https://vimeo.com/169280480

I’ve known Eric Dishman for about five years, because we’re both kidney cancer patients. I’ve known that he’s a really sharp thinker, and a high-ranking executive at Intel, deeply interested in and involved in their work in healthcare.

May 3 was his last day at Intel, and he gave what may be the most mind-expanding reality-popping speech I’ve heard, and I’ve heard a thousand. (Really, I was fixated, and at one point my jaw dropped.)

Where’s he going from Intel? He’s going to head up the “million person cohort” project at the National Institutes of Health. An Intel guy heading up a huge NIH project?? When you listen you’ll hear why.

The occasion was the annual meeting of NEHI, the Network for Excellence in Health Innovation, where I had my patient engagement fellowship last year. Their new President and CEO is Susan Dentzer, former editor-in-chief of Health Affairs, and boy do things look interesting there.

Minute one of this video is Susan’s introduction; 32 minutes are Eric’s speech; the balance is Q&A.

I can pretty much promise that this video will contain things you’ve never heard before – things that are very new but quite real. Yet you’ll also hear things that are very familiar to students of this blog:

• “Knowledge is survival” – something that was taught to him by another e-patient, Verna – 29 years ago!(1987! There’s more to patient engagement than the Web, eh?)
• Information his providers had was way out of date, so the prognosis they gave him was misguided. (They said 9 months, 29 years ago)
• Changing healthcare is a big complicated systems problem, so it’s a mistake to attribute any shortfall to a single factor.
• And – most mind-blowingly, his own experience with being saved by genomics.

Below is the transcript of his speech, so you can text-search it. But it has much much more impact hearing his voice, so I hope you’ll listen.

---

It is an honor to be here. For a long time I have wanted to speak to NEHI so I literally did do it on my last day at Intel: “Wait, I am going to add a couple of more days and stay on.” My Intel email address doesn’t work anymore so don’t send me anything there. I don’t know what my NIH one is yet, so don’t send anything there, I can’t access it, I am in this betwixt and between state.

But I wanted to be here, because you are exactly the kind of audience that I want to talk about ecosystems with, because you are an ecosystem and you are forming an ecosystem, as Susan just said, of combining people from different parts of the sector and outside of the sector – and that’s what it’s going to take.

I call this “Journey to personal health for all,” I changed the name a little bit. And I’m just going to share with you some of my both professional journey and my personal journey in that regard.

I want to start by saying 29 years ago I was in a Duke University hospital, I’d already had cancer, I had been diagnosed with cancer for about a year. I was 19 when I was diagnosed at Chapel Hill. And I met this woman named Verna who taught me to be a patient advocate, taught me not to be just a sort of automaton as a patient walking around and letting them do unto me whatever they wanted to do. She had two things that she would say constantly to me. The first was “Knowledge is survival,” and the second is, “You must have the most knowledge on the ‘team.’” And she would use the word team sarcastically, because at that point the notion of a health team was sort of more of a vision than something that was actually happening.

It’s in that regard that if I think about what I have been doing at Intel for 17 years – and I think about what I am about to do with the Federal government, they really have the same mission, I’m just wearing a different hat – that is trying to drive what Intel has called personal health, but NIH and the government are calling Precision Health for All. Really from an Intel perspective, we were trying to build the data infrastructure that facilitates the notion that knowledge is survival.

And at the same time, as I think about what I am going into with the PMI cohort, we are going to build the world’s largest, most diverse cohort of humans ever and collect the most data, most diverse data types that have ever happened, with a very participant focused model – we don’t call them subjects, we call them participants.

So really, from an Intel perspective and from a PMI perspective, both of these are about accelerating the knowledge. Accelerating from data to knowledge to clinical and medical breakthrough and just revving up that innovation engine is what the essence of my job has been and is going to be going forward.

So as I think about this and I think about my history at Intel, it’s been incredibly rich and it might be surprising for you to know that for more than 15 years we have had a focused group on health and life sciences. And we have actually done field work globally in more than 50 countries studying everything from the front line of those delivering care to the patients and the family members around them who are trying to actually support them as they go through the “system.” And grounded in that, we have seen and been a part of, as a company, driving things like electronic health record adoption.

The very first study – and there is a picture of me up here actually on the slide, the top right of the slide, that’s like my first day of field work at Intel and I am studying a hospital that’s startin’, to fixin’, to get ready, to think about, movin’ to maybe sort of a kind of electronic health record, right? And so from the early days – I mean we did the studies with Kaiser when they were just starting to roll out EHRs and then starting to use mobile devices.

So from EHRs to starting to use the early laptops which eventually became tablets and now phones, so that you have a mobile workflow, now to the buildout of cloud and a lot of those environments around the world, those who are trying to figure out how do we automate the quality metrics and actually capture quality metrics, so that you’re not delivering even worse quality care by having people spend more of their time filling out the quality paperwork as opposed to actually delivering care with the patient.

Patient centered medical home, payment for results, all of these transformations Intel has been both trying – a part of from a policy perspective as well as from a business perspective trying to figure out how are we going to build the IT infrastructure that facilitate these new kinds of care models and economic models.

And now we’re facing this disruptive shift towards bringing big data the biggest of the big data, or what I think of as big knowledge, because if we have a bunch of data but it doesn’t turn into knowledge that’s not terribly helpful for driving personal health for all to healthcare.

As I reflect back on my years at Intel, there has been two fundamental lessons learned. I mean so many I can’t even sort of imagine them all, but two at the highest level:

• Intel knows how to design for scale. How do you build systems not that just work for the prototype level or the pilot level but never moves beyond pilot … how do you design for scale, and
• how do you design ecosystems to achieve that scale?

And I am going to just harp on this issue of ecosystems with you today because I think NEHI has been and has the potential to be a disruptive player by bringing together an ecosystem that works in a unified way towards driving disruptions in the healthcare world.

Now one of the things I learned about building ecosystems at Intel, I could give you a 10 hour talk on how to build ecosystems at a level of detail. What Intel does when we imagine “Okay, we want to go here over the next 15 years, and we literally map out an ecosystem of industries and players and those that are going to be resistant to it and then we try to figure out how do we get them to change their business model so that they’re no longer resistant to it – I’m going to give you the really quick version of this, but step one when we build these ecosystems is, if we want to transform, we set an audacious goal.

If you think back to the PC industry, when it was a radical notion to say, “Hey we want a PC on any/every desktop” … I mean how far we have come since then… that was a radical, audacious goal – that was a multiyear effort. At Intel, we started working to try to figure out –

• who were the players that are going to be resistant to it? What would it take to make this possible?
• What are the other industry players who don’t even exist yet?
• We might need to create a whole new sub-industry to facilitate the existence of a PC on every desktop.
• Are there new kinds of computing workers who need to exist to make this innovation happen?

And now as we think about, you know, our new audacious goals of “anytime, anywhere, any device” computing, we’re doing that same set of activities to think through who that is. And there are four main dimensions to it every time we look at it.

• Technology, which Intel starts surprisingly with first, but then
• What’s the workflow of the people, from the people that are going to work at Intel to those who are going to be using these systems in their home or in their office?
• What’s the workforce needed? I just hinted at that, you might need a whole new curriculums and whole new invention of different kinds of workers that don’t exist now to achieve that goal. And then
• What are the policies and standards that you actually need to get there?

The first time I built a telehealth startup was for [Microsoft’s] Paul Allen 27 years ago, and it technically worked, but the workforce, workflow and policy and standards were not there. Great technology without covering all of that circle means you’re really in trouble very, very quickly. So if you think back to the multimedia era of PCs – you may not know this, but Intel lined up hundreds of other organizations to make it commonplace to where you suddenly could use a computer for multimedia. We developed the codecs and then spun off a lot of the software companies that would use those to be able to use, do video on a PC in the invention of CD-ROMs and the hardware equipment, and there’s that ecosystem that needs to go bring the cost down on that … what could you get Microsoft to put into the operating system at that point? Investing in and creating a whole bunch of software vendors and software developers; and a lot of times that meant teaching new curricula to these software developers because they had never programmed anything like this before. That’s an example of bringing together an ecosystem.

And what I challenge you to do as NEHI thinks about the transformations that you want to help unleash in the world is, think through these four dimensions and think through who you need to begin to do that.

This is exactly what we want to do if we want to enable personal health for all. If we are going to achieve that then we’ve got to take an ecosystem approach because of the audaciousness of it.

So first, set an audacious goal – personal health for all – and I will share you some of the others that we’re actually walking through, at Intel.

This really means – personal health for all – an individual, at the center, of a collaborative, data driven, or knowledge driven, team. And there are so many pieces of that we have to put together:

• individual at the center we have to invent
• collaborative care, we have to invent and scale out, and
• data driven team we have to invent and scale out.

When we do this, we’re going to have a range of types of data that are analyzed to produce a holistic – not one-disease view of you – a holistic view of the individual with dynamic knowledge. I am going to talk about genomics in a little bit.

If we were doing it right today and genomics were affordable and scalable, we would likely be doing genomic sequences of cancer patients every time they come in for chemo. The body responds, tumors morph, right? And you’ve got to sort of see as a dynamic ongoing individual how you can set that up.

Our data infrastructure today is not designed for holism or dynamism, right? These are challenges that we are going to have to do going forward. And what this would mean in the end, for all of us, is a prevention plan and a treatment plan for your needs, your body, your social situation. Because all of those come into play, in terms of the health outcomes that you are going to carry forward.

Now if we are going to leave behind today’s paradigm of a reactive kind of mainframe-centric healthcare paradigm – and it’s really designed for the non-existent average of all of us. When I was first diagnosed and they walked me in and said “You’re going to die in 9 months,” thank God Verna, the woman that I met, was an actuary. And she took me in and said, let’s look at all of the research that’s behind their proclamations about your 9 month death sentence. And sure enough you come to find out that most of the studies had been done with 85 and 90 year olds. And the recommendations, for somebody at age 19 with this cancer that they had never seen before, just didn’t apply.

And even for those 85 or 90 year olds these clinical trials washed out individual difference and said, “You are the average of all of those who have been studied.” The problem is, none of us are that average. We do the best that we can to extrapolate from averages to individuals, and we kill people and we cost an enormous amount of money as we go do that. And to be fair, we never had the tools to do it any other way prior to now.

So what are the elements of personal health? I have used a version of this slide for I think 15 years, it gets prettier – you know I finally got people with better graphics skills than I had to be able to render it.

But there are three fundamental elements that I talk about when we talk, we are moving to an era of personal and precision health.

Before I go through them you have to stop and think about that for a minute. If we say to the populace, and we say to the politicians, and we say to ourselves we’re going to move to an era of personal health or precision health, then we have to admit for a moment that we are now in an era of impersonal health, imprecision medicine, that’s incredibly fragmented, incredibly data-poor and very institution centric in terms of how we deliver care.

That’s going to be a careful message of my new job as we talk about trying to accelerate precision health or precision medicine for all: I would say well, wait a minute, what exactly are we doing to ourselves today, if we don’t yet have precision and it’s not yet designed for the person?

The three elements that we are trying to bring together – and this is true globally, I mean Intel does this work in dozens of countries around the world – fundamentally, it’s about collaborative care, distributed and personalized care. These are the three elements of what we call personal and precision health.

In collaborative care we do these exercises – I’m a social scientist by training – as we study these people around the world, we’ll have them do this exercise called a place map, and we will take an individual or a family sit down and talk to them and say, hey map out for us all the nodes of, all the places that you actually do care, or receive care, or are a part of your life and care. And they very quickly will draw like a hospital but they will draw all these other places around the community from their gym, to their pharmacist, to the particular person at the grocery store that helps them think through what they are going to bring home. Their map is like a DNA footprint in and of itself, of what they stitch together in their lives in the community.

If all of those parts of the personalized care system for that person or that family are not stitched together from a data sharing and from a “IT” perspective, and we don’t connect them all, we are going to be in trouble.

We’re doing some work in China, helping to stitch together elder care teams, and in China they are thinking through “We need whole new kinds of care workers to use the IT.” So for example they are looking at things like, “W’re going to train a new category of person that has a combination of some IT training, some social work training and other sort of community health kinds of training,” to facilitate the kind of IT of a very neighbor-driven care model for seniors as well as technologies that are tracking the quality of the care that the neighbors are actually delivering for one another? That’s a collaborative care team stitched together in a very different way than we do today. And it’s not all about technology, it’s about workforce, workflow and other kinds of things along with that.

On the distributed care, right from a policy perspective I will share with you a goal that we have been actually trying to drive both as a large employer in our own ACO-like model but across about 12 countries working on health reform right now, is: setting quality metrics that are based on place of care. Was the care delivered in the safest, least restrictive, preferred setting of choice by the patient or by the consumer?

And if you start measuring for and paying for that question then the advent of things like using telehealth appropriately … right now at Intel we are working on some very aggressive hospital at home models with partners that we are quite confident can actually help treat things like sepsis and pneumonia and a whole list of other conditions that we do in a hospital in a home setting safely, effectively and at far lower cost than actually what’s happening today, right.

So just the beginnings of telehealth that we have today – this ought to be a fundamental mixed mode care model and a clinician who has the right and the responsibility to choose what dangerous drug they are going to put you on, can make a damn decision about what’s the right mode of care to follow-up with you on? Is it going to be phone calls? Is it going to be in-home? Is it going to need to be coming in into the institution, right? So distributing care in the significant way is a big part of making health personal.

And then the third is personalized, and this is not just genomics, people equate this with genomics and that certainly “omics” in general are a big part of that, but this is n=1 care or n=1 medicine, based on a wide range of data types. We just finished a pilot at Intel called U24.7 with the combination of clinical and wearable data that was all made available to the individual themselves, including their EHR data from multiple EHRs, from different places and different times and different vendors.

And a fundamental premise of this was a lot about giving data back to that person. By the way, the million person cohort, we are going to do exactly the same thing. So personalized could mean as simple as some sensor information in context to where information from your smartphone is brought into help you know how to customize medication prompting for you as an individual. We have done studies on this for years at Intel. For some people having Oprah’s voice, remind them to take their meds was the most effective strategy; for others it was blocking their television and the sports wouldn’t play again, until you got up and took your meds.

The point is, even that is using data to personalize care in a deep way. And obviously when you start to add things like genomics, then you’re talking about having a genetic map and baseline that helps to know how do we prevent or how do we customize drug treatments for you specifically. A broad set of things go into that.

At Intel we have been helping to build out the end-to-end infrastructure in multiple countries to deliver on these three pillars of personal health for years. But I’ve managed to prototype it for myself and as a way to survive. So I will share with you, now 29 years of a journey in one slide in just a matter of minutes of my own particular situation.

That’s a picture of me on the right, really big forehead, it’s embarrassing, I don’t know why I keep showing it. I just told my parents they could rent billboard space on the top of my forehead when I was a baby.

I was born without hip sockets. I have met people who are wheelchair bound – because knowledge is survival, there, my parents … when they got this proclamation that my hip sockets hadn’t been formed said, we have got to find somebody else who has the knowledge on how to fix this. And this was about the time that new procedures were coming out. I mean I grew up with the notion that knowledge is survival because if they hadn’t gotten a second, third, fourth, fifth opinion until they found one that they actually wanted to go with, I would, you would have been wheeling me up here today, right instead I am a runner.

So I mean it’s been in my life for a long time that’s a picture of my transplant care team up there, that’s a picture of me in the ICU after my successful kidney transplant. So here is the thing, collaborative distributed personalized care is something I have had to create and fight to create for myself all these years. From collaborative care as I had cancer, I had a life threatening cardio event because of meds mix that my team had no idea of what each other was putting me on, first off-label uses, right? How did I fix this? I started using paper lists, I started tattooing it on my body, saying here I am, this is what I have, please make sure you are not killing me, by adding yet another medication to the cocktail.

I used Groove which was an early sort of social networking tool and forced all of my clinicians to get a login and use Groove to monitor whether or not they were killing me or not, because they weren’t talking to each other.

And then I eventually used different fields in the EHR that I knew were not used by clinicians very often that would pop-up to the top of the screen and said, put these meds right there, I want all of them to see it when they go look into the EHR, right? An example of me forcing collaborative care and collaborative communication by my, you know at some points I have had at one time 21 different experts working on me at one time, right? I am much healthier today – it’s down to four.

In terms of distributed, my two other, my three near death experiences – well the first was that one, my other two were both hospital-borne infections while I was on intense chemotherapy and they had wiped out my immune system, right. I mean, hospice-kind-of, you know, bringing in last rites kinds of things.

And after the second one of those happened, I said, “I will do chemotherapy at home; you will teach me either how to help self administer, you will send a nurse in and we will start using videoconferencing.” And I would force my clinicians with the, you know I mean, God, what were the first videoconferencing tools you could get on a PC – I would teach them that and I said, you are going to do this because you have just told me not to go to Toys “R” Us or the public library because those are two dangerous places with germs but actually the place that you want me to come to, ranks above those – right?? It just doesn’t make cognitive sense. So I started forcing this.

I gave a TED Talk a couple of years ago, even … just showing after my transplant, how you could start to use a cellphone based ultrasound to not have to go into the transplant office for the three months afterwards three times a week, which is very painful after you just had a transplant.

And then the third was personalized, 23 years with cancer – I told you I was diagnosed at age 19, said you had 9 months to live – more than about five dozen rounds of chemotherapy, radiation and/or immunotherapy over those years, 57 different definitive diagnosis codes and $6 million in cost.

I am about to die, I am about to go my, I am going on my last Intel business trip, a startup that needed computing power sequences me, and comes back and says, after seven months by the way it took seven months, three months of compute, to do the computing part.

I got the whole genome sequenced. It took three months of compute time, four months of humans to try to find all of the data from all the clinical trials and places I had been and pulled my EHR data together. And after all that I didn’t even know they were doing it, I walk into, I was seeing a doctor at three times a week, I was about to go on dialysis, I had put in the AV fistula in my hand to support the dialysis. And I walk in and they are like, it’s multiple doctors, two on video conferencing and my doctor from Seattle had come down to Portland and they’re in the same place. I mean if you are a patient, you just know this never happens unless it’s bad news, right?

But this was good news and they said, “92% of what we put you on was destined never to have worked. We have never used this kind of data for a patient before, it was very painful for us to learn how to do it. We were FedExing 2 terabyte hard-drives of data back and forth and it took forever to get your EHR data together to try to figure this out. That was the bad news – my wife still struggles with that: “92% of the things that almost killed you for all of those years, we now understood were not supposed to work.”

And they said, “We think, even though your cancer is in your kidneys and it has wiped them out, it looks more like pancreatic cancer, the mechanism. And we are going to put you on an experimental drug for pancreatic cancer. Three months – not a bad round of chemo – it was the kidney failure that was really making me sick. I come out of it, I walk in, they do the test two days in a row and they said, “You’re cancer free for the first time in 23 years.” All right?

[Applause]

And they said “You’re eligible for a kidney transplant.” Me, Mr. Proactive Patient, have advocated for well over a thousand people with cancer, didn’t even know what was entailed in a kidney transplant because it had never been in the realm of possibility. Intel employee who doesn’t know me donates to me and suddenly I am healthier today than I was at age 48 than I was at 19.

That’s personal health, that’s the personalized part of that.

The challenge is, I came back to Intel and said, “Personal health or precision medicine can’t take months and millions of dollars per patient.” So we came back and we created this initiative at Intel, it’s not our initiative, it’s what we named it, of bringing together an ecosystem of players called All in One Day by 2020.

The kind of care that I had, that took 23 years and seven months, has to happen all-in-one day by 2020.

How do you bring in all of that data type? How do you collect the tissue or the blood by morning of somebody that has presented and by that evening your clinician is giving them a customized care plan? Comparing against your own data as well as the world’s data to try to find somebody else that looks like you genetically is a needle in a haystack, right. It was phone calls and FedExing and luck, in my own case, as opposed to systems and infrastructure and repeatability.

If we’re gonna do all-in-one day, and we’re gonna form a precision health or personal health ecosystem, we’ve gotta go through those four things I talked about with ecosystems.

• What’s the supporting technology?
• What do we gotta do for workflow, from the clinicians to the researchers and the labs?
• The standards and policy?
• And what new workforce do we need to create to do that?

We’re actually making great progress since we announced this goal and not surprisingly, Intel, that’s who we are, we started with technology. So I am just going to walk through each of these elements in closing here.

On the technology side, one of the things that we have done is Intel’s driven Moore’s Law to help make computing more powerful. We have been a key part of enabling it to come down to where the $1000 genome of sequencing somebody with the whole genome sequence.

The problem is, that’s capturing the data, that’s not analyzing it. The cost and time to analyze it could still cost a million dollars or more per patient – that’s just simply unscalable.

So what have we started to do in that regard? Well, a lot of this is about computing performance, this is the biggest of the Big Data problems, much larger than meteorology, much larger than physics, much larger than astronomy. There is a guy that did all this analysis that’s said, “We should start using the word ‘genomical’ to mean really, really large as opposed to ‘astronomical,’ because these datasets are so much larger.”

So we’ve helped work with the sequencer, all the sequencing companies, and somebody like Illumina, the top sequencer company, and we have helped increase the speed at which they can actually do this by 25x over the last four years. That just means suddenly your patient doesn’t sit there and take a month on a computer to actually do it. And you are able to generate more throughput through there.

And we have worked with major players like Broad, I was at the Broad last night here in Boston, one of the leaders worldwide in tools for helping to do genomic analysis. Their GATK, the Genomics Analytics Tool Kit – we’ve helped work with them to optimize that software, open an open source and take it from 8 days to calculate to 18 hours. And we’ll continue to actually drive that down. These are the kinds of things that you would expect Intel to do – the kind of company.

We have launched a whole program called the Collaborative Cancer Cloud … this is really focused on trying to get big data to big knowledge, to actually help people with cancer. If we sequence the 1.65 million Americans who are going to be diagnosed with cancer once – and I’ve just told you earlier that you would probably do it multiple times, and not just for cancer, but just those people – that would generate 4 exabytes of data, 5 exabytes of data would be the digitization of every human word ever spoken. And here is where we are going: worldwide on sequencing, we are on a path over the next decade, to generate 2 to 40 exabytes of data each year, from the kinds of precision health that we are actually moving towards.

So the Collaborative Cancer Cloud is creative and open and open source tools to help researchers and clinicians share data without moving it. You cannot move this data, there are not enough FedEx discs to carry it around, there’s no networks fast enough to do it and the vast majority of the data is in the clinical centers where the patients are being treated, and for privacy and other reasons they don’t want to give it up. So this is about distributed, secure analytics of doing the analysis where the data is. And that’s one of the tools that we have put out there to help in that regard.

Let me move to just the workflow piece of this. Our ethnographers and social scientists have been studying researchers and we are watching the precious researchers that we have in America and elsewhere spend more time on IT than actually doing the research. So we are just automating a lot of their repetitive tasks so that they can get to research as opposed to actually getting caught up in how to develop the IT to do this.

But we have also been doing global studies of the pioneering clinicians who are starting to do precision medicine or precision health. And we are publishing the barriers and best practices of things like, “There’s just not enough genetic counselors in existence!” Right? How do you incorporate the ethics and these challenges for a patient of genetic data into an encounter? This is a new thing that they have to learn how to do.

And there is just too many tests coming out. For those who are on the cutting-edge of it, there is 8000 genetic tests today, 60,000 are being tested right now, and there’s 10 new tests per week. How do we set that up to actually help them separate the wheat from the chaff and know how to use these systems as they’re coming forward? So that’s the big challenge

The other thing that we’re doing is we are using Intel’s lean engineering principles to help teach the front line of research communities as well as clinical communities how to redo and rethink their workflow, whether it’s a workflow of doing big data analytics on a bunch of chemistry or whether it’s a workflow of delivering this into a clinical encounter. So we have got to enroll those folks.

If we think about the workforce, we have got to fundamentally reeducate the ologists, whether they are oncologists or whatever, about omics. They don’t know it. We will go into clinics where the oncologist who is interested in this and passionate about it, is an expert, and the two next to them are, don’t even think that it’s really viable yet, even though it is and depending on which patient goes to see which of those people, you may get that leading care and you may not, as you go forward. Educating the workforce on how to actually go about doing this, as well as new kinds of jobs, like the one I mentioned in China. While the genetic counselors we have today aren’t quite right, do we need to invent a new kind of genomic counseling worker that doesn’t exists today?

And the last that is we just need more bioinformaticians. We do not have in the United States or anywhere else in the world – there’s a huge immigration issue, because most of them, the best ones, are coming from other parts of the world – we can’t get enough visas to all get them here, how do we mint more bioinformaticians who can actually do this data science?

And then lastly on the policy and standards piece: anything that we can do, anything that NEHI can do, to continue to accelerate pay-for-value rules and laws, is key. If you don’t have the shift towards payment for results or value, driving these innovations is almost impossible.

The day Obamacare passed, all the folks, a lot of you know that I worked on teleheath forever, particularly independent living for seniors, suddenly all of these providers and the hospitals and so forth were like, “oh wait, now we’re going to have to start doing some of the stuff you’ve been talking about for a long time.” If you don’t have the air cover of that aggressive shift – I hope that CMS can accelerate even more, it’s great – they were moving more and more of the payments to value based paradigms. In the EU, we’re working on a range of policies with both individual countries as the EU, to try to accelerate that reform.

The second is to accelerate EHR interoperability and patient ownership of data, this will be a huge part of my next job, we are already doing pilots at NIH with those around the Sync for Science program. Here is a button, I am a patient, I want to donate all and all of my future Electronic Health Record to research. I want to donate my standardized, normalized consumer wearable data to research. And making that unbelievably easy, and a right that people actually have, and not months for clinicians to reply in “whatever data format they want to,” but in standard data formats, and making it easy for them to do it at a touch of a button.

We have got to have new data in semantic standards for the new kind of data. God forbid that we let genomics data or consumer wearable or a wearable medical device data, not start out with standards so that we are in the same hell that we are now with Electronic Health Record data, 5, 10, 15 years out as those scale and become part of clinical practice. And we are doing things with like the Global Alliance for Genomic Health and others, just start working on both the omic and the wearable standards.

And then finally how do we accelerate the legislation in multiple countries around scaling out precision health and precision medicine. In the US, it’s between MACRA and 21^st Century Cures … the Senate Health Committee working on advancing the Precision Medicine Act … these are all things that we need to move forward and keep the pressure on, moving towards knowledge of survival, individualized care, that’s based on facts, not the law of averages.

So these are the kinds of things that as we have a roadmap at Intel, I encourage you to actively think about as NEHI. If you are trying to achieve some audacious goal, set forth the pieces, you ask yourself what would it take to accomplish this and then start layering on top of that the different parts of the ecosystem that you would actually need to carry forward.

So in wrapping up and then we can take a few questions if there’s time, you know if I think back, I’ve been lucky in so many ways – I mean I’m lucky to be alive, I have been so fortunate to work at Intel for 17 years … I thought I would stay for two, and it’s in part that this ecosystem thinking in action that they have imparted on me is just magic. I’m trying to teach everybody else in the world to start doing that kind of thinking.

I’ve tried to share with you a little bit here today, just a sort of tip of the iceberg of that, because I really do believe NEHI and the nature of who you have been and the nature of who you are becoming, could be a key instigating node to bring together an ecosystem to make it possible, to make personal health available for all.

How can you make All in One Day happen? How can you drive care that’s collaborative, distributed and personalized for all of us?

I worry sometimes that the kind of access to care that I had is going to be our next 1% problem. Fewer than 1% of patients today across all disease states get access to the kinds of stuff that I have. It’s not lost on me that you are more likely to get access to it if you are a one-percenter financially like I am. That is not right, and I can tell you that I have been put on this earth and somehow survived incredibly impossible odds to make this happen.

I know Intel even as I leave will continue to work with you to help do these kinds of bold endeavors, I know I will do that from DC, and I hope you will too.

Thanks very much.

[Applause]