Outstanding. Sam, hank you for that message of hope. There's no doubt you guys are making some strides in this space of helping people own their data and recognize the true value of it. Excited to keep up with the progress. And again we just really want to thank you for spending time to share your thoughts with us.

: Thank you so much for having me. I wish you a wonderful day. I love you.

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Recommended Books:

Skin in the Game: Hidden Asymmetries in Daily Life

Best Way to Contact Sam:

LinkedIn: Sam De Brouwer

Email: samsm@doc.ai

Mentioned Link:

Doc.ai

Episode Sponsor:

Addressing the Opioid Epidemic with a Mindful Meditation Solution with Dr. Ruben Kalra, Founder, CEO at WellBrain

: Welcome back once again to the outcomes rocket podcast where we chat with today's most successful and inspiring health leaders. Today I have a wonderful treat for you. I'm sitting here with Dr. Ruben Kalra. He is a physician and MBA, is the co-founder and CEO of Wellbrain. It's a mission driven company addressing the opioid epidemic by providing a proprietary scalable digital health platform that decreases human suffering and optimizes patient function. He's a Harvard trained medical doctor with double board certifications in anesthesiology and pain medicine Dr. Kalra is a physician and entrepreneur passionate about combining mindful meditation practices which you all know I'm passionate about as well and biofeedback technology to customize a better patient experiences. Now Dr. Kalra also is a partner and current president at pain management consultants. It's a practice in the San Francisco Bay Area with top trained physicians who take comprehensive approaches toward addressing pain therapies. Dr. Kalra is passionate both for helping patients as well as improving the way that we address the opioid epidemic. And it's with great pleasure that I welcome him to the podcast. Ruben welcome.

: Thank you. I really appreciate the opportunity to be on your podcast. I'm a fan and I was considered and honored to be invited and share our knowledge and experience at Wellbrain and hopefully share with other leaders and even help more patients out there.

: That's outstanding Ruben and I really appreciate that. So tell me what is it that got you into the medical sector to begin with?

: Well the young age my dad a research professor at the University of Southern California medical school he's actually been there I guess almost 50 years. Is the kind and the smartest man that I know and you know, he inspired me to make a positive difference in the lives of others at a young age. And he was a researcher and I always liked the social aspects and being on the front lines and I just remember a young age knowing that it wanted to be a doctor.

: That's so awesome and shout out to your father for having such a great influence on you. So fast forward now Dr. Kalra, you've got a tremendous impact in your community, your leadership as a physician and now entrepreneurship as well. What do you think a hot topic that needs to be on every medical leaders agenda today. What is that and how are you guys approaching it?

Well I think the one buzzword out there is not necessarily a buzzword but fast approaching machine learning and artificial intelligence. I don't think people realize the positive impact that artificial intelligence is going to have in helping make better decisions and guiding care. At Wellbrain, we're integrating machine learning and artificial intelligence that help the 100 million patients in the United States living with chronic pain. And I think the beauty of our artificial intelligence is rather than this cookie cutter medicine approach we're going to be able to unscale to the power one where we're providing personalized care, using data that and knowledge provide better patient experiences and outcomes.

: That's really interesting and so I'm always fascinated by companies that are able to take it as a buzzword. Like you said and actually apply it. So Dr. cholerae can you give us an example of how Wellbrain you and your team there are creating results and improving outcomes through this?

: Yes absolutely. I mean I guess one of the good example is just imagine in the doctor's office, a patient comes in they get handed an iPad which has the Wellbrain platform on there and the patient answers a battery of different psychological questions and then based on the results customized the mindful meditation and chronic pain management program that doesn't involve opiates to be personalized physical therapy. And as we get more and more patients into our program tens of thousands of patients at this point we're learning what works and what doesn't work for patients. The good example that we have a 42 year old female who maybe had Bachelor's degree also has some anxiety depression and some addiction issues. We're able to sort of identify that using our program and I can tell you so far with the data that we know we sort of have to approach the anxiety before we get to the addiction. Otherwise we won't get this patient engaged in the program and this is just based on the data that we're looking at and what we're seeing so far with Wellbrain has been pretty impressive with the patients that are using the program. We're seeing a reduction in possibly emergency room visit, a reduction in opiate use. And most importantly an improvement in pain. And I think it's only going to get better as we get more patients in the platform and we learn from them,we'll be able to personalize the management program for each patient.

: That's super fascinating Ruben. And folks if you're curious the website as wellbrain.io you'll be able to take a look at what they're doing really just kind of taking a look at this problem of chronic pain management. I mean it's an issue that that is really affecting millions of people in the U.S. and why not take a note from the east and take some of these medication practices and combine it with the science of machine learning and do something about it. Now as I understand Dr. Kalra there's there's a Buddhist monk as part of your development team?

: Yes. Yes so the Sean Pargo was a former Buddhist monk and yet of all things he approached me and then a couple of years ago and said this was sort of his calling to bring mindful meditation to those folks that might not otherwise be exposed to it. And he also educated me that there were specific meditations that may be more effective for certain medical conditions than others and he helped create a pretty robust platform where we have specific meditations for plotting or knee surgery or specific meditations for migraines and post-traumatic stress disorder. It was sort of terrific having this foundation of Michael meditation which is where we started. And now we've sort of moved and realized that mindful meditation's fantastic but we can continue to customize it and provide patients other validated evidence based modalities that are help for pain such as personalized physical therapy. We just partnered with like routine Behavioral Therapy Service so that we can provide patients with different modalities that are helpful and then like I said in the background use machine learning and artificial intelligence to personalize the recommendations for our patients.

: Super intriguing. And so folks if you're looking for a different ways to tackle this problem the opiate problem and also the pain chronic pain issue. Something to take a look at. So Dr. Kalra, as far as getting folks on the platform are you guys mainly targeting payers are you mainly targeting providers. Who's your main audience may Customer?

: Yeah right now we've been targeting providers and it's been sort of figure out who the ideal customers are and providers who are looking for other options have been our initial target. But like anything else everyone's eager for opiate epidemic solutions so that we have hospitals Kaiser specifically their innovative team be excited about what we're doing and Evencare to come to us and said well if you can make a difference we're interested in the end of the day we want to make a great product was helpful and it will not only be in the interest of patients but providers hospitals and even the pairs.

: Very cool. I think it's a super fascinating approach. Can you give the listeners an example of a time when you had a setback, what you learned from that setback and how it's made while brain or even yourself stronger because of it?

: Yeah definitely it was early coming out of the gate. I guess a little brief history that we started Wellbrain, we didn't intend to start the company, it sort to meet a need or practice a few years ago before the epidemic came to fruition and the news we started to see a lot of patients are coming to our offices of pain management where they maybe wanted opioids for the wrong reasons maybe they wanted it for anxiety, history of addiction or insomnia and the child we had at the time as patients didn't want to see a psychologist or a psychologist and take insurance so we were taking on a lot of risky patients. Incidentally my partner Dr. Longton one of the founders wash it had talked about in meditation neuroscientist that went to India studied the brainwaves the month and came back with the first measurable form of meditation. Why is that important said. Ruben I look at all the data and the data from mindful meditation for pain anxiety depression is phenomenal. It's way better than anything that we do and so we sort of put two and two together and the genie in office we can do a battery of psychological tests and based on the results give me my meditation in the office and instead of patients complaining about reading about the Kardashians and US Weekly well while Zollverein write at this because essentially the most management tool and over the course of three four months we started page we started seeing patients go wow this is traffic. I'm getting better I'm using less opiates and the mistake that we made is we said OK let's go to a conference we have something that's going to be mind blowing. It's terrific. I went to a conference for pain doctors and pretty much the response at that point this was years ago was actually not that long ago it was "a Dr. Kalra, you're an idiot" on mindful meditation. But the press conferences are like why do we think this is something fantastic. You know there's a bias coming from San Francisco and mindful meditate. You know the rest of the world they want it to hear too. So we we sort of took that lesson and like doctors and it's maybe something unique about our companies what role as well it's shown the data. So when it did a 200 page study said noted that 60 percent of patients who were offered this platform would want it. So basically we could come back and tell doctors say 6 percent of patients who use this in a bunch of offices of the country would actually want it if you offered it to them and the other cool thing that transpired was while he did this in the medical office that they actually reported reductions in both physical and emotional pain those people were like OK patients only want this but it uses that money you really you're actually going to maybe get better.

: Love that. What a great story. Ruben and thank you for sharing it. You guys didn't let that stop you. You developed the clinical data to support and then you brought it back and now it's starting to get some traction. So kudos to you and your team for getting that going.

: Thanks Saul, I appreciate that.

: And I think that's a lesson for everybody listening to take a lot from. So you could have your product but when you're playing in this healthcare space you really have to have your evidence based results out there. And the U.S. is one thing,if you're looking to go beyond they do it differently in other countries and then it's the payment model making sure you have that payment model in place and finally the logistics to be able to support the manufacturer, production and distribution of it. And Dr. Kalra is really highlighting the importance of this clinical piece. So again just talking to Dr. Ruben Kalra from Wellbrain. Check them out at wellbrain.io. Fascinating approach to chronic pain. So taking a look at the other side of the coin, Ruben, tell us about one of the most exciting and successful moments you've had in medicine today?

: That's a tough one. I mean I definitely enjoy getting patients better. One in a one on a daily basis. But with wellbrain and digital health I think there's an ability to scale that to a much larger audience and it's a proud moment. Sometimes they know. Several years ago before Wellbrain our group was approached by this entity top acquires and Sensing that working for a big medical group and most of the other doctors sold and we said no. And I think one of it was just trying to maybe let a lot of money and label but there's something to be said about controlling your own destiny and control your own time rather being an employee. And with that decision it enabled us to have her own schedule and essentially enable Wellbrain to come into fruition wouldn't have that would have happened otherwise just because we were able to scale her own we decided on time schedules and focus on something that was going to be much much bigger than our own practice and the patients that we helped.

: You know that's so fascinating and yeah there's been a huge wave of I mean I think we're on the on the end of it now because the majority of physician practices have been acquired and so kudos to you and your team. Dr. Kalra for holding strong and now having a huge impact because of it.

: Thank you, I appreciate. You ever heard of a dying breed like Prabal. But we hope so. We hope there will always be a room for private practice doctors.

: You said like travel agency cozI love it. Oh man. So while brain is obviously an exciting project within Wellbrain itself, Ruben, what would you say. An exciting focus area or project that's going on right now?

: I think one of the most exciting things we're we're doing right now is we actually just recently acquired another digital health company soon to be announced probably as we called Nevoked.

: And what does it called?

: Nevoked, N E V O K E D.

: OK, Nevoked.

: And it's a company that uses big data and behavioral phenotyping to basically help patients with postpartum depression. Postpartum depression underdiagnosed and that only affects families children mothers. And what's unique about the company is not only another a vertical force and we know the company and the management team for a long long time. We always talk about working together but we are sad about the technology that they're going to bring to us for the chronic pain which is not only with Wellbrain we're getting a valuable objective data through surveys and questionnaires and patient profile but we're also with Nevoked and to be able to not only help manage patients but manage patients at the right time because with behavioral phenotyping, we will know a patient let's say through their phones. Have they been on the phone the entire night looking up the web or and not sleeping today. Do we need to send them insomnia medication to get them better. Then I left their house in 3 days. Maybe they needed to for a wellness check to make sure they're not profoundly depressed. And I think we're excited about the future of not only artificial intelligence but helping deliver the right care at the right time and acquisition of Nevoked will not only help patients with chronic pain but really be able to soon enough cases of postpartum depression with a nicely intergrated product.

: That's fascinating. Dr. Kalra, what percentage of what you do then within these companies and it's pretty exciting. You know the acquisition of this firm. What percentage of it is mental health including your workout Wellbrain.

: I would say almost 100 percent mental health. What's interesting about chronic pain is almost 60 percent of chronic pain, 6 percent of patients with chronic pain have some degree of anxiety or depression or what we would define as a mental health condition and too often it's challenging to figure out the chicken or egg which one came first. The pain came first or the anxiety and a lot of time it's a self-fulfilling prophecy the patient hurt, they can't move, then they start getting aches about moving then they get depressed because they can't do what they like or muscles get because they're not exercising. And it fuels this cycle that sometimes can spiral into addiction and overdose. Definitely, everything I do is focus on mental health.

: So fascinating and and I think listeners were getting to the point where we've got to make this realization and they feel like you know Dr. Kalra here and his and his team have made that connection. But I think as as a whole in health care, we've got a beginning incorporating the mental health piece with the physical health piece in a way that's impactful and it's super exciting Ruben to see that you and your team are doing that.

: Thank you, I appreciate that Saul.

: So getting to the end here what would you say. Right now we're going to build a leadership course. OK. And so it's called the 101 of Dr. Rubin Kalra on how to treat chronic pain and mental health to improve outcomes so I've got four questions for you lightning round style followed by a book that you recommend to the listeners. You ready?

: Yes.

: All right. What's the best way to improve health care outcomes?

: I'm a specialist so this will be surprising coming from a specialist a specialist doctors say but is being proactive and preventive rather than reactive. Digital Health and artificial intelligence is going to help prevent problems before they become problems and at least enable unable to manage them better?

: What's the biggest mistake or pitfall to avoid?

: Making sure key stakeholders are involved in the decision making process when you're bringing a product to market. This was important at Wellbrain where we felt engaged in positions was important in eliciting positive change on the part of patients.

: How do you stay relevant as an organization despite constant change?

: And the tough one but being adaptive and iterative and always keeping your eyes on the ground and what's coming next. I think having a noble organization such as at Wellbrain where our offices are essentially below a pain practice so we can actually rapidly go upstairs, deployed product get feedback continually get feedback from the customer and continue trying try to develop in a positive way.

: Outstanding, and what is one area that should drive everything in a health organization?

: I think the mission every company has a different mission for Wellbrain, We, our mission is pretty simple. We're to protect on the obesity epidemic by trying to provide physicians and patients with everything that isn't obese to get them better. And by having this focus attracted just a plethora of phenomenal people to come to the Wellbrain team who are not only focused on delivering a great product but actually making a positive change in the community.

: Love that. What book do you recommend to the listeners?

: My wife give me a hard one part time when we were surfing at Costa Rica and I brought along a survival in Auschwitz by Primo Levi and she said that was a pretty hard read for being a shore of Costa Rica. I tell you. It's the story of a survivor of the Holocaust. All my time at Auschwitz. And while it's appalling it is a testament to the power of the human spirit and our ability to overcome. And as a founder and entrepreneur, we are heartily tested and this book you know, I just referred to HealthSpring restrength during challenging times.

: Wonderful recommendation. I haven't read that one but I'll add it to the list Ruben. I had a chance to read Viktor Frankel's Man's search for Meaning and boy.

: It's terrific book.

Oh my gosh. Yeah I mean talk about giving you strength when you need it most. Just inspirational. I Appreciate that recommendation. Hadn't heard about it before. Listeners, if you're in this entrepreneurial space or also as a provider looking to tackle huge challenges. Take this book make a note of it and read it. You could find all the show notes as well as a transcript of our discussion go to outcomesrocket.health/wellbrain, that's well, W E L L, brain, B R A I N. This has been a ton of fun, Ruben, I appreciate the opportunity to connect with you if you can just leave us with a closing thought and then the best place where the listeners could collaborate with you?

: Oh awesome, sure. Her life is a gift enjoy it maybe as a clinician I've seen a lot of my debt a lot of debt during my time but burnout is real especially for founders. As I told my patients you take good care of yourself before you can take good care of others. So both are high for go surfing and smell the roses don't travel. If you're looking for a rational reason to do that evidence basis since I'm a doctor. Studies have shown by taking vacations shut out your phone, it'll actually make you more productive and a ton of fun.

: I love it. I love the evidence base there at the end and the encouragement. What would you say the best place for the listeners to reach out to you or collaborate with you, email address?

: Yeah,sure. They can email me anytime. It's just my my first initial rkalra@wellbrain.io.

: Outstanding.. Again, just want to thank you Rubin for spending time with us this has been insightful and really excited to see where where your company takes the space in the future.

: Thanks I'll look forward to listening more of your podcast.

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Recommended Book:

Survival In Auschwitz

Best Way to Contact Ruben:

LinkedIn: Ruben Kalra, MD

Email: rkalra@wellbrain.io

Mentioned Link:

Wellbrain

Episode Sponsor:

Using Deep Learning to Transform Radiology Practice with Kevin Lyman, Chief Operating Officer and Lead Scientist at Enlitic

Thanks for tuning in to the Outcomes Rocket podcast where we chat with today's most successful and inspiring health leaders. I want to personally invite you to our first inaugural Healthcare Thinkathon. It's a conference that the Outcomes Rocket and the IU Center for Health Innovation and Implementation Sciences has teamed up on. We're going to put together silo crushing practices just like we do here on the podcast except it's going to be live with inspiring keynotes and panelists. To set the tone, we're conducting a meeting where you can be part of drafting the blueprint for the future of healthcare. That's right. You could be a founding member of this group of talented industry and practitioner leaders. Join me and 200 other inspiring health leaders for the first Inaugural Healthcare Thinkathon. It's an event that you're not going to want to miss. And since there's only 200 tickets available you're going to want to act soon. So how do you learn more? Just go to outcomesrocket.health/conference. For more details on how to attend that's outcomesrocket.health/conference and you'll be able to get all the info that you need on this amazing healthcare thinkathon. That's outcomesrocket.health/conference.

: Welcome back once again to the outcomes rocket podcast where we chat with today's most successful and inspiring health leaders. Today I have an amazing guest for you. Someone that's had a contribution in healthcare in a lot of ways from the bench to the frontlines. His name is Kevin Lyman. He's the chief operating officer and lead scientist at Enlitic. Enlitic is a medical Deep Learning Company. And twice named one of MIT technologies reviews 50 smartest companies where he applies deep learning to the early detection of cancer. Kevin is also the founder of the inventors guild a team of over 40 students from 10 of the world's top universities who earn course credit and money consulting for startups. Competitive at heart, Kevin is a former professional Halo 2 player and was once the world's highest ranking Warlock in World of Warcraft. Not an easy thing to do ladies and gentlemen. He has since focused his energy elsewhere winning over a million dollars in the words from hackathon and business plans to competitions. And now he's with one of the most forward thinking health companies, Enlitic. So it's a pleasure to welcome you on the podcast Kevin.

: Pleasure to be here and thank you for having me.

: Absolutely so anything that I'll leave out there in your intro that maybe you want the listeners to know about you?

: No, I think you covered my background pretty well. It's been a long journey to end up in healthcare but I'm pretty excited to be in the space now.

: Hey man that's really great. And you know I'm just curious why health care. Like how did you end up here?

: Well I come from a family unfortunately with a lot of medical disability. In particular I grew up caring from my mother who loved bed down for multiple sclerosis and so that had me sort of growing up in that environment where I was forced to recognize the importance of patient care and that exposed me a lot to being in and out of hospitals and needing to care for in different ways just coming very close to that type of problem. And throughout the remainder of my childhood unfortunately a number of my other family members suffered from many different types of cancer and other rare abnormalities. And so it's always just been something on my mind. But even outside of that the most important thing to me has always been use cool technology to solve important problems. And in the quest to do that, I had started a couple of companies one of the machine learning space on the medical device space and running both of those concurrently. I've been introduced to Jeremy Howard the original founder here at Enlitic and he just really got me inloved with this idea of the intersection of those two things of machine learning and medicine and really just made me realize that even being an engineer in today's world, I have an opportunity to be a doctor to then ever since I've just been really in love with that idea.

: That's super cool. And what a great story of how you ended up doing more work within medicine and and folks Kevin's been a speaker at TED MED. He's also been a participant of the hive. So he's he's doing some really neat things here in healthcare. So thanks for sharing your story of how you ended up here. So sorry to hear about your mom and sort of the hardships and it sounds like these are the things that really kind of formed your basis your empathy which I think is something that is missing in many health tech companies. So really great to hear that that you do have that I couldn't possibly agree with that more and I appreciate you saying that.

: I think that's probably been the biggest learning experience for me being in healthcare that unlike any other industry I've been in, empathy is more important here than anywhere else. And every decision really needs to be made with the mind set of how will this impact patient down the line.

: Man I couldn't agree with you more. So tell me Kevin, what do you think today is a hot topic that needs to be on every the leaders agenda and how is Enlitic approaching that?

: Well I think I'm obviously a little biased here and I'd say that intelligence and I think that that's probably becoming increasingly more and more unavoidable from pretty much any health care professionals perspective that AI is attending Ubiquiti and it's getting to the point where these promises really are coming into fruition and very, very quickly. But given that that's something that is really on its way in I would say the thing that people really need to be worried about right now is how to prepare the infrastructure for the largest for AI but for all of these other technical innovations that are right down the road if we don't set up our systems now to welcome these new tools in, now we're going to have to deal with that in the future. And even though we don't know exactly what all of these solutions look like today I think we do have a reasonable idea of what needs to be done to get our infrastructure into place to actually implement some of those solutions. And so as far as actionable things go today I think that's really what should be on everybody's minds just infrastructure and planning for that inevitable upcoming future.

: Kevin, I think that's such a great point. In fact I'm putting together health care meetings starting in September where our theme is innovation is implementation in healthcare. And you got to be able to implement and you've got to do it well for the sake of the listeners, Kevin, I love if you could just level set everybody on Enlitic. I don't want to assume that everybody knows what you guys do who is Enlitic, what problem you guys solve, who do you solve it for?

: We're a team of about 16 data scientists and fulltime radiologists out of San Francisco along with a team of about 60 plus part time radiologists that work with us and we develop clinical applications of artificial intelligence. We do this sort of all across the spectrum of digital diagnostics but our primary focus is within radiology and so we train neural networks and other forms of machine learning models to interpret medical data primarily medical images and text in order to assist radiologists and other diagnosticians with the clinical diagnostic process and that can mean a lot of things. But in general we try to enable them to perform diagnoses faster more accurately and in many cases with insights that they otherwise couldn't. And a lot of our focus up to this point has been BORGIALLI in chest imaging. So building solutions to read things like just x-rays and chest CDs but we're increasingly expanding that aiming for whole body coverage over the next three or four years hoping to have models that regardless of where the images and what type of study it is ideally have something that can work with the doctor to enable them in that diagnosis. And I think there's a lot of many very different types of solutions. We've implemented to this effect. But for the most part they're usually focused around trying to spot things within the images and help radiologists understand what those are and how to treat them.

: Outstanding. Now thanks for that level setting listeners check out their website. Go to www.enlitic.com that's E N L I T I C, dot com and you'll see some of their applications. Some of the news, some of the updates, their mission. I think it's really interesting the way that they're using deep learning as a tool to augment the work of radiologists and it's pretty inspiring stuff that you guys are up to there Kevin. Tell me can you give us an example of how you and your organization have created results or improved outcomes by doing things differently?

: Yeah I think that this starts to play a little bit back into that whole empathy thing but one of the big insights that we've had in working on these problems is that AI is very much a user experience problem that I think a lot of people like to look at AI development as being hardcore software development. I think when you are very close to the field it's very easy to assume that but it's an incomprehensible amount of very intimidating math, a lot of software that might require a lot of specialization to understand. But what I think the helpful way to look at it is that the art of building AI is really building black boxes. It's building a system that is really good at taking a given input and extracting a desired output from that. And so once you've built that black box, the remainder of the problem really becomes what do what you want to go into that black box and what should subsequently come out of it and to train that black box requires lots and lots of examples of that input output pair and so very quickly it becomes a problem of working with people more so than crafting good software. So we've taken this approach then of building our own network of radiologists and building our own tools that these radiologists can use in order begin to label historic data to generate this input output pairs that we can then trade models on. Then we've had to go this route of building all of this in-house because while tools exist that can be used for these purposes they don't really enable you to be very expressive. And another very important insight that's come out of this is that you can collect all the data in the world but ultimately it's meaningless if you didn't ask the right question when you were collecting that data then I like to use an example of that in the interpretation of just expertise where we find that a lot of people these days are trying to train models to identify things like tuberculosis in a chest X-ray. But unfortunately people don't diagnose tuberculosis with just the x rays and so it's a little jumping the gun to try to shoot right for a model doing the same that what people look for as far as TB goes in a chest x ray or signs they look for consolidation of calcified lung nodules, plural of fusions, things that are indicative that the patient might have TB, but in reality you need more information than just what is present in that image. I would also need to know about your clinical history. We need to know what country you're in. I would need to know if you travelled somewhere recently where TB is very frequent. If you've been coughing and unfortunately the X-ray alone doesn't have all of that information in it. So if the question you ask your radiologists when they're labeling your training data is does this patient have tuberculosis will still try to answer it for you but will be answering a flawed question. Unless the data you're gathering is flawed. And what we found is a must we're building these tools. We can't structure it the right way to ask the correct questions. And unfortunately you don't realize you're asking the wrong question until very far down the line. And so that's why we wanted to make sure upfront that we're building with this kind of concept in mind.

: What a great insight you've provided there Kevin. And oftentimes you don't realize this like you said until much later in the process. Can you share with us a time when you had a setback and what you've done and what you learned from that?

: Yes actually the example I just gave is a good example of exactly that. The very first thing that we built was a fracture detector because..

: Ah, OK.

: One of the most common types of things that people come to the doctor with as far as a radiologist goes are fractures and then often in the extremities like a wrist fracture for example. So we built a model that could ingested an x-ray of the wrist towards the arm and would automatically circle a fracture in that scan if it found one. The intent being that when the radiologist brings the scan up it's a lot easier for them to find the fracture if a model already did it for them.

: Right.

: And when we collected the data for this the way that we tackle it, this was before we had all these systems we've built ourselves in place. We looked at what sort of image reading tools for radiologists exist today that are open source that we could mess around with and we chose one particular and set up a bunch of mac books for a radiologists to use. But all we did was load those x-rays of historic x-rays from our partners. And we asked the radiologists to circle the fractures and unfortunately that is not a very specific set of guidelines to give them. And so the data we got back even though you and I as non radiologists circled the fracture might seem pretty straightforward to them it could mean a lot offense. What do I do about the non wrist fractures. So the fractures that exist in the elbow or the fingers were somewhere else. Now what do I do about sesamoid bones which look like fractures and are often reported like them but are not fractures how tightly do I contour anything that I circle that was a big problem we and where when we trained the model the first time we found that it was getting all sorts of false positives and false negatives. So the first thing we did was we went back and we looked at the training data collected by each of the radiologists that participated in this exercise and we found that one person was just completely off the mark. They missed all sorts of fractures. And so we completely wiped them from the training data and we retrained the model and we find that that drastically improved results. And once we got rid of the bad actor things improved but we still had a big problem which was that the model in addition of getting the fractures correctly was circling all sorts of little artifacts that were not fractures they were just meaningless little blips. And again looking at the training data we realized it was because one of the radiologists who prepared training data did not know how tightly to contour them because we didn't tell them how tightly contour it. So he circled every fracture as tightly as humanly possible but a fracture just looks like a line. It looks like if you were to pluck a hair and put on a white piece of paper it's just that very thin line. If you zoom in on it enough anything looks like that any digital image when you zoom in enough looks like just a lot. And so having the model placed attention just that tightly on the fracture caused it to lose sight of the fact that the context around the fracture is what makes it a fracture. It's not just a line anywhere. It has to be aligned through otherwise healthy tissue. So what we did was we went back and we modified that training data to programmatically expands the size of each of these regions of interest they drew on the pictures by 30 percent and then retrained the model. And when we did that, we got amazing results. But the big thing that it really ingrained in us was this understanding that you have to be extremely specific when you're asking these questions where people are free to make up the rules on their own right. So now every time we launch one of these tasks it usually comes with about a hundred pages of these guidelines and several rounds of tests that we make them go through to begin with.

: Wow, what a lesson learned and sounds like at this point for the chest imaging you guys have set some parameters very specific guidelines to ensure that you guys get more success upfront.

: Yup absolutely. And that's been where a lot of the difficulty comes in.

: My goodness. And it's a lot of work. You guys have to do all this stuff up front but at the very least you get what you need and and when you don't know what you're looking for you don't know what you're looking for right now. Now you do.

: Yeah. No, actually it's hard enough that most of the time our task is finding any number of nondescript needles in a haystack. So we're learning more and more specifically about the problem.

: It's a good way to put it. Kevin what would you say to date is one of your proudest medical leadership experiences?

: You know I think it's hard to answer that specifically limited to medical leadership but I think it's been incredibly rewarding to see as the company progresses just that are the way that we vocalize our meticulousness about this data because of how ultimately this is how we ensure the best patient outcomes to see how well received that's been in this evolving market. There has been great and very rewarding because early on I think there were a lot of deceptive actors in this space that made a lot of very bold claims about what this technology could do and very quickly people realized that the promise is not there yet and it soured them toward the market and it's been very rewarding to see that with us being up there being very transparent about this being the voice of this is what we really can and cannot do in this space. How well that's been received I think that that's I say very rewarding because being in healthcare transparency is everything. And even though this is the intersection of technology and healthcare I think that's more true now than ever. And so it's amazing to see that other people agree with that message. And that that's something that's leading to success. But outside of that to sort of nail to some concrete moments, I think one thing that was very rewarding for us was last year doing a blind test. And this was something that I alluded to when speaking at TEDMED that we did a blind test mobile group radiologists that found that our lung cancer models weren't just picking up lung cancer but they were often discovering malignancies up to 18 months earlier than human radiologists were that this emergent insight came out of this approach to knowledge discovery and data integrity. I think really illustrates the true power of these types of solutions.

: Wow that's really interesting 18 months prior?

: Yeah.

: That's amazing. Well congratulations Kevin. I mean no doubt that it's tough right. Because when you're in the market and you see the potential in a technology what it could do and then all of a sudden the bad apples will column come in and sort of muddy up the water. You guys have stayed consistent and you've stayed true to making this data as as clean as possible, working with the best parameters to get the results that you guys are looking for and you've gotten some wins so congratulations on that. And these results I mean 18 months beforehand. I mean that's huge.

: Yeah and this is those are the main reasons that we pick lung cancer is an early thing you're working on. There were some abnormalities that it doesn't matter how early you pick it up. Unfortunately there's nothing we can do. But with lung cancer, the early you pick it up the more likely the patient is to survive. Then I think 18 months is quite significant. And so we really hope to see that be something that it's clinical practice if not this year or the next.

: That's wonderful. And the other thing that you said Kevin that really struck a chord with me is the other factors. Right. You can't just rely on the image itself what's the context of this image? Today, I think there's a larger influence of the Social Determinants of Health and the influence that they have on specific diagnoses. And you talked about hey was this patient traveling or where did they live or what did they do. And these these things are now also included in the models that you guys are putting together?

: Sometimes those factors are put into place sometimes they're not. It really depends on the specific problem that's being solved. But in the case of trying to build a general system for the diagnosis of chest x-rays just to limit the problem the one specific study time. I think it's critical to keep in mind that it's not enough. Just look at the picture. And if that's all you have then the answer you provide should take into account that that's the only information you have. In clinical practice. The hope is to use not just the report the image itself but any report that might exist about it. Any patient history that might exist part of the reason that we have that 18 month early detection is because of our use of longitudinal data. So the patients whose data train that model had several years of scans that the model has learned from and as well as a lot of demographic patient information and biopsy results and all sorts of other clinical data that has enabled us to extract those emergent insights then more and more so you'll see that become the common way that these systems are implemented where you'll have multiple models in tandem reading lots of different types of data and then they'll marry that output in the end in order to give you a much better representation of what we believe is going on.

: Fascinating folks again just a reminder If you've tuned into this podcast a little bit later I've got Kevin Lyman here chief operating officer at analytic you could check them out at www.enlitic.com. They're doing some pretty amazing things. They're at the forefront of AI and in radiology. Check them out. Press rewind on this podcast because conversations have been really good. So tell us a little bit about an exciting project that you've been working on today?

: Well all of it is very exciting. By the way I think you know one thing that is going down a wall unfortunately my way of boiling it down will be to expand that a little bit further back. I think one thing that's got us all extremely excited right now is we've had a lot of innovations around how to scale this process horizontally across the vast majority of digital diagnostics, as I said it's helpful to think of these systems as a black box that we can build a couple of specialized black boxes. But at that point the problem becomes around tuning it to all these different data sets that we collect so that it can work to a lot of different types of problems and that's really what we're focused on right now. How do we take something that does fracture detection and arrest or or lung cancer detection in the chest and now translate that to look for anything anywhere in the human body. And that's something that we're currently fundraising for right now. And as we close that round we'll be moving towards actually starting to act on that scale and I think that's really where we're going to see some of the biggest patient impact down the line because up to this point each of these solutions each type of study each specific problem you tackle has been a massive lead time in the development of those systems. Look at how long it's taken us to get where we are today or how long it's taken our competitors that many of whom are also doing good work to get where they are. But the exciting thing I think is as far as what we've recently come across is now greatly reducing that cycle to be pumping these systems out with very high quality for many different types of problems on a very short turnaround time.

: Truly exciting and it's awesome that you guys are aiming toward this broader spread of these solutions across different applications. It's pretty exciting man. Congratulations on that.

: Thank you.

: So Kevin time does fly my friend. We could talk about this stuff all day but we do have limited time here on the podcast. We may have to do a part two but for now we're getting into this part of the podcast where we walk through set up a syllabus for the listeners. Since you mentioned earlier today sort of the importance of setting up the appropriate infrastructure for these types of innovations I love to take the focus of this course that we're going to put together for the listeners and the lightning round around that structure implementation idea. If you're good with it.

: Yup.

: Awesome. So we're going to call this the 101 of Kevin Lyman on setting up the infrastructure for innovation. And so as we go through this lightning round I've got four questions for you around this focus. And then we'll finish that up with the book that you recommend to the listeners and a podcast. You ready?

: Perfect.

: Awesome. So what's the best way to improve healthcare outcomes?

: I think within the context of setting up infrastructure for any kind of administrator or leadership at the hospital I think it's important to re-evaluate the systems that are in place today. And I think we find from a lot of the partners we work with that they're still using systems from 10 plus years ago. And I know that all of these tools are very expensive to put in place and there's a lot of risk involved. But technology has progressed quite a bit in the past decade and I think it's really time to start updating some these tools to be more receptive to the incoming solutions from A.I. and other improvements and software that ultimately are going to lead to much better patient outcomes. But only if we set them up for that right now. And I would extend that by saying just a little bit but nothing is more important than patient safety. Then of course what stems from that is patient privacy. But anonymization is quite good today and so is the siloing of patient data. And while it might be very scary to give up patient data in this way I think the appropriate systems are in place these days that the risk is greatly reduced. And I think it's worth the risk, it's justified by the benefit that comes from sharing this information with the research community that can do amazing things with it.

: Outstanding. What's the biggest mistake or pitfall to avoid?

: Surely within this context of infrastructure I think getting to married to any one particular system can lead to big problems. I think we found with a lot of our partners that they put one system in place and it introduces problems. And rather than fixing the underlying problem they put more and more bandaids in place and so ultimately 10 years down the line when it is time to update that infrastructure. It's a massive amount of work in undoing all of these individual solutions that were put in place. If you come across a problem you solve the underlying problem.

: Great message. How do you stay relevant as an organization despite constant change?

: I think in our case we thrive on that change is where research organization but for a lot of these other groups that are sort of stuck in ways where it's a lot harder to adopt this change. I think it's important to listen to the research community and listen to evolving methods of how one measures risk in the field. I think the FDA is increasingly catching on to that and is growing more and more away from lots and lots of expensive clinical trials upfront and more and more toward what's pulling in the fields after doing a little bit of checking and then monitor it in the field to see how it does. And I think that this is a really powerful philosophy that in software development is pretty much what we call agile. But I think that hospitals in particular need to adopt this mentality a little bit more and understand that while there is risk involved in taking some of these leaps, you can minimize that and you'll get a lot better data by taking the leap and seeing how it goes. As long as you get the appropriate fixes in place.

: Beautiful what's one area of focus that should drive everything in a health organization?

: Patient outcomes that should be the number one thing that drives every decision. And I know that a lot of times financial decisions are hard ones that need to be made in order to optimize for patient outcomes in the grand scheme of things. But ultimately that's the only reason that money should be the focus in mind. For all others it should always come back to patient outcomes and everything should always derive from that.

: What a great syllabus here listeners. This is again directed toward the implementation of infrastructure to support new technologies. Kevin Lyman here from Enlitic. So Kevin what book would you recommend for the listeners?

: My favorite book is the 80/20 principle. I think I've learned a lot both from the book and from the principal in and of itself that in many cases you can get 80 percent of the value with 20 percent of the work and that is in no way me condoning only doing 20 percent of the work in certain circumstances. But when you're in a very multidisciplinary field, the way that we are it's critically important to be very well educated not across just artificial intelligence and computer science and software engineering but also clinical science and medicine. Then the reality and gravity of the practice that you're trying to build solutions for and we're in a multi disciplinary field like that it's a very helpful mindset to understand that I will never be the best doctor in the world but if I'm smart about whom I spend my time with the people that are the best doctors in the world then I can learn enough of what they know to do good work in my field.

: What a great message man.

: I just want to make sure I also give a quick shout out for the tech intern blueprint. It's a book that was just written by two of my colleagues from the inventors guild or any software students or engineers out there that are graduating college and looking for a good tech internship. They've put together an incredible book full of Amazing Tips and tricks on how to optimize your chances of getting your dream job or your dream internship. So check in turn blue print. Check it out on Amazon.

: That's awesome. Hey thanks for the recommendations Cavin listeners. Don't worry about writing any of that down. I know we've been talking about a lot of great things. Just go to outcomesrocket.health/enlitic that's E N L I T I C. outcomesrocket.health/enlitic. You're going to be able to find a transcript. All of the show notes and links to all the resources that our friend Kevin Lyman here has been sharing with us. This has been a ton of fun Kevin and I'd love if you could just share a closing thought. And then the best place for the listeners could follow up with or follow you.

: Yeah absolutely. I think I always like to close these things just by telling people that they should be very excited about the future of health care because even though it's a field that from a technology standpoint hasn't seen a whole lot of rapid evolution, now is the time that really we're seeing more work done than ever. Well a lot of us would probably consider to be science fiction is actually creeping up on us a lot quicker than we could anticipate but in very good ways. And so it's something that I find very exciting and I hope to leave everybody very excited about this as well.

: Thank you so much for that and Kevin what would you say the best place for the listeners to get in touch with or follow you as?

: You can follow me on Twitter @ktlyman, or you could always e-mail me kevin@enlitic.com. I'm happy to answer any questions you have about clinical AI or anything of the sort.

: Outstanding. Kevin this has been a blast really just want to acknowledge and congratulate you and your team for the hard work that you're doing and the advances that you guys are making. So just want to say thanks again for spending time with us. Looking forward to staying in touch.

: Fantastic. Thank you so much for organizing it was really great chatting with you.

Thanks tuning in to the outcomes rocket podcast. If you want the show notes, inspiration, transcripts, and everything that we talked about on this episode just go to outcomesrocket.health. And again don't forget to check out the amazing healthcare thinkathon where we could get together to form the blueprint for the future of healthcare. You can find more information on that and how to get involved in our theme which is implementation is innovation. Just go to outcomesrocket.health/conference that's outcomesrocket.health/conference and be one of the 200 that will participate. Looking forward to seeing you there.

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Recommended Book:

The 80/20 Principle: The Secret to Achieving More with Less

The Tech Intern Blueprint

Best Way to Contact Kevin:

Twitter: @ktlyman

LinkedIn: Kevin Lyman

Email: kevin@enlitic.com

Mentioned Link:

www.enlitic.com

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How AI and Data Analysis Can Improve Cancer Treatment with Dr. Andrew Norden, Chief Medical Officer at Cota Healthcare

: Welcome back once again to the Outcomes Rocket podcast. We're chatting with some of the most successful leaders in healthcare today and I have a wonderful guest for you. His name is Dr. Andrew Norden. Andrew is a Neuro Oncologist and Physician Executive who joined Cota in 2017 as the Chief Medical Officer. Prior to joining Cota, Dr. Norden served as Deputy Chief Health Officer and lead physician for Oncology and Genomics at IBM Watson Health. Previously he worked at Dana Farber Cancer Institute in Boston in several capacities including Associate Chief Medical Officer and Medical Director of Satellites and Network Affiliates. Andrew served as Physician Leader for the Dana Farber community network for more than five years. He attended medical school at Yale School of Medicine before moving to Boston for residency training at Mass Genn and Brigham Women's hospitals. He's got a phenomenal track record in health and now he's serving at Cota as CMO. I'm so excited to welcome you, Andrew. Thanks for taking time to being on the podcast.

: We'll thank you for having me, Saul.

: It's a pleasure. Now is there anything in that intro that I left out that maybe you want the listeners to know about you.

: Well frankly you covered almost everything. So I would say no, I think that was a great start and I appreciate it.

: Awesome Absolutely. My pleasure. Now Andrew why did you decide to get into health care? Why the medical sector?

: Well to be honest I never wanted to do anything other than healthcare from the time that I was a child. Now that said my initial thinking about that meant something much more traditional than where I've ended up in the sense that I thought I would be a physician taking care of patients my whole career. And I infected trained to do that and ultimately became a brain tumor specialist. I work at Dana Farber Cancer Institute in Boston for about ten years in a variety of roles some of which you mentioned and what I learned over time is that there are great rewards associated with taking care of patients. But the overall magnitude of the impact for me felt somewhat limited because of the way patient care involves one patient at a time and particularly in the area of cancer research and care that I was involved in brain tumors. The pace of progress was really slow so it was kind of with that lens that I began to look for ways to get involved in something that might have impact on a much broader scale. And I had always been really interested user of technology fairly sophisticated user of technology and had some opportunities to implement new technology systems in an administrative capacity I had leading Dana Farber's network. So I enjoyed that work a great deal. And when I had an opportunity to join industry and work for IBM Watson Health as a leader of their physician leader of their cancer care offerings I took that leap couple of years ago now and then ultimately made the move to Cota.

: What a great journey and it sounds like you were very focused. You've always wanted to be part of this industry helping people but now you sort of took that next step and in your role now you're able to influence and even broader subset of people in a more agile way. Cotais doing some pretty impressive things maybe to level set the listeners on what Cota does. Andrew, I'd love if you could just give us the quick just understanding of what they do.

: Yeah absolutely. I'll try to keep it as brief as I can. So Cota is a kids cancer focused data and analytics company and we were founded by a group of oncologists a number of years ago who serve that doctors were spending an awful lot of their time entering data into the EMR. I think most people in healthcare today can identify with that perspective that the EMR has become ubiquitous and yet despite the fact that we spend all of this time working on it we as physicians are often unable to answer the most basic questions that our patients ask us questions like how many patients like me have been treated before and what have been the outcomes associated with the decisions you've made in those patients. And people want to understand how do you Dr. Norden compare to other doctors and other centers. We can't answer those questions and that is really what Cota's primary goal is. We connect with provider organizations. We pull out data from their electronic medical records and from other clinical systems and then we present it back in a way that's useful and allows them to understand the way that they're treating patients and what are the impacts of the various decisions that their providers are making. Day to Day. We also have a really unique method of grouping patients almost like a digital barcode. We call it a CNA or a Cota Nodal address which is a novel way of grouping patients based on all the known clinically meaningful factors and patients who enter our system electronically or are assigned to this. This barcode this CNA which then enables one to compare groups of patients who are clinically similar between doctors insights and particularly when we marry that information up with outcomes data that we track clinical outcomes data and cost data. We can reveal a lot of useful insights that help our customers.

: What a great explanation there Andrew and sort of offering the providers an opportunity to gain insights on a siloed data. Your guys are helping liquify that data bring it to them in a presentable form but also offering a precision medicine type of approach by matching these patients that have similar conditions and backgrounds with outcomes.

: Exactly.

: It's beautiful and you know what I've been having a lot of conversations about this and it's striking that the important things like measuring outcomes need to happen more so I'm really thrilled to hear that this is a focus for you guys.

: Yeah. I mean you often hear the adage these days that you can't manage what you don't measure. And I think it's really quite true in healthcare measuring outcomes just hasn't been part of our routine work until recently. Our systems aren't optimized for doing that. That is definitely a major focus of Kodos efforts today outstanding.

: Now we've already dove into several hot topics without even asking this but what would you say if you had to boil it down to one hot topic that needs to be on medical leaders agendas. What is that hot topic and how should they be approaching it?

: Well at the risk of using a cliche I mean I think the answer is data data is an absolutely hot topic. We're drowning in it. There are systems that surround us. And you know if you ask a typical CIO of a healthcare organization how many systems he or she works with on a daily basis. How's meaningful data pertaining to patients. The number is huge and sometimes I've heard it said as high as a hundred or more systems. I think we all need to be thinking about an approach to make meaning out of this data. There are forward thinking health care organizations provider organizations and other types of health care organizations that are doing this in-house and others who are working with vendors like us to do it. But my general sense is that if you're not thinking about how you're going to use your data to your advantage at this point I think it's an important topic to jump onto as quickly as possible.

: That's interesting and definitely spot on. Now give us an example how are you guys Andrew at Cota are creating results and improving outcomes by filtering and processing this data.

: Yeah I'll do that for sure as I think about potential examples some of the ones that come to mind are things that are strikingly easy. If you have the right data at hand we work with a large hybrid or healthcare organization. It's sort of a community academic hybrid and also with a major local player in that centers region and one of the things that we have looked at as we've assigned the CNA that I described to patients this organization is patterns of variability and what we see in oncology are that there are two fundamental patterns of variability. One is that there is variability in the treatment decisions that physicians make for similar patients. So you take two patients who have the virtually same set of attributes and often you see a wide variety of treatment choices being made. And unfortunately in oncology oftentimes those variable treatment choices are in fact all acceptable according to local consensus guidelines which is to say that our consensus guidelines are quite broad and they leave the provider perhaps in many circumstances too much leeway to make a variety of different choices. The second and perhaps more surprising variability pattern that emerges is that when you take similar patients in whom their physicians have made the same treatment choice you still see a great deal of variability in cost and that's somewhat counter-intuitive because people often imagine that the treatment choice in oncology is the most critical driver of cost. But it turns out that it's only one piece. The other piece relates to all of the elements of care that surround the treatment choice. How often does the doctor see his or her patient. What types of scans the doctor order and how often are those scans done. What types of labs and how often are those lab done when the patient has radiation therapy which specific radiation technology is used. All of those different things have really meaningful impacts on cost and in some circumstances they may also impact important patient reported outcomes like quality of life. So that said we've been interested in delving into this issue of how patients who are similar clinically and are treated similarly still have differential costs and so one of the insights that we uncovered at the provider that I mentioned is that in a common scenario in breast cancer patients need to receive a drug that is called Adramycin which is potentially toxic to the heart. As a result when patients are going to go on this therapy they need to have baseline cardiac testing to ensure that the heart muscle is functioning properly. The reason being that if there is some baseline dysfunction then this would be a potentially dangerous drug for the patients to receive. There are two common tests that physicians order that are equally effective in assessing cardiac function. One is the echocardiogram and one is a nuclear medicine test called the Mugga scan. In this particular scenario that I'm describing it turns out that the mugger's scan costs hundreds of dollars more than the echocardiogram. So simply by looking at these patterns of care and cost impacts we uncovered that a set of physicians in this network were routinely ordering mogas scans getting no more meaningful information than the echocardiograms and contributing to hundreds of thousands of dollars of additional spend per year. So just by highlighting this for the system we were able to change practice and save money with frankly no resistance from the providers because they don't care at all which scans they use. It's simply a matter of what they're used to doing. All we had to do is let them know that is one test was more expensive than another and practices changed right away. And we have uncovered just countless examples like this where you can simply identify almost meaningless differences that are driven by habit and physician behavior more than by data or any evidence of superiority. And you can save a lot of money for the system at large.

: Andrew so insightful what a great example. Very niche down to oncology very differentiated in the treatments that you're able to tease out for your provider listening to this. I'd definitely bet the light bulbs going off in opportunity right to reduce costs to offer more resources to these patients that need different treatments. So don't worry at the end of the podcast we'll get you a way to connect with Andrew and Coda but definitely continue the conversation and you know one of the things that I really love about the intel that you're sharing here Andrew is that it was derived by you and your partners which you guys are oncologists and in the grand scheme of sort of tech companies that come up in healthcare and you've got the tech focused people that think that hey since I built Uber I could solve healthcare problems. And then you have the providers that have the intel and are approaching this which is the category that you and your team fall into. And I think the insights that you're able to make come from those with knowledge and experience and insights that are going to be able to be useful in a faster way. So kudos to you and your team for bringing up these examples. It sort of reminds me my wife and I we were in Hawaii several years ago and it was February. We wanted to see the whales and we would just drive we would see no whales. Then we got into the boat and the whale watchers sort of taught us what to look for the water that comes out of the spout. The fin that hits the water all these things that we should be looking out for. And Andrew before you know I would see whales everywhere like I went from not seeing anything to there's whales everywhere. And when my wife and I got off of that boat and we drove up the mountain and we were driving back to the house that we rented. I swear to you from miles and miles away we saw whales everywhere.

: Wow.

: And it's because we were educated and here you are with your colleagues. You guys are on that boat and you guys are the experts and I'm sure that when you talk to provider executives you're like their whale watcher counterpart that helps them see these things.

: Absolutely. And you know what's exciting for us is that the kind of information I just talked to you about comes from a data set that we build at a population level that maybe the chief of oncology or the administrative leader of oncology or the hospital leadership is looking at what we're really excited about at Cota is that we're now in the process of of offering Point of Care tools as well so that we can actually influence the way providers behave and the decisions they make at the point of care based on on these sorts of population level insights so we can bring it right past them at the time that they're making decisions.

: Wow that is interesting and it sounds like you guys are making this to a more and more useful so so kudos for you guys. Now tell me this Andrew. You know it hasn't always been smooth. Can you tell us about a setback that you had and what you guys learned from that setback?

: That's a very good question and I think I'm going to take it from the standpoint of this industry in general.

: Absolutely.

: And that is to say there has been a great deal of interest in encouraging providers to do the all right thing more often. And there have been a variety of different non technological and technological tools that people have built to help nudge decisions in the right direction. My sense is that in healthcare a lot of what we have done in the realm of clinical decision support particularly around treatment decisions relates to so-called clinical pathways or the idea that you can bring together a group of experts to make recommendations for how physicians should. Act in particular scenarios and then push those expert recommendations into the hands of frontline decision making staff to change their behavior. There's nothing wrong with that approach per se but you can imagine that there is a fair amount of pushback when oncology professional or any health care professional who's trained his or her whole life to be able to make a particular set of decisions is told. You're now going to follow this particular expert guidance. So our approach is distinct from that in that we bring actual historical data to the fore in a way that makes it really objective and non-threatening. When you're a physician and I show you data that says the last 10 times you saw a patient like this and you gave treatment X and your colleague did saw very similar set of patients and chose treatment. Why. But in the case of that colleague the patients had invariably fewer side effects and the cost to the system was less. It makes providers think twice in a way that I think they're much less likely to if you say here's how you have to do it going forward. So we are taking that approach of presenting objective data that's straightforward and easy to understand. And what we find is that physicians actually appreciate the opportunity to see the impact of their decisions in ways that they haven't been able to before rather than taking the approach of sort of telling them what to do.

: Now that's so interesting Andrew and you know the other thing too to call out here is is that when it comes from a peer it's that much more well received. And they think that one of the things that differentiates your company from others out there is that it's peers right. You guys are oncologists and you're offering credibility. And with that they open up their ears and they listen.

: Yeah I think that that's really true in a lot of ways I think about it also that data is the language of science and medicine and expert consensus is valuable but it's not as powerful and it's certainly more emotion laden and sometimes controversial. So that's our philosophical frame.

: Yeah I think it's great. I mean it beats somebody from Google Sean up that knows nothing about oncology telling them what to do.

: Well no question no question about that although we all know that our colleagues at Google have been doing some smart interesting things in healthcare in months and years as well.

: Without a doubt. But you know you know I'm just saying that to make a point.

: Well taken.

: That for sure Andrew. So tell me what's one of your proudest medical leadership experiences debate.

: Well I think unique in that I've had a variety of different careers in healthcare. I had a career as a clinician and clinical trial list and then a career as a hospital administrator and now a career in health I.T. and I could probably answer this question in a different way for each of those. But maybe what I would say is that in my current world where I work with certainly a number of folks with oncology experience but also a huge number of folks who don't have oncology experience people who come from the technology world or the business world or fresh out of school or data science biostatistics. All of these are key disciplines that bring a lot to what we do. But for me what has been most gratifying is really helping our team at Cota to understand just how valuable data and simple visualization and analysis can be in healthcare. I think everyone would agree that healthcare is behind many other industries in terms of the way we use information technology day to day. We still are faxing records between provider organizations on a daily basis. We have limited ability to see population level analytics. All of these sorts of things. If you want to have if you show up in an emergency room the odds that the provider there has access to your recent test results remain really really low. So I've spent a lot of time at škoda educating our team about how even things that seem technologically unsophisticated can in fact make major major impacts. And so for us simply organizing the data and bringing it to the fore at the right time is so powerful. And I have found it really gratifying just to be able to show our team how that matters and how by doing that we can actually help to ensure that patients are getting the right care or not having duplicated tests or the unnecessary treatments provided and the like. So that is probably where my pride is the chief medical officer Cota comes from today.

: Andrew you brought up such a great point on this point that he didn't have to be technologically amazing. It's the simple fact that if you find a way to implement it you just find a way to implement whatever is out there and in a useful way that's what makes a difference. I teamed up with the Center for Health and innovation and implementation sciences at Indiana University's School of Medicine. We're putting together a conference. It's called the healthcare thinkathon. And our theme is innovation is implementation and health care.

: I love it.

: You don't have to keep coming up with new things. And your point here is it folks if you're curious about that Scott outcomesrocket.health/conference you'll find more details about that there. But yeah Andrew I love this point you're talking about something real here is that it doesn't have to be complex, it has to be useful. Exactly. Most powerful man. So that's exciting now. Now take us down the path of something exciting that you're working on a project or a focus that you guys are working on at Cota today. What's lighting your fire today?

: Oh sure I will. We have spent most of this conversation today talking about what we do that helps providers and patients and of course providers and patients are absolutely at the forefront of what we do Cota and in the healthcare industry in general. One of the really exciting things that we're working on right now relates to the pharmaceutical industry and the drug development process. I think all of your listeners will agree that drug development takes too long and is too costly today and there is universal agreement that anything we can do to get effective drugs into the hands of providers to prescribe them and patients to receive them is warranted. That's one of the things that we're working on at Cota is called the concept of synthetic control arms. You may know that as a drug is developed when it's promising it often needs to be tested in a randomized Phase 3 trial before the FDA or other regulatory agencies will approve the drug for use in people on a routine basis. And we also know that an unexpectedly large proportion of drugs fail in phase 3. So that is to say that perhaps they've been tested in comparison to historical controls in a Phase 2 study and the results look promising. So they go into Phase 3 where the drug is then compared against the existing standard of care or against the placebo and oftentimes after years and billions of dollars spent in Phase 3 we learned that in fact the drug is not more effective than placebo or not more effective than the standard therapy and drug development is abandoned. We think that there's a great opportunity to change that reality by providing a contemporary high quality synthetic control arm in Phase 2 and I think it's important to understand what often happens in Phase 2 studies is that the comparison group is a historical control group that may have been reported 5 10 even 20 years ago and the details of which may not be well published are well known at present. So we are working with a variety of healthcare stakeholders and agencies to develop a synthetic control arm concept in which we could statistically compare a drug in a small phase 2 study to a synthetic control arm created of for example historical patients in Cota's real world data set so that if the drug still appears promising after Phase 2 it's much much more likely to succeed in Phase 3 and ultimately be approved. Alternatively if it looks unlikely to be more effective than a synthetic controlled arm then drug development can be stopped at that point averting the need for additional years of Phase 3 patient enrollment and again billions of dollars spent. So this is a work in progress that a variety of different entities including us continue to work on but I think that the potential to really help speed up and make more cost efficient the drug development process. I think that's really exciting and is going to be real.

: There's no doubt you guys are focused on improving outcomes and cutting costs and I think it's all being done in a very thoughtful way. Andrew so thanks for sharing that listeners if any of this is resonating with you. I encourage you to check out Cota on a deeper level. Go to www.cotahealthcare.com and you'll be able to find out their solutions are technology more about the company and their hiring too. So if this seems like, right you're telling me at the beginning of the before we started recording folks. They're hiring engineers they're hiring medical directors, they're hiring delivery and human resources so check out Cota as a workplace. But also if you're a provider check them out to see what they're offering because I think you'll be very intrigued and pleased to know that they may have something for you and help you and what you're working on today. So this has been fun. We're getting close to the end here. So I've got this medical leadership course you and I are going to build. It's what it takes to be successful in health care the 101 of Dr. Andrew Norden. So we've got four questions. Lightning round style followed by a book and a podcast that you recommend to the listeners. You ready.

: OK.

: Here we go. Lightning round. What is the best way to improve health care outcomes?

: I would say measure what matters and use data intelligently.

: What is the biggest mistake or pitfall to avoid?

: Remember that hype and results are not the same thing. And it's important to ensure that you're able to do what you say you can do before you go out into the world and start announcing it.

: Love that. How do you stay relevant as an organization despite constant change?

: I think the answer there is you need to focus. You need to pick one problem to solve and make sure you can solve it better than anybody else out there.

: I love that Andrew one of my favorite acronyms as focus. Follow one course until success.

: I like that too.

: What's one area of focus that drives everything in a health care organization?

: Well I'll tell you in our company it's about having a high quality data set and being sure that it's collected in a way that that means it's real.

: Beautiful. What book and what podcasts would you recommend to the listeners on the syllabus.

: So my favorite book not about health care at all but has been meaningful to me throughout my professional life is the Dale Carnegie book. I suspect many of your listeners are familiar with it How to Win Friends and Influence People.

: Yes a great book. What a great one. And folks listen. One of Andrew's favorite books being Dale Carnegie's. Then surprise me why he's done the amazing things that he's done and has had the career shifts that he has had. So if you haven't checked that one now be sure to check it out. How about a podcast?

: I'll tell you I also have really been enjoying the A16Z podcast put out by the Silicon Valley VC firm Andreessen Horowitz they talk about technology and healthcare entrepreneurship and I find all sorts of tidbits of wisdom in there when I listen.

: What a great recommendation listeners. All the things that we discussed today the podcast that he recommended, the book, and all of the show notes and transcripts as well as a link to the company. All of that could be found at outcomesrocket.health/cota so visit that and check out all the links there and resources. But before we conclude I'd love if you could just share a closing thought Andrew. And then the best place for the listeners could get in touch or follow you.

: Yes you bet. So as we close you know I would say that a key to the next step in health care data and analytics is going to be around how we capture high quality data in the course of our daily work. I think Cota and others like us are beginning to do a really nice job of trying to make meaning of the data that exists in the EMR. But wouldn't it be nice if the EMR were constructed in a way that the data that flowed freely from it was high quality and helpful from the get go. I think that's going to be the next frontier for this work. I would be delighted to hear from your listeners. I'm at andrew@cotahealthcare.com. I think he spelled it out before but cota.healthcare.com and it's just andrew@cotahealthcare.com.

: Outstanding Andrew. What a great close there that you left us with that aspirational EMR I think is a destination that we're all going to enjoy getting to. And with the efforts that you and your colleagues over at Cota I know it'll probably make it faster so just want to appreciate all that you've done for us today and sharing your thoughts. And we're looking forward to staying in touch.

: Thanks a million. I enjoyed it

Thanks for tuning in to the outcomes rocket podcast if you want the show notes, inspiration, transcripts and everything that we talk about on this episode just go to outcomesrocket.health. And again don't forget to check out the amazing healthcare thinkathon where we could get together to form the blueprint for the future of healthcare. You can find more information on that and how to get involved in our theme which is implementation is innovation. Just go to outcomesrocket.health/conference that's outcomesrocket.health/conference be one of the 200 that will participate. Looking forward to seeing you there.

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Recommended Book and Podcast:

How to Win Friends and Influence People

A16Z podcast

Best Way to Contact Andrew:

andrew@cotahealthcare.com

Mentioned Link:

www.cotahealthcare.com

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Digital Marketing Tips to Help Your Organization Increase Sales, Attract Talent and Win Mindshare with Gary Monk, Healthcare Innovation Consultant

: I thank you for tuning into the podcast again. I really appreciate that. You know I've gotten a lot of information, a lot of e-mails saying how certain episodes have resonated so don't be shy follow up with us on Twitter at @outcomesrocket, we'd like to hear from our listeners because today I have an amazing guest and I also invite you to rate and review us at outcomesrocket.health/reviews. This guest is an amazing collaborator in health care- a digital healthcare innovator with over two decades of experience. Originally from London, England. But now here in the United States specifically in New York City. His focus is on helping healthcare institutions differentiate themselves through innovative strategies using digital and also technology and so his focus is social media. Its digital platforms for marketing, anything that will help you as a healthcare professional as a healthcare leader within an organization. Promote what you're doing but also get it to the right hands at the right time. So Gary just want to welcome you to the podcast and fill many of the other gaps of that introduction that I may have missed yet.

: So I think that's great, that was that was all good. I should say I moved over from London to New York several years ago. I'm actually originally from Birmingham so I don't want to forget my roots. That's from I'm originally from the UK but I spent many years living in London and I've worked over that at that time in healthcare. Worked within pharmaceutical companies a lot of Simon Johnson Johnson and then working in agency and consultancy. So a broad broad experience but I think you covered it very well. So yes looking forward to this.

: Absolutely. And so are we. So the reason why I wanted to bring Gary on here is to get a little taste of outside of the normal health care box right because in general we've got to find better ways to target our customers our patients and really get a better outreach. And I think we all struggle at this. And so Gary is here to provide us some insights. But before we do get into that Gary what got you in the healthcare to begin with?

: Yeah I mean I'm a real science nerd so my study I guess you'd call a major here and majored in organic chemistry and medicinal chemistry. Yeah and I was really fascinated with how these humans build molecules can interact with the body receptors at these sites and have a profound sense of profound positive effect but also how we could minimize side effects and make sure they were really specific. So it's I found that side of it is fascinating so that got me into healthcare and interested in pharmaceuticals and also the scientific pursuit of it, very exciting but also that potential for doing something good for humanity was compelling. So that's got me into it. I spent some time in the lab. One small anecdote probably in my life I definitely have got the skills for science but in terms of the humbling part of that is I certainly did not have the practical skills because at my time at the Glaxo research center in England I was working in the hydrogenation suite there and Trott's and finely divided catalyst on the floor, started a small fire really created the next small fire has to be the catalyst kind of expose the air and set on fire. So luckily we didn't end up with the next Hindenburg but I kind of realized I have in mind for science that maybe not the body and the practicality and the coordination but that got me in there and then I moved out of the lab and the rest is kind of history really.

: But that's awesome I'm nothing terrible came out of that Gary but your passion stuck and now you're helping people build fires so that they can get attention to their practices and businesses so you're doing it in a positive way.

: Exactly, a lot that's Yes that's true.

: So that's fascinating. What would you say today Gary is a hot topic that needs to be on every medical leaders agenda and how are you guys approaching this?

: Yeah the thing I think of is data an artificial intelligence sounds like two topics but clearly they're very deeply intertwined. And when I say data I'm talking specifically about personal and patient data and they kind of like sound like dirty words now particularly with the times with what's going on with Facebook. But we got these initiatives going on around real world data, population health, outcomes driven health care lot of those was but important initiatives. But none of these are actually going to produce anything of value without the right use of data. The right approach and the use of artificial intelligence for example in artificial intelligence is will highlight we can set up a program, say Population Health Program. Artificial intelligence is going to actually highlight factors that the researchers program managers have not even considered in the set-up page and really help us join the dots in the ways we might find it hard to do. So say yes that's very big and it's a complex challenge. So when I think about my approach and our approach to that one, thing that comes out is very specific. Clearly we need to get all the set up right about understand the problem make sure asking the right questions. But what I would say is probably actually more of a general point that could apply to other things outside of artificial intelligence as well but is to really think broadly in the thinking in the ideation phase. So to give you an example in most cases pretty much all cases you want to go super broad in terms of the types of data collection. But let's take a hypothetical example if we're running a program in New York around mental health and we're trying to support patients who may be on medicines but we've got a coaching program on online coaching counseling program support program that they can go to. Obviously we can pull a lot of metrics of how patients are engaging but we probably want to take as much information about that patients as possible and those patients to feed into the system. So what I'm talking about the ideation phase is when the planning that is to really look at the types of datas that would be useful to us. And look at them without judgment. So conceivably we could think for those patients that would be great to you know where they are, whether they're going out, use a geolocation on that phone, how active they are, how much exercise they're doing, any activity based from their phone. Any wearable devices they are using, if they got a sensors in their home measure their exact movements, monitor their phone calls, a number of phone calls, frequency duration of calls. Same with text messages how long they are and even what they are saying from their voice modulation intonation to actually what they're saying. The more I can't keep saying it probably sounds very very creepy. But the important point I'd want make in it, yeah.

: In the back of my mind I'm like holy cow. Like that's a lot of information and it makes you think right like we could get a lot of information from our cell phones. So how do we use it. What are some guidelines there and what are some examples of what you guys have done.

: Yes. So there's a lot of good examples of that. I mean this one I wasn't directly involved in but I think it's a nice example one that I'm actually involved in kind of sharing out, blocking around it. It's a little while ago now. I think the company slightly pivoted but a company called Ginger.io. So I've actually pulled that into proposals, the clients, the pictures has been actually build it out but that was fascinating technology where they actually use the mobile phone I believe they use the tracking of the phones of the geolocation, and the sensors, the patient moving around as a proxy for how their depression was going so clearly if they're sitting around they're not moving much generally that probably moves probably lower if they're functional moving around, going to the shops, going going out, seeing friends, socializing that's obviously good. And I mention a bit about voice to kind of throw that in there. But actually I believe they using not going as far as monitoring what the patients were are actually saying which I appreciate sounds creepy but understanding their voice modulation. So how often they are speaking. So actually, now okay, if they're isolated and they're not sending text messages, they're not calling their family, they're probably not in a good place. But if they're making frequent calls you know we're not interested in what they're saying, snooping on the conversations but actually if having those conversations on a regular basis, it's probably a good thing. So using those metrics. So I think that's a really good a good good use case all. The reason I put this about listening to the patients in there, it's kind of to be provocative. But I think it's a really important point when we start thinking big on these projects. There's no harm in thinking these things initially, I feel the problem I'm kind of going on a ramp here now. But I found a problem with big companies as opposed to start, having work in both will shot down ideas like next lessons what the patients are saying.

: Right

: Explore that and we might get to a point of actually ethically that doesn't work, it doesn't work for the patient. But let's explore where that could lead to and maybe it leads to the point of actually we listen to the patients conversations. Not what they saying but how often are they saying it, the voice modulation that we anonymize everything, they identify everything. So we get to kind of an exciting place because we've opened our thinking rather than someone then say a farmer of a big biotech company. No we can't do that, we can't listen to what's patients are saying over the phone and it kind of gets shot down as soon as it's thought about and conceived and then the end idea often ends up very vanilla and really not that valuable. So you see what I'm saying.

: I totally agree.

: Thinking big initially. Yeah, and then we pull it back in and we make sure we're doing the right thing on the patient ethically and we don't go spying on patients et cetera. We start thinking what data could we actually use and how would we get it and how would it serve us.

: Yeah. Gary, and you bring up a good point, right? The point here is listeners you've got to be open-minded if you're going to innovate, you've got to be open minded and sure, it might be a little edgy but let's find ways like anonymizing and de-identifying and stripping away the things that are patient information and making those voice markers or key keywords something that could serve the people that it's intended to serve. And Gary the thing that brings up kind of thought in my mind about this discussion is the whole area of digital therapeutics and what's being done with digital technology to help patients. It's super interesting what's going on out there isn't it?

: Yeah absolutely, absolutely. And you know obviously what you said I can cover a lot of things but it's simply fascinating when you've got digital tools that can even, that actually help patients. I was speaking to a friend who works for a startup and I say what he does as a digital therapeutics but actually helping patients sleep better. So analyzing understanding their sleep patterns by sensors on the body but also in the room where they're sleeping. And then part of the digital therapeutics is actually adjusting their environment, the temperature of the room but also the important thing that he's doing is actually using research to actually place specific segments of white noise at certain times when patients are sleeping, deep sleeping, their having their delta waves of deep sleep and the scientific research shows when the right sound is played at that time it can actually extend the period of deep sleep.

: Fascinating.

: And mean, the patient, the human being gets a lot more restful sleep. So I would say that's a good example of a digital intervention where it's listening, understanding but also giving that kind of response via feedback and there's a good patient outcome hopefully at the end of that.

: Gary what a great example and programs like video games to help you with ADHD instead of Ritalin. Listeners,the point here is what Gary is telling us is that we've got to think outside the box and we've got to push the envelope and oftentimes large organizations get trapped with the knee-jerk 'No'. And the little guys come up the little digital Davids and they kick butt. And so just a little thing to consider this little warning like be open to innovation and be open to ideas even though up front they may not seem like it distill them to the point where you can actually maybe get something that's not vanilla to Gary's point and it doesn't make an impact. So Gary can you give the listeners an example of some of the things that you've done to help your clients create results and get things done better improve outcomes?

: Yeah, I got a couple of examples. One thing is coming to mind that I've been working on quite extensively recently which is a hot topic is a social media. So I can't get to many specific examples but I've worked on clinical trial recruitment using social media which is very exciting because we've been able to get patients to enroll to play with trials faster than they normally would. And also more of them faster but also importantly at a lower cost as well. The cost of acquisition is between 10 and 100 times lower than using traditional methods. So that's been very exciting using social media for that. I even shared something yesterday I wasn't involved in it but the use of artificial intelligence attached to medical records to recruit patients for a clinical trials, that's how it's kind of evolving, that's such a big a big area where there such potential to help patients that there's a global shortage of clinical trial patients and also ensure that done cost effectively as well. So that's the big thing. I kind of broaden out to social media generally again because it is such a hot topic. So I've been working on, I mean I love social media from the perspective that using things that Facebook, you can target patients directly and actually understand whether they've taken specific actions seen adopt the measure if they've moved on that journey towards better outcomes. And the reason I mention Facebook sub-16 in the news a lot recently Zuckerberg been hold up in Congress. But yeah, it's very it's got a lot of good potential within healthcare but obviously it's got the potential for misuse as well so that I'm optimistic we can get to a point where the goodwill will triumph and we can use it but I'm just really concerned that the people don't get the point of like Facebook using this is bad, start using it. There's a lot of good that can actually be done if it's done in the right way using using this and other other channels.

: Now totally man and you know Gary let's talk about Facebook. So a lot of folks in the industry will think about campaigns whether it be driving patients to a trial, medication trial whether it be a training business clients in the healthcare space. I've heard the debate Facebook versus LinkedIn, which one is more effective. What's your take on that?

: Yeah I mean I've got a lot of experience doing this and obviously it does depend a lot on who you're targeting and exact and what you're doing. Overall, forget about the audience in terms of the power of the targeting. Currently Facebook I know they're pulling back some of that based on you know some of the abuses that they've had. So we'll have to see how that nets out but it still looks like the targetings would say a lot more powerful than LinkedIn so from a fuel targeting perspective, I find Facebook more valuable. In terms of treating patients in most cases Facebook is going to be where more of the patients are and easier to reach in context. Obviously a number of them maybe on LinkedIn, but in terms of actually reaching them the right way around that condition it's usually accepted more for that message to come through something like Facebook than LinkedIn. The work I've done targeting health care professionals actually it's been a mix of, I've had mixed results depending on the type, the type of project, the type of physicians working on LinkedIn versus Facebook. Often my advice would be, you know without knowing more about a specific project, if it's healthcare professionals, look at doing both and then see what's really working. Why are you getting the most benefit, you the getting the most reach and then send over the, leave the budget on to one that's working. So I'd always advise clients to be flexible. You have got this pot of money. We decided we're going to put like, play safe part on LinkedIn, half on Facebook but we have to quickly dial it up one way or the other if we're getting impact one one platform versus the other.

: So overall you feel like Facebook allows you to do more acute targeting meaning more specific targeting and LinkeIn not as much but you recommend sort of try a mix of both measuring and then pivoting once you figure out what's working out.

: Yeah absolutely. And what surprised me from practical expense is how effective Facebook can be about reaching doctors because you know you see the statistics a lot of doctors are using Facebook for personal reasons.

: Right.

: But a lot less using it for professional reasons. But that's kind of a bit of an arbitrary distinction because when a physician is on that for personal reasons, if someone is coming out in context the doctor's not going to switch off that it's relevant to them or their practice. So they're still going to click through on that ad if they're using it to keep in touch with their family or look at their friend's holiday pictures they're not going to ignore it and say oh I'm not clicking on that even if it's interesting and relating to my profession. Now that's not going to happen, they're going to they're going to click on it. So yes, definitely consider Facebook for doctors.

: Fascinating. Now that's some really great insights. And listeners as you consider these newer digital platforms you know take some of these thoughts from Gary and plug them into your strategy and do some testing as you work to reach those people that you want to impact most whether it be patients whether it be providers or industry. Just do these tests and ultimately the end result will come from being able to tweak, tweak until you get the result that you're looking for. Gary what would you say one of your proudest leadership moments in healthcare have been today?

: Yeah. So that's a tough question, there's a lot of work I've done. But yes but the one thing that's coming to mind that kind of leaves lodged in my memory because I kind of built on it since was a couple years ago I led a team hackathon in Cleveland Clinic.

: Nice.

: Yeah it was great, it's very exciting and we created a solution to potentially helps chronic pain patients reduce their dependence on opioids at new stage or not artifitially intelligence to learn what interventions were having an impact outside of the medication. So even things like kind of acupuncture, yoga, meditation. So there's a great achievement by full disclosure on that, it won an award at a hackathon which was great so it was successful from that perspective Due to array of reasons didn't get that built out. I'd still love to build that out. So I think that's extremely exciting but the real positive from that and I'm proud of it is the learning of thinking from Math is there. I have been able to move that on into other projects, advising startups, biotech pharma companies on similar projects. You know if you examine the field of mental health. So it's taking that value even though not directly in that project and using that knowledge in other projects. I think the reason I'm proud of that and those type of projects is you know I really believe in what pharmaceutical companies can do. What I also believe in is the importance of having that kind of a holistic approach of what's working for the patients. Sometimes drugs are great sometimes they are not right great. Sometimes they are very important in the context of other interventions. So that's really important for me is having the right interventions for the patients that may or may not include drugs but we're not just totally focused on the early onset is a pilland a medicine so you know that's kind of where my head is with that.

: Yeah that's really interesting Gary and thanks for sharing that I know a good percentage of the of the listeners are also entrepreneurs building things. And so if what Gary mentioned to you sounds interesting. By all means at the end of the podcast Gary will share his contact information how you could get a hold of them. Maybe it's a project that you and Gary can pick up, dust it off and get it going because there's definitely a need for solutions to solve the opioid epidemic. And so the imitation is there, right Gary?

: Yes absolutely. I'd love to keep working on that. Definitely.

: Tell us a little bit about an exciting project that you're working on today?

So, I'm working on as I said those types of projects there where I'm working on actually using real world data to support patients from various different devices. It's hard to talk like exact specifics but to give you an idea of some of the range of stuff I do something important is working on a number of digital transformations for mainly pharmaceutical companies which is really moving them from a position of not using much in the way of digital channels and communications to their patients and their doctors in their in their marketing. Actually using it in a really defined smart way in a way I don't even want to say multichannel but in a way that really understands the needs of the end customers and actually takes them on the journey and the digital tools they use in the right way and that's exciting for me because that's measurable using digital and technology to take whether it's doctors patients on a specific journey and get to an endpoint. And the beauty of that measurable pace is we can really tie that back to outcomes rather of the the easy way of doing things it's like we need to be digital, let's do e-mail, like Websites that builds an app and just kind of throw things at the patient not the doctor. There's a fair chance that's not to work anyway. But if it does work we kind of don't even understand what's really working and what's not. So some of those transformation projects you know for me are very exciting. And then the more those some of those projects working on building in the technology were actually supporting patients not just using medicines but actually using technologies and other interventions so those ones but those are the ones that I find even more exciting.

: Super exciting and you know we need more of that Gary, so keep up the awesome work there. There's no doubt that companies are starting to come to grips with the fact that this is the way that things are going so keep up the great work.

: Great.

: So Gary getting to the end here let's pretend you and I are building a leadership course in medicine, the Digital Leadership Course in Medicine, the 101 of Gary Monk and I want to build out a syllabus with you. I've got four questions that our lightning round style so some quick responses to these followed by a book and a podcast that you recommend to the listeners. You ready?

: Yes great.

: All right. What's the best way to improve health outcomes using digital?

: So the key thing is understand the patient's situation. I know you wanted it sure but that probably sounds like a cliche, really challenge what you know about the patient and observe the patient understand that pain points. I always like to think if you were if you wanted to understand how a lion lions hunt you don't go and watch and see to the zoo. So forget focus groups just really observe the patient and understand them.

: Great analogy. What's the biggest mistake or pitfall to avoid?

: The key thing to me is we need to stop by asking the right questions. So yes I mentioned dates you and I are important. But if we're not careful we might start to get the right answers to the wrong questions.

: How do you stay relevant despite constant change?

: The two big things I've mentioned the focus of the patients are really understanding them as they evolve but also involving the changing technology landscape so involved both. Get both reported, the patients actually more so because if we understand the patients and not the technology well enough the outcomes are going to be sub-optimal. If we understand the technology and not the patient, it's going to be a disaster.

: Love it. What's one area of focus should drive everything in a health organization, a digital area of focus.

: A digital area focus. So I was going to just answer the easy thing which is important and bring it back to the patients. But actually if you saw a digital area of focus it's understanding that patient, the patients not to see things out necessarily digital, non-digital but just really understanding what they're using, what channels they are using but also why are they using them, what problem are they actually trying to solve with that so just getting real deep in understanding that from a patient's perspective.

: Outstanding. What book and what podcasts would you recommend to the listeners, Gary?

: Yes. So in terms of a book. I finished a recent book actually called Life 3.0 by Max Tegmark and it's about the future of the artificial general intelligence now the some healthcare examples. But what I love about it is it really takes the future forward about where artificial general intelligence can go when machines get smarter than humans. And before I read think more about science fiction. But actually this stuff will be a reality it's just a question if it's whether it's 30 years or 300 years from now. I mean that's what the experts are debating, not whether machines will get smarter than humans but just will it be hundreds of years away that we have think about it in our lifetimes or could it be sooner. But actually it was really good. So understand that from a kind of visionary perspective and then to tie things back from healthcare and understand where it can go.

: Life 3.0. And how about a podcast?

: Yeah. So I feel like your questions I'm comfortable with them all but this one's kind of stomp me you, know I listen to a range of podcasts like not including yours, but I'm just starting to really get into them because you know I've mentioned that book Life 3.0 and it was the first book that I listened to on Audible. So yes, I've found that now in New York when I'm I've got so much time to kind of more like listening to stuff and reading stuff you know when I'm on the subway it's a lot easier to listen than to read so probably next time I'll have a list of cast but really anything to do with technology so I dip into any podcast-related technology. I have listened to digital marketer, once on digital marketing, such really keep up to speed on digital social media and technology so I kind of dip in but also it's a recommendations from you and your listeners as well apart from this podcast and the others I should be listening to so yeah.

: Outstanding Yeah. And now sinner's that's the beauty of podcasting. You know you could go into the podcast app type in your topic of choice whether it be health care or if you want to just take a breather from health care and learn about tennis or cooking or marketing whatever you want. It's all there. The platform is powerful. So do like Gary does you know search for what you're feeling in the moment and just go for it. Gary, before we conclude I'd love if you could just share a closing thought and then the best place for the listeners can get a hold of you.

: Great. Yeah, I mean the closing thought really would be that the one thing that we discussed that kind of that I feel the most strongly about is just that real you know without you know not wanting to sound like a cliché but thinking big and by that is like just really fearlessly going out thinking about what you need to do to achieve the specific outcome without judgment and criticism. And you know I've read the Debono book many times and it's kind of that green up thinking where I'm judged, not you are creative, we're not judging. And then we bring in the critical thinking later about what the current issues to regulator issues might be. So to think big and open it first would be the really big change to make this stuff happen and don't let me off thinking initially. So that's be the really the big thing to me and yet I'd love love if the listeners want to get hold of me, that would be great. I'm very easy to find on LinkedIn. And I'm very open to connecting so you can put all the extension into LinkedIn and it's Gary W. Monk would just search for Gary W. Monks that's one 'r', search for me their own LinkedIn and switchapp, it's just simply @GaryMonk,so that's where the two best places to find me and I'd love to connect.

: If you're on the road don't worry about writing anything down just go to outcomesrocket.health/monk and you'll be able to find all of Gary's information, links to the books that he recommended and a transcript of today's conversation. So Gary, just want to say thanks again for spending time with us and looking forward to staying in touch.

: Yes definitely a pleasure. Thanks all and looking forward

Thanks for tuning in to the outcomes rocket podcast if you want the show notes, inspiration, transcripts and everything that we talked about on this episode. Just go to outcomesrocket.health. And again don't forget to check out the amazing healthcare Thinkathon where we can get together took form the blueprint for the future of healthcare. You can find more information on that and how to get involved in our theme which is "implementation is innovation". Just go to outcomesrocket.health/conference that's outcomesrocket.health/conference. Be one of the 200 that will participate. Looking forward to seeing you there.

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Recommended Book and Podcast:

Life 3.0: Being Human in the Age of Artificial Intelligence

Best Way to Contact Gary:

LinkedIn: Gary W. Monk

Switchapp: @GaryMonk

Mentioned Link/s:

https://ginger.io/

Episode Sponsor:

The World’s First FDA Cleared Wrist Pulse Ox Sensor with Leon Eisen, Founder & CEO at Oxitone Medical

The World's First FDA Cleared Wrist Pulse Ox Sensor with Leon Eisen, Founder & CEO at Oxitone Medical

: Welcome back once again to the Outcomes Rocket podcast where we chat with today's most successful and inspiring healthcare leaders. I really want to thank you for tuning in again and I welcome you to go to outcomesrocket.health/reviews where you could rate and review today's program because we have an amazing guest for you today. His name is Leon Eisen and he's a Ph.D. inventor, entrepreneur and contributor to healthcare. He is most recently well known for the formation of Oxitone Medical where they invented the world's first FDA cleared risk sensor blood oxygen monitor without a bulky fingertip probe to meet the basic health care needs. Keeping people healthy or at home by providing hospital grade digital continuous care with AI capabilities. We're going to be diving into some of the things that went into that and the thought processes of how this could improve health care are a little bit later. But what I wanted to do is offer Leon the opportunity to fill in any of the gaps of the introduction. He is coming to us recording from Israel so a big thanks for jumping on with the time difference Leon. Welcome to the podcast and tell us a little bit more that you want the guests to know about you.

: Thank you much. I think you'll said a lot about me even more that I could say about myself.

: It's a pleasure. It's a pleasure Leon. There's no doubt you've done a lot in technology and also in medicine and I love to get a better understanding of what got you into medicine to begin with.

: Oh it's interesting. After I graduated from PHD, I went to post doctorate research one of my friends just asked me to help with optical design of new redesigned sensor.

: Yes.

: Device. And today this device is in the market by the way it's the only device on the market to measure hemoglobin. And I said okay, I can help you. So this way I get involved into a very interesting, very promising and very important for all of us healthcare business, technological business, technology business. So I was so much excited about doing and the building medical devices so I left my post doctorate research and joined this company. So I joined another company and another company like executive then my father just go out on the street being free hours discharge from the hospital.

: My goodness.

: I called our physician and ask him, so what happened? Why?

: Yeah.

: He said I don't know. I saw him three hours ago. He was great. I don't have any capabilities to check what happens in real time. So it will sound someone came it took 15 minutes to make some trash to measure all this stuff. Thank God, my father was still alive. But this was my humbling. So I have all capabilities, all knowledge even technology in my hands which I can use to monitor patient continuously did what happened before. Why can we monitor oil, engine, but why we cannot monitor continuously human being?

: Totally agree. That's a great point.

: So we decided to do something that's impossible. We decided to move graph, decided to start up oxygen sensors from fingertips to the reef. So this way it becomes very comfortable. It allows us to measure 24/7 and just we left the state we have about 2 middle patients under continues oxygen administration. That's really where fingertip device is 24/7 impossible to look to their fingers how they look like. So we decided to solve this problem before. So we are first on the market. Many, many companies just entered into this area. They decided to like Wombles for example failed to measure what pressure, glucose has always maintained patents to allow nothing except it. Will that work for us wireless sensors for oxygen monitoring, FDA cleared and by the way you take Apple with all noise around apple health care. There are no medical devices. You know oxitone is a world first FDA cleared medical device which measure pulse, rate, or medical grade.

: And when did you guys get your FDA approval Leon?

: But with did very complicated clinical trials in Colorado only two sites in the United States where you can make this iteration tests. Here are can come comparative test invasi oximeters.

: Yes.

: Like my Seema like any medical like all other devices today fingertip devices.

: Yes.

: The unit is just trial deals they didn't believe because they said many companies came to us, it doesn't work. We succeeded they checked it many times. And finally they said OK, it works. This is where technology, so this is literally technology without more than 5 portals ground paternalistic knowledge world wide and we're using very unique ways, unique configuration of sensors that nobody could repeat it.

: Congratulations on the approval. When did it happen.

: Exactly a year ago. By the way today I have my birthday.

: Today is your birthday?

: Yep.

: Happy birthday.

: Thank you very much. Exactly at my birthday a year ago. We got FDA clearance.

: Did you really? Talk about an amazing birthday gift. That's amazing. That is amazing. So big congratulations to you Leon. It's not easy to get approval especially on a device that others have tried to develop and have failed and so a year ago you got approval. What are you guys planning to do now?

: We've planned this year on developing sales infrastructure. Because it's not just sale like other devices for atmospheric measurements. It requires some technical support. It requires continuous connection to the healthcare environment. We've developed finalized with portal patient or the patient application because I can't even tell you that some companies they are not ready to take wire to catch up this. It's such such a huge stream of data. They are all dedicated to omcethey are once we mainstream and by the way all these measurements you post when they feel that, they get measurement. In our case will whole digital continuous care. While the US entry into the digital continuous care. And what is the difference? The difference that each should have continuous care yoi have produce.

: Yes.

: A lot of evidence base. So if you a once a day once a week, you cannot predict anything but it does have some impact on vital signs. And by the way we measure what oxygen saturation holds the rate activities, temperature, pulse rate variability so it's against stress. So we have the department continues potom of data. So if something changes, it's a blueprint or a patient like they may. And this is will be catch up in time.

: It's definitely exciting. And so you're putting together the infrastructure you're putting together the platforms for for patient portals connectivity to help others do the digital continuous monitoring and definitely exciting for this technology to come forth. For you, Leon what would you say the future looks like? Let's call it five years from now. Where is this technology being used? How is it being implemented and who cares about it?

: Very very difficult question because this creation belongs to resistance of the current medical system to new development of design and I think in any it's importance for high risk patients.

: Yes

: So the main important use case is the high risk patients recently discharged from the hospital. All we talk about hospital at home. So patient in stable going to the hospital to be admitted after the emergency room visits. They could be sent back home with the same level of hospital grade monitoring like they would have in the hospital. So I think at least acknowledge it. And by the way there are other companies like wide to come that they also they provide the digital continuous care or heg from that patch. Maybe she's not so comfortable like a small wrist watch made case it was. So there is some cohort of companies we should just write to all the right who the market with their medical system to accept our technology. Digital continuous not only monitoring because it's a digital continuous care. This is the hospital great care at home. So I see them move using these technology. We can move hospital care and monitoring to the home so we can remove or reviews hospital stay very dramatically because instead of whether we have to spend two days in the hospital just for measurements of vital signs I can pull up that they take off my small fingers to monitor. Everybody knows what to do and take oxitone, go home and continue the same level of care of monitoring. So we have three main changes that will happen and our technology will intensifie just readmission reduction, very low readmission and very low, very efficient readmission because all readmissions reduction to date has been very high new workload it's very high, very costly. In our case, everything happen automatically. So you have automated continuous door at the same time. You don't have to call every day to check the patient, to care to go to the patient every day, to ask what happened. Everything goes automatically up while you're waiting for that a lot. And a lot of cell will be before something happens. The other emergency room to hold. And then our water or another change it will be a real reduction. Will the hospital stay.

: Well there's no doubt this technology will be providing a lot of benefits to patients to health systems potentially a big way to reduce costs. Right getting patients home faster and it's pretty exciting. Now maybe something that I'd love to hear from you Leon as the listeners also are working to bring forth their innovations. What would you share of a setback that you had in the long process to get this technology finally approved? Can you share a setback or a failure that you experienced and what you learned from that?

: Well you do something new. You go through a hole pitfalls you can find it. So.

: Yes a lot of pitfalls.

: Doesn't allow the easy way, you know so if you have some pitfalls you will get in. So yes it is the real problem. Somebody said if it doesn't kill us, it make us stronger. So really we investigated each mistake. It was a mechanical mistake it was technical, it was optical, so everywhere. So we made a very small step then stepped back, step fast, step back. So we systemised all these mistakes, we build working system, working system I would say and this allows today to anticipate some mistakes and to avoid it.

: Fascinating. And so there's no doubt Leon, you're a patient man.

: Not sure.

: You're a patient man with the vision. Right. And so folks if you're listening to this you know it wasn't an easy road for Leon to get to where he is now with him and his team finally having an FDA approved product and building systems to actually commercialize and distribute this product. It's Pptients. It's a vision. But to Leon's point it's also building the systems that are going to help you avoid the failures and the setbacks that you had to begin with. And so Leon really appreciate that share. What would you say today is your proudest medical leadership experiences that you've had?

: I think I can just separate leadership, medical or executive or I don't know. So just have to move. We have to move all the time. We can't just watch what happens. Dawn Oh I do not have to move all the time and the leadership experience that once I stop, I lost a lot. Never stop it doesn't matter do we have money, do have customers. If you believe in what you're doing all of the world will follow you.

: I love it. And this is such a great message. Leon I last week I had a chance to be at the Beckers healthcare meeting where I was able to hear both President Clinton and also President George W. Bush speak and they shared the same message and that message was stand for something, believe in something and stand for it and do something. So coming from two past presidents and also Dr. Leon Eisen I think it's piece of advice worth following. Listeners stand for something and do something and the world will follow you. Yeah very great share Leon. Very Great share. Tell us a little bit more about an exciting project within what you're doing now that you're so excited about and you want to tell the listeners.

: This is still the same project to have to improve our device. And the more vital signs with and more capabilities and the most important we're going to launch sales this summer. Official sales.

: Awesome

: Even from our website we have a long list of preorders. just from patients, from physicians, from institutes, universities and companies. And so our project today is to launch sale...

: So being that it's an FDA cleared device. Do you need a prescription to have it or can patients buy it directly. How does that work?

: Because you have 5000 K we need a prescription.

: So you do need a prescription, nevertheless it's available. Once you have that prescription patients could buy it for themselves.

: They could buy for themselves or insurance companies to provide, hospitals who provide them who tried different business models. Because again you don't have very well established business model yet though. So why. Because for example any proximeter is not induced by Medicaid or Medicare. It was reduced because while you do more so so be the whole use all at once a week measurements will pay for that. In our case another challenge would have to show that there is the real Weidensaul, we bring medical device or medical device in different level and we have to the reason why in this device and we have to get in there. And this is another project we are just getting started working on.

: Excellent. Well we definitely wish you the best on this on this project. I mean you've been persistent even passionate and you've been consistent in your approach and I have no doubt you're going to succeed at this Leon. Now let's pretend you and I are building a leadership course on how to be successful in health care leadership. It's the 101 of the Dr. Leon Eisen. So we've got a syllabus. We're going to put it together four questions that are fast, lightning round questions followed by your favorite book that you recommend to the listeners. You ready.

: Yup.

: Alright. What's the best way to improve health care outcomes?

: To get patients involved.

: What's the biggest mistake or pitfall to avoid?

: To accept industry resistance as no.

: How do you stay relevant as an organization despite the change?

: The whole world is changing.

: And finally what's one area of focus that should drive everything in a health organization?

: In our organization it's device.

: What book would you recommend to the listeners, Leon?

: I recommend Art of War by Sun Tzu. This book, I read every once a year. I read it again and again. I don't know, like bible. And every time it gives me inspiration and understanding how to fight.

: That's wonderful. The Art of War and listeners. Don't worry about writing any of this down. You could find the show notes as well as links to all the things that we've talked about including links to Leon's company Oxitone medical as well as the link to the book that he just recommended and a full transcript of our conversation. Just go to outcomesrocket.health/oxitone. You're going to be able to find all that there. Leon this has been a lot of fun. Really excited for the innovative approaches that you guys are taking. If you can just share a closing thought with the listeners and then the best place where they could get in touch with you to learn more.

: Here's to follow. I very much appreciate our listeners for their time. So thank you very much. And what I suggest first of all, move all the time. Do not stop, if you have an idea, you have to start to elaborate this idea. I called business you around this idea so I'm open to any questions if you have something - starting from zero. Do something personal. I'm here for you.

: Outstanding and Leon, really appreciate you spending time with us and looking forward to seeing your success and you to add value to the health system with this innovative technology. Thank you very much.

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Recommended Book:

The Art of War

Company website:

https://www.oxitone.com/

Episode Sponsor:

How to Increase Engagement with Chronic Condition Patients with Cory Kidd, CEO at Catalia Health

: I really thank you for tuning in again and I welcome you to go to our outcomesrocket.health/reviews where you could rate and review today's show because we have an amazing guest for you today. He is an amazing person, super smart and a great contributor to Health Care. His name is Cory Kidd. He's the CEO at Catalia health. His background involves over 20 years of health and technology half of which was academia at the MIT group in the Media Arts and Sciences Lab as well as just being at the frontlines in business and so he's got such a great mix of experience in both of those and now with his new venture at Catalia health. I thought it would be wonderful to get him on talk to us a little bit about robotics, artificial intelligence and the beautiful amazing things that they're doing at Catalia. So Cory, welcome to the podcast fill in any of the gaps there that I may have missed.

: Well first thanks for having me. It's great to be here. I think that was a great overview of it just to kind of ground the conversation. Yeah. Quickly My background is a mix of number of different things an undergrad of computer science focused on artificial intelligence and human computer interaction all applied to healthcare. That was a Georgia Tech and that was at MIT as you said I did my Master's Ph.D. at the Media Lab, spent a few years at Boston University Medical Center in Endocrinology and observing and getting to spend time in the clinic seeing patients. End of the last decade, I've started a couple of companies commercializing some of the things that I found during that academic period. But the overall arc has been how can we leverage cutting edge technology to solve some of the big challenges in healthcare.

: Beautiful and so no doubt Cory that you have a rich level of experience across a lot of different areas and so just out of curiosity What got you into healthcare?

: You know I always had an interest in healthcare. 20 some years ago when I was trying to decide what I wanted to do with my life you know give very strong consideration to going to med school. A lot of my friends from that time are now practicing doctors and decided that actually the route I wanted to go was combined my interest in health care and technology as a way to potentially help many more patients that I could do as a practicing physician. So now fortunately I get to work with a lot of people in doctor and nursing and other clinical roles. But the route that I took was a way that I think we can leverage as I was saying a moment ago a lot of technology, cutting edge technology to solve some of the challenges that we see today in healthcare.

: That's so awesome and I'm so glad that it worked out for you. Obviously you've intertwined these two loves and now you're here you're doing some amazing things with the different organizations that you're involved with Cory with the company that you're focused on right now. What would you say today is a hot topic that needs to be on every medical leaders agenda?

: Well if we look at what's specifically hot right now you know we see artificial intelligence and machine learning. If we look at kind of technology and impact on healthcare those are definitely the buzzwords. But I think what needs to be on everyone's mind is not necessarily those specifics although it is worthwhile knowing some about those but how the world is rapidly changing technology is really impacting medicine today. And depending on your particular area of healthcare and that's going to vary a little bit. But broadly speaking we definitely see technology moving into actual healthcare at a much faster pace. And so developing and understanding at an organization around you that can support that I think is critical. You know what we see our healthcare system and healthcare institutions and companies that aren't adopting changes in technology are going to fall behind very quickly.

: Yeah and they're definitely a very big risk. Listeners, this is something that is worth reiterating. You know if you're not embracing some sort of organizational structure to help you embrace these digital advances these computer advances then you're gonna be left behind. And so Cory maybe we can ask you what would you recommend them. You know the listeners trying to stay up with the times. What would you recommend them as a basic step they could take.

: Well I think there are a lot of things that can be done. I mean just keeping up with technology trends and if you are not someone who's deeply embedded in the technology yourself at least have an understanding of what these things are and what these things mean artificial intelligence machine learning like I was talking about bitcoin and block chain. I think there's going to be an impact of block chain on healthcare. What does that mean to your business. You don't have to be the expert but have a high level understanding with them bringing those people around you or structure your organization so that you can at least start to answer some of those questions about what should we be doing today. What do we need to be looking at the next 6 to 12 months. What's a few years out and was completely irrelevant to us. You should have enough knowledge to be able to answer those questions and at least know where the impact in your business is going to be. And I think most importantly where the impact on providing care and providing patient outcomes is going to be.

: Beautiful. So listeners if you take anything from this episode there's plenty more to come but take just that. That framework that Cory laid out for you. Hit rewind on this. Listen to it again. Write it down. Because it's happening and it's happening fast. And so you don't want to get left behind. And so Cory you're obviously on the front end of this advances. Can you share with the listeners what you're doing potentially at the organization you're at now to improve outcomes.

: Absolutely. You know I think that we're on one of the many many front edges and that's what challenges right now is how many different things are happening. So Catalia Health is a chronic disease care management company. Now there are a lot of other people trying to deliver care management particularly when we think about the domain that we're in which is outside of the hospital or the clinic now helping patients do that everyday follow up. Now one way this is done today is you know we've got great home care agencies out there that are sending people out into the homes at a much bigger scale. This is happening using call centers full of nurses and other clinicians at times to make calls to patients. But both of those are really challenging to scale you know home health actually sending someone out that's extremely tight. It's a very expensive in many of these call center based programs. The other quote unquote high touch programs means you're going to talk to a patient a couple times a month. And that's great for the level of care that we're providing today. But we want to be able to do so much more. And that's where Catalia health comes in. So instead of these completely human driven interactions, we of course bring a bit of technology to play. We give our patients a cute little robot. It sits in their home on their kitchen counter bedside table coffee table wherever they want. And by the way if you to get a sense of what this looks like you can go to our website cataliahealth.com. And there's a short 90-second video there you can actually see someone interacting with one of these. And so that's the interface. And I think we can come back in a second. Talk about why we use that interface. But on the technology side most of what we do is the artificial intelligence behind that that's creating a conversation on the fly for that patient at that point in time. Now we build these around particular disease states for example we have these out with heart failure patients today. And these are checking in with a patient about what's going on related to their condition in the background we're modeling that patient that we can talk more about how this happens as well to tailor that conversation specifically to them. So this is partly about checking in. How are things going? Did you take your medications? What was your weight this morning? Partly about education. Helping the patient better understand their condition and the management of it and partly about motivating that patient to stay engaged. So one of our big challenges today in chronic care management is how do we keep patients on whatever that therapy whatever that program might be for an extended period of time. And that's a big area of focus for us. Now of course through this we're getting a lot of data. We have a lot better understanding about what's going on with that patient day to day than is practical to get now. So on the back end we're gathering that data doing the analysis and then sharing it with the doctor or the care manager and nurse for the pharmacy as needed depending on what patient population and we're working with. So at core we're focused on chronic care management but we have a very unique and scalable way of going about it.

: Cory, super cool and listeners take that link from Cory and you'll be able to see what the little robot looks like but more importantly you'll be able to see what the company is all about and it's that chronic care management in a way that provides data you know patient reported data. It's tough to get. And now with the advent of voice. With the advent of artificial intelligence like Cory said there's so many fronts to so many things that I think they're doing some really interesting work to help manage the patient when they leave the hospital which is a very challenging thing. Now Cory question for you, a lot of things come up you know people say it's a robot. We need humans. Is there a human touch to the robot. How's that whole thing work?

: All right there's a bunch of pieces to that you know. So let's start with what are we doing here. Where do we fit into the healthcare system. Our goal is not to replace any humans in doing their job. We're trying to help them do a better job. So we're not getting rid of those hom care programs. We're not replacing those call centers but as we were talking about those interactions tend to be infrequent. If I'm a patient dealing with a chronic disease, I'm dealing with that every day. This helps to fill in those gaps and then let the clinicians who are providing care understand the when and where they need to reach out to patients. So with that data we're able to better target the people time that we have in order to solve some of those problems. Now let's talk for a second about two quick things so one is why do we use a robot the first place? It would be a lot easier. Right. So it would be a lot easier to deliver these conversations through a smartphone or a tablet or through a web browser, on your laptop. But yes the analogy here and where this comes from is you know we're listening to a podcast right now but it would be different if we were having a face to face conversation. Now it would be logistically challenging for each of us to do that. But in business that's exactly what we do. As CEO of Catalia Health, I spend the majority of my time on the road with our customers, our partners, our investors, our patients and we all do that in business and in medicine because we understand that face to face makes a difference. And from a psychological perspective we actually know what that difference is. We're face to face with someone as opposed to a phone call or an email or even a video conference face to face means we're more engaged. We're creating a stronger relationship. We even find that person that we're talking with to be more credible more informative more trustworthy. Now as it turns out, those differences carry over into the world of technology. In other words, I put that robot in front of a patient that can literally look them in the eyes while it's starting to them. We get those psychological effects of face to face engagement. Now one or two interactions that you know may or may not be important but where that really makes a difference is over time. And if we compare head to head using an interface like we do with the robot versus delivering the same thing through an app, we're going to get much better engagement over time with our patients. And so that's what it really comes down to for us. And then the last thing I'll say on response to your question is how we go about creating this is not like a chatbot. So this is not technology that's listening for the patient to say something and then you know going out and searching a database doing some statistical analysis and trying to come up with some answer. The robots are really directing the conversation and all those conversations start with people start with experts in that disease state. At our company, obviously we are building a bit of technology but less than half of the company have are people with technology backgrounds. The other half of our product team are people who are clinicians, doctors, nurses, psychologists, writers our head writers are former Hollywood screenwriter and it's the interplay among all these things that make this work. In other words everything that maybe a robot is saying to a patient is clinically valid. It's been created by one of our researchers using you know best practices or literature that's available on managing a particular disease state. We have consulting clinicians who are experts in that disease state as well to help us understand that process and create that content but then also working with our writers to make sure that it comes across in a very friendly approachable way that's appropriate for that particular patient. Now the adaptation to that particular patient happens automatically. That's what helps the scale. Once we develop an application for a disease state it doesn't matter for rolling that out to 100 patients or 100000 patients. That part becomes easy once we have the first piece of this created around that particular disease state.

: Very cool Cory and no doubt that it's been very thoughtfully done. You guys are taking a very scientific but also human touch approach in the way that you guys are deploying the technology to help these patients. And also the people that are taking care of these patients. Can you give an example to the listeners of how your company has already improved outcomes with what you've done?

: So this company is about three and a half years old and as you might imagine from looking at the product there's a lot of infrastructure to build to get ready. So you know we've been fortunate that early this year we have finally launched with patients so we're still fairly early in the data.

: Congratulations.

: Thank you. However the first version of this was put in front of patients 11 or 12 years ago. So there's a lot of research behind this showing the ability to use this to keep patients on therapy for longer. Now our first roll-out this year of the Mabu commercial product is with heart failure patients and what we're seeing from the initial data is that patients are using this very frequently. So on a very regular basis once or twice a day and for a reasonably long period of time. So what that really means though is we're able to get the important information from patients. So in the case of heart failure we're asking about daily weight we're asking about shortness of breath and other symptoms. Now the critical things that we would want to know about a patient is as a clinician we were able to talk to them everyday and were also able to spend time educating that patient. Now, if we think about the example of heart failure but this applies in so many other places. You know, a patient gets a new diagnoses and all of a sudden there's a new drug there are three or five drugs in the case of many of these patients. And look you need to do this and you need to follow this diet. And you know here's your first follow up appointment here's your second I want you to think about this everyday and do this. It's overwhelming. It made this patient in the moment may feel like they understand it but they leave the hospital, they leave the doctors office and wait what was that. They don't recall what my doctors said about this. And the other thing that we see with our patients is that many of them are hesitant to reach out to call the doctor. I don't want to bother someone but knowing these things are incredibly important to managing care over time to improving outcomes on this disease to not going back to the hospital. And so what we're able to do and what we're seeing is that patients are willing to talk to Mabu the robot about these kinds of things day after day and so it's a way to deliver this educational content in a time and place when the patient is ready to receive it. So those are the things that we're really focused on in terms of being able to improve outcomes over time.

: That's wonderful Corey and one of the biggest problems is medication adherence right? Whatever we could do to improve medication adherence will be amazing.

: That is definitely one of the critical parts of it. You know we try to take a very broad view about managing an overall disease state. But you're absolutely right. Many of these diseases, the medication that that patient is on and today often the lack of proper adherence to it is one of the big challenges that we see.

: Yeah absolutely. Big problems you guys are doing some really great stuff to get them solved. Congratulations on launching this year with the first patients. And so now you guys are rocking and rolling as you've moved forward in this process. Cory, can you tell the listeners about a time when you had a setback on the way to this process. This launch finally and what you learned from that setback?

: Well you know it's kind of one of those things that you often see in business and particularly in technology where people see this now and you know think of it as brand new and I've been building stuff like this for two decades now. I launched my first company just over 10 years ago and obviously that was very early in terms of this kind of technology. And one of the challenges then is just figuring out what's the channel, how do we get this to market. We ended up doing deals with Pharma, with payers, providers, self-insured employers, direct to consumer and trying to figure that out. But there were a lot of setbacks along the way. You know one of the challenges when you're trying to do something new and different in healthcare is just figuring out where you fit in. And actually this is really shared across a lot of business but healthcare you know we definitely see this because for good reasons healthcare can be very slow moving. We figured out what works with patients. We don't want to change that. We don't want to introduce any risk in what we're doing. But that also has its challenges when we find something new that works in figuring out how to get it out there. And so I think one of the setbacks that I've seen often on over 10 years of working to sell this kind of technology is just figuring out who's going to pay for it and why. Part of what we're doing here is obviously developing a very new interface for patients. And what we're doing is unique. We're very differentiated in terms of that. But one thing I've had to figure out over the last decade is on the other side of this, the business side and where we fit into healthcare. How do we basically do the opposite and do nothing new? Because we have to fit into existing business models, existing payment models, existing workflow and understanding how to fit something new that we're doing into all of that has been a huge lesson learned over my career.

: That's such a great share Cory. Listeners if you're working on a new idea and even large companies. If you're implementing a new technology or a new product, who is going to pay for it and why. Truly understanding this is going to save you from a lot of headaches, heart aches, and over a hundred. Isn't there a Cory?

: Absolutely correct!

: Yeah, so make sure you think about this. You know so many people don't think about it. Make sure that you implement this thought into your strategy your go to market strategy. What would you say one of your proudest leadership moments in healthcare have been to date Cory?

Well I'm excited right now that I get to do a lot of public speaking about not only what we do with Catalia health but the impact of technology in healthcare particularly around artificial intelligence and sometimes around robotics and it's very exciting to see right now the response of this is receiving. People are genuinely excited about it and really trying to understand how they can use this to make a difference. Obviously I'm not the only one out there talking about this but it's something that I've focused on for a long time. So it's very exciting for me to see how this kind of thing is starting to have a real impact at health care.

: Tell us a little bit about an exciting project or focus that you're working on today. It could be something within Catalia or anything else that's on your mind?

: Well right now I'm very focused on what we're doing with patients with heart failure. So we launched with one of our customers about a month and a half ago it's Kaiser Permanente. So they're a great partner for us in rolling this out but we've also launched an internal pilot. So we are shipping these directly to patients and we're now getting feedback from those patients in terms of the data that we see every day. You know a data feed about what's going on across those patients but some of our nurses are on the phone with those patients and going to their homes and interviewing them and getting direct feedback. So this is something that's very exciting on the minds of not only me but everyone here at Catalia Health right now really focused on how do we make an impact on these patients and how do we use their feedback to continue to make what we're doing even better.

: Wow, that's so awesome. Definitely exciting Cory and you know I'm sure you and your team are are working around the clock to figure out how to best tweak these devices to best get patients what they need.

: It's a very important part of what we do. Starting with you know the foundational principles of medicine and psychology and building based on that but then using that real world feedback to continue to improve.

: Super amazing. I think you guys are doing some really great things Cory as we get to the end of this podcast, I've got a lightning round for you for questions. You and I are going to build a medical leadership course right here.

: What it takes to ..

: Alright.

: It's the 101 of Cory Kidd. So four questions on this syllabus. And then we're going to follow that with a favorite book and podcast. You're ready?

: Alright

: All right. What's the best way to improve health care outcomes?

: I think what I'm seeing right now is evaluate all angles to look for opportunities. So what I mean by that is you know health care problems are complicated. Sometimes the answer is in technology like we've been talking about, sometimes it's in process. Sometimes it's in people sometimes it's how do you do something earlier or how do you postpone something to later. And just thinking about it from many different ways which usually means a pretty diverse group of people who have some knowledge of that problem I think is the best way to go about it.

: Awesome. What's the biggest mistake or pitfall to avoid?

: One thing I've seen in my career being involved with the technology side of healthcare is kind of the desire for the shiny new thing. I thought about this a little bit tangentially earlier in understanding where AI or a block chain or machine learning or whatever it might be is an impact on your business. And one of those options that I stated was it has no impact, right? It doesn't matter. Understanding that answer I think is incredibly important and I think that's the answer that's often overlooked. There are these hot technologies that catch on in certain areas. Well it must have an impact on our business. Let's do something. And I've seen a lot of health care organizations spend a lot of time and money and figuring out that that just doesn't matter to them.

: What a great call out. How do you stay relevant despite all the change?

: You know I think that's always a challenge particularly as an organization grows. I think part of it is you know just following the trends that are going on and you know understanding what they are at least enough to be able to explain what it is. I think also you know as organizations grow keeping people around you who do the same. Trying to find people who aren't just about the status quo in whatever that is, whatever aspect of your business or the health care that you're providing, but people who are excited about trying and doing different things.

: And finally what's an area of focus that should drive everything in a health organization?

: Patient outcomes. What are we actually doing with our patients. I think that's critical.

: Love it. And what book would you recommend to the listeners?

: All right, I'm going to take something from a technology perspective this is an older book several decades old called Society of Mind. So this is a book that was written by Marvin Minsky 3 or 4 decades ago now. So everyone is familiar with the term artificial intelligence. Not many people know where it came from. Marvin was one of the early people working in this space and he and Joe McCarthy coined the term artificial intelligence a little over 60 years ago now. And so the whole premise of this book one of the ones in the middle of his career is that a mind or thinking or this higher level thought processes all come from simpler things that are happening under the hood if you will right smaller simpler things that we can search to figure out and decompose. And if I look at the work that I've done for the last 20 years this is one of the principles that it's really based on. You know we build these really complex systems with Mabu and the data analysis that we're doing on the back end. But any one piece of it is fairly simple. I was fortunate to be able to study under Marven grad school and get some of these ideas from him firsthand but well before that at least a decade before that I'd read this book and I highly recommend that if you want to understand the basics of artificial intelligence. This is a very approachable accessible book.

: What a great recommendation and what podcasts would you recommend to the listeners?

: What I'm enjoying right now is Masters of scale by Reid Hoffman, he was one of the founders of linkedIn. He is a venture partner now. But he has done it. You know he has access to a lot of amazing entrepreneurs whether they be small companies or many of them are a very very big companies now. But what does it take to do something at scale? He approaches that from many different angles and I'm greatly enjoying it and trying to figure out how he can apply many of these lessons in my business today.

: What a great recommendation. Listeners don't worry about writing this down. Just go to outcomesrocket.health/catalia and you're going to be able to find the show notes as well as a transcript just so you know catalia is C.A.T.A.L.I.A. Just go to outcomesrocket.health/catalia. You'll be able to find the links to the book that Cory recommended, the podcast and everything that we talked about today. Cory, this has been a ton of fun. I'd love if you could just share a closing thought with the listeners and then the best place where they can get a hold of you.

: Closing thought would be make a change. Try to do something different. Try to figure out where you can have an impact. That's what really drives everything that I do in my career. And I love working with people who think the same way regardless of what that change is. And a couple of great places to reach me. I'm on Twitter @Coryk. I'm pretty easy to find on LinkedIn as well. If you want to reach out just add a message to it.

: Outstanding. Cory, thank you so much. We really appreciate all the things that you share with us today and we're excited to keep up with all the outstanding things that you're up to. So thanks again for making time for us.

: Well thank you so much for the invitation. This was a great conversation and I look forward to hearing from the listeners.

Automatically convert audio to text with Sonix

Recommended Book and Podcast:

The Society of Mind

Masters of Scale podcast

Best Way to Contact Cory:

Linkedin - Cory Kidd

Twitter - @coryk

Mentioned Link/s:

http://www.cataliahealth.com/

Episode Sponsor:

Leveraging Data and Practitioner Insights to Improve Outcomes with Blake Marggraff, CEO at Epharmix

: Welcome back once again to the outcomes rocket podcast where we chat with today's most successful and inspiring health leaders. I really thank you for tuning in again and I welcome you to go to outcomesrocket.health/reviews where you could rate and review today's podcast because we have an outstanding individual in health care. His name is Blake Marggraff. He's the CEO at Epharmix. Over at Epharmix, they're focused on keeping the toughest and most expensive 20% of patients in touch with their outpatient care teams at risk bearing health organizations. They're really focused by using their digital health platform to make this hard to take care of group even easier to take care of and to take costs out of the equation all at the same time while improving outcomes. He worked so hard to do this. We had his co-founder and chief medical officer Avec Sam on the podcast and I'm thrilled to be able to have Blake carve out some time with us on the outcomes rocket. Blake, welcome to the podcast my friend and maybe fill in any of the gaps that I missed in your intro.

: Thank you, no, say it's a it's it's a pleasure to join today. My background is still relatively brief and I'm 25 years old and my passion in healthcare started kind of paradoxically when I moved from through medicine research into the technology side of things back in 2011. I ended up participating in a winning something called Intel Science Engineering Fair and that frankly it gave me the chance to meet folks like folks like you and having conversations. I mean you're surrounded by these mind that Medtronic right. But it is pretty rare to have conversations about things that are impactful but impactful and really scalable way. And I fell in love with the idea of spending every moment that I could. Working not just on making the world a better place for some people but for as many people as possible and jumping to the point really the two ways to do that or help people live better lives or to help people live longer lives and health is two birds with one stone in that regard.

: That's awesome Blake. You know you guys are so passionate about what you do there at Epharmix and there's no doubt your leadership and what you bring to the table is a big part of that. What today in your mind is a hot topic that needs to be an every medical leaders agenda. And how are you and your team at Epharmix tackling that?

: Oh great question. So I'm first going to stand on my soapbox for just five seconds. I think that a lot of folks cite AI as the hot topic of the day and really artificial intelligence machine learning those are means to an end and multiple ends, right? I think that the real hot topic the crux of it is data and specifically the rare data that enables those AI engines if you will to run the most powerful way possible. So my focus and I think for a lot of health care leaders should be focused is on asking the right questions and then collecting the pertinent data to help inform the answers to those questions. That's why our team is focused on not just all the data we can get but the right pieces of data.

: Getting the right data. And it's not easy right? And so maybe you could talk to us about what you guys are doing at Epharmix to get clean data and how you're doing it and maybe some of the results that have come out of that.

: Absolutely. So Epharmix keeps the toughest patients engaged for a really long time. As you said and it turns out that it's pretty easy to get most patients to answer a few questions once or twice. It gets much more difficult when you look at engaging chronically ill especially poly chronic populations that are not tech and able and you keeping those patients engaged for months or years on it. And that's where we specialize. So by the numbers Epharmix has more than 63% engagement for a full 52 week window. We're over 50% engagement for 100 weeks. So pushing that 2 year mark which is pretty striking given that in some of our populations the average income is $12,000 a year and I think very humbly made made all the more impressive by the fact that independent clinical researchers now shown that Epharmix tools drive real outcomes when combined with care management. It's not just Epharmix but Epharmix is a necessary piece of that puzzle. And an example there we reduce the hospitalization likelihood for COPD patients versus control by more than 60% drop A1C for patients with diabetes by more than one absolute percent. So starting with an A1C of over eight even help get hypertension patients under control and moving about half of the hypertensive patients back into the prehypertensive state. And we do that to your point and to your question by not just asking all the questions that we could ask but instead by almost sniper picking the right questions and collecting those rare data that are then related to the care teams. The care team can reach out use their clinical expertise and inform care.

: That's pretty cool Blake. And so you guys have a very thoughtful approach. You're getting results. The evidence is is in the numbers. You've also been featured in a lot of different publications like entrepreneur Moby health news, Bekkers and so you're definitely creating some traction out there and you're getting some attention through the process. What would you say has been one of the key learnings right I think as the listeners that tune in that our digital health entrepreneurs they are going through the trenches and the peaks and so maybe you could share with us a time when you had a setback or a failure what you learned from that and what you do now as as a result of it?

: Just picking one time as the challenge to spend at least 15 minutes those since my last one so I'd say a theme of failures. Not only that we've experienced to be Epharmix but I think that a lot of folks coming in to try to be really good industry partners struggle with is health care is not a turnkey industry. Most enterprise sales have some level of complexity but I would say that healthcare has to rival the most complex ones. So going in and saying we have this fantastic software as a service offering we're going to throw it over to you. You're going to buy, you're going to pay us money then we're going to stay hands off and watch it as it delivers tons of value. That's unrealistic to say. So big failure is acting that way. And then of course the converse of that is by being really hands-on, by treating every health system has its own unique entity with its own flaws and opportunities. We can help them succeed. Maybe a more specific failure. I think something that's fascinating on the research and development side is Epharmix also supports populations such as Mothers on Medicaid or feeding postpartum depression and a number of other related indications or stages. And our first attempt at EPX breastfeeding which was intended to increase the number of months for which a new mother would breastfeed her first child. That first attempt flopped. So it was a blaze of failure. It was incredible. Folks stop using it within days the feedback was that it was almost offensive and we were applying all of our best design practices to this. Right we gone through the same. So we pulled back really embraced the patient centric design mentality. We even brought in ... to begin providing feedback on the product. And finally landed on something that wasn't good academically or at least wasn't driven by the academic best practices but was instead driven by real feedback from those new mothers and the folks who helped support them right after you know immediate postpartum. And it was night and day. The engagement the theme.

: Nice!

: That suddenly became a tremendously positive,so.

: That's such a great share Blake and friends. You listen to Blake's passion you know even when he's talking about his setbacks he's engaged he's all in and you know this topic of high tech versus high touch. There's no versus. You got a little bit of both. If you're going to really succeed in this field and for those thinking that they could just throw on software and walk away like Blake said you're making a big mistake. So Blake I'm glad you highlighted this very common misconception that people make when they come from tech into health. And it seems like it's something that you guys learn very quickly and you're implementing very quickly as well to scale.

: I appreciate that. Hopefully we keep learning more and more.

: Hey Blake, so tell us about what are your proudest leadership moments to date with Epharmix?

: We've helped a lot of patients. Well into the high thousands of patients now across the range of disease states and I think one of the most impactful moments was early on as a team. But you won't have a company and now we're more than two and a half years old and we had just closed one of our first commercial customers and one of the care managers shot an email to one of our managers saying hey I have some feedback for you. Essentially explains that Epharrmix had helped a patient who later admitted that he had given up on his self and helped the patient to begin tracking blood sugars. You know really simple just basic diabetes management and had really fundamentally changed the trajectory of that patients health by empowering the patient which was our focus really is sustainable outcomes long term outcomes. But seeing that shift in someone who frankly had been failed by the healthcare system not through any malice but simply as a result of the of the conditions and incentives that surrounded that patient. That was pretty powerful. That got smiles on our faces for a few days afterward.

: That's awesome. Yeah and you know specially when you're impacting the lives of people and you're seeing them come through your system and you know that you're actually making the lives of folks better. There's nothing more awesome than to be able to do that. So within Epharmix, you guys are working on a lot right? You already have a lot of specialties that you focus on. But what would you say today is one of the most exciting projects or focuses that you're working on?

: Sure. So a couple of categories. One is really making the most of the rare data that we have and that generally means we have an excellent tool for patient engagement and we're able to drive outcomes as a result of that long term engagement. But the next two stages are predicting adverse outcomes and then helping prevent those outcomes. So a lot of team energy in the background goes to baking those capabilities into product. For instance we have a couple of publications in the pipeline that show really compelling outcomes you know meaningful, high area under curve predictions with relatively straightforward machine learning models and we find the right model out of dumpsters that we try that can even predict for instance suicidality within a set timeframe for a pediatric Medicaid population or adolescent population really really powerful predictive models. That's one category. I mean it's amazing what you can do if you have the right data at the right time. The other area that's got me very excited is helping to make scalable some of those. As you would say high touch elements of service delivery. Right. So we have these fundamentally very strong, very robust product that helps care teams keep patients engaged. But what can we do to go upstream and make sure that patient enrollment and initial engagement is painless almost enjoyable for the provider and then go further downstream and deliver insights almost management oriented analytics to the economic buyer to the V.P. or the management level individual to not only showed that Epharmix is delivering value but also help them make strategic decisions based on those trends. So that upstream downstream I'd say it's another form of vertical integration of our product and our service offering that's got me pretty excited.

: That is pretty exciting Blake. And as you look at you know you guys are focused so clearly on getting the right forms of data. What would you say a good thing that health leaders need to focus on to get that data and maybe not just health leaders but also other tech companies right. How do you ask the right questions and how do you come up with those questions?

: Fantastic question. So that cuts to the research and development approach that Epharmix uses to try increasingly convinced it's a very strong way to build a product especially for a complex industry like healthcare which is a combination of standing on the shoulders of giants do a literature review understand what's already out there and then be comfortable iterating and failing and iterating and failing through until you have product is demonstrating itself and its value. In other words start with the best possible position you can, learn from the experts and then go through the process yourself embrace the experimental method and I would say to folks who are looking at all of the data that come from their AHRs all the way to hopefully potential partners such as Epharmix in the industry that are smaller innovators lean into the real reality that you will fail 85-90% of the time and that only by going through that process until you have a solid product can you deliver real value to your own workers.

: That's pretty cool Blake and what I love about what you guys are doing while you're a young organization. You guys are so focused on delivering value and putting together those randomized controlled trials and implementing the solutions to your different partners that you already partnered with. And it's so cool to have met you guys two years ago and now seeing where you're at today is just so awesome you know so.

: I appreciate that. You've been there for pretty much the entire Epharmix story come to think of it.

: And it's pretty cool you know. And I love seeing young companies succeed and there's no doubt in my mind that if you guys keep doing the same thing you're going to keep having the success that you've had early on.

: I appreciate that.

: So let's dive into the 101 course of Blake Marggraff. This is where we are is where we talk through what it takes to be successful and healthcare through business and technology. And so we're going to write out a syllabus using some lightning round questions I've got for them for you. And then we're going to follow that with a book and a podcast that you recommend to the listeners. You ready?

: Definitely.

: Awesome Blake. So what's the best way to improve health care outcome?

: I think the single best way is to intelligently distribute risk and I say that because right now when you look at the perverse incentives that arise there are usually there because either over a certain period of time or just an order of magnitude risk is not distributed among all stakeholders.

: What's the biggest mistake or pitfall to avoid?

: Don't assume people want to change let alone that people will change if given the opportunity and when you're making clinical improvements. Keep that in mind.

: I love that Blake spoken from experience right.

: Unfortunately, yes.

: And listeners if you're hearing this is all too common with new products and health care do not assume people want to change and Blake I'm glad you brought that out. How do you stay relevant as an organization despite constant change?

: So this one kind of has a logical corollary that's pretty obvious I guess which is make yourself irrelevant as long as you're the one making your previous so obsolete then almost the fact that you'll continue to grow and prove it.

: Love it. Why and what is one area of focus that should drive everything in healthcare?

: So I have to say we're all speaking the same language here from outcomes rocket. It's sustained outcomes. It's driving meaningful clinical value and thus financial value and not only driving it for weeks or months but for years on it.

: And finally what book and what podcast would you recommend to listeners on the syllabus Blake?

: So Peter T.L. released a book that was co-written by Blake Masters called Zero to One which stands out and says one of my favorites. And I'd say in terms of podcasts I'm going to go away from the healthcare side just a little bit and recommend to all who had not discovered it yet Radiolab which I can describe as morphiscience fantastic treasure trove of mental models and an impactful memorable stories.

: Amazing sounds very intriguing one that I'll add to my list and it's called Radiolab?

: Radiolab.

Awesome. Fantastic. Listeners, there have it. You have the one on one of Blake Marggraff and also some of the best resources in the industry here that he just shares some great resources and also we'll have the transcript there for you. Just go to outcomesrocket.health/blakem. Blake M. and you'll be able to find all that there. Blake, great times here with you today. Before we conclude I love if you could just share a closing thought and then the best place for the listeners could get a hold of you.

: For everyone out there who's part of a team leading a team anything consider asking yourself and your team the simple question. If we weren't already doing X would we start doing it today? And I think a lot of a lot of the fundamental flaws in health care would at least be solved a little bit. If folks would ask that question and getting in touch is pretty easy. We've made my email very tricky it's blake@epharmix.com. Drop me a line and I'd love to set-up time or follow the company or me at Epharmix or at @blakemarggraff.

: Oustanding Blake. Listen this has been a blast. Really appreciate the time that you spent with us today. Folks if you haven't checked them out Epharmix they're doing some pretty amazing things so definitely check out the show notes, click on that link. Find out what these folks are up to because they're really taken health care to the next level and Blake again, just wanna say thank you on behalf of all of us my friend.

: Thank you all. Really a pleasure. Appreciate it.

: Thanks for tuning in to the outcomes rocket podcast if you want the show notes, inspiration, transcripts and everything that we talked about on this episode. Just go to outcomesrocket.health. And again don't forget to check out the amazing healthcare Thinkathon where we can get together took form the blueprint for the future of healthcare. You can find more information on that and how to get involved in our theme which is "implementation is innovation". Just go to outcomesrocket.health/conference that's outcomesrocket.health/conference. Be one of the 200 that will participate. Looking forward to seeing you there.

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Recommended Book and Podcast:

Zero to One: Notes on Startups, or How to Build the Future

Radiolab

Best Ways to Contact Blake:

blake@epharmix.com

@BlakeMarggraff

Mentioned Link/s:

https://www.epharmix.com/

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