0:01

You're listening to There's a Better Way,

0:04

smart talk on healthcare and technology.

0:07

If you're up for energizing and story-driven

0:10

conversations with national healthcare

0:12

leaders driving industry innovation across

0:14

the country, then you are in the right

0:17

place.

0:22

I am so pleased to welcome Anish Chopra

0:25

to our podcast. Anish

0:27

is our ninth and final guest this year,

0:30

and who better to cap off our second

0:32

season than the nation's first

0:35

Chief Technology Officer who served

0:38

under President Barack Obama. There

0:41

was a lot that led up to that, though, and I

0:43

can't help but think of the stepping stones.

0:46

It was 1995. Anish

0:49

was at his first job at Morgan

0:51

Stanley, working in investment

0:53

banking, and he had a front-row

0:56

seat to when Netscape went public.

1:00

It was here that Anish saw firsthand

1:02

how technology, the internet in this case,

1:05

could make huge changes in the world.

1:09

Jump forward a decade to 2006, and Anish

1:12

was serving as the fourth Secretary

1:14

of Technology for the state of Virginia,

1:17

where he led technological innovation

1:19

in the state government. It

1:21

was a kind of training ground for

1:23

what was to come as the nation's

1:25

first CTO. And

1:28

he's still innovating today as

1:30

President of health IT company

1:33

CareJourney. We're honored to

1:35

have Anish join us today, so let's get

1:37

right into this episode.

1:42

Welcome to There's a Better Way, Anish. Thanks

1:45

for having me. Your career is quite

1:47

amazing. Among other things, as I noted,

1:50

you were the nation's first Chief Technology

1:52

Officer under former President Obama,

1:55

and today you're the President of CareJourney.

1:58

We're going to cover a lot of things.

1:59

and healthcare and in technology

2:02

in general. But with luminaries and

2:04

health IT like yourself,

2:06

we like to start where you started.

2:09

So tell us a little bit about yourself. Where

2:11

did you go to school, grow up, and that kind

2:13

of thing? I grew up as the son

2:15

of Indian immigrants in New Jersey. Dad

2:17

went to Villanova and then went home to marry

2:20

mom.

2:21

When I grew up, he had

2:23

shared with me the stories of this

2:25

famous college classmate of his by the name

2:28

of Sam Petroda,

2:29

who was from rural parts of India, but

2:31

came to this country for graduate

2:34

school. But Sam was an entrepreneur

2:37

who was an expert in the field of telecommunications

2:40

and the country was going through a transition

2:43

from analog phones to digital

2:45

kind of infrastructure for phones.

2:47

And so he caught that wave and was

2:50

able to pioneering entrepreneur on

2:52

the next turn of the crank

2:54

for innovation

2:55

in telecommunications.

2:57

I became a very successful entrepreneur, patent

2:59

holder, and he sold businesses

3:02

that have been successful,

3:03

but decided in his like 30s,

3:06

after having exited all this, to go

3:08

back to India for a penny a year

3:10

salary

3:11

and effectively became the chief technology

3:14

officer for India.

3:15

And in that particular time,

3:18

the goal was to get access to telephony

3:21

to all 100,000 plus

3:23

rural villages. And I

3:25

grew up learning about the

3:27

idea that we can use technology and

3:29

innovation to solve public problems

3:32

in a way that was different than an argument

3:34

of,

3:35

hey, we should subsidize

3:37

existing telephone lines. I

3:39

think India had 300,000 phone lines for a nation

3:42

of 300 million people.

3:44

You can say we need a multi-billion dollar subsidy

3:46

to bring all this Western phone technology

3:49

to the rural parts of the country,

3:51

or another political party would say, well, we

3:53

can't afford it, low taxes, let

3:55

the market solve it. And the engineer

3:57

said, hey, there's a better way.

3:59

we can actually invent a domestic

4:02

Indian approach that was able

4:04

to, for $30 million, design a native

4:08

digital first modern

4:10

telecommunications pipe.

4:12

And that allowed the private sector

4:14

to work off of the open standard

4:16

to actually extend that telephony.

4:18

So by the end of the decade,

4:20

without a huge amount of political subsidy

4:23

arguments, they were able to extend phone

4:25

service to every remote village.

4:28

And that story I share

4:30

with you, because it was in the back

4:32

of my mind while I was a policy

4:34

geek and interested in government, I

4:37

always had the lens of an engineer's mind.

4:39

So well, let's dig in on your role, serving

4:42

with President Obama as the first chief

4:45

technology officer for the nation. How

4:47

did that role come about? President

4:50

Obama was campaigning and said

4:52

that part of what he wanted to do

4:54

was tap the technical capabilities

4:56

of the country to solve problems. If you remember,

4:59

President Obama was a bottom up change

5:01

agent, not a top down change agent.

5:03

And he had seen firsthand from the campaign

5:07

how technology allowed for everyday

5:09

Americans to get involved.

5:11

I don't mean this to be a political statement, but

5:13

just his philosophy was to bring

5:15

that mindset to governing.

5:17

Now, at the time, there were very few

5:20

state governments that were similarly

5:22

inspired to put technology in the cabinet

5:25

rank.

5:26

Virginia happened to be one of them. I was

5:28

Virginia's Secretary of Technology. We

5:30

were just awarded best managed state,

5:32

best state for business, best state to raise a

5:34

family. And

5:35

the dot that connected

5:37

was that my governor, Governor Tim Kaine, was

5:40

a finalist to be vice president.

5:42

So as the Obama team was

5:44

doing diligence on Governor

5:47

Kaine, they saw

5:48

his success managing a world

5:50

class government.

5:51

And it was bipartisan, by the way.

5:53

We have a tradition in Virginia to have governing

5:56

be a priority, regardless of party.

5:59

And that was resulted in me serving

6:01

on the transition team, helping to

6:03

advise what it is that a technology

6:05

secretary does in government.

6:08

Wow. With a focus on healthcare, what we

6:10

haven't covered there is how did that focus in

6:12

healthcare happen? So what happened was,

6:14

if you recall, we're in the middle of economic

6:16

recovery, and the president,

6:18

to his credit, said, I'm not going to just throw

6:21

cash in terms of stimulus, which was

6:23

needed at the time. About $100 billion

6:26

of the Recovery Act was dedicated to these

6:29

seed investments for national priorities.

6:32

So we put $10 billion into the electrical grid.

6:34

We put $30 billion, $40 billion into broadband

6:37

expansion. We did work, obviously,

6:39

with the High Tech Act for electronic health records

6:41

deployment.

6:42

So that portfolio happened

6:44

before I was even nominated for

6:46

Senate confer. So there was already

6:49

a healthcare IT agenda that

6:52

had people in charge of execution

6:55

of the plan. We had ONC, and they were doing

6:57

a great job. But specifically,

7:00

the president wanted an advisor in the

7:02

White House that can cut across all

7:04

of the business units or the functioning parts of government

7:07

and the public-private sector relationships

7:09

to make sure we were maximizing

7:12

the value of technology, data,

7:14

and innovation.

7:15

And to segue into the next part of our discussion,

7:18

a big gap in our health IT strategy

7:20

was it was the last vestige

7:23

of on-prem, locally

7:25

constructed software. We

7:27

were entering the period of internet-based,

7:30

cloud-based electronic health record systems,

7:32

the chance to move to modern

7:34

internet standards for data sharing.

7:36

And so that whole what is now the Fire

7:38

API ecosystem

7:41

began as a

7:42

modest $15 million R&D

7:45

grant that ONC administered that I had

7:47

a big role in championing. And

7:49

that, of course, was the beginnings of what now

7:52

is a regulated internet standard for the

7:54

entire industry, which I'm very excited about.

7:56

Absolutely. Take us through that story

7:58

of what happened from 2010 or so to today.

8:03

We wanted to build

8:05

a more population health-based

8:08

care delivery system.

8:11

That was

8:12

obviously what was anticipated with the

8:14

later Affordable Care Act,

8:16

but we had for reasons of timing

8:19

and economic reality,

8:20

we frontloaded the IT investment. And

8:23

as your audience might know, you

8:25

don't put tech

8:26

in front of care redesign

8:28

in a dream world, you want care redesign

8:31

to drive the tech.

8:32

But that's okay, we were given the hand we were given.

8:34

So we needed to land a pre-demand

8:38

signal, meaningful use

8:40

construct that was really geared

8:43

towards value-based.

8:45

We thought we could do that with the subsidies

8:47

to say, look, I know you don't want to record blood

8:49

pressure at a discrete place or smoking

8:52

status. It was seen as

8:53

data entry clerk type work and frustrating,

8:56

but it was critical if you're going to look longitudinally

8:58

at the population to say who should be

9:01

engaged to reduce their risks of heart

9:03

attacks.

9:04

So then the next triple-axle piece was

9:06

that

9:07

if we could gently

9:09

nudge the industry over

9:11

a decade,

9:12

we could ideally

9:14

transition the demand signal from

9:16

government regulation as the requirement

9:19

to the

9:20

concept of value-based care, the

9:22

Affordable Care Act would take hold,

9:24

while CIOs would tell the EHR systems,

9:26

this is the way we want to prioritize our work anyway

9:29

and we'd emerge in

9:31

this beautiful orchestrated 10-year

9:33

roadmap.

9:35

We're laughing because obviously we

9:37

did not land the triple-axle.

9:40

So we had

9:43

a period of rough patch in

9:45

terms of, did people do

9:47

the government compliance with gusto

9:50

and love or was it like minimum

9:52

necessary to get through the regulatory

9:55

loopholes to get right back at the fee-for-service

9:57

features that

9:58

customers really wanted to buy?

10:00

And so we had this frustrating underinvestment

10:04

in stuff that worked

10:05

and overinvestment and stuff that wasn't

10:08

really aligned with the vision of where we're heading

10:10

and increasing pressure

10:12

points to say you got to move to these more detailed

10:14

standards.

10:15

It's been a bit of a challenge for

10:17

the first part of the decade, but

10:20

we come to you with good news. We don't come to you with bad news. The

10:22

Cures Act, bipartisan, and where

10:25

we are today. Now I believe there is

10:27

a more balanced demand signal

10:29

for

10:30

these value-based features.

10:32

And the market is building up that

10:34

natural request.

10:36

And so the implementation

10:39

of the Fire APIs in the Cures Act,

10:42

the roadmap on where we're heading to

10:44

solve more progress in more areas,

10:46

it's going to feel a lot better

10:48

this next decade than maybe the spotty

10:51

transactional history we had in the first.

10:53

Without the first, you wouldn't have the second. There's

10:56

a lot of progress that's been made. We've

10:58

got an electronic health record

11:00

adopted. We have the concept

11:03

of value-based care, and we keep

11:05

saying, what is it going to tilt the scales? And it

11:07

hasn't quite yet.

11:09

If we could dream the dream, maybe

11:11

we would have ripped the Band-Aid sooner and

11:13

said, go to internet-based APIs

11:16

in stage two

11:18

and not wait for stage three and Cures

11:20

Act.

11:21

So there's a dream where we kind

11:23

of pulled forward some of the requirements, and

11:25

would that have put us in a better place? Who knows? But

11:28

that's the academic discussion. It's enjoyable to

11:31

have a podcast to discuss. But remember,

11:33

Sure Scripts was a huge part of the moving

11:35

of the hockey stick up and to the

11:36

right.

11:37

Nothing made us happier than to have the Sure Script

11:40

slides of E-Prescribing going up and

11:42

to the right.

11:43

And it was like affirmation after affirmation

11:45

that we can move to digital

11:47

and it can have an impact. And so to some degree,

11:49

I

11:50

wish we had the same up and to the right

11:52

for

11:52

the rest of the transaction staff.

11:54

That is progress that needs to continue

11:56

to happen. Well, so let's talk about that. I

11:58

mean, there's so much to just talk about. about in the history,

12:00

but let's just move on a little bit.

12:02

So let's go to interoperability, because that's

12:04

where we're headed. You just talked about

12:06

the Cures Act and all,

12:08

and interoperability, the ability

12:11

to exchange health information for the right

12:13

person at the right time, when they need it,

12:15

is still evolving.

12:16

That's the

12:18

best way to put it. I'm more bullish on

12:20

where we are now than I think the perception is.

12:22

So that's why I was keen to have a chance. Oh, so tell me why you're

12:24

bullish.

12:26

Okay, let me do a process

12:28

reason for bullish,

12:29

and then a substantive reason.

12:31

The process reason

12:33

is we flipped it,

12:35

I think correctly,

12:38

to engineer interoperability

12:40

to the patient

12:42

as the first use case for

12:44

the new technology standard.

12:47

And the reason why that's critical

12:49

is that there doesn't need to be a trust

12:51

framework and a governance and

12:54

a national TEFCA and a whole

12:56

litany of things, the minimum data necessary,

12:59

B2B,

13:00

business friction and technical challenge.

13:03

All of that falls

13:05

by the wayside when a consumer invokes

13:08

her right of access. And

13:10

if we could supply that right

13:13

of access with the technical approach that

13:15

allows anyone to put their health information

13:17

on their phone, today,

13:19

every American can put their medical record,

13:22

their common clinical data set now called USCDI,

13:25

on their phone

13:26

for free. If they have an iPhone

13:29

or an Android phone for free,

13:32

without any middleman vendor fee

13:34

structure, it

13:35

works because everyone knows

13:38

how to point data to the consumer.

13:40

And so we spend more time getting the technical

13:43

standards right

13:44

in terms of the data model, and less

13:46

time arguing over that quote trust framework

13:49

on how you can request data

13:51

of me and I can determine whether it's appropriate

13:54

and then respond with a minimum data necessary

13:56

and then look up to the contract and are we allowed

13:59

to share this? We want to share this and

14:01

what are the business terms of sharing

14:03

it. Generation one of

14:05

interoperability, the original four

14:08

NHIN networks, two

14:10

of them were in Virginia, so I had a front row seat.

14:13

When you start with B2B and

14:15

then you want to get technical consensus on

14:17

data model and technical consensus on

14:19

transmission method,

14:21

you're putting a lot on a burden.

14:23

You can barely get out of the room years

14:26

and hours later with just consensus

14:28

on what's minimum data necessary when you're

14:30

asking for data in the context of a

14:32

care transition.

14:34

So that's why we've been stuck in treatment-only

14:36

CCD minimum data necessary

14:39

land

14:40

in B2B Interop for the last decade.

14:43

We're now moving in a slightly different

14:46

lens because the process was all

14:48

data elements to the consumer

14:50

and now we can reapply

14:52

that same technology stack

14:55

to the more thorny business

14:57

model challenges.

14:59

And the key transition technology

15:01

from the consumer facing to the B2B

15:04

world

15:05

is the advent of bulkfire.

15:08

That piece of technology

15:10

that

15:10

has now shipped across 270

15:12

plus

15:12

EHR certified products as

15:17

of 1231, 22 when they all had to meet the deadline.

15:21

We now have the technical

15:23

ability to

15:24

implement data sharing,

15:27

facilitating it point to point

15:30

without let's call it special effort

15:33

as the language of meaningful use called

15:35

for, Cures Act called for.

15:37

That's a gift.

15:39

Now what's missing are the contracts

15:41

and the negotiations to

15:43

unlock it.

15:44

But maybe this is an assignment your colleagues at

15:47

Sure Scripts might say, we're best positioned

15:49

to facilitate

15:51

point to point data sharing through bulkfire

15:54

to bring that future interoperability world

15:56

that seems like it's another half a decade away

15:58

to something

15:59

that's not a big

15:59

that can be demonstrated this calendar

16:02

year.

16:03

Let's go back to the patient and

16:05

to data being deployed to

16:07

the patient or the consumer. So having

16:09

tried some of those things, it does

16:12

take it outside of HIPAA protection. And

16:14

most consumers don't know what that means.

16:17

Yeah, so this is an important part

16:19

of my, call it, volunteer job.

16:22

With Governor Levitt, with David Blumenthal,

16:24

with David Brailler, we co-chaired the

16:26

creation of the Karen Alliance as

16:28

a kind of a multi-stakeholder collaborative.

16:31

One of the first deliverables we shipped

16:34

was a voluntary but enforceable

16:36

code of conduct. And in the

16:38

voluntary but enforceable code of conduct,

16:40

believe it or not, we exceeded

16:42

HIPAA requirements

16:45

in terms of trust.

16:47

As an example,

16:48

today, there's literally no

16:50

disclosure when my hospital

16:53

takes my data, de-identifies

16:56

it and sells it to third

16:58

parties.

17:00

I get no notice.

17:02

I get no

17:03

agency to

17:04

say that I'd rather not do that.

17:07

But

17:07

because it's outside of HIPAA,

17:10

it happens every day and it's a multi-billion

17:12

dollar market where people are buying

17:15

and selling my de-identified

17:17

data. In

17:20

the Karen Alliance code of conduct, we

17:22

required any app that agreed to take on this code

17:27

to publicize what their policy

17:29

is

17:30

with respect to de-identification. And

17:32

to make sure

17:33

that whatever that policy was

17:36

carried

17:37

all the way through its supply chain of third-party vendors. Now,

17:42

are there people that say

17:44

in their disclosure, we have the right to sell this data and you don't have

17:47

a choice? I'm sure.

17:48

Because that's how the healthcare system operates. But

17:51

at least there's disclosure.

17:53

My doctor doesn't tell me that disclosure. My

17:55

hospital doesn't tell me that's disclosure.

17:57

And so I thought that was progress.

17:59

But let's go backwards before we go to problems.

18:02

Let me describe why that was an opportunity for goodness.

18:05

As you remember,

18:07

we made the business decision in

18:09

our policy that

18:11

you can keep proprietary

18:13

data models in healthcare.

18:16

We regulated the conversion

18:18

of some of those data elements into

18:21

what is now the USCDI

18:23

and made them a fire-based

18:25

data model so that data element

18:28

now sits

18:30

in a format that has no

18:32

intellectual property

18:34

constraint.

18:35

Anyone, you or me, can read

18:38

a fire data model. I don't have

18:40

to pay anybody for

18:41

a code set to learn

18:44

what this fire language means in

18:46

the real world.

18:48

That's not how the rest of healthcare operates. I have

18:50

to pay to interpret CPT

18:52

codes and this and that and the other. Everyone's

18:55

got a hand in the cookie jar. But

18:57

in the fire data model,

18:58

it's completely free and open

19:01

source, which means

19:03

everybody is moving their proprietary

19:05

data sets

19:06

who's subject to regulation

19:08

into an open data model.

19:10

This is critical because

19:12

it then doesn't matter whether the destination

19:14

is the consumer who's requesting it

19:17

or I use that to share

19:19

information for a value-based care contract.

19:23

That data model is open.

19:25

So because we built to the consumer

19:28

first, we got everyone

19:30

to build version one of an open

19:32

data model. And the transmission

19:34

method was to a consumer-designated app

19:37

triggered by their username and password.

19:39

With bulkfire, we've now got

19:42

a second transmission method where

19:44

you can aggregate patients

19:46

into a cohort

19:48

or a registry.

19:50

And then you can transfer all

19:52

of the records in that registry

19:54

to a third-party application

19:56

that doesn't need additional patient

19:58

consent or...

19:59

or to involve the consumer

20:02

in any kind of administrative friction

20:04

if they follow existing legal

20:06

frameworks for data sharing.

20:09

OK, all right. Let's go to

20:12

artificial intelligence. Yes. As

20:15

we're talking about interoperability, it's data

20:17

everywhere. And now we've got

20:19

this amazing tool

20:22

that is going like wildfire. It's

20:24

going at exponential pace across the

20:26

country,

20:27

across the world. Lately so. All

20:29

right, right. I'm more giddy about

20:31

this moment than it was when we saw the internet

20:33

blossom. So this feels like

20:36

I'm a kid in a candy store with excitement about ways

20:38

to solve big meaningful problems in a

20:40

relatively short period of time and at low marginal

20:43

cost. So let's go. So

20:45

let's

20:45

talk about it. Where does your mind go

20:47

immediately around artificial

20:50

intelligence? Let's start there. Well,

20:52

yeah. So I've been speaking of a

20:54

dream

20:55

for a digital

20:56

health adviser

20:58

or what I refer to as a health information

21:01

fiduciary service

21:03

whose role is to

21:04

basically run decision support

21:07

in my best interests based on the information

21:09

that it has about me.

21:11

So much of our health care system is that

21:13

the data is inert

21:15

until it's too late.

21:17

And then we show up in the emergency room, and then

21:19

the systems start running, and then everybody starts

21:21

asking questions. And oh my goodness,

21:24

putting you on dialysis, even though if we knew

21:26

you had kidney disease even just two years

21:28

earlier, we could have put you on the new meds

21:30

that can actually eliminate the need to be on dialysis.

21:33

My goodness, avoidable dialysis. Are

21:35

you kidding me?

21:37

How could we have not missed that as an opportunity?

21:39

So part of this is at

21:42

scale, if one has access

21:45

to longitudinal information and is trusted,

21:47

has access and

21:50

is trusted,

21:51

then we can run these models

21:54

to predict

21:55

the next best course of action

21:58

that

21:58

either might involve. involve me seeing

22:00

a new doctor,

22:02

getting a new test,

22:04

adopting a new care plan.

22:07

These are all known

22:09

if we understood

22:12

and could read all of PubMed

22:14

and all of the recommendations. People like

22:16

me have had an interest of this and you should track

22:18

for that.

22:19

I'm South Asian descent, so I've got a genetic

22:21

predisposition to heart disease and I should be monitoring

22:24

and making sure I'm on a statin a little bit

22:26

earlier, even if the guidelines say this or that.

22:30

So how do we create a

22:32

marketplace that will reward

22:36

health information fiduciary investments?

22:39

The challenge I see is

22:41

that the technology is often put

22:43

to its highest and best economic use,

22:46

which may be different from the highest and best patient

22:49

use. Highest

22:51

and best economic use is, hey,

22:53

I'm in a Medicare Advantage plan, they

22:55

need to get

22:56

revenue by looking up my

22:59

health conditions. The highest and

23:01

best use of AI might actually be risk

23:03

adjustment code, which

23:05

is about getting paid more for what I have

23:07

and the conditions that I have. And

23:10

I say that in a slightly negative way. I don't

23:12

mean to be negative. I love everybody. I love MA.

23:15

I love everything. But our economic incentives

23:17

today

23:19

don't reward organizations to

23:21

invest

23:22

in consumer

23:24

decision support.

23:26

We've got CareGap analytics to

23:28

the doctor.

23:29

We've got

23:30

some kind of patient matching. I

23:32

want to get an appointment with the first available orthopedic

23:35

surgeon. We might have scheduling systems

23:37

and access

23:38

texting and chat options.

23:40

But

23:41

fundamentally, should I be going to that

23:43

doctor for this reason or should I be

23:45

going to see a physiatrist first to do some

23:47

more conservative treatment on my back pain?

23:49

Those kinds of decision support systems about

23:52

not accessing the system and

23:54

not using the thing that I'm looking to get into in

23:56

a fee-per-service way. There's

23:57

no financial incentive to build those.

24:00

And so that's an area where I see

24:02

great potential in the use of AI

24:04

and healthcare. I'm not 100% sure

24:07

that the current

24:08

economic incentives

24:10

will drive us towards the highest and best

24:12

use of this capability. That's really

24:14

interesting because it's really the combination

24:17

where you end up as the combination

24:20

of value-based care and super

24:22

consumerism. That's what puts

24:25

this on fire, so to speak. And

24:27

this is why I'm so bullish on policies

24:29

like voluntary alignment,

24:31

where I'm a Medicare patient, I can see any

24:33

doctor I want. I might go to a primary care

24:35

doctor and paternalistically, that

24:38

doctor chose to be in an ACO, so

24:40

I just follow suit. But you know what? They

24:43

haven't done anything for me. Maybe in theory,

24:45

they sent me a letter and said they're going to coordinate

24:47

my care, but

24:48

I'm not so sure I know what that means at the moment.

24:50

But

24:51

with voluntary alignment, there could be a

24:53

competing clinic down the street and say, you know

24:55

what?

24:56

Check us out. We've got a South Asian

24:58

heart clinic

24:59

and we might want to track you. One

25:01

of that's going to be monitoring-based and data-based.

25:04

And if you want, we can give you some specific

25:06

guidance based on your health needs. And

25:09

maybe if I switch to that doctor, I'm not switching

25:11

my health plan,

25:12

I'm switching my doctor, I might

25:14

be enrolled in their value-based care arrangement

25:17

through voluntary alignment. That's

25:19

a really powerful change to this. Oh, sign

25:21

me up. So if CMS is launching

25:23

that right now, calendar year 22,

25:26

it really took off in the ACO REACH

25:28

model.

25:29

Only a couple million people are enrolled in

25:31

that model, but 10% of them

25:33

signed a form that said, I want to voluntarily

25:36

align because you are offering

25:38

me something

25:39

that's going to feel like I'm getting more coordinated care.

25:42

That's a different model, direct to consumer

25:44

value-based,

25:46

than this sort of paternalistic, you

25:48

just do whatever you do and behind the scenes, we're

25:50

going to true up all the math and the books

25:52

and everything else.

25:53

I love consumer agency

25:55

in

25:56

voluntary alignment. And so let's

25:58

fingers crossed think.

27:59

ideal world, you'll have a two by two matrix.

28:02

What gets me productivity in

28:04

the enterprise and what gives me

28:07

improved clinical outcomes?

28:10

And so you really want to have a portfolio

28:12

approach of AI projects.

28:14

And perhaps in reality,

28:16

we're going to lean a little bit more on the

28:19

behind the scenes,

28:21

administrative burden reduction, use

28:24

cases, and be a little

28:26

bit more careful about when

28:28

to introduce. We don't want hallucinations. It's

28:31

too early. We have

28:32

not yet trained models

28:35

on longitudinal clean

28:37

health data to give

28:39

really good information about

28:42

what to do next. I have a path that

28:44

I see

28:45

to move us in that direction. You see

28:47

a clue of this in the announcement with Epic

28:49

and with Microsoft,

28:51

which is that we're going to train the AI models

28:54

to write really good queries to

28:56

ask questions of the sensitive data

28:59

if we're not going to give it itself the sensitive

29:01

data. So then it's like a derivative

29:04

works of AI, where you're

29:05

teaching it to ask smart questions,

29:08

but not actually exposing the PHI

29:10

in the process.

29:12

So I've spent some time with our technology

29:14

team on AI, just understanding

29:16

it and just cleaning the data

29:19

itself is most of the battle.

29:22

Yes. So let me separate out these concepts,

29:26

I think in threes. Today's

29:29

foundational model,

29:30

let's call it, it reads the internet

29:33

and everything that's been written in the internet and

29:36

is fed that through a machine and

29:38

these parameters are getting bigger

29:40

and bigger. So GPT-4 is like a thousand

29:43

X the size of GPT-3 and who

29:45

knows where GPT-5 will be, but

29:47

you can start to feel like

29:49

it's going to learn everything, whether we actively

29:51

and explicitly taught it healthcare specific

29:54

things or not. It's sort of a natural and

29:56

inevitable training exercise.

29:58

Not a lot of organizations have the cap. capital

30:00

to fund the kind of compute necessary

30:02

to do all of that work. So today, that's

30:05

in the hands of the few, the training.

30:08

But then we have this opportunity to take

30:10

that training

30:12

and to organize it

30:13

for our specific

30:15

environment. We can tune it.

30:17

So say I'm a health plan, I can

30:19

take all of my criteria

30:21

for prior authorization,

30:24

which maybe it doesn't know because it hasn't

30:26

read those materials. And I can add that

30:29

additional information into the mix.

30:31

And so there's going to be a layer of analytic work

30:34

to design the fine

30:37

tuning step. You're not going to do a lot

30:39

of data manipulation in that

30:41

step. You're mostly going to

30:43

feed it like

30:44

one of those incinerators. You can throw

30:46

back to the future style, you threw every bit of

30:49

food scraps into the machine that converted to

30:51

energy. I think it's going to be whatever data

30:53

sets you have

30:54

without it being fancily curated,

30:57

will go into this fine tuning step.

30:59

And then the third layer is the interaction

31:01

layer. And that's where I was describing the

31:03

business strategy of say, teaching

31:06

it

31:07

how to fish in

31:08

a data set that we otherwise don't want it to get

31:10

access to.

31:11

And it could learn how to investigate

31:13

that data set. So that

31:15

unlocking your sensitive PHI

31:18

through an

31:19

AI analyst

31:21

may be the near term

31:23

opportunity to

31:24

unlock the value. It doesn't

31:27

require what you're describing,

31:29

which is pre-generative AI.

31:32

When you were just doing predictive AI,

31:34

oh my goodness, you had to label

31:36

everything. And

31:39

so 80, 90% of the budget was data labeling.

31:41

Now that we're in a world of generative

31:43

AI,

31:44

it does create a new option

31:46

to engage with these tools without having

31:48

to do that data. Great. So

31:50

now you're with Care Journey, where

31:53

you've been the president for eight years.

31:55

You took this rollover shortly after

31:58

being the US chief.

31:59

technology officer. So

32:03

tell me about the mission and what you're doing

32:05

there. So to rewind the tape,

32:07

I actually ran for Lieutenant Governor of

32:09

Virginia

32:10

after I left USCTO. And

32:12

my dream

32:14

was that we would improve the public-private

32:16

handshake. There

32:17

would be opportunities to problem solve.

32:19

And I was hoping to bring state governments into

32:22

the future by saying for health, for energy,

32:24

for education, assume we have

32:26

the laws that we have,

32:28

we now want to execute those laws in

32:30

a way that help people. We can do a lot

32:33

more together if we could improve that

32:35

what I called handshakes and handoffs. The

32:37

government's largely agreed to open up a lot of

32:39

the digital infrastructure. And if we could hand

32:42

off that information to partners that are

32:44

trusted to solve problems, we can make a difference.

32:47

In the Affordable Care Act, one of those

32:49

examples was that CMS

32:52

agreed to release the longitudinal Medicare

32:54

claims data for

32:55

purposes of provider performance

32:57

measurement. I can't give my mom and dad recommendations

32:59

on who the best doctors are because the Yelp

33:02

reviews are all about things like is the room

33:04

clean and it's not exactly data-driven.

33:08

So Care Journey was born after my

33:10

campaign loss because my board chair and

33:12

a big supporter of mine, Sanju Bansal, co-founded

33:15

MicroStrategy, had a long history in technology

33:18

and data sets, said, Anish, if you want

33:20

to be on the government side encouraging the private

33:22

sector to do stuff, why don't you just step over

33:25

the line, stand on the private side, take

33:27

a lot of that information that's been public and help make

33:29

it useful. So we tried half a dozen ideas

33:32

from Blue Button to a whole range of ideas.

33:34

We put ideas at the wall and said, which of these

33:36

are going to have an impact in healthcare? And the

33:38

one that's taken off

33:40

is the idea that we could use the Medicare

33:42

data

33:43

for purposes of provider performance

33:46

measurement.

33:47

And it's still early days, but I'm grateful

33:49

that we're able to mine the largest

33:51

linked longitudinal data set

33:54

with openly available measures of quality

33:57

and outcomes and to bring that to

33:59

life through our own.

33:59

our membership program, we're serving over 130 organizations,

34:03

mostly ACOs, but health plans and

34:05

entities like US News, who's now incorporated

34:08

some of our data into their provider profile

34:10

pages. I love it because I feel like I'm

34:12

continuing the work I was doing in government

34:15

just on this side of the public-private handshake.

34:17

So we're going to wrap up here with a couple of questions

34:20

I always ask. And it is

34:22

perfect right after you talk about the

34:24

ideas that you put on the table around

34:27

how you can bring public and private together

34:29

for a project, what inspires you?

34:32

How do you get inspired? So Sam

34:35

Petrotta was my inspiration that you can actually

34:37

make meaningful change to a

34:39

billion people by bringing technology,

34:42

data, and innovation to solve problems. What a great

34:44

high on problem solving if

34:46

I'm not arguing over a tweak to an old law,

34:49

but I'm actually engineering a better way to

34:51

do what's already

34:52

in the political domain is consensus.

34:55

So boy, I wake up every day thinking

34:57

about how do we do more of that in energy and

34:59

health and education and banking.

35:01

Yeah, that's amazing. Inspired

35:03

from a very young age and still

35:05

today is what inspires you. That's great.

35:07

And what excites you most about healthcare

35:09

today?

35:11

It is the creation of the health information

35:13

fiduciary. I see the

35:15

sort of earliest of indicators that

35:18

value-based care organizations in

35:20

total cost of care with a voluntary

35:22

alignment and these new technologies.

35:25

They're going to usher in a completely

35:27

better care experience without any

35:29

new law or any new action

35:32

and budget. We can make the current

35:34

systems work

35:35

better. And so that

35:37

to see members of Care Journey I love

35:40

work on those problems gives me joy.

35:43

That's fantastic. Thank you so much. It

35:45

was, it's been a great conversation. We've got

35:47

the history of where we've been and how

35:49

we got where we are and the vision for

35:51

where we need to go. It's just been a delight

35:54

talking with you. Thanks so much for joining. There's

35:56

a better way.

35:57

Have a great day. Thanks for

35:58

having me.

36:03

Our conversation today, Anish, was

36:05

a great reminder for why I work

36:07

in healthcare and for why the work

36:10

we're doing here at Sure Scripts is so

36:12

important. I love how you

36:14

spoke about making meaningful change

36:17

by bringing together technology,

36:19

data, and innovation to

36:21

solve problems, and how

36:24

that can be done at scale for

36:26

a billion people, like your

36:28

father's famous classmate, Sam Petrota,

36:31

who helped to modernize telecommunications

36:33

in India. Of course, I'm

36:36

biased, but I love what you

36:38

said about nothing making you happier

36:40

than to see the hockey stick of e-prescribing

36:43

moving up to the right, in

36:46

no small part because of

36:47

Sure Scripts.

36:48

And this affirmed that we can

36:51

make a digital transformation in

36:54

healthcare. And I love

36:56

when President Obama needed a

36:58

White House advisor who could bridge

37:01

public and private partnerships in

37:03

the name of technological innovation.

37:07

Everything you've done in your life, like serving

37:09

as Virginia's fourth Secretary of Technology,

37:12

meant you were ready for

37:15

the role. Thank you for being on our show

37:17

today, Anish, and for inspiring

37:19

both me and our listeners.

37:26

Thank you for listening in today. If

37:28

you've enjoyed this podcast, please rate,

37:31

subscribe, and review. There's

37:33

a Better Way, smart talk on

37:36

healthcare and technology.

37:38

With your help, we'll

37:40

continue to bring great conversations

37:42

to the fore and to the wider

37:44

listening public.

37:46

Thank you.