Hard Problems, Smart Solutions: The Newfire Podcast

And what I've seen decade over decade,
'cause I can actually say that now

I've been doing this for a long time,
is those who wait, I wouldn't say they

get hurt, but they lose advantage.

And negative advantage is the
same thing as getting hurt

when the market moves fast.

So I would say get connected and then
start finding tools for the specific

things that you're looking for.

It's not like a sea-change
moment when you into interop.

It's an incremental movement that
leads other increments, movements

that leads to general success.

Welcome to Hard Problems, Smart
Solutions, the Newfire Podcast where

we explore the toughest challenges and
the smartest solutions with leaders

across technology and healthcare.

I'm Brendan Iglehart, Staff Healthcare
Architects here at Newfire Global

Partners, and your host for this episode.

For today's episode, we have the
pleasure of speaking with Paul

Wilder, the executive director of
the CommonWell Health Alliance.

Paul brings more than two decades of
experience in health IT leadership,

deeply committed to transforming
healthcare delivery through

technology and data exchange.

He's at the forefront of driving
nationwide interoperability,

working to empower clinicians,
practitioners, and individuals

with robust data exchange services.

Paul's work at CommonWell aligns
perfectly with our podcast mission to

discuss the toughest challenges and
the smartest solutions with leaders

across technology and healthcare.

He is known for his insightful
perspectives on the complex world of

health data from regulatory shift to the
practical realities of implementation.

Paul, thanks for joining us today.

Great.

Thanks for being here.

Thanks for letting me be here.

It should be fun.

So to get started, Paul, I'm, I want to
begin with your journey in health IT.

So, you've had a significant tenure
back at, before with the New York

eHealth Collaborative before moving
into your current role as the

executive director at CommonWell.

So what drew you into this crazy
world of healthcare interoperability?

Well

First I was drawn to

healthcare starting technology
that was quite outside.

I was doing network support cellular
networks kind of stuff, and immediately

got pulled over and about six months
into that first out-of-college

job into records management.

So, the, this is precursors to EHRs
going back in the late nineties and

there was the document flow and the
fun thing about that one, I was young

and got to travel on the country.

That was fun.

But, I really got a flavor for the
business backend side of healthcare.

I originally thought I was going to Med
School, actually got accepted to one,

decided not to do it, but always had
an interest in healthcare in general.

And I realized there's multiple
areas that people can help with.

And the really fun part that I thought
about then, but really thinking about more

about now, is how much it affects your
everyday life and how you're influencing

something that influences a lot of
people around that you love, admire.

And some people that you just want to be,
you know, better humans going forward.

For listeners who may not be familiar,
can you explain a little bit about

what CommonWell is and the role
that you all play in this industry?

Yeah,

Given

the best generic part of healthcare
is fun to play with 'cause you get to

influence stuff and make things better.

Interoperability i s
the focus of CommonWell.

CommonWell was founded 2013, so a little
over a decade ago, by some preeminent

electronic health record and other health
information technology companies with

the belief that data availability and
exchange across providers was necessary

for a better person-centric healthcare.

And the original philosophy was
that it can't be a, or shouldn't be,

shouldn't be a single vendor solution.

'Cause patients see many different
providers, different types of specialties,

and they're not picking by EHR,
they're picking by many other factors.

So we were built with as a 501(c)(6),
a trade association nonprofit type.

And our goal was to make sure all
the data was available every time

a provider needs it across every
healthcare entity across the country.

And we continue to strive to do that
with both within ourselves and across

partners to move data from provider to
provider and provider to patient and

keep adding Ps, payers, public health.

Keep going down the list.

One of the things that was interesting
when we were chatting last week in

preparation for this podcast is that
you were talking about how CommonWell

has been on the forefront of enabling
patient access to their own data for

quite some time, which is, and currently
a big topic within interoperability.

So can you explain a little bit about
what you've been doing there and why

it's taken so long to get more visibility
and focus on that sort of work?

Yeah,

we started 2013.

It really was a treatment centric
network provider to provider exchange.

It was 2016 when we first added
what we called, patient access.

And sometimes in the standards
called request, patient request.

And I'll be honest, the first couple
years didn't go amazingly well.

We had two general headwinds.

One, there wasn't that much the
tracks laid for provider-provider.

We thought we were doing well in 2016 with
a high number of thousands of connections.

By the time I got here, and we go about
two years in, so we're around 2021,

we were at tens of thousands, right?

So we added in almost a factor
from that point forward.

And the reality is most patient access
applications, or individual access as

we like to call it now, or individual
access services, they don't work well

if you can't get to all the data.

Because the patient is looking
for their most recent thing.

It's a very atomic level entity.

It's provider Bob, provider John,
provider Lucy, that has my data or

hospital X, Y, or Z. And when that
one's missing, they kind of disengage.

So you needed more of a network
effect to make this work.

The second part was the network itself
was designed for provider to provider,

and we didn't actually write our
agreements to give this data to patients.

And those of you who are HIPAA experts
and know things about healthcare

data, you don't move data to things.

You're not allowed to move them to
without a contract staying as such.

So we had to do a fair amount of
retrofitting to get things up to

snuff to be able to do patient access.

Fortunately, the rest of the market
or at least the industry or us as just

citizens and active healthcare users said,
Hey, we really want access to our data.

And more and more people heard that
and it started to appear in other

networking frameworks, which increased,
it increased the ability for us to

take the time to focus and fix it.

So we recently did that with one
of our largest members being Athena

just moved in their entire cohort of
providers into our patient access aware

application that is also TEFCA aware.

And now we're off to the races with
people, I wouldn't say playing catch-up,

I think we're all clotting to the same
point at the same time, which is great.

So, Paul, I know a lot of us in
the industry have been tracking the

recent administration's movements
around health IT, and specifically

watching the recent RFI and events
that have been held by CMS and ONCASTP.

I think that you've been involved with
some of those events in Washington.

Do you wanna tell us a little bit
about the kind of tone and conversation

going on in there and what you expect
to come outta those of those meetings?

Yeah, there are really three
major events that occurred.

One goes back to May where CMS
released an RFI, looking for commentary

on the benefits of health IT and
what are good apps out there, as

well as other things related to
technology and data interoperability.

It culminated in a, well, actually the
culminated was the end of the RFI the

day you had to submit everything, but in
the middle they did a listening session

where they had the, the higher-ups of
HHS, so this was Secretary Kennedy,

then Dr. Oz from CMS side, down the
line explaining what's going on.

Amy Gleason, et cetera.

And the morning session was presentation,
followed by a bunch of panels in the

afternoon was more working sessions
to figure out what to do next.

The morning panels were full of
people just banging the floor

looking for better patient access.

And you have to think about this for
a second, realize that the people

putting together this listening
session had to have set a tone.

They chose who to put up there.

Right.

And there were people they knew
that were gonna say these things.

You don't have to, you don't
have to wind people up and

tell 'em exactly what to say.

Just get the right people.

So the fact that CMS and HHS put a
lot of people they knew they were

gonna be focused on individual
access on a stage during their big

show is interesting unto itself.

That says the administration
is very interested.

And then the conversation that happened
after that, which then led to this

idea of a CMS aligned network and a
further event that happened a couple

weeks ago at the White House where
the CEOs and other officers of many of

the companies are at that event, and
actually a smaller group than that,

were pledging to be aligned to CMS as
we go forward with a significant focus

of that being, how do we help patients
make better decisions with better data?

And I think in the first administration
round of Trump, you saw financial data.

There was an attempt to do getting
price information, price transparency

to patients, which I don't think went
as well as everybody wanted it to,

but it was an interesting idea of
more information, better decisions.

And I think this is the next evolution
to how about the clinical data, too?

Maybe the two together
start to move the needle?

Understanding that the first
tools probably won't do as much

as you wanted to, but you have to
start every journey with a step.

And a significant step would be
getting the ability for apps to

get data in patients' hands so they
can start doing something with it.

You mentioned Amy Gleason and just then,
um, who was the acting head of the newly

formed department of government efficiency
or DOGE, under the federal government.

And obviously she comes from a
background in, in healthtech.

So I'm curious for your perspective
on someone like her, who's known

for really getting things done,

how do you think her tenure
and involvement in this

will impact the outcome?

Well, there's two things.

She has she has a good patient story
in her daughter's story, which is

for those who have not seen it.

I won't give you a full summary,
but you can find it on the interweb

looking up Amy Gleason story.

Amy Gleason, CMS, YouTube,
whatever you wanna find it on.

And she does a good job of delineating
a, you could think of a generic patient

with a rare disease and without data
and AI tools and the like to be able to

process that data, how things were missed.

And I think there's a lesson in there
that, providers, i n the past you

would, you have seen some resistance
to some adoption of technology.

For example, we saw an initial bad
reaction to like direct messaging,

provider to provider direct, but
then they tried applying patient

to provider and we skipped that and
went instead to portal conversations.

And when you start to learn as people
are generally pretty nice, people don't

abuse your, you know, my, my mobile
phone number's in my signature line for

my email, and no one calls it, right.

, No one bothers people that way.

They have other ways of communicating
and I think they realized after that push

of communication direct to patient, that
they're not gonna get abused as much.

Maybe it's time to think about using
technology in a more augmented way.

But Amy in particular, is
like, no, go do it faster.

You're hurting healthcare, you're
hurting yourself actually by not allowing

patients to supplement what you're doing.

And her brain in terms of doing things
faster but efficiently and effectively,

on top of the passion to do it from her
own personal story, is usually the kind

of secret sauce you need to move things.

And you put someone in a central position
where they can convene people and blast

through what I, I usually call the first
mover disadvantage of network effects, the

first guy does all the work and a lot of
people follow in after, i s significant.

Like that kind of the beat of the drum
being consistent across many parties who

normally compete and don't wanna be synced
with each other is very powerful when

you're trying to develop network of x.

Speaking of building out networks, one
of the big developments that I've really

tracked from, from my side and the
customers that we worked with in the last

couple years is the rollout of the On
Behalf Of designation with Carequality,

which I understand that you had a hand
in originally developing that concept.

Can you tell us a little bit about, on
behalf of our OBO and a little bit of

the story about how that came about?

Yeah.

I wanna see healthcare move faster too.

And you can imagine running a trade
alliance, which is supposed to be

supportive of trade and not just the
entries, entities are in it right now.

It's supposed to be also supportive
of the next thing to enter.

I kept thinking of what
are we missing, right?

If I just, if all we did was work with our
primary EHRs and the like, t hat's great.

They'll fund the enterprise and
we're a true nonprofit, we make

too much money, we give it back.

I was like, who else needs help?

And I kept looking to the startups
and the neat little things being

developed at the edge that are
the first step to their existence.

And I had done some accelerator
type things in my past as well.

And how did you do an
accelerator in healthcare?

Usually it was by getting
your first customer, right?

You would link them up with a technology
set and say, Hey, I'm bringing this

preeminent academic in as a pilot customer
to help you develop and go forward and

then get more contacts and go from there.

But when you start looking
at patient stuff and littler

tools, it doesn't fit as well.

Like we're talking like, one
person, one diabetic, we need to

move faster and get things going.

So I said, why i f providers are hooking
up their EHRs at scale, and we're getting

the data to the network, we're solving
the data availability problem, right?

The data is going to be there.

What I was missing was, who else needs
to use this data, the supply and demand.

I said, can we hook up these
applications to the network?

To get the same data to accelerate their
ability to do what they need to do.

Iinstead of integrating to one
hospital or to one ambulatory practice,

why don't they hook up to all of them
and do that without having to hook up

through the high primary EHR 'cause
it's expensive and time-consuming?

And I was more worried about the
time-consuming, to be honest.

I mean, it's fine for, again, we're
a trade association we support trade.

I'm not against people charging
for services that's fine.

You just don't want it to be a barrier.

And so I felt like we weren't getting the
right tools in front of the right people.

So we built this OBO.

If your EHR, if your EHR is already
connected, why can't you connect

every other product you bought
that is for treatment purposes?

All of them.

In the dermatology app that takes a neat
picture from your iPhone and sends it up

to some AI tool to do a skin lesion check.

Why shouldn't it have access
to your history of skin cancer,

family history, and the like?

To better inform the answer of what it's
about, to help suggest in that clinical

decision support thing it's doing.

And do it cheaply.

And by cheaply we make the
network an interface engine.

Everybody can access the same
information at the atomic level of

you, Brendan, Paul, whatever it is.

There was some resistance at first
and unfortunately it got changed a

little bit in the way it got word
that people found loopholes to

use it for, semi-abusive things.

And we were still addressing
that trust issue today.

But I still stand behind the idea
that we need more access, not less.

And we just need to do it safely and
securely so that, we maintain trust and

provide the right solutions to patients.

Paul, when we think about the future
of patient access to their own data,

obviously there's a lot of different
applications for that, including

data correction, which was one that I
have experienced as a patient myself.

You know, seeing things in my own patient
record that is, is incorrect, and then

trying to take steps to address that.

Why is that specifically such an
important aspect of kind of unlocking

data for patients that ultimately they,
they should have the right to use?

Yeah.

At the risk of giving the standard answer
at every technology conference, and

especially healthcare conferences, AI, so
we got this artificial intelligence thing

going on, and I think it's important to
remember how AI actually works, right?

It's statistic space, right?

It's taking... when you do an LLM
and have it write an RFP for you

in Copilot, or whatever you use,

it's just aware of what kind of words
go together when it's, look through

the history of time of everybody
writing things and gives you a

suggestion that seems to be within the
confines of what you're looking for.

And when you get to healthcare
data, it's doing the same thing.

Going back to the days of Watson and
other early precursors where we are today.

The one thing you don't
wanna do is confuse it.

We, you'll hear people talking
about AI hallucinations and it

starts to fill in data gaps.

Another problem is when it has a
piece of data that doesn't belong

and it doesn't always know what
should go around it or ignore it.

So if you have errors,
bad things can happen.

Lemme give you an example.

I had a shot, a flu shot last
season and my record said I

had gotten HPV vaccination.

Now, it is actually more common these
days for or for especially younger males

to get HPV vaccinations, but not very
common for a 48-year-old male to do that.

And my doctor would probably look over
that, if he was looking at fantastic

cancer drugs that would be the
all-end-all to cure prostate cancer

it's available and says, but what if
that prostate cancer drug material

said it's contraindicated to people
who have the HPV vaccination?

My provider might skip it, but the
AI provider may not know what to do.

And so it's statistical analysis.

We're gonna start suggesting
different therapies.

Could underweight the perfect drug, right?

Everything else could fit in, but
this thing is a bang-out criteria and

bang-out means eliminate it at all costs.

You don't want that.

And there are various things that,
little tiny nuances, little nudges you

can do that make the model messed up.

Providers can do the same thing.

They already have clinical
decision support tools on their

side, and contraindications X is
contraindicated to Y. You can't

have these two things together.

Automatically set off red flags.

Right?

So that would be, that'd be an
extreme example, but it could

also say there is no data on this.

Anything that decreases that
Superdrug now being not a Superdrug,

because of my potential biochemistry
and the things I have in it.

So I think it's really important
that we have the right data.

I mean, today, most of us probably
worry about the wrong data being

things we get billed for, right?

I didn't have this done.

I don't want to pay my $20 co-pay.

This was supposed to be an annual
exam, why do I have a co-pay?

It's supposed to be free.

And those guy, oh, it's coded wrong.

You like, okay, you fix it.

Fix it to an annual wellness exam
and not just a normal office visit.

And that's fine for the $20,
a hundred dollars, a couple

thousand dollars even, you pay.

But the clinical stories could get
really messed up if we confuse the AIs.

And it is, you could argue
whether it's the future or not,

but it's definitely a factor.

So getting data into the hands of
patients is the most likely way

to make sure the data is accurate.

'cause I probably care more my
data than anybody else does.

And on the topic of AI, Paul, as we
continue to see, meaningful advancement

toward making data more liquid for
different use cases, involving including

those that patients are directing,
how do we make sure that patients

stay protected or that f olks' privacy
is respected in this whole process.

You know, I saw, we talked about
the events that happened and then

there was the big White House event.

And I don't, it doesn't really
matter where you sit in the political

spectrum, I did see something disturbing
happen that happened that, that day.

There was an article put out by a, what I
consider a good media outlet, that talked

about the federal government is trying to
make a system to collect all your data.

Big tech is getting into your data,
be careful and got quotes from some

preeminent professors about the
security and privacy concerns alike.

And the irony there was the dialogue
was exactly opposite that, right?

The dialogue was, we want big
tech to do the right thing, to get

data into your hands so that you
can control where it goes, right?

We're not trying to
collect it for ourselves.

We're trying to collect it on your behalf
and then let go of it, right, put it

into the storage thing of your choice,
into the application of your choice.

And you do what you wanna do.

If you wanna be in a research
study, you release it.

Right?

That's not, we're trying
to get in the middle.

So I think we've banged around the
edges of security and privacy for a

long time, but I think the current push
right now has the right philosophy.

The danger of securing privacy
around healthcare data is, you

gotta be really careful just not
disclosing data that might help you.

You kind of have to trust your
provider to do the right thing.

And we, if we go too far, making
it locked up, that you have to

anatomically every piece of data one
element at a time, I think we are

actually gonna negatively affect care.

Because patients have not been given their
data for so long, they don't quite know

what's important and what's not important.

And so, if you start scaring people that
your data's flying around everywhere, and

then say you have control, the a knee-jerk
reaction could be to not give it to

anybody and you could be doing yourself
serious harm, which actually is a lesson.

The lesson here is get the
data to the patients faster.

We have to get past that episode.

We have to get past that, that
fear bubble as quickly as possible

to get back to the right balance.

And we see in everything,
there's often an overshoot.

I'm, I would not be surprised, if
we give patients all their data and

we give them audit capabilities to
know where it's flying that many

people will shut it down first.

'cause they don't understand
how to control it.

And then we had to bring it back up.

But that's gonna happen.

So you might as well do it now.

'cause doing it later is worse.

And also on the topic of data liquidity as
I think we talked about, there's a number

of different factors in that beyond just
the technology factors that have made

that challenging in healthcare to date,
but w ith the advancement and adoption

and rollout of FHIR by different vendors,
we're seeing some kind of other technology

pieces of that being addressed as well.

So what's your kind of vantage
point on the current state of

FHIR rollout and where that stands
to advance in the coming years?

FHIR has finally taken some leaps forward.

I do think it's interesting.

You mentioned security and privacy, right,
went right to FHIR because I think they're

actually very linked in a way that isn't
always obvious to the average consumer.

The primary link here is there's
a fair amount of security and

privacy control embedded in HIPAA
and other state and federal laws.

About minimal necessary.

Don't share more than you need to
particularly when you go outside

our provider relationship, right,
so that be to your payer, it could

be to public health and whatever.

And sending a document with all
your data, it makes it difficult to

redact what I'm not supposed to send.

Imagine you're getting a mortgage.

And the bank requires to know
your current salary and they wanna

know it from your gross income
from last year's, uh, tax return.

Sending your 110 page tax return to
get line one is a little silly, right?

That's a way over disclosure of
a lot of things about you when

they only needed one number.

And today most exchange is
being done via documents.

These large things with a
whole bunch of data in them.

It makes it much more difficult
to assert this is the minimal

necessary for the purpose.

And I think that is a huge
advantage of FHIR there.

There are public health departments
out there that are on the sidelines.

During COVID.

During COVID, we allowed public health
departments over Carequality and

therefore over CommonWell as well to
access data about COVID patients that

they were following up with through
the networks using the treatment lane.

And I say the treatment lane.

'cause the treatment lane, the
treatment use case is the most

open public health, not as open.

So they said, just go through
the treatment lane, we

know it's you, it's cool.

And they said, what about
the minimal necessary?

I said, you tell us this data is minimal
necessary for this, and we're good.

Only two states figured out how
to talk to their AGs to figure out

they're allowed to make that request.

Right?

That minimal necessary for this use
case was everything and will only keep.

They didn't know what to do.

So we need the ability to be more
atomic or more focused on the data

we exchange 'cause everybody's
actually trying to do a pretty good

job on the security and privacy.

It's just hard to do when you have a blunt
force instrument of a massive document.

So I think FHIR goes a long way there.

It also allows for more current
information, 'cause a lot of

documents are created at the end
of exams, at the end of encounters.

There's a ton of advantages.

I will say though I am not... FHIR is the
panacea solution for interoperability.

It solves some problems and it helps
with some things, but we still have

a lot of our things to work on,
including just laying the tracks and the

philosophical change from holding data to
exposing data as the right thing to do.

We've talked a lot about the kind of
current advancements in interoperability

and the progress that's being made that
advances a number of different use cases.

Here at Newfire, we obviously serve a
lot of different innovators, including

those in the digital health space
vendors that just sell to health

systems and payers and things like that.

So, what's in this broad world of interop?

Like one mistake that you see
organizations make most commonly when

they approach data exchange that really
ends up hurting them in the long run?

Waiting.

I think waiting is the
worst thing you can do.

There's this desire to say I'll jump in
when X. And for a while it was jumping

in when there was enough data, right?

If you went back when I first started
doing this, going back to 2009, 2010,

the adoption of interoperability and
connecting provider-provider was pretty

low to the point that if a provider
pressed the button, the likelihood they

found data for the patient in front
of 'em was actually relatively low.

Now the problem is flipped.

There's too much data, right?

So all these documents are flying
around and they do have a fair amount

of duplication right within them.

So it is sometime difficult to work with.

But waiting for technology to make
that better, for example, waiting

for FHIR, like I got news for you,
the documents we sent around today

are pretty well coded, right?

They're just, we were lazy.

There's a lot of industries that do this.

They bandaided knowing that the other
side may not have a good parser.

We made a human readable format version
of it, and that's with all display on the

screen you get a discharge summary, which
has a human readable displayed version.

Underneath that human readable thing
is a machine readable version that

has lab results and times, and all
the stuff you would need to do like a

lab chart showing how things changed
over time, both inpatient and then

before inpatient and after, you can
show the differences in between.

But we've seen people now look
and go, there's too much data.

Everybody's gotta organize it
better or I'm not coming in.

And what I've seen decade over decade,
'cause I actually say that now I've

been doing this for a long time, is
those who wait I wouldn't say they

get hurt, but they lose advantage.

And negative advantage is the
same thing as getting hurt

when the market moves fast.

So I would say get connected and then
start finding tools for the specific

things that you're looking for.

It's not like a sea-change
moment when you into interop.

It's a incremental movement that
leads to other incremental movement

movements that leads to general success.

And on that topic uh, what are,
what's a capability or tool in

the interop space that you feel is
most underutilized or overlooked by

folks looking to do data exchange?

There are two things that that are, that
apply there and I'm a little surprised

'cause they seem almost obvious.

And I'll be honest a fair amount
of entities have recognized

this and are starting to fix it.

But the data is large.

The data sets are not tiny.

They do take time to move.

The movement of my data from one
provider or a collection provider

to another is generally not a
good thing to do interactively.

Interactively, meaning I click
the button and I see it come up.

It takes a little bit of time.

I'm amazed at how many EHRs that I
consider relatively mature, don't have

a pre-access workflow, you know, like
a, a prefetch that is based on triggers.

Most healthcare and a lot of people
think about healthcare as having,

different types of encounters,

you have a thing, your ambulatory,
your wellness exam every year, you have

specialty stuff, you have inpatient that's
scheduled, then you have things that go

through the emergency department alike.

We often focus in interop, or at least in
the beginning, we focused on the ED stuff.

I don't know anything about this patient

so I'll hit this button to
go find something out about

them before I start a workup.

And that makes perfect sense.

If the person's coming through the
ED, absolutely positively get their

allergies before you start injecting
penicillin or whatever you're gonna do.

That makes perfect sense.

But there's so much information
between episodes and most of the

tolerance for delay amongst most
clinicians is incredibly short.

Three seconds and you're gone.

I'd say a second.

Most people don't like the application.

You have to prefetch stuff.

And then if you prefetch it, based
upon the scheduled exam for tomorrow

or the scheduled exam for next
week, 'cause again, most of it's not

emergent, most is planned a little
bit or at least sometimes a lot.

And from there, pre-chart
some of it do something what,

what do computers do for us?

Computers are programmed that
do things that are monotonous,

that advance our cause.

Make the computer do some work.

Have it pre-chart out medication history
so you can do reconciliation faster

and say These are all duplicated out,

I see four things that
look relatively current.

Hello, Mr. Patient or Miss Patient.

Which one of these are
really currently active?

What'd you take today?

And I see four things that are candidates.

As opposed to, tell me everything
that you wanna tell me about yourself.

Use the data to pre-stage that,
that first interaction so you

can get to the meaty stuff.

I think the great power of interop
and data availability in healthcare is

gonna be allowing for providers to work
to the level of their capabilities.

By having more time to
interact with the patient.

The data and the computer should
help get out of the way, not

in the way if done correctly.

Paul, thanks so much for a thoughtful
and insightful conversation.

Before we close it out today,
what's one last piece of advice that

you'd offer healthtech leaders and
innovators to navigate the sometimes

confusing world of interop and to
drive great outcomes for patients?

Well, first of all the main thing
I have to say, especially if you're

on the startup side, is be prepared
for a longer haul than you'd like.

We think of healthcare going fast.

Healthcare technology does not
change as fast as you think it does.

There are some brilliant engineers I've
met who worked at amazing institutions

that paid them a boatload of money
because they were PhD, computer science,

super geeks that saw healthcare as a
place that needed help and said, I'm

gonna go over there and help this thing.

And what you find out when you
get here is there is bureaucracy

partially for a reason.

It's a science, not just a
technology and science, it's

actually an artful science, right?

It's not, you're not gonna get the same
result from two different providers.

So there's some artistic license involved
here and there's a lot of regulation.

Be prepared with your VC and whatever
money you've got, it's gonna take

a couple years to get traction.

And I'm not saying that doesn't
mean you shouldn't start.

It just means be ready.

I often talk about leadership and how you
should act with your staff and employees

and how you interact with others.

Be fair, but also
understand what's going on.

And healthcare is a it's a
hard industry to crack into.

You need to get that those
first customers, but be patient.

You have to have a good sense for how
long to stay the course before you pivot.

Over pivoting in healthcare
sometimes makes you irrelevant

'cause no one knows what you do.

Paul, thanks again for joining us
and for sharing your perspective.

And to our listeners, I hope you've
gained valuable insights into the ongoing

challenges and promising solutions in
healthcare interoperability, especially

unique opportunities around patient
access and the future of data exchange.

Thanks again for joining
us on Hard Problems, Smart

Solutions, the Newfire Podcast.

Until next time.