Transforming Diabetes Care Management
Episode 393

Anand Iyer, Chief Strategy Officer at WellDoc, Inc.

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Episode 393

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Transforming Diabetes Care Management with Anand Iyer, Chief Strategy Officer at WellDoc, Inc. transcript powered by Sonix—the best audio to text transcription service

Transforming Diabetes Care Management with Anand Iyer, Chief Strategy Officer at WellDoc, Inc. was automatically transcribed by Sonix with the latest audio-to-text algorithms. This transcript may contain errors. Sonix is the best way to convert your audio to text in 2019.

Welcome to the Outcomes Rocket podcast, where we inspire collaborative thinking, improved outcomes, and business success, with today’s most successful and inspiring healthcare leaders and influencers. And now your host, Saul Marquez.

Saul Marquez:
Welcome back to the Outcomes Rocket. Today, I have the privilege of hosting Anand Iyer. He’s a Chief Strategy Officer at WellDoc. He’s a respected global digital health leader, most known for his insights on an experience with technology, strategy, and regulatory policy. He has been instrumental in WellDoc’s success and the development of BlueStar. The first FDA cleared mobile prescription therapy for adults with Type 2 diabetes. Since joining WellDoc in 2008, he has held core leadership positions that included Chief Data Science Officer, President and Chief Operations Officer. In 2013, Anand was named Marilyn healthcare innovator of the Year in the field of mobile health. He was the founder and immediate past president of the In-Building Wireless Alliance and teaches advanced wireless courses to senior officers in the U.S. Department of Defense at the Institute for Defense and Business. Prior to joining PRTM, he was a member of the scientific staff of Bell North Research and Nortel Networks. He held an M.S. and PhD in electrical and computer engineering and an MBA from Carnegie Mellon University. He’s also has a B.S. in electrical and computer engineering from Carleton University. He’s very talented health leader has many insights that we’re going to dive into, as well as the mission that they’re up to at WellDoc. And it’s with a true privilege that we host him here today. So Anand, thanks for joining us.

Anand Iyer:
Thank you for having me Saul. It’s great to meet you and great to share some of these perspectives and to have this dialogue.

Saul Marquez:
Yeah Anand you know, gosh, you’ve done such great things and WellDoc’s off to a just a tremendous trajectory. What is it that got you started in healthcare?

Anand Iyer:
It’s a fascinating start to this dialogue. So part of it is a professional and part of it is personal, believe it or not. But as you alluded to earlier on, I really came from almost two decades of innovation in the wireless industry, really with wireless technology strategy, first building out the networks. So I think about founding and helping launch Nextel, Vodafone, but then moving up the ladder to the services layer where we actually started working with automotive companies like Ford and General Motors to launch their telematics programs like OnStar and then took the value proposition of kind of real time communications anywhere, anytime, if you would, whether it’s voice data, et cetera. We started implementing things in the supply chain, most notably with the Department of Defense, and then really turned my attention to what you could do inside the building with wireless, not just to come back the coverage, can you hear me now issue, but certainly what you could do with public safety, energy efficiency. And in that journey, and it was really a journey because the learnings were amazing throughout that I developed Type 2 diabetes myself. And this has been sold in about 2002 and said, “my god we’ve done wireless in every other industry. Why not healthcare?”

Saul Marquez:
Yeah.

Anand Iyer:
And so we started we started working with the usual suspects, right. The GE’s, the Siemens, the hill rums, smart beds, and you think about it even today. Misprescriptions at hospitals. So giving the patient the wrong medication or wrong dose is the eighth leading cause of death in hospitals. So these are not trivial. These are important problems to solve whether you put an RFID bracelet or the patients and tie it to the bed so that when the nurse comes in, she knows exactly this is what I need to give and administered to this patient. So we start to do that kind of stuff. And it was one of those proverbial napkin discussions at a conference where I was sitting with an endocrinologist and she was lamenting the state of diabetes management. And we asked a simple question, you know, back in two thousand five six, believe it or not. And this is before the iPhone. I mean, this is when you had a Nokia 60 100 to get to press the three key four times to get a rough ride. It was kind of device.

Saul Marquez:
Yeah yeah.

Anand Iyer:
And we said, could we actually leverage technology to help patients? And I obviously had a personal rationale for this discussion just because I had diabetes. But in short, I joke about it, but it’s serious. The two things that find me one is kind of good wireless in my blood. And one is not so good. Too much sugar in my blood somehow. WellDoc’s managed diffuse so that’s kind of how I got into it is the honest truth.

Saul Marquez:
Wow, what a story. And in a very personal one. I appreciate you sharing it. And yeah, it’s a big challenge for a lot of people. So it’d be great to better understand the technology and sort of why it’s different and how it makes an impact on. So what exactly is BlueStar?

Anand Iyer:
Yeah, it’s a great question. So let me personalize it once again. Just to give context, the answer becomes fairly evident, which is as a patient, I have to manage multiple things throughout the day. I have to manage, of course, my glucose.

Saul Marquez:
Yes.

Anand Iyer:
And that could be done by poking my finger, whether the data’s beamed to something, be a Bluetooth or it’s manually entered or as we see today with the advent of CGM, with the likes of Dexcom in rapidly break. I acquire a signal and that signal is my glucose. But that’s just one vector and one very hope. At the same time, I need to manage all my medications, which could range from just simple orals to complex orals to complex combinations of basal and bolus insulin. I have to manage my diet. In many ways, what I eat is the biggest wildcard in my diabetes, right. I have to manage my activity. I have to manage my mood, my sleep. And so there is this kind of 360, as I would call it, the 360 degree vectors that affect my wellness. And there is this wee little thing called life that gets in the way every now and then. Right. And we try hard. We try our best at the same time. If I look from the other side of the coin and I’m now the healthcare provider, I personally was a little bit of a nerd. Hence the chief data science officers stint at WellDoc and I would graph my data and take it into my doctor. But what’s the doctor going to do in a three minute office visit the humanized and trained to do that kind of pattern recognition. And so what the patient actually requires is rather than just tracking data, they need to convert the data to information, knowledge, action and outcomes. And a key mechanism to do that is if they enter data, then a solution should actually provide them coaching and feedback. And of course Saul what you may do with, say, a an after lunch reading of two hundred fifty five and what I may do with the same two hundred and fifty five may necessarily be different. Why? Your medications may be different, or your history may be different, or your comorbid conditions may be different. And so we book this concept of precision that says if I can precisely tell the patient when they enter any parameter from any of those six vectors what to do and tell them over time how they’re doing on that vector. And don’t just say you’re improving. Tell them why they’re improving. So if there’s a positive correlation between their activity and their glucose control, tell them that because it’s the teachable moment and they’re like, “aha, now I get the effect of exercise. I understand why it’s important to exercise.” At the same time, if I have violating meals or I ate too many carbs or I skip my medications, you can turn those quote unquote negative events into positive teaching events like, “oh, this is what happened.” So in many ways, what BlueStar does is it provides that real time, precise, contextual coaching and uniquely online and offline, which is an FDA requirement that says what happens if they don’t see the Internet? What happens if they’re in a airplane or parking garage? And how many solutions today if it doesn’t have an open connection to the Internet or life human coach, doesn’t work. So the FDA said, well, it’s got to work. And so BlueStar provides that coaching for the patient both in real time as well as longitudinally in these multiple dimensions. But for the healthcare provider, it takes all of that data and it runs it through evidence based guidelines using A.I. and it suggest to the provider, hey, this is what you should do based on this is where they were. This is where they are. This is what’s changed. And this is what evidence suggests you should do. But you’re the provider to which I think is right for your patient. And what we’ve seen when you combine those two pieces of… the BlueStar combines, if you would, that patient facing provider clinical decision support, the outcomes are amazing. In the tune of a two point eight 1C reduction on average, that’s four times what the FDA requires for a new drug. And it’s tectonic in its shift, as we’ll discuss, I’m sure, in the economics of what that patient bares or is a burden to the overall healthcare system. So in summary, think of BlueStar as that kind of automated software, scalable, intelligent, adaptable program that supports the patient. Precisely, but that also loops in to the health are provider to allow them to get the patient to the right treatment pathway with a little delay in interest as possible.

Saul Marquez:
Very cool. Very cool. So you guys are probably listening and saying, “wow, this is some pretty cool stuff.” And probably also wondering like I am. What are the inputs and how do you get the inputs? Are they automatic? Are they swear bowls they manually entered? What would your nutshell answer to that be?

Anand Iyer:
All of the above. And seriously, because you can’t tell a patient who has had diabetes for 40 years who has a old meter that’s not Bluetooth. Well, you need to switch your meter because…

Saul Marquez:
Right.

Anand Iyer:
Why would you at the same time, if somebody wants to connect their Fitbit, their Apple phone, their Samsung phone, whatever they want to connect, you want to let them such that the data in a frictionless way appears into the product. And then lastly, we’re talking about data on the consumer side. We can’t forget the data on the healthcare system side. So the ability to integrate labs, pharmacies, pharmacy data, EMR data. So what’s… necessary we believe condition for success is you allow for that kind of full system into operability, but that means you have to do it in a way that’s responsible. From a privacy perspective, and you have to do it in a way that’s responsible from a cybersecurity perspective. Because now I have, WellDoc’s BlueStar on an iPhone or Samsung phone and I’m connecting a Fitbit and it’s talking on the other end to EPIC and to my Walgreens pharmacy, who’s protecting that data? And so it’s incumbent upon the provider of this digital therapeutic solution to take that security very seriously.

Saul Marquez:
Now, that’s insightful and great to hear that you guys are definitely concerning yourselves with the data from patients, providers, EMR’s. And so as you think about the work that you guys have done at WellDoc, can you come up with maybe an example of an extraordinary result or an improved outcome that has happened because you’re doing it differently?

Anand Iyer:
Yeah. So I can speak to many. So let me speak to the average and then I’ll speak to some of the interesting tidbits, which is if you go back to that comment about A1C. In diabetes today, diabetes is actually quite a simple disease. And mathematically, it’s a disease of average and standard deviation. The average blood glucose is measured every three months and it’s known as hemoglobin A1C… And whilst I have to keep that average, which the market is established by the American Diabetes Association is 7%, which in English means 7% of the total blood volume is sugar. The reason for that, by the way, is if you don’t have diabetes, that number is typically five and a half. But the reason you should keep it seven or below is every one point delta away from seven. So seven to eight nine represents about a 42% increase in the risk of heart attacks, kidney failure, blindness, amputation and stroke. And the FDA heralds a drug if it drops A1C by a half. So, in fact, Saul, if you take the top 15 drugs today and diabetes and look at their published literature, their clinical trials, you’ll see that they average about a point eight point nine, Delta, and A1C, which is fantastic rate. We see on average a two point reduction to the point to the tumor where people would ask us, you know, kind of tongue in cheek in the early days, what are they doing swallowing the phone? And we’re like, no, they’re doing what their provider has told them to do along these vectors. So to see a two point A1C reduction on average is really important. At the same time, diabetes is a disease, a standard deviation. I can have an average, but I could be going the high, low, high, low, high, low. And my doctor sees the average and says, hey, you’re doing good. Come back in three months. Meanwhile, I’m the one who is going to have the acute event. If I’m bouncing up and down, blind coma, blind coma, blind coma. So the CGM, the continuous glucose monitoring world, the habits and the next comes of the world are introducing this notion of what they call time and range, which is really a proxy for standard deviation that says, can I also keep people safely within a range such that the average, of course, is well controlled, but their standard deviation is well controlled as well. So all of that to say a 2.8 1C reduction and a significant reduction in excursions or improvement in time and range. And what’s fascinating Saul is we actually look at this data fractionally. And by that I mean, let me not just look at the 2.8 1C reduction on average. Let me look at what happens when a patient safety starts quite out of control. So let’s say you have a patient who starts above any one C of nine, and those are the ones who are costing the healthcare system the most. Those are the ones who are having the comorbid complications. On average, we see those drops around three and a half points, which is seven X, what’s required by the FDA for a new drug. So I think from a data standpoint, we see exciting. We see an ability to bend the A1C curve in ways that can be done with just medicine and human coaching alone, just can’t be done. And the corollary to that is we were very fortunate to work with our friends at Truman Analytics. Now IBM, Watson Health, and they were actually able to take several thousands of patient data. And they A1C data, the identified, of course, and they were able to look at claims, data for a equivalent population and real claims adjudicated annual claims that looked at total cost, which included the cost of acute care, which is hospitalizations, E.D., and doctor’s office visits, the cost of supplies, which included meter strips, medications, etc. on the cost of what they called comorbid, which is the usual suspect five; hypertension, Hyperloopedemia, retinopathy in Europe at the in the property. And they looked they looked at what would the cost of a patient be? On average of 31C’s was between 6 and 7, 7 to 8, 8 to 9, above 9. And so we were actually able to create a cost curve. That said, if you’re able to shift a guy who is A1C is nine and a half down to six and a half, this is what you should save. And on average, we see that number as being about thirty one hundred and fifty dollars per patient per year, which is tectonic given the three hundred and twenty seven billion we spend annually here in the United States on diabetes. So I see that as there are some fascinating health outcomes which obviously lead to quality of life, better life. All of that good stuff. But it also leads to a significant economic value proposition for the system. That’s important.

Saul Marquez:
That’s a good call out. And you know, small shifts can lead to huge value. And I think that’s a great call out. And not trying to reinvent the wheel here. Just trying to help providers help patients do what they should do to live healthier lives. And so I think it’s a really unique approach with the use of technology that really kind of keeps the algorithms and tech heavy stuff away from the users. So. It doesn’t always happen without any glitches or just pitfalls. I love if you could share with us Anand maybe a mistake or a setback that you guys had that you learned a lot from.

Anand Iyer:
I’m chuckling only because it’s like, “oh, which one?”

Saul Marquez:
Right. Which week are you talking about? Speak your last.

Anand Iyer:
I think it’s the advantage and perils of being first in this space where you’re sitting in the front and you’re driving and you’re kind of it’s an exploration and it’s a journey. And so indeed, whilst we’ve had many, many successes that we’re fortunate and proud of, we’ve had what I would call the teachable moment, like, “why the hell did you do that?” So one of them that jumps out at me is that in the early days… this is prior to the FDA having any sort of structured group and guidance on mobile health, as it was called back in 2008, ‘9. And this was prior to Cool Patel being at the FDA in his capacity with CDR age and having the mobile medical guidance document. And so we kind of looked at this and said, “well, we’re taking data from a predicate medical device in this case, blood glucose meter.” And we were interpreting it, analyzing it and providing feedback. And under the FDA existing accessory rule, we too, became an accessory to this device. And of course, the blood glucose meter is a Class 2 device. Therefore, we are to a class 2 medical device. So we approach the FDA and said, well, we think we’re a class to medical device. We think we’re in that kind of low to medium risk because you’re talking about medication management, that to insulin, which Chaco considers its fourth most dangerous drug to self administer. So they said, “Okay, probably makes sense that you are a class two, but we’re really concerned because we don’t know what you are or your phone. Are you trying to clear the phone or are you a meter? What are you.” And we’re like, no, we think of it like an app. And they’re like, what’s an app in jobs with the iPhone? A year ago and the whole concept of apps, this was still very new. And they said, you know what? Everything you submitted makes sense. But we’re going to put a little bit of a shackle on you, which is we’re gonna give you an RX only indication for use because we wanted to come under the guidance and authority of a licensed healthcare provider to make sure that John doesn’t log into Mary’s account, take Mary’s amount of insulin and incur any harm. And we’re like, “okay, that’s not going to happen.” But we understand kind of the psyche of where you’re coming at from a patient safety perspective. But in the beginning, we were in RX only. And whilst it was so innovative, I don’t know how many awards and keynotes and softwares and drug. Well, how cool. Because it’s RX only it inherently lost a scalable value of software. Software inherently is scalable versus human carried, it’s not scalable, but you know, it’s scalable with access cost. And so I think one of the lessons learned for us was, well, whilst we had to go to market, initially we almost became a Merck or a Pfizer or a GSK where we had to go in detailed providers, leave samples on their desk and say, “hey, when you have a diabetes patient who comes in, who meets these criteria, consider putting them on this drug. That happens to be enough. Here’s an access code.” And so whilst we learn a whole lot in that journey about physician interoperability, you know, when how often and what detail the doctor wants to see data coming back from BlueStar, it was also kind of it was a one off, one off, one off, one off, and we lost scalability. So I think the good news is we went back to the FDA years later with enough data and said, “look, Barry’s alive. Chan’s alive, too.” We really need the RX. And they reviewed the data, said, no, we can graduate, no TC clearance as well, which is fantastic. So I think lesson learned that there are multiple regulatory pathways to approach in the realm of visual therapeutics. There are multiple channel pathways. One is, of course, through the doctor. It may not be one could be through a self-insured employer, one could be through a health plan. So you’re taking advantage of somebody sending out a mass invite scale are targeted. So I think that was an important lesson learned for us, because had we known that at time T 0, we might have applied differently and made the case differently, that would have caused us to scale perhaps quicker in the early days.

Saul Marquez:
Man So when did this happen? When was the initial RX approval from the FDA?

Anand Iyer:
It was back in 2010, 2011. And then when we went back several years later with the armed with all of the initial data to show…

Saul Marquez:
You guys are way ahead of your time man. it’s a it’s a bonus and it’s also a peril at the same time.

Anand Iyer:
Right.

Saul Marquez:
Yeah. To your point, and I’ve got to just recognize you guys in a big way, because to have lived through that and then pigeonholed as an hour X only clearance, you could’ve died. You a company could have died there and you guys managed to navigate that and find new pathways for approval for over the counter and then find ways to disseminate the technology at scale. So big kudos for you guys.

Anand Iyer:
Saul that’s very kind of you. Thank you. But I think the rationale for that was not just our own conviction that we shouldn’t give up, that we should continue and we should push, but I think we were also fortunate that there were several other factors that moved in our favor. So, for example, the proliferation of apps, it was becoming far more common. Two, the shift towards value based care. All of a sudden now payers were interested in not just paying for a solution, but they wanted to see outcomes. And the fact that we have three randomized controlled studies today and over 40 peer reviewed publications, it’s Dr. Collins famous quote from the National Institutes of Health, which is, is the absence of evidence? The evidence of absence? Right. If you want to be a player, you better have evidence. And so I think in the early days, we spent time, a lot of time almost underground, doing a lot of these clinical studies to show the efficacy in different cohorts, et cetera. But I think the winds of healthcare reform, the advent of apps and certainly the advent of the things that support these apps. So, for example, in those days, what was an API that connected into EPIC didn’t exist. But now all of a sudden you have API is to connect into whether it’s epic or Cerner or it’s Walgreens or CBS or doesn’t matter. The technology itself has evolved. Wearables have evolved. It’s easy to acquire sleep data and exercise data. So I think we’ve been the beneficiary of societal adoption of these types of technologies. But we had the homework and we did the heavy lifting on the clinical side with evidence and with FDA clearance. And so it really allowed us and poised us well in the latter years to really take advantage of that.

Saul Marquez:
That’s a great call out. And, you know, I’m very, very humble call out because, you know, there’s definitely still all the work that you guys put in. But, yes. So you’ve got this societal shift, the clinical reform shift that definitely played to the advantage. There has to be a cultural reason that you guys stayed in the game. Why would you say that is?

Anand Iyer:
Oh, boy, one word, passion. I think that if I were to ask every single WellDoc employee, whether it’s here stateside or it’s our development team in Bangalore, India, every single person is committed and passionate. They come in every single day with a purpose. They come in every single day with the mission. In my case, I’m personally tied with the disease in many of our employees cases there one degree of freedom or two degrees of freedom away from a loved one or a family member or a friend who is either suffered or passed from complications of diabetes. And I think that passion that people bring and this kind of uncanny unwillingness to fail. And it’s like,”Okay, that’s okay. We failed today that that means we won’t. That’s one less thing for us to try again. We’re going to try that again. We’ve we’ve eliminated it out. And so our field of opportunity has now become clearer. Every time you make a mistake, by definition, your opportunities start to illuminate more. And so I think just that passion and perseverance at the corporate level, certainly as it relates to the management team, our strategic vision and mission. But as it relates to every single employees kind of credo that this is what I’m going to do and this is how I’m going to do it. I think that’s what’s propelled the success. And I think in many ways it’s not just germane to health. I think in any startup environment, if you look at the successful startups in any domain across the globe, there seems to be that common ingredient of just you have to love what you do and you have to do it for a purpose. What is the saying Saul? It’s a doing well by doing good. In many ways, we’re anchored and doing good because the current methods for managing diabetes or any other chronic disease aren’t working. They’re just not now.

Saul Marquez:
That’s awesome, man. I appreciate that. And I could tell from just speaking with you and you know, the results you guys have had, it’s definitely true. If you had to narrow it down to one thing that you guys are working on, what would you say is the most exciting project?

Anand Iyer:
Wow. How much time do we have?

Saul Marquez:
Seven minutes.

Anand Iyer:
Okay, I’ll give you I’ll give you the short answer, which is… so there’s multiple vectors, if you would, given where we’re at. So we’ve we’ve come through checkmark RCT’s clinical outcomes, checkmark FDA clearance, checkmark clinical intergroup into ability, checkmark cybersecurity, checkmark clinical evidence based guidelines, all of that good stuff. So here we are today. The first vector of expansion is multi domain. So 70% of diabetics also suffer from hypertension and they don’t want to go to two apps. Why would they? I say they don’t think that their hypertension and their diabetes simply think of their health? So today in BlueStar, you have the comorbid conditions of hypertension, managing their lipids, managing their weight, obesity, all in one inclusive what I would call cardio metabolic and soon to be expensive to type 1, to gestational to congestive heart failure is a kind of rounding out and pre diabetes to kind of round out that full cardio metabolic suite. So that’s kind of one vector of expansion, which is domains. I think a second vector of expansion is this continued quest for connectivity. As in when new technologies, techniques, API, et cetera, are made available. We want to make the. Acquisition and the dissemination of data as frictionless as possible. And so what used to be “Okay patient I now need you to enter your med regimen.” Oh, God. Can you imagine the patient with the pillbox that had the red pill? The blue pill? The white bill? The orange bill. And now I got to enter each one. But now it’s click and it pulls it in from your pharmacy. So I think continued connectivity and removing friction. And then I think two more. One is, needless to say, geography. So we’re we’ve launched in Canada. We have our Health Canada clearance as a class to MDL. We just re certified or ISO certification thirteen for eighty five for USA, Canada, Japan, UK, Australia. Higher ups. Yeah. And then so there’s a geographic that’s a geographic expansion that we’re also in the process of submitting CE mark for Europe. And then lastly and perhaps the most important one to save the best for last, which is data, and we have this moniker, we call it IDEA, which is inform, discover, extrapolate, adapt. Can I look at the data in real time and can I inform myself of what’s actually happening? So what happened? Can I then discover means? Can I look for trends and patterns automatically? Exercise patterns, medication patterns? Can I extrapolate? We wanted to call it predict, but IDP doesn’t spell anything and IDEA does so we said, okay, let’s call it we extrapolate. Can I extrapolate and build predictive models so I can predict hypoglycemia. I can predict if they’re going to skip their meds, etc. And then lastly, can I adapt? Why software? So I can use the data to actually drive different algorithms and invoke different logic in real time, which is fascinating. And so I think that’s the Holy Grail that says now I’ve truly created a platform to deliver precision medicine in many ways. And it’s not just us if I think of our role. WellDoc’s role in the Digital Therapeutics Alliance, which we co-founded with other leading companies in the therapeutic spaces peratherapeutics actually propeller of a this, etc. There’s a similar approach that says, can I use that data to actually help, whether it’s diabetes or whether it’s neurological, whether it’s substance abuse. What we’ve seen is the scalability in that data realm, and I think that’s going to be really cool. So maybe just a snippet in terms of kind of where we’re headed.

Saul Marquez:
Well, I think it’s I love your your acronym of IDEA and it’s definitely, I would say also a good framework for entrepreneurship.

Anand Iyer:
In fact, we actually presented that at the first joint summit with the National Science Foundation, NIH, and FDA a couple of years ago. And we introduced this notion of idea as a moniker and a framework for people to. These are the four classes of data and I did my doctoral work in pioneer recognition. So for me, this is a bit of a kid in a candy store. It’s the four mathematical domains of pattern recognition that you then apply and move forward. So it’s pretty exciting.

Saul Marquez:
Is that right? That’s pretty cool. Love that.

Anand Iyer:
Yeah. The old days are all coming back. It’s all a circle. Everything’s coming back.

Saul Marquez:
I love it. This is great. Well, folks, I’m sure you’re enjoying this just as much as I am. We’re get going into the lightning round, followed by a book recommended by Anand. Then we’ll be concluding here. After that Anand, you ready for the lightning round?

Anand Iyer:
Okay. Fasten my seat belt. Go.

Saul Marquez:
What is the best way to improve healthcare outcomes?

Anand Iyer:
Engage the patient. They’re the active ingredient in the missing ingredient. If you can engage the patient, then you have hope and if not, rethink your approach.

Saul Marquez:
What’s the biggest mistake or pitfall to avoid?

Anand Iyer:
Don’t be set on one pathway or one solution and think that you’re the only answer. Flexibility is key and adaptability is key, in whether it’s adaptability in your approach, algorithms, channel, pricing, support, be flexible and if you’re not flexible, then you won’t be as successful as you can be.

Saul Marquez:
Powerful. How do you stay relevant despite constant change?

Anand Iyer:
Easy answer. Just make constant change a key ingredient in your fabric. I think you always hear the word pivot, right? I think a series of pivots. It’s almost like a cruise control mechanism. Right? You set the cruise control at sixty five, and when it’s 64 it pivots back to sixty five and one at sixty eight. Pivots back to sixty five. So you kind of you’re not in exactly a straight line but you’re kind of a little bit of a jagged line and each of those little jagged turns when well controlled actually there’s lessons learned in each one of those. And so I think. Embrace the change. Embrace the change because it’s happening at such a rapid pace, because otherwise what’ll happen is you blink, you close your eyes, and when you wake up, you’re going to be in a different realm, in a different horizon in life. And then the opportunity may have taken a sharp right turn and you didn’t catch it.

Saul Marquez:
That’s awesome. What’s an area of focus that drives everything at WellDoc?

Anand Iyer:
I think it goes back to what I said, which is passion and purpose. And without that kind of fabric, without that kind of true north, you start to dilute if that’s what the right word is. The efforts of having that strategic focus and passion for delivering against that focus is really important.

Saul Marquez:
Love that. That is next to our more on a personal note for the listeners to get to know you. What is it, your number one health habit?

Anand Iyer:
Oh, wow. I want to say something as mundane as exercise or whatnot. But believe it or not, for me, it’s meditation. I meditate every day. And for me, it’s a little bit of an escapism from reality. It kind of recenter my mind and having come from the Indian subcontinent myself, there’s just a cultural tie back to meditation. But I think the value in terms of your breathing, in terms of your oxygenation, in terms of your overall well-being, blood pressure, et cetera, is that people are starting to rally around that as, “oh my God. That’s a legitimate form of therapy.” So for me, that’s an important one.

Saul Marquez:
And when do you do it during the day?

Anand Iyer:
Every morning.

Saul Marquez:
In the morning?

Anand Iyer:
Whether every morning, whether I’m here or whether I’m travelling, whether I’m on an airplane, flying over night, it doesn’t matter. And that’s not negotiable for me. Everybody at home knows that. That’s quiet time. So…

Saul Marquez:
I love it. That’s great man. I got into meditation regularly, got out. But, you know, I’m definitely working to get it back into my daily ritual so love that you reintroduced that here today. And Anand the last one here is what is your number one success habit?

Anand Iyer:
I think just the perseverance. Just perseverance. And it’s okay to fail, but you better fail quickly. And if you failed, don’t hang on to the failure. Drop it and move on to the next thing. And I think if you have that mentality that you are accepting of failures, then you’ll succeed. In many ways, I think if you’re not accepting of those failures, it’s an impediment to success. And so that’s just a mental psyche that not only drives you as an individual, but it should drive the corporate culture. Because then if everybody has the same, they’re all pulling in the same direction. You get to move forward. Otherwise the company becomes stagnant.

Saul Marquez:
I love that. What book would you recommend to the listeners?

Anand Iyer:
Oh, wow, you know, one that jumps to my mind, given the uniqueness of this digital therapeutic space is a book by a fellow named Charlie Fine. Charlie is a professor at M.I.T. and the name of the book is Clockspeed. And it’s a fantastic thesis on what happens when you mix industries whose innovation cycles are fundamentally on different clock speeds? So think about our industry, right? You have healthcare which moves at a God awful slow pace and then you have software, which is exactly the opposite of that. It can change every sprint cycle of two weeks. So we think of the old physics experiment where you have constructive interference of light and destructive interference. You always want constructive interference because in the wave, the wave forms magnify versus destructive interference wave forms cancel. So now if I’m mixing these waves of different frequencies, how do you do it in a manner that aligns the energy of the wave such that you actually get productive output. So in English, if you’re going to mix the regulatory wave, it’s got its own characteristic frequency. The healthcare wave, the sensor wave, the technology wave, the data wave, which is moving at lightning frequency. How do you actually align those to actually deliver positive output? And the book is a must read for anybody who believes that collaboration is key to unlocking innovative value. And that, too, in today’s world, it’s collaboration between wireless and pharma and life sciences and regulatory and policy and this kind of public private academic mixture, all of which are happening at different clock speeds. And so it’s a must read. I think it’s so, so insightful. And we’ve applied so many of Charlie’s lessons inside of WellDoc.

Saul Marquez:
Such an insightful book, listeners of things that we’ve discussed today. A full transcript, the short notes, links, you can find all those at outcomesrocket.health in the search bar type in Anand or type in welldoc and you’ll be able to find all of the magic ingredients to today’s discussion there. Anand this has been tremendous fun. I’d love if you could just leave us with the closing thought and then the best place for the listeners could continue the conversation with you and your company.

Anand Iyer:
Yeah, I think I think the closing thought is as a patient to myself, if I look around and see other people who are worse off in their diabetes. What I often notice Saul is that they’re lonely and we know it statistically. The number of people who have diabetes or hypertension or congestive heart failure who also have undiagnosed depression. And when they’re lonely, bad things happen. It’s the spiral. It’s as a base of misery, if you would, that never gets better. And if technology… if technology is what can lift these people out, if technology is what can give these people hope, then we all kind of go to sleep everyday, thinking we’ve done something good for humanity and we’ve done something good that your your kids would be proud of you. And remember you for. So my parting thought is, is really what I said earlier, do well by doing good. And you won’t achieve greatness unless you do good. You have to do good before your great because otherwise you’ll never achieve greatness. So we should never forget the important societal things that we need to focus on as leaders and solve these problems with the insights and technologies and the passion we have, so that’s my parting thought. And then happy to continue the dialogue with anybody. You can follow me on Twitter @DrAkIyer and follow me on LinkedIn. You can follow us at BlueStar and of course, at welldoc.com our website, but really want to thank you for this discussion and really a fun discussion that hopefully folks will tune into and take something away back into their work environment that they can act upon.

Saul Marquez:
Love it Anand. Really appreciate that strong, strong message. Doing well by doing good, clock speed. So really appreciate the time you’ve given us.

Anand Iyer:
Thank you Saul.

Thanks for listening to the Outcomes Rocket podcast. Be sure to visit us on the web at www.outcomesrocket.com for the show notes, resources, inspiration, and so much more.

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