GiganTECH

Episode Transcript
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(00:00):
Welcome to Tech It To The Limit, the humorous and surprisingly informative podcast that

(00:22):
makes digital innovation and healthcare as entertaining as it is relevant.
I'm Sarah Harper.
And I'm Elliot Wilson, and we're here to pull back the curtain on the world of digital
transformation in healthcare.
Don't worry, you don't need a medical degree to join in on the fun, just a sense of humor
and a penchant for all things health tech.
So buckle up folks, it's time to Tech It To The Limit.

(00:45):
What's up, Elliot?
What's up, Sarah?
Guess what?
It is episode five of Tech It To The Limit.
So great to be here.
It's awesome to be back.

(01:06):
I feel like I have so much free time this summer vacation.
I don't know what you've been up to, but I've just been relaxing on my patio with some lemonade
and a nice copy of HealthTechNerds.
Yeah.
The other night, I was enjoying a glass of Pinot Noir out in front of my fire pit reading
the new proposed Medicare physician fee schedule, really having a great time.

(01:30):
Really enjoyed it.
There's some really nice things coming out this year.
Can't wait to see it put into action, you know?
Yeah.
Set story.
I was lying.
I don't have any free time.
Oh, I was talking about hot regulation summer.
Hot regulation summer.
Oh my God, yes.
No, the reason I have no time, and I'm curious to see if in New Jersey they offer childcare

(01:53):
in August because in Minnesota, it's like not a thing here.
Apparently everybody just takes a month off as if we live in Spain and you get to parent
plan, try to work from home.
It's so amazing.
Now, we don't have time for that on the East Coast.
My kids went to camp.
My oldest goes to day camp every day.
It's like a quintessential 80s day camp with a lake and cabins and she comes home with

(02:18):
bug juice stains around her mouth and like, you know.
I protein snacks.
I like it.
Oh yeah.
No, it's good.
It's good.
It's wonderful.
My youngest goes to daycare.
She's too young to have around the house.
She's too young for a wet hot regulation summer.
Wet hot summer?
No.
Well, let's talk about lakes.

(02:39):
I think it's something that we're actually looking forward to about the summertime because
we don't want to paint it black.
Well, right.
I mean, it's not necessarily like the summertime, but like the summertime ending, right?
This is the end of August and here we are about the transition to fall and having enjoyed
the summer aside from sending our kids back to school.

(02:59):
What are you looking forward to this fall?
You know, I'm actually looking forward to cheering my team on from the virtual sidelines.
So typically this time of year, I'm headed to Verona, Wisconsin, which everyone who works
in healthcare IT knows what's located in Verona, Wisconsin, the cultural capital of the United
States of America, home of Epic Systems.

(03:22):
And August is typically their user group meeting, but team got together and taken enough pictures
with random Blues Brothers statues that it was somebody else's turn to go.
So I'll be cheering my teammates on.
They are going to be presenting some amazing work about leveraging some care coordination
automation tools within Epic to create a closed loop referral system for meeting patients

(03:49):
on met social needs in partnership with community based organizations.
So it's so neat to see how technology is stepping up to drive these types of health system,
not for profit community based organizational collaborative partnerships to address social
determinants of health.

(04:10):
And I have to say that it probably has a lot to do with with the regulations that are in
place now that mandate that we screen for on that social needs.
So it's a great example of how the whole ecosystem is really kind of converging at this inflection
point where we're going to start to see real change upstream in healthcare.
I'm excited about it.

(04:31):
Wow, what a thing to be excited about.
That sounds really cool.
Yeah, tell me you're a nerd without telling me you're a nerd.
Yeah, right.
I wish I could be there.
I wish I could be there out in Verona, Wisconsin to see that.
That would be really cool.
I am looking forward to this fall judging the Digital Health Hub Awards competition
again at the health conference.

(04:52):
I got to do this last year and through the process got to look at and examine hundreds
of startups in the industry trying to make something really cool happen.
The kinds of technologies that they have are wide and varied and interesting.
And half of my life is spent in working with startup organizations, helping them bring

(05:17):
their products to life or to the market.
And this is a great opportunity I get to have every year to kind of really survey what's
new and what trends are we seeing and what problems people are trying to tackle out in
the marketplace.
It's fun.
It's a lot of work.
But the end result is some winners of some really neat categories too that it's just

(05:37):
very exciting.
It's exciting to watch and it's a great program at health.
So looking forward to that.
It's going to be a good time.
I remember you mentioned hundreds of reviews.
I remember last year I think you had to get like Lasix surgery after being a Digital
Health Awards judge because you're staying at the computer screen for so long.
Yeah, I'm proud of you.

(05:58):
It was a lot.
It was a lot.
It was worth every minute.
Well, let's talk about what we have going on today for our fifth episode of season two.
Super pumped to welcome my friend Anish Chopra to the pod.
He is a fellow giant like myself.
So we bonded immediately when I met him in person because we both could see each other

(06:19):
at eye level.
We gave him a really fun tour of some of the historic properties around Mayo Clinic when
he was visiting us for a ground rounds speech.
And he said he'd love to join our pod and come and talk about some of the successes and failures
during his tenure as the first chief technology officer of the United States.

(06:40):
So yeah.
So Elliot, you know who we had on today, but can you tell our listeners like, you know,
they're used to this segment of our pod being the comedy segment being the game, right?
What are we doing differently this time?
You know, I hate to inform our listeners that we're actually not going to play a live game
between you and I before our interview because we tried something a little bit different

(07:06):
this time and we actually played a game silently in the background while we were having our
interview with Anish.
I think it just goes to show how amazing we are that the most humble.
So we are so the most humble.
How amazing we are that we were able to multitask and play an entire game while having this

(07:27):
incredible conversation with Anish at the same time.
It was really great.
I can't remember if we even told him that we were going to be doing this while we were
talking to him or not, but in the end he learned.
It was a good sport about it.
He just had to be his expert, loquacious self and we had to multitask as you mentioned.
So it was a lot of fun and just so that you listeners can kind of get a bit of that interactivity

(07:53):
as you listen to the interview that's coming up, Elliot and I are going to share with you
kind of the structure of the game so you can listen along and play along as well.
We played a game called Buzzword Bingo.
I should have a sound effect.
It should.
It needs one.
Tell them how the game worked, Elliot.
Well, it's Bingo.
If you've ever been in a pandemic and had to transition to remote teams and ended up

(08:18):
playing a round of Zoom Bingo, like did somebody say I'm on or your microphone's on mute or...
Someone's dog barking in the background.
That's right.
Somebody walks across the screen naked.
That's the center square.
Oh my God.
Yes.
Or no.
Keep it PG.
So we decided to play Buzzword Bingo so we knew that we were going to be talking to someone

(08:46):
that had a lot to say about a lot of different kinds of technologies within our healthcare
market and so we put together some bingo cards of the various different buzzwords that we
expected to be able to hear and through it you, Sarah had a card, I had a card and we
were playing along trying to capture bingo while Anish was talking.

(09:08):
So Sarah, what were some of the buzzwords that you were bingoing?
Bingoing.
I love that you made that a verb like Google, you know, we're Googling things.
Artificial intelligence, AI, big data, open source, API, data privacy, data analytics,
EHR, interoperability, cloud computing.

(09:28):
Those were just handful of the ones that I was listening for.
My free space, thank God, did not involve anyone being naked on the screen.
My free space was just the fact that Anish had a foosball table behind him in the back
and he was wearing a hoodie, which was my theory that he was going to be dressed like that
when he joined the call.

(09:48):
That's great.
So I had some fun ones too.
I had really great ones like interoperability, clinical decision support, data privacy,
health IT, big data analytics, the cloud, fire, digital health, mobile health, blockchain,
never got there.
Thank God.
I know, right?
Seriously.

(10:09):
And I spent an inordinate amount of time trying to get him to say wearables, but he just wouldn't.
So it was a really good bingo card.
We're not going to spoil who won in the end, but I will say for our listeners that someone
did win during the interview.
Someone very humble.
You'll just have to stay tuned to find out who that person was.

(10:29):
So without further ado, Sarah, should we bring our listeners the amazing interview with Anish?
We absolutely should.
I just want to mention one more thing, Elliott, for all you nerds out there who just can't
wait to play along, we will put our bingo cards in the show notes and you will get a
free Techitiva Limit t-shirt if you post a picture of your completed bingo card on LinkedIn

(10:54):
and tag Techitiva Limit.
I've seen the designs, folks.
They look really great.
You're going to want one of these shirts.
Be sure to check out that bingo card and play along.
Without further ado, let's bring you that interview with Anish.
We'll be right back.
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(13:14):
Welcome back, listeners.
I'm excited to introduce you to Anish Chopra, the towering colossus of healthcare technology
and innovation standing tall, both literally and figuratively, in the world of health tech
and data management.
Anish is the chief strategy officer of Arcadia, a data sharing and analytics platform for
value-based care organizations.

(13:36):
Arcadia recently acquired Care Journey, which is an organization that Anish co-founded and
led after his public service as the first chief technology officer of the United States
of America.
Wowza.
This guy literally towers above us mere mortals, helping providers, payers, and pharma market
leaders make data-driven decisions.

(13:56):
In 2006, when I was in college, Anish cemented his stature in the tech world when he served
as the fourth Virginia Secretary of Technology until 2009.
Not one to be satisfied with a puny Commonwealth position, Anish delivered the ultimate tech
career slam dunk serving as Obama's CTO.
Most of in the Air Jordans.

(14:18):
As a public servant, Anish aimed to foster better public-private collaboration, a theme
central to his 2014 book, Innovative State, How New Technologies Can Transform Government.
Check it out at your local library.
It's like a box of Wheaties for your brain.
Who knows?
You might just grow a few inches after reading it.
Anish currently serves on the boards of Integra Connect and Virginia Center for Health Innovation,

(14:43):
and he also chairs the George Mason Innovation Advisory Council.
Word on the street is that all boardrooms across the Mid-Atlantic have had to be expanded
to allow for ample legroom and extra-wide doorways to accommodate his enormous cerebrum.
Mr. Chopra's transcript is just as impressive as his three-pointer.
He earned a Bachelor of Arts from Johns Hopkins University and a Master's in Public Policy

(15:05):
from Harvard Kennedy School.
This beanstalk probably had to duck under a few doorways during his tenure as Harvard's
inaugural Walter Shorenstein Media and Democracy Fellow.
That's a mouthful.
Move over, Atlas, Goliath, and Andre.
There's a new giant in town.
Mr. Chopra has also been named one of the 100 most influential people in healthcare by modern
healthcare and one of the top 25 doers, dreamers, and drivers by Government Technology magazine.

(15:31):
With a resume that tall, it's no wonder Anish stands head and shoulders above the rest of
the field in healthcare innovation.
Welcome, Mr. Chopra.
May I call you Anish?
You may call me whatever you wish.
It's a pleasure, Sarah.
Thank you so much for having me.
Yeah, that was a really fun introduction to do.
I have to ask, though, being 6'1", I'd like to know the name of your tailor.

(15:52):
I'm 6'1", for our listeners to know.
It's impossible to find quality suits for giants at retail stores in America.
Not a giant.
I'm all good, but you're very kind.
I go off the rack.
I'm good.
A nice, simple off the rack for me, it works.
I need some equity in retail, I think.
There isn't anything off the rack for me.

(16:13):
To kick off this interview, Anish, we are a humorous and informative podcast about healthcare
technology.
We like to break the ice with our guests and ask them, what is their favorite dad joke?
Okay.
Well, I do have a household of kids.
We have three of them, 17, 15, and a nine-year-old.

(16:34):
I get my fair share.
I think in the spirit of healthcare IT, I often make the joke, which is essentially,
what's the doctor that repairs websites?
I don't know.
A urologist.
Oh, my God.
That's awesome.

(16:56):
My brother-in-law is a urologist, so it's a little bit of a funny play on the family.
Anyway.
That's delightful.
I think the three-year-old is going to love that.
Thank you for making my dinner time entertaining already.
Thank you for that.
U-L-L, that's hard to say.
It is.
It is.
You got it out.
Great delivery.
Thank you.

(17:16):
Anish, thank you so much for being here.
Let's just jump right into the meaty kind of stuff.
Healthcare is a data-rich industry, but I think you'll agree that we have yet to tap into
its potential to revolutionize the industry or to improve outcomes or even just to bring
down costs.

(17:37):
What hurdles do you see standing in our way and how do we get around?
Well, let's get back to first principles.
Economies work because there's a demand signal and a supply, and we can work out the highest
and best use of the asset.
We're in a bit of a weird dynamic in that the growth and supply of data, the explosion

(18:00):
of the meaningful use era and all of the broader set of data sets that are tied to
your health status.
At the moment, they're not valued as much in a fee-for-service healthcare system.
There is much more of a gap in the supply side to the demand side when you're largely

(18:21):
responding to an inbound request for clinical care and you have a machine that can address
it kind of inside your walls.
Now, Mayo is obviously unique in that you push the envelope on best practice.
There's a business model around evidence-based learning and so forth and so on, and you've
got a plan to do a lot of that work in-house because it lifts up the success you have in

(18:43):
a fee-for-service world.
For the traditional community hospital, they're not going to tax their own paycheck in order
to maximize the value of data.
If you moved to value-based, that is almost the inverse opposite, so the edge you get
when beating standard of care that has a high degree of waste and inefficiency is by being

(19:06):
smarter about identifying disease progression earlier when treating it will result in better
outcomes and lower cost.
That reward puts a heavy premium on data access, aggregation, and use.
So we're at a bit of an inflection point where the dollars of revenue tied the kind

(19:28):
of benefits of being proactive and using the data for care management in a primary care
setting where you're treating the local market less than 1% of them in bottom line.
I don't know, but it ain't big.
And forget Mayo, for the average community, we're still in the 10%, 15%, 20% range.
Now CMS has set a goal that the Medicare portion of the lives you manage should be at 100%

(19:52):
by 2030, but we're still early to get there.
We're about 40% at the moment, and even that has a lot of what I'll call upside soft risk.
And so we've got now a weird dynamic where the first decade of value-based care was people
screaming, I need more data, I need more data.

(20:13):
And now we're seeing the data pipes open, and it's like, ah, I'm not that motivated
to fund the work needed to extract value from the data, but for those who are all in in
value.
I do think that that's going to start to converge.
And so the single biggest barrier is a motivation to use the data, not necessarily a technical

(20:37):
gap or any other barrier operationally.
Anish, as a follow-up question to that regarding motivation to use data, because I really appreciate
that you kind of talked about the arc of value-based care.
People get frustrated, at least in the professional conference world, say, we've been talking
about value-based care for decades, right?

(20:58):
It's never going to happen.
There's a lot of cynicism out there, but it takes a lot of effort to change, to shift
the Queen Mary, right?
And that's essentially like the healthcare industry in our country, right?
And so it's going to take a couple of decades, maybe longer.
And so I appreciate that you're kind of identifying, well, the initial problem was the lack of

(21:18):
data.
And now it's more tied to motivation or to use another word, incentives, right?
So what kinds of policies maybe are lacking to properly incentivize the shift of value-based
care that haven't yet been implemented?
Funny enough, I think we're at the 80-20 rule on policy signal to do it, so we could do

(21:39):
more to get to the last 20, and probably in that last 20 are the difficult decisions
of mandatory value-based care models.
That's the last kind of big rock to lift on the public demand signal.
But our healthcare system is uniquely and proudly public-private.
So what's happening, Sarah, in my view, the market is starting to wake up, and the definition

(22:05):
of value-based is shifting.
We are referring to value-based as a financial contracting vehicle, where there's an expected
treatment path, and if you perform better than the expected treatment path, you get
that prolactal better term arbitrage.
That's complicated math.
And if you're a large employer, and you just want your employees to get access to the best

(22:28):
possible care, and you care about quality, you're not really trying to arbitrage the
waste and efficiency.
Maybe value-based care isn't that exciting for you relative to the burden of coming up
with all that math.
So an interesting dynamic has emerged in the era of price transparency.

(22:51):
This year, we're surveyed for the first time and said, hey, there's all this mandatory
price transparency, and by goodness, we should have more price transparency.
We'll have some standardization so that we have apples and apples comparisons.
So cancer treatment at Mayo should be roughly comparable in terms of what it does to cancer
treatment at Community Hospital A, B, and C, and I should be able to see the relative

(23:13):
improvement in outcomes and make judgments as to whether I'm willing to pay a premium
or to pay differently for that quality.
When you look at the surveys, the National Business Group on Health specifically, the
number one priority for employers was to attach quality transparency to price transparency.

(23:34):
Now, that's changing what value-based care means.
Now I want to read to you a quote, the official definition of accountable care, which we've
been short handing to value-based care, implying of financial arbitrage.
Accountable care, as defined by the CMS Healthcare Learning and Action Network, which is a public

(23:56):
private partnership I happen to serve on it, is that accountable care is when aligning
care teams to help realize the best achievable health outcomes for all the population through
comprehensive, high-value, affordable, longitudinal, person-centered care.

(24:17):
You can do that without doing a complicated arbitrage math.
Now am I incentivized to do that?
Does it mean I get more volume on traditional fee-for-service?
Can I find my way?
I think you're going to see this next chapter of value-based care look a lot more like care
rewarded through the traditional systems, and there may be enough signal to really be

(24:43):
that pull-through on the use of the data.
Now in addition, when you democratize data access and analytics, because in the age of
AI it's easier to make use of the data, it makes it a lot cheaper to just make that
care.
And if we're in the extreme, data use in its natural form, even in a traditional fee-for-service

(25:07):
system, but with a few tweaks, may just be the way care is delivered, so it naturally
routes people to higher and better teams for referrals and tracking of results.
Well done fielding my follow-up question on the fly, Anish.
You get a gold star.
I'm going to pivot and ask another question.

(25:31):
So what I learned a little bit more about Arcadia, which is your newest endeavor, it
also sounds like a really cool game from the 1980s, like an Atari game or something.
So I'm intrigued.
Arcadia uses open data to drive smarter decisions.
So can you tell our listeners a bit more about the problems that your company is specifically

(25:51):
looking to solve and how you're measuring success?
Yes, so Arcadia merged with Care Journey, so Care Journey, which we founded, was built
on open data as bedrock.
And the idea was, as data becomes available in aggregate, what people refer to as a learning
health system, the most valuable data set that was difficult to access were the linked

(26:14):
longitudinal claims files held by the Medicare program.
It was actually illegal for that information to be used commercially.
So academic researchers could write papers on it, but there wasn't a way to use it.
And Care Journey, once the doors opened up that were allowing for commercial use, went
right through and said, hey, we want to use it to score quality.

(26:39):
We want to understand the best performing teams, health systems, ambulatory surgery
centers, physicians, et cetera.
And to see where in America you're seeing, if you have back pain, where would you want
mom and dad to go to treat it?
And that work was at the heart of our Care Journey business, which meant networks that

(27:03):
were incentivized to do that math, that arbitrage of here's the expected cost and here's your
cost you're going to look like you can capture the savings.
They're motivated to identify high value specialists because it's a source of savings.
Why send you to a doctor that's going to image you all day without needing it or all the low
value care that we've read in the paper.

(27:24):
So now you've activated the physician networks to be a bit more discriminating about where
a patient should get care and it's informed by data.
So Care Journey had been doing that.
We were doing that quite well.
Largely that doesn't involve actual patient level data.
That's kind of aggregate statistics and insights derived from it.

(27:45):
So you're kind of buying a directory, like a high value network directory, essentially.
But many of our customers actually wanted to also run a lot of these analyses at the
patient level.
And so Arcadia, our new home, was an early pioneer in the data engineering necessary

(28:05):
to stitch together all the available data sets from my own electronic health record,
the health plans records, maybe some other pieces that need to connect like the community
records, some social determinants and health survey work.
And their role had been to aggregate the data, not in an encounter-based electronic health

(28:26):
record, but a patient-centered, kind of more like a quality and value-view record.
Yeah, that data plumbing, data engineering, that was the expertise that Arcadia brought.
So when we looked over our shoulders and said, huh, a lot of our customers need what they
do, they're really good at it, then we're respectful of the fact that we have big competitive

(28:46):
market.
And so when our customers have lots of choices as to where they put that data, we felt that
by putting our teams together, we could actually maximize the value of one and one and hopefully
get to three.
In the way of the goal of democratizing this data infrastructure, if it's an artisanal

(29:06):
investment and you can make a lot of money succeeding in value-based care, you might be
willing to tolerate higher-cost IT administrative systems.
But if it's just going to be part of care and it's in the traditional fee-for-service
system but you're looking to get better value, you might pay something to get there, but
you're not going to pay a lot.
So how does one do that?
Well, you need a world-class data engineering team.

(29:29):
You're going to need some data science folks that can generate these sort of benchmarks.
You want to be able to put these pieces together at lower cost.
So a lot of what motivated me to choose to merge these two companies was to sort of see
a future where this infrastructure could be benefiting everyone that may not necessarily
be in a kind of capitated agreement.

(29:55):
It's funny, just as a comment, might be here over and over again the challenge that people
have, bridging the gap, living with the foot in both worlds of fee-for-service and value-based
care.
So to me, you've made this wonderful bridge to be able to walk across for a lot of healthcare
organizations.
Yeah, and I don't want to suggest that we're the only people thinking about this.

(30:18):
I mean, large tech platforms, the Google Cloud and the AWS, I mean, you need kind of their
core cloud platforms to kind of be cost-effective.
Then you want to sort of optimize those tools.
You want to get access to data.
You want to organize it and then run some growing library of questions like, what's the best

(30:41):
way to avoid unnecessary admissions to the hospital for patients that have chronic heart
failure?
So this sort of thing...
This particular region, right?
I mean, and there's so much geographic difference in our country around access to care and quality
of care.
Your zip code tells you more about your life expectancy than almost any other measure in

(31:02):
this country.
All of that is the data sets around all of those different things are gigantic and they
can only be done from a cloud-based platform.
That's the only way you can get the computing power necessary to even churn through all
that.
Yeah, I mean, if you think about it more fundamentally, when folks feel sick, it's often too late.

(31:25):
They've already progressed in their disease to the point where you're kind of treating
something on the tail end.
And if you could have found out earlier that you had these problems and you could have addressed
them, the system would be much cheaper and we'd have much longer health outcomes, a lot
of life expectancy, et cetera.
So the creative question, it's not do you have insurance or not?

(31:49):
That's one part of the battle.
Do we expand access to insurance coverage?
It's really an entrepreneurial question.
How do we take in consideration all available knowledge about your health status, traditional
and non-traditional sources as an example, to surmise who'd be a good candidate for
a proactive outreach and not to tout the Mayo Clinic horn, but incredible work in the AI

(32:16):
team to use housing tax records, like your housing real estate assessment records, the
things that tell you how many floors and so forth.
And from that alone, having the highest positive predictive value of future chronic conditions,

(32:36):
that's the good stuff.
Are you talking about the houses index?
The houses index, you got it.
That's awesome.
Okay, we can link to that in the show notes for our listeners.
As an example, for sure, that's going to be cloud-based and analytically driven and better
math tooling and all the rest, but it's a good point.
And I think another one is as we start to track blood pressure, don't wait for the patient

(33:02):
to come into the doctor's office to just have the blood pressure checked and say, this
over a million heart attacks in this country that are estimated we can avoid, eliminate
just by monitoring your blood pressure and using dirt, cheap statins and basic things
to keep people out of harm's way.

(33:24):
Basic things, I just want to expand on that just a moment, basic things like from a technology
perspective that you can take basic, cheap medications to make sure that your heart is
pumping.
Oh, yeah, yeah, sure.
I just meant from a, so I'm trying to drive it back to the health IT and digital transformation

(33:47):
kind of topics that we work off, right, as part of that longitudinal and near real-time
evaluation of trends of the person's data, right, you were talking about BP as a specific
data point, right, where you're looking at thousands of data points over time as opposed
to the white coat syndrome blood pressure point that you took when the patient came

(34:08):
into the office, nervous because he's been, that person hasn't been eating right and is
nervous to tell their doctor about it, right?
So I'm just going back to that technology.
What kind of technologies are being deployed at scale to be able to support those models
that you were just referring to?
Well, the Houses Index doesn't require IOTA of healthcare, you know, traditional PHI,

(34:34):
personal health information.
So that's an extreme example.
Somewhere in the middle are going to be surveys, which is, you know, let me ask you some questions.
And if I see a change in the answers, I think the ASCVD risk calculator is one that there's
an article in JAMA this week or last where the team that was responsible for the CMS-funded

(34:55):
Million Hearts program said that if you actually paid a small fee, like $10 a month or whatever
it was, max, for patients that get screened for this survey that tells you the 10-year
risk of your heart attack, it's the American College of Cardiology AHA risk calculator,
openly available, having a doctor ask you to kind of track it and educate you on if

(35:18):
you changed your behavior, if you did this, if you did that, we can reduce your risk of
a heart attack.
It showed a 4% relative risk reduction in heart attacks.
Was that a complicated AI model?
No.
Survey, forms, it's not complicated, but tethered to a doctor that cares about you and has that
interest in mind to ask you to follow up critical.

(35:43):
Now we are getting to the point where we could go to Best Buy and pick up a relatively low
cost blood pressure cuff.
And so you might see a world where through your insurance premium, if you're at risk,
we're going to ship you a cheap blood pressure cuff and ask that you report back to your
doctor a few times a week, maybe a little bit of an ongoing tracking.

(36:03):
So there'll be some noise in the signal, but hopefully enough trend to say, ah, that medication
you're on isn't really doing what I think.
I've got four other options.
Let me quickly swap out the choices.
So there's a role for really advanced analytics and AI for sure, but there's also a lot of

(36:25):
really simple dirt cheap math that can be run if incentivized and incorporated into
your trusted healthcare system to do those things.
At the moment, that's not how our system is structured.
Right back to this fee per service versus value.
Yeah, I think you're right.
I think you're right.
So I want to, if we can, just turn the car a little bit on this conversational journey

(36:47):
because I'm really interested in your time as the first US chief technology officer because
I think that's a really cool job to have had.
And you kind of got to define it.
So I imagine as that CTO, you've encountered a lot of tech nightmares in the past.
So I'm curious, can you share with us like one tech disaster that just haunts your dreams?

(37:14):
And what did you learn from it?
Yeah, look, let me make a couple of observations before I answer it.
So I want to make sure people understand the context.
There was and is a United States CIO that has accountability for what is now over $100
billion of IT spent.

(37:36):
And Elliot...
Dr. Evil.
Dr. Evil.
$100 billion.
So that, my colleague happens to be one of my best friends, Vivek Kundra, he lived every
day the pain of failures, billion-dollar failures after another.
I'll give you an example.

(37:57):
I think it was in the 2000 census, Congress authorized $700 million to create this completely
janky, palm-pilot Frankenstein that was supposed to be used in the door-to-door census process.
And I don't think it even saw the light of day.

(38:17):
I mean, it was a complete, an utter boondoggle waste.
Like from manufacturing, all the way down to the...
They built from scratch some convoluted hand-held device.
That's an outsourced thing, opportunity.
Yeah, like they just built DeNovo a device.
And look, I don't recall all the details.

(38:39):
I didn't have any hand in it, but these are like in the folklore of failures, like many
like this.
I was more on the R&D and innovation side.
So when you have failures, they're almost acceptable by design.
You want to throw ideas at the wall.
You want thoughtful people to test, validate and scale.

(39:00):
Think of it more as like supporting the DARPAs of the world, the folks that are there to
shoot for ambitious but achievable targets.
So I didn't have my hand in a lot of substantial failures.
The one obvious exception which haunts me to your question was the healthcare.gov rollout.

(39:22):
And I was not...
And you were going to say that.
Yeah, but if you'll indulge a few minutes, there's actually three stories of healthcare.gov.
And the one we know is the failure.
But if you go back in time, when the president signed the Affordable Care Act in March 2010,
there was a deadline, the first deadline of the ACA was a website called healthcare.gov.

(39:47):
And it was supposed to be ostensibly an Expedia.com experience so people could shop the crappy
plans that could discriminate against you and upcharge you.
But there wasn't really a national e-commerce site of individual plans.
Like that wasn't a thing.

(40:08):
So in 90 days, we stood one up.
And a powerful story there was that it was originally slated to be like a marketing website
to hire contractors and kind of make it like a quote website, not a database e-commerce
platform for shopping.
And so I asked Nancy Ann DePaul who ran healthcare reform.

(40:30):
I said, Nancy Ann, can we think about just shifting a bit about the governance of this
thing?
And we merged that marketing talent led by a dear friend and frankly added a kind of
product mindset.
That was my successor, Todd Park.
And so Macon Phillips was the kind of the social media lead, the web and messaging lead

(40:54):
for President Obama.
But by pairing up Macon with Todd, we were able to hit the ground running in what I thought
was such a glitch-free launch that President Obama himself recorded.
And you could look at it on a YouTube video, Obama YouTube healthcare.gov demo.
And you see him literally like doing a sales demo, healthcare.

(41:16):
It was glitch-free and it was amazing.
And in chapter two, the piece that haunts me was I was anxious.
I asked the CIO who my buddy left and a second, a new CIO replaced him.
So the second CIO of the Obama administration said, I think we need to keep an eye on this
and maybe do some shared oversight long before they actually launched it to say, hey, can

(41:38):
we ask questions?
The messaging I was hearing from the staff that were running it was a little bit like
not what I wanted to hear.
I don't want to get in their way, but I also didn't want it to just kind of be free rein.
And so you have to be delicate in these roles to be an influencer.
So that was a failure for lots of reasons, not worth hashtagging here.

(41:58):
Everyone's heard about it.
But then in chapter three, when Todd basically took over the design, he created team A, continued
to fix the mess, and then recruited a dozen people to be in team B, rented a house in
suburban Maryland, said rewrite the damn thing, use only internet engineering principles,

(42:24):
not legacy enterprise software, which is kind of what they were doing.
And let me see what happens in six months to see whether or not I can kind of make a
choice.
And the end of having his cake and eating it too, the team B was so successful, they
put them on the front end of the user experience.
And only if there were complications in the kind of tax credit someone needs or their

(42:47):
health history or whatever, they get kicked out to a more traditional experience.
And that worked like a charm.
And it also embraced open principles.
So now you could go to healthcare.com and shop for plans, not just healthcare.gov and
get your tax credits elsewhere.
And so that open government wholesale digital services philosophy was very much the positive

(43:10):
that came out of the tragedy of healthcare.gov.
I love that team A versus team B concept.
I think all too often we feel like it's, you know, they're mutually exclusive.
You either have to fix the car while you're driving it, or you have to abandon it.
Right on the side of the road and get a new car, right?
And he was essentially fixing it and then investing in a future car, right?

(43:36):
Putting away savings each month or, you know, even pulling from previous savings to say,
we need to go shopping like yesterday.
I think that philosophy of team A and team B is when we're going to get back and forth
to in the healthcare data and interoperability world.
Because so much of our pipes were built in a pre-regulated era of custom connections

(44:01):
and interfaces and bespoke HL7 v2 feeds.
We're moving to a regulated clean pipe, but all of our incumbent applications are kind
of ready and willing and working on this like Frankenstein.
So what does an organization do?
When do you pull the cord and say, I want to build tomorrow's application on the clean

(44:25):
regulated pipes and not feel tethered to the legacy nonsense that we have, you know, in
the decades prior?
We're not there yet.
I would say 80-20 rule more are on the stay in the crappy lane longer than build on the
better future lane.
And that is another one of those gaps where the supply exceeds the demand for the use.

(44:48):
I also love that Frankenstein analogy.
I think your vocabulary is very impressive.
I hope I'm not the first person to have told you this, Anish, but you would be a great
candidate for like a podcast or a show with Will Shortz, you know, the puzzle guy from
New York Times.
I just think that would be fantastic.
You'd be like a celebrity contestant, just knocking out of the park.

(45:09):
I'm writing down all these words on the side here, like, oh, that's another word of the
day for me.
Okay, I've got another series question or semi-series question for you.
We worked in both the public and the private sectors.
So you have a very unique lens on the healthcare technology industry.
But I'm hoping you can share with our listeners maybe a funny anecdote about the biggest cultural

(45:30):
differences that you experience between the two sectors, because I don't know, this is
a humorous and informative podcast.
Yeah.
You must have some good stories.
You know, if you think of the proverbial hoodie wearing tech private sector vibe with the,
you know, foosball tables, public sector.
Right, that's what you look like.

(45:52):
Yeah, that's me.
This is the classically visual medium podcasting.
So just for our listeners at home, Anish is very much foosball behind them.
Hoodies pulled down.
Yeah.
He's got a latte in his hand.
We have a very formal culture in the proverbial White House, you know, senior levels of government

(46:14):
and the kind of to bring it home in big rooms.
There's a table in the center and then chairs on the walls.
Most of the meetings I attended, the center table had plenty of open chairs, but only
the quote principles were invited to sit.

(46:37):
And the staff had to surround in the outside walls.
The culture was very like hierarchical.
And so, ooh, you're a principal.
You sit at the table and no, no, how dare you?
You're like the analyst that has to like sit, take notes.
I was like not into that.
And so the role of CTO, the culture of the tech community, we kind of just let people

(47:02):
into the welcome to the table, hang out, have fun.
And one of the examples of this story is Sachin Jain is the CEO of Scan Health Plan.
And he is a staffer at the time, along with another staffer walks into the room with David
Blumenthal, who is the National Coordinator for Health IT.
David comes and meets me, sits at the main table.

(47:23):
I'm there.
But my style, first of all, I love my fellow Indian American brothers.
And so I saw my, you know, young Indian American brothers.
I was like, what's up, brothers?
And I did a little bit of a, tell me where you're from and our family name games.
And do we know each other?
And he was like, oh my God, this is breaking every kind of protocol.
I'm like, come on in, let's go.
Here's the brotherhood.
So it took a few minutes.

(47:44):
Now, David is a legend in our healthcare and IT community.
He's a guru, is a godfather.
I have known and loved him for years.
So there was no need for formality, even though we were, you know, in a traditional White
House-like meeting.
But the point is, you can break down some of those cultural barriers.
And I think a few years later, Sachin joked about like feeling proud of being an Indian

(48:06):
or something in some part that, that White House experience may have given him a little
bit of an upper.
Oh my God.
That last part just landed on me.
Oh, that's amazing.
That's great.
I love the breaking down of those corporate governmental hierarchical norms, right?
That are so pervasive, not just in governmental culture, but in corporate America culture

(48:29):
as well.
I happen to do a lot of work with startups and it's so very, very different.
Most of my career came from a very corporate based healthcare provider organization and
you know, have since moved out of that into the startup world.
The culture is very different.
So do you find that you sometimes have to bring a more structured culture to the tech

(48:56):
world?
Well, let's caveat with healthcare tech world where the culture of formality meets a little
bit more the sort of hoodie world.
And so you have in the healthcare IT landscape, what looks a lot more like my government experience

(49:19):
with an edge, I think, and probably an extreme, but in the formality of how healthcare institutions
want to meet with potential partners, it does have more of that feel.
So it's actually interesting.
What I find is that the joy of recruiting non-healthcare executives to healthcare organizations,

(49:43):
one of the interesting cultural clashes is they're like, wait a minute, I was a little
bit more of like this, you know, proverbial, you know, run fast and break things.
These people have really understood that, no, I come with humility to healthcare and I want
to bring my talents, but I want to sit and listen and observe to the challenges and I
want to engage.
So you see that a lot more, at least amongst those that are more successful in the healthcare

(50:06):
IT space.
Yeah, I think that's a great point.
You really have to pull out your co-design skills and voice in the customer skills if
you're coming from the tech industry into healthcare.
Right?
I think that's one of the things that I think is really important for me, is that I'm
really interested in the role of that first hand in my roles at Mayo Clinic and you're

(50:27):
right, the ones that are successful, the ones that end up staying and making a meaningful
difference through their work do just that.
They do a lot of shadowing, they do a lot of listening before any kind of strategy
gets formulated.
I know we're coming up on time and we have a few questions up, but just I was going to
bring in to healthcare because they ride on this message of move fast, break things and

(50:53):
they think that they know because I know tech, I know healthcare and we've seen them fail
to deliver on bringing something new and sustainable and valuable to the healthcare market, I think
because of that hubris, or at least that hubris is not helping them.
So I have a contrary in view.
I don't think big tech has failed.

(51:15):
I think it's lazy reporting to describe the failure because Apple Health's decision to
put a free app on your phone to be able to aggregate your medical records did more to
accelerate interoperability than the regulations at the time.
In fact, back to the demand signal, I remember vividly begging CIO friends of mine, please

(51:39):
open up an API for consumer apps.
The government is all but begging you soon will be regulating you.
You got to embrace this.
Well, when are the rules do I'll do later?
I don't care.
And the user experience as a consumer to get your medical records sucks.
And if Apple didn't make the decision to make it free, they scared the bejesus out of the

(52:00):
healthcare industry.
And so a dozen or more health systems said, well, voluntarily do the fire API with Apple
and we as a society have really benefited from what is now the Apple decision to embrace
the fire API before regulation created the roads, the highways that are now all healthcare

(52:24):
data flows will be built on that fire API chassis for consumer and B2B.
So that's number one.
Number two, I helped organize this cloud commitment at the White House Blue Button Developer Conference
circa 2018 Google, Microsoft, Amazon, Oracle, IBM Salesforce stood on stage together and

(52:45):
said we may fight absolutely to the death on winning cloud business.
But as it comes to healthcare, we will all build on the open fire API standard and we
will build tools to simplify the onboarding of that technology into the environment.
So what I'll tell you is that in many ways, the plumbing, the infrastructure, the core

(53:11):
big tech needs really have been tuned to healthcare in a respectful and responsible way.
And a lot of the great work we're seeing builds on top.
Now the last mile, like do I want to go to healthcare at an Amazon clinic?
Okay, maybe I'd rather go to the Mayo Clinic.
But that's not the failure of big tech.

(53:33):
That is like stay in your lane big tech, build the tech pipes and infrastructure to accelerate
healthcare success.
And it's doing that quite well in a collaborative and open fashion.
There are wonderful points and well taken.
And I think that's where I think folks identify the hubris, right?
And that whole concept around, hey, stay in your lane.

(53:54):
Don't come in to deliver healthcare.
That's not your core competency.
The flow, data management, data integration, building those highways, those informational
highways that you were just referring to, that is that world.
So great points.
Thank you so much.
Yeah, thank you.
So switching gears once again in your book, Innovative States, you highlight the potential

(54:20):
of open data in transforming public services.
Can you elaborate a little bit more on open data initiatives that have specifically advanced
healthcare delivery and outcomes over the past decade?
And what do you see as the next step in all of that?
Yeah, thank you for asking.
So number one, by the President Obama declaration on day one that we're going to move from a

(54:43):
closed to a more open government, it created a safe place for data sets held by the government
to be made more publicly available and accessible.
In fact, the care journey business would not have existed if it weren't for that decision
to open up that data set.
Prior to that, if you wanted to learn something about the healthcare system, you had to kind

(55:03):
of scrounge together private sector data sets and people were inappropriately monetizing
medical records in my view and just did gnarly, nasty stuff.
Here we've got a pristine, clear, privacy-protecting, learning health system strategy.
Second, the API movement.
Early in the Obama administration, we began understanding the benefits of having an open

(55:27):
data model that locks down access.
APIs are powerful because you can program the controls into the key.
So like a valet key to the car, some keys open up the ignition, the glove and the trunk,
some just get you the glove and some get you the trunk and some work in certain times and
some work in other times.
It's a programmable key.

(55:49):
And since healthcare is so heavily regulated, we've now created open doors, think plugs and
sockets in the walls, but the plugs you stick in have to meet privacy, security, and contractual
rules.
And so the API movement in many ways was a public-private movement.
And the government did a lot.

(56:10):
We put the first $15 million R&D investment in Zaccajone and Ken Mandel's lab to create
the smart on fire protocol.
We have funded acceleration efforts.
We did Blue Button to give consumer access to data.
And so you start to see this world where the government can open up data sets, can facilitate

(56:30):
or accelerate interoperability standards, can shift its buying power from buying widgets
to paying for outcomes.
And that's creating a new dynamic market of achieving the outcome with more novel ways.
And we're starting to see governments start recruiting tech and engineering talent at
the table, seeing that as a critical part of delivery of government services.

(56:54):
And so for all the reasons, this is now a playbook.
In fact, that was my book.
Innovative State was on the playbook.
So anybody looking to be a public servant can be an entrepreneur in problem solving on
a mountain of open philosophy and policy.
And that to me is the greatest gift because both political parties embraced it.

(57:16):
And it's about a forward looking strategy and not a left versus right divide.
I say that's a mic drop moment.
Well said, Anish.
So I'm very sorry to report that neither Elliot nor I won the Buzzwood Bay.
Wait, wait, I'm sorry.
Just a moment.
Wait a minute.

(57:36):
Just a minute.
Wait, so Anish, what do you call it?
What do you call it when a system, a health system uses data in a way that presents potential
choices of care delivery to the user about their medical options that they might use?

(57:56):
What do you call that sort of grouping of technologies where a physician, provider might
use this data to make a medical choice for their patients?
If you answer this question, Anish, our friendship can't continue.
I will leave your buzzword bingo.

(58:17):
But I will say this.
Let me say this.
Yeah, yeah.
While we're recording, it's the day that's ONC has dropped the new regulation called
HTI2 and for the first time, we're going to mandate CDS hooks implementations.
And what that will mean is that there will be an opportunity for any app developer or

(58:39):
knowledge management company to insert their logic into an EHR so we can have a smarter
learning health system.
So buzzword bingo would be CDS hooks if that's one of the items on the menu.
You know what?
Yeah, that is just too great.
So first class we though.
You know what?
I had a farm and on that farm, I had a dog.

(58:59):
That dog's name was a bingo.
I had to go for it, Sarah, because it's news and I had to educate the audience about the
HTI2 rule.
You know what?
It is greatly appreciated, sir.
Thank you so much.
So having now won the buzzword bingo game, I'm going to go ahead and ask the bonus question.

(59:20):
You know, free throw shootout versus Barack Obama and you, who would win?
That's not even a choice.
He's a talented athlete.
I am a skinny Indian dude with no athletic skills.
So obviously he would win.
I will say one funny anecdote.
A buddy of mine is a reporter down in South Florida for all the sports down there.

(59:42):
And he mentioned to me early in the Obama administration that D. Wade, Dwayne Wade, had
not played basketball with President Obama and he wanted to.
I went and told my buddies who worked with the president directly about this.
And the next thing you know, boom, D. Wade's in the back shooting hoops with President
Obama.
So I felt like I helped facilitate a game that maybe otherwise wouldn't have happened

(01:00:04):
or would have taken a lot longer.
And then I was bummed.
I didn't get a chance to get a ticket to the game.
So I missed out that day.
I think I just thought of a great way for you to make up this betrayal to me.
I would also love to play basketball with Barack Obama.
You are 6-1.
So there's a little bit of a.
I would say 6-1.

(01:00:24):
It would be competitive.
We could live stream it.
I love it.
I love it.
Yeah.
And then, you know, fundraise for a good cause perhaps.
Elliott, did you have a closing comment or apology for me?
No, there's not going to be any apology from this short king.
But we do want to thank you so much, Anish, for joining us today.
This was a fantastic conversation.
Thanks, Anish.

(01:00:45):
We are so grateful and we're honored that you chose to spend an hour of your life with
us.
Thanks for having me.
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(01:03:14):
Welcome back, listeners.
I hope that you enjoyed that message from our incredible sponsor, Daki Dramma Exchange.
I don't know about you, Elliot, but it's late in the game and I'm starving.
What should we do?
I don't know.
Maybe we could order something like something to snack on, maybe a small order of nuggets,

(01:03:35):
maybe learning nuggets that we can chew on for the rest of the episode.
What do you say?
I think that's great.
Let's make sure they're well done so we can chew on them.
Just take a long time.
Nothing.
Nobody wants a mealy-mealed nugget.
All right.
So let's serve it up first.
You're usually famished as a triathlete.

(01:03:56):
You need to get right to that protein post-workout.
Yes.
Thank you.
Yeah, for sure.
I had a couple.
They're very much related to each other.
The first was earlier on in the conversation.
We were talking about the value of the work and data analytic work when you live in a
fee-for-service world versus a value-based care world.

(01:04:19):
We talked a lot about the supply of data and the demand for data.
In a fee-for-service world, there is a lot of supply.
We are plenty of supply of data, but the demand for the data is not there because the incentives
aren't there.
We don't pay for it.
There is no ROI in having somebody do all the data analytic work to extract good information

(01:04:40):
from that supply to make something happen.
So because you live in a fee-for-service world, you're just trying to churn out as much volume
as you possibly can.
How that work in not being valued and how it's not incentivized really just stuck in
my brain as I was thinking about it.

(01:05:00):
Then after I listened to the interview again, I realized it was right around the time when
the new physician fee schedule came out.
I was joking earlier about having drank a glass of Pinot Noir while reading through the
fee schedule.
No, I'm not actually that crazy.
However, I did read a few summarizing articles about the new physician fee schedule.

(01:05:24):
We'll share a link to one of my favorite breakdowns of them.
One of the things that I was really impressed by the new physician fee schedule are a couple
of brand new codes that they're bringing specifically designed to incentivize the transition to
value-based care.
And the crowd goes wild.
I know.
Yay.
And Fetty popped.

(01:05:44):
That's nice.
But they have these three new codes and they're based off of a number of different things
that go into it that for how much you get paid for each one.
But essentially, the more complex the patient is in terms of comorbidities, the more you're
going to get paid.
But it pays you for the longitudinal, not necessarily how much time you actually spent

(01:06:06):
on this person's care.
Like a lot of the care coordination and remote physiological monitoring codes do where you
have to spend like 16 days or gather 16 days worth of data.
So it's not time-bound.
It's not arbitrarily some set number of parameters to pull back.
It's just you get paid this amount of money per month for this patient to take care of

(01:06:30):
their care, however you want to go ahead and do it.
Now, I'm oversimplifying, but it's a huge step in the right direction and really speaks
to what Anish was talking to in how we value the work associated with value-based care.
So I was really excited to see that and he kind of triggered that for me.
So he wet my whistle and then I went out and got a big taste of the physician fee schedule.

(01:06:54):
He delivered the Amuse-Bouche and you got the entree.
Sorry, I couldn't answer.
I knew how to glass a Pinot Noir.
I mean, that's perfection.
Yes, that's right.
It paired very well.
Say, PAP-Pay.
So, and then the second thing that I wanted to talk about is the fact that you're not
a PAP-Pay.
Again, it's tied, it's kind of sort of related to it, but we were talking about how there's
a lot of really inexpensive things that we can do to improve value-based care, especially

(01:07:19):
on the preventative side, to improve the lives of the population.
He talked about if we can monitor blood pressure by fairly cheap cuff being out in people's
homes, then we can monitor that in a longitudinal way.
These can make decisions much earlier on, maybe change a statin, prescribe something
else, change in diet, et cetera, to help avoid some of the more acute presentations of some

(01:07:44):
of these disease states later on.
And he talked about how it's all dirt cheap to do that, to use.
And he's absolutely right.
It is completely dirt cheap to use.
And he talked about you can just have the insurer can just send a blood pressure cuff
out to a patient to use it.
He then mentioned that there would be some noise coming in, but in overall, the analytics

(01:08:07):
would kind of smooth out and you'd be able to see these trends and take action on these
trends.
And that's fine.
And all of that is great.
But the noise and the analytics and the automation that's necessary to absorb that extra data
that's coming in, analyze that extra data and present it to a physician or medical decision

(01:08:28):
maker in a way that is going to not overburden them is not cheap.
That's not inexpensive.
And no one has talked about who owns the burden for that financial responsibility.
Sure, it's really cheap for insurer to send a blood pressure cuff to their patients so

(01:08:49):
that they can get data points to their physicians.
But are they also paying for the automation and the analytics and the AI necessary to absorb
that for the physicians?
No, they're not.
And so I think these, like I said before, these codes are a nice step in the right direction,
but we're still missing a piece of the puzzle where the physicians are not incentivized to

(01:09:10):
do anything with this data.
So it's not just everybody gets a cuff and we're all happy and we fixed it.
So those were my nuggets.
Those were my kind of musings as I was on my bike trainer listening to our conversation
again.
I love it.
I thought you were going to say bike trainer while drinking Pinot Noir and reading a new

(01:09:31):
physician piece schedule.
I'm like, that's an interesting health regimen there, pal.
I couldn't agree more.
Like I'm not cheap, right?
Like an army of Sarah Harper's and Elliot Wilson's working on a data analytics team or
an artificial intelligence team isn't cheap.
You know, you could say, well, we'll have AI do it.
Yeah, but it's not inexpensive to deploy artificial intelligence and healthcare and to maintain

(01:09:54):
it and monitor it for quality assurance.
So one excellent point, like we haven't gotten through that last mile yet.
So my nuggets, I'm going to endeavor to keep it brief here.
My nuggets are as follows.
So my favorite by far was when Anish went into the folklore of failures.

(01:10:15):
I love learning from failure and the failures of others.
And I love it when people feel chomped at it enough to talk about their major mistakes
on the air, right?
And so and to be fair though, right, you're not, you don't like to listen to their failures
because of any kind of shot and foida.
You like to hear their failures because you like to learn from others mistakes as well,

(01:10:36):
right?
Because I'm a sadist.
Okay, right.
I want to learn exactly like we have an opportunity to learn from failure, right?
It doesn't mean we're trying to fail.
But when we do, if we reflect and build that as a practice, we have an opportunity to learn
from our mistakes and those of others.
So the healthcare.gov rollout was the example that Anish gave, but he's still to this day

(01:11:00):
ruminates on and I wouldn't blame him, you know, but I do, I really appreciate this concept
of the team A versus the team B that he brought in and his CIO colleague to remedy the situation,
right?
So you have a team A that's maintaining the car, that's really crappy, you know, as it
breaks down along the side of the road, but they're still moving it forward, right?

(01:11:22):
I'll be at slowly and with a lot of smoke.
And team B is working on building the Ferrari, right?
In a special shop out in wherever Italy.
And you have these two teams that you're willing to fund at the same time and see who can solve
the problem first, right?
And I really think that's very relevant to healthcare data transformation and digital

(01:11:45):
transformation because we're trying to retool the system, as Anish said, on this new, clean,
regulated data pipeline and abandon our incumbent Frankenstein tooling, right?
And so we're trying to bridge that gap, just like we're trying to bridge the gap between
a fee for service and a value based care world.
We're trying to bridge gaps from old systems to new ones, right?

(01:12:08):
From a data infrastructure perspective.
My second nugget was this sort of tale of two cultures, right?
In the health information technology space, where you have the hoodie wearing, foosball
playing, latte drinking, techies meeting, you know, health policy bureaucrats in Washington,

(01:12:28):
meeting healthcare systems administrators at the suits, right?
With the hierarchy, right?
And the red tape.
So I appreciate where that conversation went.
Especially between the two of you talking about what has big tech failed us as a healthcare
industry.
And Anish's perspective was really fresh, right?
He said, I don't think it's failed.

(01:12:49):
And he gave the example of Apple Health and their decision to put a free app on our smartphones
if we happen to own an iPhone that will allow me as a patient to aggregate all of my medical
records into one.
And he said that did more to accelerate interoperability in our industry than any regulatory rule or
statute at the time.
And so big tech is a compliment to our industry and has intentionally designed their infrastructure

(01:13:16):
to meet our needs.
But to your brilliant insight, you know, they do need to stay in their lane, right?
That their competency is not evidence-based medicine, right?
And you know, like Amazon and Walmart and the failures that we're seeing across the industry
and trying to figure out how to deliver primary care at scale, they need to focus on the tech

(01:13:37):
infrastructure and partner with expert organizations who have the knowledge base to deliver quality,
timely patient care, right?
So those are my two nuggets.
They were tasty.
Thanks.
I worked hard on them.
So this has been fun, Elliot.
I just so love mashing on nuggets with you.

(01:13:58):
It's my favorite meal of the month.
I just want to remind our listeners that we are ever present on LinkedIn.
Please follow us.
Leave us a review there or wherever you pod.
Make sure you tell a friend, tell a friend of me for goodness sake, just tell someone
that you love Tech at the Limits.
Do you want to send us off with our HealthTech haiku of the month?

(01:14:21):
There is nothing I would rather do than send us off with a HealthTech haiku.
Tell me about rhymes.
Although haiku is aren't supposed to rhyme.
I learned that.
I know, I know, I know, I know.
But still, poetry and life, data bridges wide.
Public meets private in stride.
Innovation blooms.

(01:14:42):
All listeners, if you could see the poetic expression on Elliot's face.
It's so poetic.
Well, thank you so much listeners for listening.
We will see you next time.
See you next time.
See you next time.
Okay.
How did we, how did we forget?

(01:15:04):
Tech at the Limit is produced by Sarah Harper and Elliot Wilson in consultation with ChatGPT.
Because they are masochists and also don't have any sponsors.
Yet, music was composed by the world famous court minister Evan O'Donovan.

(01:15:25):
To consume more hilarious and informative content by digital transformation and healthcare,
visit us online at Tech at the Limit dot fund.
And don't forget to follow us on LinkedIn, Twitter, Instagram and across the event horizon.
See you next time on Tech at the Limit.

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