b0ad4a3b-725b-479e-bd24-d99a7854f012/51-0
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Emma,
the VP and Chief Digital executive at

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Northwestern Medicine for those who don't
know,

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Northwestern medicine is a health system
headquartered in Chicago, IL,

b0ad4a3b-725b-479e-bd24-d99a7854f012/51-3
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with 2700 inpatient beds and 11,
000 providers across 12 hospitals and

b0ad4a3b-725b-479e-bd24-d99a7854f012/51-4
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other ancillary facilities.

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Danny,
thank you so much for joining us today.

b0ad4a3b-725b-479e-bd24-d99a7854f012/56-0
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Thank you for having me.

b0ad4a3b-725b-479e-bd24-d99a7854f012/92-0
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So today's topic that we're gonna be
discussing is fire as a gateway to Gen.

b0ad4a3b-725b-479e-bd24-d99a7854f012/92-1
00:00:28.923 --> 00:00:31.961
AI.
Now everybody as you know and as everyone

b0ad4a3b-725b-479e-bd24-d99a7854f012/92-2
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who's listening to this knows who's in
healthcare dealing with data.

b0ad4a3b-725b-479e-bd24-d99a7854f012/97-0
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The word is Gen. AI.

b0ad4a3b-725b-479e-bd24-d99a7854f012/110-0
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And that's the marching orders on the tip
of everyone's tongue.

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There's a lot of questions about is this
vaporware.

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How does IT support our mission?

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How does it improve clinical outcomes?

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How do we integrate it into our workflow?

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You know what should we do?

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A lot of organizations are saying we know
we need to do Gen. AI.

b0ad4a3b-725b-479e-bd24-d99a7854f012/156-0
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I, but what's next?

b0ad4a3b-725b-479e-bd24-d99a7854f012/173-0
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So, northwestern, Danny,
you have a story about how you've

b0ad4a3b-725b-479e-bd24-d99a7854f012/173-1
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leveraged fire as a means of getting
there. Would you care to elaborate?

b0ad4a3b-725b-479e-bd24-d99a7854f012/175-0
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Yeah, sure.

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So we've been on kind of our digital
transformation journey for several years

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now,
probably five or six and very early when

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we started to look at how we wanted to
design the platform.

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We landed on a kind of a fire first fire
centric approach for for a couple.

b0ad4a3b-725b-479e-bd24-d99a7854f012/232-0
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Of reasons one is we really thought we
wanted to leverage interoperability

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standards to,
to organize and normalize the data.

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There are a lot of of of value
propositions to us for that,

b0ad4a3b-725b-479e-bd24-d99a7854f012/272-1
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but really the the main reason was we
really saw kind of the future for

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healthcare data was going to be about
real time intelligence and and as the

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advent of Gen. AI Gen. AI has come.

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Up that that that of course is going to
be very important,

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being able to make inferences within
workflow based on real time data I think

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is going to be the differentiator whether
Gen. AI,

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particularly in the clinical setting.

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Will work and we'll have adoption.

b0ad4a3b-725b-479e-bd24-d99a7854f012/351-0
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Because we've seen kind of a traditional
ML prior to kind of the advent of Gen.

b0ad4a3b-725b-479e-bd24-d99a7854f012/351-1
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AI that the modeling itself isn't really
the hard part,

b0ad4a3b-725b-479e-bd24-d99a7854f012/351-2
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it's getting the data right and it's
integrating into workflow.

b0ad4a3b-725b-479e-bd24-d99a7854f012/363-0
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And so I think the same is true about Gen.
AI,

b0ad4a3b-725b-479e-bd24-d99a7854f012/363-1
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and we think fire can be an enabler to to
to support that.

b0ad4a3b-725b-479e-bd24-d99a7854f012/385-0
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So talking about workflows,
I'd like to dive into a concrete workflow

b0ad4a3b-725b-479e-bd24-d99a7854f012/385-1
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that's in use at Northwestern.

b0ad4a3b-725b-479e-bd24-d99a7854f012/404-0
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I believe you're building a cancer
registry and a fire standards are being

b0ad4a3b-725b-479e-bd24-d99a7854f012/404-1
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leveraged to enhance that functionality.

b0ad4a3b-725b-479e-bd24-d99a7854f012/417-0
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Would you care to talk about how fire
particulars being used to for the cancer

b0ad4a3b-725b-479e-bd24-d99a7854f012/417-1
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registry?

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And then also, if there's any Gen.
AI component?

b0ad4a3b-725b-479e-bd24-d99a7854f012/450-0
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Yeah.
So I think one of the first use cases

b0ad4a3b-725b-479e-bd24-d99a7854f012/450-1
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where we had a third party ready willing
and wanted to partner with us on

b0ad4a3b-725b-479e-bd24-d99a7854f012/450-2
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leveraging fire was for our cancer.

b0ad4a3b-725b-479e-bd24-d99a7854f012/459-0
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So we're a nationally certified Cancer
Center and it's part of that.

b0ad4a3b-725b-479e-bd24-d99a7854f012/491-0
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We have to submit data to certified
cancer registries that eventually go to a

b0ad4a3b-725b-479e-bd24-d99a7854f012/491-1
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centralized body,
and as we were looking for a new vendor

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several years ago,
one of our first questions as we would

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talk with.

b0ad4a3b-725b-479e-bd24-d99a7854f012/498-0
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Third parties was, you know,
can you use fire?

b0ad4a3b-725b-479e-bd24-d99a7854f012/506-0
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We were starting to push our third
parties to think about fire integration.

b0ad4a3b-725b-479e-bd24-d99a7854f012/544-0
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As kind of a first step versus you know
HL 7 or batch files and the vendor we end

b0ad4a3b-725b-479e-bd24-d99a7854f012/544-1
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up going with was was very open and
wanted to because they saw the the

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opportunity as well that if they could
figure this out,

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it makes integrations a lot easier.

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For the future.
So that was our first real test at kind

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of really using fire at scale.

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So we do have a fire server that's set up.

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It's leveraging the EHR.

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It's kind of the back end for the for the
fire resources.

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The vendor makes API calls to get at the
patients that they.

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Need for the registry and it produces lab
results, medications, notes, et cetera.

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And the Gen.
AI component of that is because they're

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able to get the notes with API calls.
They're able to apply LLM models and try

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to extract data elements kind of
automatically.

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That might be embedded in those notes.

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Things like pathology notes,
which are are really rich source of

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information for cancer registries,
and that's been a great productivity boon

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for for the organization and for the
abstractors that do that work.

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And again proves the the value
proposition.

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Now,
it's not really kind of the real time

b0ad4a3b-725b-479e-bd24-d99a7854f012/698-1
00:04:13.033 --> 00:04:16.968
inference use case that we have in mind,
but it was a great use case to kind of

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dip our toe in the water.

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And again,
really make it work for the third party

b0ad4a3b-725b-479e-bd24-d99a7854f012/716-1
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because again, that's,
that is what fire is meant is for data

b0ad4a3b-725b-479e-bd24-d99a7854f012/716-2
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exchange and and that was a successful
use case.

b0ad4a3b-725b-479e-bd24-d99a7854f012/727-0
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So I appreciate you diving into that.

b0ad4a3b-725b-479e-bd24-d99a7854f012/755-0
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Some of our listeners are kind of on the
front end of the journey that you just

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described and they have business owners
of various service lines at their

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healthcare delivery organization that are
saying, OK, what?

b0ad4a3b-725b-479e-bd24-d99a7854f012/760-0
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Please tell me how would I capture the
ROI.

b0ad4a3b-725b-479e-bd24-d99a7854f012/779-0
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What is the value proposition? You know,
why would I invest in this third party to

b0ad4a3b-725b-479e-bd24-d99a7854f012/779-1
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build this fire server when we don't know?

b0ad4a3b-725b-479e-bd24-d99a7854f012/790-0
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That this will actually work and maybe it
works at Northwestern Medicine but not at

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00:04:54.248 --> 00:04:54.408
all.

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Our organization, cuz we're unique,
special and different.

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So and I believe you even mentioned that
sometimes third parties will claim to be

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able to be fire native.
But then once you sign the contracts kind

b0ad4a3b-725b-479e-bd24-d99a7854f012/838-3
00:05:09.198 --> 00:05:13.998
of promises may fall by the wayside when
you try to rubber hits the.

b0ad4a3b-725b-479e-bd24-d99a7854f012/856-0
00:05:13.998 --> 00:05:16.946
Road.
So how do our listeners who have not yet

b0ad4a3b-725b-479e-bd24-d99a7854f012/856-1
00:05:16.946 --> 00:05:20.521
gone upon a journey,
begun a journey that you've already

b0ad4a3b-725b-479e-bd24-d99a7854f012/856-2
00:05:20.521 --> 00:05:21.838
started? How do they?

b0ad4a3b-725b-479e-bd24-d99a7854f012/860-0
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Approach business leaders.

b0ad4a3b-725b-479e-bd24-d99a7854f012/870-0
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In a way, is saying just trust me,
there will be ROI.

b0ad4a3b-725b-479e-bd24-d99a7854f012/876-0
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How do you have that conversation?

b0ad4a3b-725b-479e-bd24-d99a7854f012/878-0
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Yeah, it's a good question.

b0ad4a3b-725b-479e-bd24-d99a7854f012/912-0
00:05:31.038 --> 00:05:35.911
And you bring up some great points and I
think the maturity of the ecosystem and

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00:05:35.911 --> 00:05:39.220
and vendors and third parties with fire
has been slow.

b0ad4a3b-725b-479e-bd24-d99a7854f012/912-2
00:05:39.220 --> 00:05:43.972
And I would say five years ago when we
talked to vendors, most were not ready.

b0ad4a3b-725b-479e-bd24-d99a7854f012/912-3
00:05:43.972 --> 00:05:46.198
I would say these days like you said.

b0ad4a3b-725b-479e-bd24-d99a7854f012/923-0
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Most of these claim to be aware and and
ready and want to try it.

b0ad4a3b-725b-479e-bd24-d99a7854f012/929-0
00:05:49.878 --> 00:05:51.478
But there are some that still struggle.

b0ad4a3b-725b-479e-bd24-d99a7854f012/950-0
00:05:51.718 --> 00:05:55.740
I think the ROI is a couple of things.
So so one is from a from a pure kind of

b0ad4a3b-725b-479e-bd24-d99a7854f012/950-1
00:05:55.740 --> 00:05:56.198
hard ROI.

b0ad4a3b-725b-479e-bd24-d99a7854f012/958-0
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So we we think there's a hard oi for for
our res.

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This is our technical resources in the
sense of today.

b0ad4a3b-725b-479e-bd24-d99a7854f012/990-1
00:06:02.834 --> 00:06:05.515
If we need to do an integration with a
third party,

b0ad4a3b-725b-479e-bd24-d99a7854f012/990-2
00:06:05.515 --> 00:06:09.382
we either have to write our own HL 7
interfaces or have to produce our own

b0ad4a3b-725b-479e-bd24-d99a7854f012/990-3
00:06:09.382 --> 00:06:13.198
batch extracts and that takes resources
from our internal is teams to to.

b0ad4a3b-725b-479e-bd24-d99a7854f012/1001-0
00:06:13.198 --> 00:06:18.118
Build out those feeds. In theory,
you know using fire and APIs.

b0ad4a3b-725b-479e-bd24-d99a7854f012/1013-0
00:06:18.118 --> 00:06:21.718
Kind of puts the onus on the the effort
on the 3rd part, right?

b0ad4a3b-725b-479e-bd24-d99a7854f012/1028-0
00:06:21.718 --> 00:06:25.115
That's why we're using the standard.
They can look up the specs that the the

b0ad4a3b-725b-479e-bd24-d99a7854f012/1028-1
00:06:25.115 --> 00:06:26.438
standards bodies have defined.

b0ad4a3b-725b-479e-bd24-d99a7854f012/1035-0
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They can make the API calls assuming all
the security permissions.

b0ad4a3b-725b-479e-bd24-d99a7854f012/1073-0
00:06:30.118 --> 00:06:33.792
Properly set.
I think that's another value proposition

b0ad4a3b-725b-479e-bd24-d99a7854f012/1073-1
00:06:33.792 --> 00:06:39.203
for business leaders is we believe in a
modern API ecosystem is is just gonna be

b0ad4a3b-725b-479e-bd24-d99a7854f012/1073-2
00:06:39.203 --> 00:06:44.614
much better from a security perspective,
from an auditing perspective provides a

b0ad4a3b-725b-479e-bd24-d99a7854f012/1073-3
00:06:44.614 --> 00:06:49.958
lot of tools and opportunities to just
again make sure that we're securing and.

b0ad4a3b-725b-479e-bd24-d99a7854f012/1092-0
00:06:49.958 --> 00:06:53.761
Protecting the data with as as modern of
technologies as possible and so I think

b0ad4a3b-725b-479e-bd24-d99a7854f012/1092-1
00:06:53.761 --> 00:06:56.438
those are the the two main like hard
value propositions.

b0ad4a3b-725b-479e-bd24-d99a7854f012/1098-0
00:06:56.758 --> 00:06:59.118
I think there's another value proposition
that's a bit more.

b0ad4a3b-725b-479e-bd24-d99a7854f012/1100-0
00:07:00.078 --> 00:07:00.358
Maybe.

b0ad4a3b-725b-479e-bd24-d99a7854f012/1138-0
00:07:01.968 --> 00:07:06.217
Altruistic or public health standpoint is
we just really believe that if fire

b0ad4a3b-725b-479e-bd24-d99a7854f012/1138-1
00:07:06.217 --> 00:07:09.759
adoption continues to grow,
there's a lot of value from a public

b0ad4a3b-725b-479e-bd24-d99a7854f012/1138-2
00:07:09.759 --> 00:07:12.810
health standpoint.
You know we thought about during the

b0ad4a3b-725b-479e-bd24-d99a7854f012/1138-3
00:07:12.810 --> 00:07:17.005
pandemic. If if if fire was mature,
that'd be very easy to actually know the

b0ad4a3b-725b-479e-bd24-d99a7854f012/1138-4
00:07:17.005 --> 00:07:17.168
EV.

b0ad4a3b-725b-479e-bd24-d99a7854f012/1166-0
00:07:17.168 --> 00:07:20.857
The incidence of COVID at any given
moment just by making API calls to all

b0ad4a3b-725b-479e-bd24-d99a7854f012/1166-1
00:07:20.857 --> 00:07:23.464
the hospitals,
and so I think preparing for the next

b0ad4a3b-725b-479e-bd24-d99a7854f012/1166-2
00:07:23.464 --> 00:07:27.448
wave of public health emergencies or how
we want to deal with measuring quality.

b0ad4a3b-725b-479e-bd24-d99a7854f012/1168-0
00:07:28.328 --> 00:07:28.728
Institutions.

b0ad4a3b-725b-479e-bd24-d99a7854f012/1198-0
00:07:29.158 --> 00:07:33.007
Kind of embracing entropy style new
standards is valuable for the broader

b0ad4a3b-725b-479e-bd24-d99a7854f012/1198-1
00:07:33.007 --> 00:07:35.660
ecosystem.
It's valuable to us to try to get ahead

b0ad4a3b-725b-479e-bd24-d99a7854f012/1198-2
00:07:35.660 --> 00:07:40.029
of it so that we're not kind of caught at
the at the too late in the game trying to

b0ad4a3b-725b-479e-bd24-d99a7854f012/1198-3
00:07:40.029 --> 00:07:41.798
catch up and and get our data and.

b0ad4a3b-725b-479e-bd24-d99a7854f012/1205-0
00:07:41.798 --> 00:07:45.238
Our infrastructure set up to to meet
those demands.

b0ad4a3b-725b-479e-bd24-d99a7854f012/1254-0
00:07:45.988 --> 00:07:51.801
So you mentioned three kinds of of ROI 2
hard ROI in terms of reducing the burden

b0ad4a3b-725b-479e-bd24-d99a7854f012/1254-1
00:07:51.801 --> 00:07:57.331
on your internal technical resources
because third parties will be be able to

b0ad4a3b-725b-479e-bd24-d99a7854f012/1254-2
00:07:57.331 --> 00:08:03.145
make their own API calls and you have a
better a modern API ecosystems better for

b0ad4a3b-725b-479e-bd24-d99a7854f012/1254-3
00:08:03.145 --> 00:08:04.988
security and auditing you.

b0ad4a3b-725b-479e-bd24-d99a7854f012/1265-0
00:08:04.988 --> 00:08:08.988
Mentioned the public health altruistics
kind of component as well.

b0ad4a3b-725b-479e-bd24-d99a7854f012/1282-0
00:08:09.788 --> 00:08:13.581
I'd like to focus on the second one.
Security, last year in 2024,

b0ad4a3b-725b-479e-bd24-d99a7854f012/1282-1
00:08:13.581 --> 00:08:15.708
there were a number of data breaches.

b0ad4a3b-725b-479e-bd24-d99a7854f012/1291-0
00:08:15.878 --> 00:08:17.798
Most notably, change healthcare.

b0ad4a3b-725b-479e-bd24-d99a7854f012/1321-0
00:08:18.118 --> 00:08:22.278
This really impacted cash flow at a lot
of organizations,

b0ad4a3b-725b-479e-bd24-d99a7854f012/1321-1
00:08:22.278 --> 00:08:27.872
turning thin margins of 1 to 2% in the
black to really being operating in the

b0ad4a3b-725b-479e-bd24-d99a7854f012/1321-2
00:08:27.872 --> 00:08:32.318
red, not being able to pay contractors,
even staffing issues.

b0ad4a3b-725b-479e-bd24-d99a7854f012/1337-0
00:08:33.888 --> 00:08:40.138
A lot of difficulties facing healthcare
because of of payment issues which came

b0ad4a3b-725b-479e-bd24-d99a7854f012/1337-1
00:08:40.138 --> 00:08:42.248
back to security last year.

b0ad4a3b-725b-479e-bd24-d99a7854f012/1339-0
00:08:42.488 --> 00:08:44.688
So how does?

b0ad4a3b-725b-479e-bd24-d99a7854f012/1346-0
00:08:46.408 --> 00:08:47.928
Fire and API specific.

b0ad4a3b-725b-479e-bd24-d99a7854f012/1374-0
00:08:49.638 --> 00:08:55.747
Assist health care delivery organizations
with doing user roles and security and

b0ad4a3b-725b-479e-bd24-d99a7854f012/1374-1
00:08:55.747 --> 00:08:59.820
provisioning.
How will investing in fire be something

b0ad4a3b-725b-479e-bd24-d99a7854f012/1374-2
00:08:59.820 --> 00:09:02.158
that a Seeso would love to see?

b0ad4a3b-725b-479e-bd24-d99a7854f012/1422-0
00:09:02.878 --> 00:09:06.863
Yeah. I mean, I think RC,
so and I think most Cso's will appreciate

b0ad4a3b-725b-479e-bd24-d99a7854f012/1422-1
00:09:06.863 --> 00:09:10.203
that the the tools,
the tool belt that comes around with

b0ad4a3b-725b-479e-bd24-d99a7854f012/1422-2
00:09:10.203 --> 00:09:15.184
leveraging APIs, the encryption standards,
the tokenization's, the user permissions,

b0ad4a3b-725b-479e-bd24-d99a7854f012/1422-3
00:09:15.184 --> 00:09:18.758
all of that is is much easier to manage
and more, more easy.

b0ad4a3b-725b-479e-bd24-d99a7854f012/1455-0
00:09:18.758 --> 00:09:23.362
To keep a centralized and monitor what's
happening with all of those integrations

b0ad4a3b-725b-479e-bd24-d99a7854f012/1455-1
00:09:23.362 --> 00:09:26.113
through APIs,
through other integration methods,

b0ad4a3b-725b-479e-bd24-d99a7854f012/1455-2
00:09:26.113 --> 00:09:30.549
particularly batch file transmission,
SFTP file transmissions of of large sets

b0ad4a3b-725b-479e-bd24-d99a7854f012/1455-3
00:09:30.549 --> 00:09:30.998
of data.

b0ad4a3b-725b-479e-bd24-d99a7854f012/1462-0
00:09:31.798 --> 00:09:33.558
Lots of opportunity for risk, right?

b0ad4a3b-725b-479e-bd24-d99a7854f012/1468-0
00:09:33.558 --> 00:09:35.998
Who knows where that file is landing at
the third party?

b0ad4a3b-725b-479e-bd24-d99a7854f012/1500-0
00:09:35.998 --> 00:09:39.355
Who knows what the security permissions
are on those files, you know?

b0ad4a3b-725b-479e-bd24-d99a7854f012/1500-1
00:09:39.355 --> 00:09:41.993
And it really just kind of don't have the
the control,

b0ad4a3b-725b-479e-bd24-d99a7854f012/1500-2
00:09:41.993 --> 00:09:45.398
you're kind of trusting either third
party is going to be responsible.

b0ad4a3b-725b-479e-bd24-d99a7854f012/1514-0
00:09:45.398 --> 00:09:48.610
That's what contractual agreements are
meant to to do in HIPAA,

b0ad4a3b-725b-479e-bd24-d99a7854f012/1514-1
00:09:48.610 --> 00:09:50.718
certificationship certification, etcetera.

b0ad4a3b-725b-479e-bd24-d99a7854f012/1531-0
00:09:50.718 --> 00:09:55.416
But I think that's what's led to a lot of
the breaches is kind of some some lax

b0ad4a3b-725b-479e-bd24-d99a7854f012/1531-1
00:09:55.416 --> 00:09:58.118
security practices.
And I think APIs kind of.

b0ad4a3b-725b-479e-bd24-d99a7854f012/1539-0
00:09:58.968 --> 00:10:01.048
Minimize the risk because instead of
start sending.

b0ad4a3b-725b-479e-bd24-d99a7854f012/1545-0
00:10:01.598 --> 00:10:02.958
Huge batches of data.

b0ad4a3b-725b-479e-bd24-d99a7854f012/1582-0
00:10:03.468 --> 00:10:07.512
We're sending individual transactions for
the API calls and again really tight

b0ad4a3b-725b-479e-bd24-d99a7854f012/1582-1
00:10:07.512 --> 00:10:10.839
monitoring. Really good encryption,
really good security tokens,

b0ad4a3b-725b-479e-bd24-d99a7854f012/1582-2
00:10:10.839 --> 00:10:13.143
and so I think from a technology
standpoint,

b0ad4a3b-725b-479e-bd24-d99a7854f012/1582-3
00:10:13.143 --> 00:10:17.033
the just the API is a much more modern
system for transmitting data and and

b0ad4a3b-725b-479e-bd24-d99a7854f012/1582-4
00:10:17.033 --> 00:10:19.388
brings with it those additional security
bar.

b0ad4a3b-725b-479e-bd24-d99a7854f012/1594-0
00:10:20.358 --> 00:10:22.838
I appreciate you delving into that, Danny.

b0ad4a3b-725b-479e-bd24-d99a7854f012/1609-0
00:10:22.838 --> 00:10:31.373
Security is an issue front and center on
many kind of CI OS stack leaders across

b0ad4a3b-725b-479e-bd24-d99a7854f012/1609-1
00:10:31.373 --> 00:10:32.638
the country.

b0ad4a3b-725b-479e-bd24-d99a7854f012/1617-0
00:10:33.038 --> 00:10:36.198
But they're also thinking about cloud.

b0ad4a3b-725b-479e-bd24-d99a7854f012/1638-0
00:10:36.198 --> 00:10:40.534
Cloud is another priority that many
organizations are shifting when they say,

b0ad4a3b-725b-479e-bd24-d99a7854f012/1638-1
00:10:40.534 --> 00:10:43.035
look,
I want to focus more on the healthcare

b0ad4a3b-725b-479e-bd24-d99a7854f012/1638-2
00:10:43.035 --> 00:10:44.758
business, the delivery of care.

b0ad4a3b-725b-479e-bd24-d99a7854f012/1642-0
00:10:44.758 --> 00:10:45.918
I want to get out of.

b0ad4a3b-725b-479e-bd24-d99a7854f012/1650-0
00:10:46.718 --> 00:10:48.878
Kind of. The data center management piece.

b0ad4a3b-725b-479e-bd24-d99a7854f012/1688-0
00:10:49.508 --> 00:10:52.916
Which, you know, disaster recovery,
high availability.

b0ad4a3b-725b-479e-bd24-d99a7854f012/1688-1
00:10:52.916 --> 00:10:57.750
I think a lot of what they're looking to
shift if moving to a cloud would be,

b0ad4a3b-725b-479e-bd24-d99a7854f012/1688-2
00:10:57.750 --> 00:11:01.468
I wouldn't wanna focus on security of
data centers anymore.

b0ad4a3b-725b-479e-bd24-d99a7854f012/1687-0
00:11:01.798 --> 00:11:01.958
Yep.

b0ad4a3b-725b-479e-bd24-d99a7854f012/1715-0
00:11:04.038 --> 00:11:08.830
So I believe that northwestern medicine
is made an investment in fire for cloud

b0ad4a3b-725b-479e-bd24-d99a7854f012/1715-1
00:11:08.830 --> 00:11:12.243
migrations and rebuilding the enterprise
data warehouse.

b0ad4a3b-725b-479e-bd24-d99a7854f012/1715-2
00:11:12.243 --> 00:11:15.358
Previously having had an on Prem custom
data model.

b0ad4a3b-725b-479e-bd24-d99a7854f012/1722-0
00:11:15.478 --> 00:11:18.638
Would you speak about fires role in your?

b0ad4a3b-725b-479e-bd24-d99a7854f012/1730-0
00:11:19.068 --> 00:11:20.908
For cloud transformation journey.

b0ad4a3b-725b-479e-bd24-d99a7854f012/1754-0
00:11:21.208 --> 00:11:24.297
Yeah.
So we have chosen a public cloud provider

b0ad4a3b-725b-479e-bd24-d99a7854f012/1754-1
00:11:24.297 --> 00:11:29.058
as as kind of our cloud and we are.
Our goal is to move not just the data

b0ad4a3b-725b-479e-bd24-d99a7854f012/1754-2
00:11:29.058 --> 00:11:31.568
warehouse, but a full digital platform.

b0ad4a3b-725b-479e-bd24-d99a7854f012/1780-0
00:11:31.568 --> 00:11:35.518
Our goal is to allow that platform to
enable analytics as we did with the data

b0ad4a3b-725b-479e-bd24-d99a7854f012/1780-1
00:11:35.518 --> 00:11:38.118
warehouse,
but also custom application development,

b0ad4a3b-725b-479e-bd24-d99a7854f012/1780-2
00:11:38.118 --> 00:11:40.968
so custom apps and software and AI and
machine learning.

b0ad4a3b-725b-479e-bd24-d99a7854f012/1799-0
00:11:40.968 --> 00:11:45.390
Those are the three main goals we're
trying to enable with the platform and

b0ad4a3b-725b-479e-bd24-d99a7854f012/1799-1
00:11:45.390 --> 00:11:49.288
the benefits of the cloud is one is we
need to be able to do data.

b0ad4a3b-725b-479e-bd24-d99a7854f012/1802-0
00:11:50.038 --> 00:11:50.678
And ml at scale.

b0ad4a3b-725b-479e-bd24-d99a7854f012/1832-0
00:11:51.108 --> 00:11:54.481
And particularly with fire,
that's that's been the challenge.

b0ad4a3b-725b-479e-bd24-d99a7854f012/1832-1
00:11:54.481 --> 00:11:58.181
If the adoption of fire goes where we
think it could and should go,

b0ad4a3b-725b-479e-bd24-d99a7854f012/1832-2
00:11:58.181 --> 00:12:01.554
it's very likely that we could bring down
our production, eh,

b0ad4a3b-725b-479e-bd24-d99a7854f012/1832-3
00:12:01.554 --> 00:12:03.948
Rs by making the amount of API calls to
it.

b0ad4a3b-725b-479e-bd24-d99a7854f012/1867-0
00:12:04.388 --> 00:12:07.421
So our intent is to actually build the
fire server,

b0ad4a3b-725b-479e-bd24-d99a7854f012/1867-1
00:12:07.421 --> 00:12:12.088
the Enterprise fire server in the cloud,
leverage the advantages of scalability

b0ad4a3b-725b-479e-bd24-d99a7854f012/1867-2
00:12:12.088 --> 00:12:16.755
and kind of cheap storage in the cloud to
to do that and make the API calls hit

b0ad4a3b-725b-479e-bd24-d99a7854f012/1867-3
00:12:16.755 --> 00:12:19.788
that infrastructure rather than our
production DHR.

b0ad4a3b-725b-479e-bd24-d99a7854f012/1884-0
00:12:20.668 --> 00:12:23.789
And so with that,
that also comes as you mentioned much

b0ad4a3b-725b-479e-bd24-d99a7854f012/1884-1
00:12:23.789 --> 00:12:25.628
better increased security, right?

b0ad4a3b-725b-479e-bd24-d99a7854f012/1895-0
00:12:25.628 --> 00:12:28.908
The the public cloud providers
investments in security.

b0ad4a3b-725b-479e-bd24-d99a7854f012/1914-0
00:12:28.908 --> 00:12:33.353
Both physical technology,
both people is is exponentially hundreds

b0ad4a3b-725b-479e-bd24-d99a7854f012/1914-1
00:12:33.353 --> 00:12:37.068
of 1000 times more than we could ever
spend on on that.

b0ad4a3b-725b-479e-bd24-d99a7854f012/1929-0
00:12:37.068 --> 00:12:39.901
And so yeah, you know,
it's still we're putting trust and risk

b0ad4a3b-725b-479e-bd24-d99a7854f012/1929-1
00:12:39.901 --> 00:12:43.228
in a third party to manage our data and
make sure that they keep it safe.

b0ad4a3b-725b-479e-bd24-d99a7854f012/1940-0
00:12:43.228 --> 00:12:45.146
But I think with the amount of
investments,

b0ad4a3b-725b-479e-bd24-d99a7854f012/1940-1
00:12:45.146 --> 00:12:47.588
places like Microsoft and Google and
Amazon are making.

b0ad4a3b-725b-479e-bd24-d99a7854f012/1943-0
00:12:48.358 --> 00:12:48.678
In security.

b0ad4a3b-725b-479e-bd24-d99a7854f012/1968-0
00:12:49.628 --> 00:12:54.175
It's it's the risk is actually less from
from a data security perspective by using

b0ad4a3b-725b-479e-bd24-d99a7854f012/1968-1
00:12:54.175 --> 00:12:58.119
the cloud and that's that's the
assumptions we've made as we've cost it

b0ad4a3b-725b-479e-bd24-d99a7854f012/1968-2
00:12:58.119 --> 00:13:00.748
out and planned out our digital
transformation.

b0ad4a3b-725b-479e-bd24-d99a7854f012/1984-0
00:13:01.398 --> 00:13:05.047
So I think a lot of our listeners now are
saying great,

b0ad4a3b-725b-479e-bd24-d99a7854f012/1984-1
00:13:05.047 --> 00:13:07.198
you know I am on board with fire.

b0ad4a3b-725b-479e-bd24-d99a7854f012/1988-0
00:13:07.238 --> 00:13:09.078
I'm on board with cloud.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2024-0
00:13:09.598 --> 00:13:16.168
I kind of get some of the business logic
behind how I might get some ROI from fire

b0ad4a3b-725b-479e-bd24-d99a7854f012/2024-1
00:13:16.168 --> 00:13:20.125
and cloud,
but I'd like you to tell me more about

b0ad4a3b-725b-479e-bd24-d99a7854f012/2024-2
00:13:20.125 --> 00:13:26.537
the real clinical and business use cases
for ML as enabled with these fire AP is

b0ad4a3b-725b-479e-bd24-d99a7854f012/2024-3
00:13:26.537 --> 00:13:28.278
in the cloud, can you?

b0ad4a3b-725b-479e-bd24-d99a7854f012/2031-0
00:13:28.278 --> 00:13:29.838
Tell us, how are you?

b0ad4a3b-725b-479e-bd24-d99a7854f012/2033-0
00:13:29.838 --> 00:13:31.038
You know, improving quality of.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2044-0
00:13:31.188 --> 00:13:33.548
There.
How are you reducing 30 day readmissions?

b0ad4a3b-725b-479e-bd24-d99a7854f012/2061-0
00:13:33.548 --> 00:13:37.280
How are you addressing your electronic
clinical quality measures and improving

b0ad4a3b-725b-479e-bd24-d99a7854f012/2061-1
00:13:37.280 --> 00:13:39.028
your scores to improve your payments?

b0ad4a3b-725b-479e-bd24-d99a7854f012/2066-0
00:13:39.028 --> 00:13:41.548
Because we're in a value based payment
program.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2071-0
00:13:43.118 --> 00:13:44.438
Can you talk about some examples?

b0ad4a3b-725b-479e-bd24-d99a7854f012/2105-0
00:13:44.998 --> 00:13:47.201
Yeah.
Just first quickly on the last point,

b0ad4a3b-725b-479e-bd24-d99a7854f012/2105-1
00:13:47.201 --> 00:13:50.806
I think that was another reason to
embrace fires as we fully expect the

b0ad4a3b-725b-479e-bd24-d99a7854f012/2105-2
00:13:50.806 --> 00:13:54.611
federal government is headed towards a
world of digital quality measures in

b0ad4a3b-725b-479e-bd24-d99a7854f012/2105-3
00:13:54.611 --> 00:13:58.116
which they make fire API calls and
calculate the measures themselves.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2105-4
00:13:58.116 --> 00:13:59.518
So getting ahead of getting.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2145-0
00:13:59.518 --> 00:14:02.930
Our data ready for that I think gets to
the the points you're making about

b0ad4a3b-725b-479e-bd24-d99a7854f012/2145-1
00:14:02.930 --> 00:14:06.297
ensuring that we have an clear and
accurate medical record to respond and

b0ad4a3b-725b-479e-bd24-d99a7854f012/2145-2
00:14:06.297 --> 00:14:09.891
reflect the quality of care we provide.
But the real kind of clinical use case

b0ad4a3b-725b-479e-bd24-d99a7854f012/2145-3
00:14:09.891 --> 00:14:11.438
that we're embarking on now and I.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2153-0
00:14:11.438 --> 00:14:12.358
Will say this has been a journey.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2155-0
00:14:12.358 --> 00:14:13.798
We're still on the path to build out.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2197-0
00:14:14.108 --> 00:14:18.850
This fire server and and really get it
live and operational with with real time

b0ad4a3b-725b-479e-bd24-d99a7854f012/2197-1
00:14:18.850 --> 00:14:22.170
production data.
But we started planning out a use case

b0ad4a3b-725b-479e-bd24-d99a7854f012/2197-2
00:14:22.170 --> 00:14:26.616
for rebuilding the current ML model
that's been embedded in our EHR for Ed

b0ad4a3b-725b-479e-bd24-d99a7854f012/2197-3
00:14:26.616 --> 00:14:29.758
Triage use case.
So patients come into the emergency

b0ad4a3b-725b-479e-bd24-d99a7854f012/2197-4
00:14:29.758 --> 00:14:30.588
department we.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2238-0
00:14:30.588 --> 00:14:34.937
Want to provide the triage staff a quick
score risk score based on the factors and

b0ad4a3b-725b-479e-bd24-d99a7854f012/2238-1
00:14:34.937 --> 00:14:39.128
of data that are in the EHR at the moment,
including some textual components of

b0ad4a3b-725b-479e-bd24-d99a7854f012/2238-2
00:14:39.128 --> 00:14:41.748
notes from prior visits as well as
documentation.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2241-0
00:14:41.748 --> 00:14:43.228
The nurses might put in at that moment.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2284-0
00:14:43.828 --> 00:14:47.075
And so right now we have a model that's
running on Prem,

b0ad4a3b-725b-479e-bd24-d99a7854f012/2284-1
00:14:47.075 --> 00:14:50.721
but we think there's opportunities to
leverage things like Gen.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2284-2
00:14:50.721 --> 00:14:55.222
AI and LLM and things like the the kind
of modern foundation models that might

b0ad4a3b-725b-479e-bd24-d99a7854f012/2284-3
00:14:55.222 --> 00:14:58.868
exist and be available in the cloud to
kind of improve the ACC.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2292-0
00:14:59.068 --> 00:15:01.348
And the usefulness of that score.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2307-0
00:15:01.428 --> 00:15:04.200
And so that's our that's our first use
case.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2307-1
00:15:04.200 --> 00:15:07.588
We're planning to make inferences using
fire API data.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2322-0
00:15:08.438 --> 00:15:10.995
And we'll train the model in the cloud
based on historical data,

b0ad4a3b-725b-479e-bd24-d99a7854f012/2322-1
00:15:10.995 --> 00:15:13.238
but then run the model and deploy it
again in the cloud.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2344-0
00:15:13.548 --> 00:15:16.996
Outweigh would make the API call get all
the data almost needed,

b0ad4a3b-725b-479e-bd24-d99a7854f012/2344-1
00:15:16.996 --> 00:15:20.868
run an inference and then provide that in
real time to the triage staff.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2377-0
00:15:21.648 --> 00:15:25.792
I wanna circle back kind of almost to an
academic topic for a second.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2377-1
00:15:25.792 --> 00:15:29.995
The third value proposition,
the public health COVID API to figure out

b0ad4a3b-725b-479e-bd24-d99a7854f012/2377-2
00:15:29.995 --> 00:15:33.488
the national incidence.
Not going to help the bottom line.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2382-0
00:15:33.488 --> 00:15:35.848
Northwestern,
but maybe good for the whole country.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2389-0
00:15:36.408 --> 00:15:39.088
That's the thing I'm going to ask my next
question in so.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2393-0
00:15:40.998 --> 00:15:41.198
The.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2396-0
00:15:43.678 --> 00:15:43.878
OK.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2410-0
00:15:43.878 --> 00:15:47.953
So for example,
ChatGPT is owned by open AI and Microsoft

b0ad4a3b-725b-479e-bd24-d99a7854f012/2410-1
00:15:47.953 --> 00:15:49.358
has a stake in that.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2432-0
00:15:49.708 --> 00:15:55.826
And they license out copilot and you can
take the copilot instance on your own

b0ad4a3b-725b-479e-bd24-d99a7854f012/2432-1
00:15:55.826 --> 00:15:56.988
private server.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2457-0
00:15:56.988 --> 00:16:01.327
Keep your Phi private and then train your
own models, for example,

b0ad4a3b-725b-479e-bd24-d99a7854f012/2457-1
00:16:01.327 --> 00:16:05.148
to create this quick risk score in the Ed
at Northwestern.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2469-0
00:16:05.668 --> 00:16:08.577
But then you know,
2500 healthcare organizations may be

b0ad4a3b-725b-479e-bd24-d99a7854f012/2469-1
00:16:08.577 --> 00:16:09.668
doing the same thing.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2476-0
00:16:09.668 --> 00:16:13.988
There seems to be a lot of redundancy of
effort.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2479-0
00:16:14.578 --> 00:16:14.778
Yeah.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2495-0
00:16:14.798 --> 00:16:17.891
Potentially this could be a more
efficient process of everyone that were

b0ad4a3b-725b-479e-bd24-d99a7854f012/2495-1
00:16:17.891 --> 00:16:19.798
to collaborate.
Of course the risk would be.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2514-0
00:16:20.228 --> 00:16:24.699
HIPAA violations with Phi and potentially
data getting out there and not used for

b0ad4a3b-725b-479e-bd24-d99a7854f012/2514-1
00:16:24.699 --> 00:16:27.588
patient care,
but for profitability in some company.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2527-0
00:16:27.828 --> 00:16:30.685
So I'd like to just ask you for kind of a
fun second,

b0ad4a3b-725b-479e-bd24-d99a7854f012/2527-1
00:16:30.685 --> 00:16:32.908
just to depart from our jobs for a moment.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2530-0
00:16:34.478 --> 00:16:35.118
What would?

b0ad4a3b-725b-479e-bd24-d99a7854f012/2566-0
00:16:37.278 --> 00:16:41.683
Be a way of is there any way you can
envision of collaborating with other

b0ad4a3b-725b-479e-bd24-d99a7854f012/2566-1
00:16:41.683 --> 00:16:46.563
healthcare delivery organizations so that
not each organization needs to reinvent

b0ad4a3b-725b-479e-bd24-d99a7854f012/2546-0
00:16:42.388 --> 00:16:42.708
Yeah.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2566-2
00:16:46.563 --> 00:16:49.718
the wheel training essentially copilot on
their own?

b0ad4a3b-725b-479e-bd24-d99a7854f012/2577-0
00:16:50.108 --> 00:16:54.068
Own data to get a use case as applicable
everywhere.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2594-0
00:16:54.228 --> 00:16:57.352
Yeah. I mean,
I think it's the to answer that question

b0ad4a3b-725b-479e-bd24-d99a7854f012/2594-1
00:16:57.352 --> 00:17:01.384
is another proof point for the
investments and kind of the adoption of

b0ad4a3b-725b-479e-bd24-d99a7854f012/2594-2
00:17:01.384 --> 00:17:01.668
fire.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2595-0
00:17:01.668 --> 00:17:02.588
The reason?

b0ad4a3b-725b-479e-bd24-d99a7854f012/2613-0
00:17:02.588 --> 00:17:07.691
The challenges that we have with
collaborating and kind of making models

b0ad4a3b-725b-479e-bd24-d99a7854f012/2613-1
00:17:07.691 --> 00:17:09.788
reusable is is the data right?

b0ad4a3b-725b-479e-bd24-d99a7854f012/2655-0
00:17:09.788 --> 00:17:12.337
Data is not even if you're on the same
same EHR.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2655-1
00:17:12.337 --> 00:17:15.928
One hospital's data is going to look
different than other hospitals,

b0ad4a3b-725b-479e-bd24-d99a7854f012/2655-2
00:17:15.928 --> 00:17:19.570
even on the same same platform,
and so fire as kind of the, you know,

b0ad4a3b-725b-479e-bd24-d99a7854f012/2655-3
00:17:19.570 --> 00:17:23.628
as was intended as an interoperability
standard, should provide kind of that.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2691-0
00:17:23.908 --> 00:17:27.005
That that playground of where we can kind
of look at data the same across

b0ad4a3b-725b-479e-bd24-d99a7854f012/2691-1
00:17:27.005 --> 00:17:30.187
institutions now full transparency,
I don't think we're there today, right.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2691-2
00:17:30.187 --> 00:17:33.493
You still make a fiery pick call one
institution make the same AP call another

b0ad4a3b-725b-479e-bd24-d99a7854f012/2691-3
00:17:33.493 --> 00:17:35.628
one's and you might get slightly
different levels.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2698-0
00:17:35.628 --> 00:17:37.148
Of completeness and things like that.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2723-0
00:17:37.468 --> 00:17:42.246
But if we as an as a help as an industry
further adopted and and move towards that

b0ad4a3b-725b-479e-bd24-d99a7854f012/2723-1
00:17:42.246 --> 00:17:45.182
kind of vision,
then you could see the ability for

b0ad4a3b-725b-479e-bd24-d99a7854f012/2723-2
00:17:45.182 --> 00:17:45.988
collaboration.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2726-0
00:17:45.988 --> 00:17:46.508
Hey, we are.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2735-0
00:17:46.508 --> 00:17:48.068
We all have the same our data in the same
format.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2740-0
00:17:48.068 --> 00:17:50.228
Let's let's bring it together with the
right, you know.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2746-0
00:17:51.038 --> 00:17:53.198
Privacy and security and consent from
patients.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2777-0
00:17:53.548 --> 00:17:57.426
And build the model together or and this
is where I think the cloud providers are

b0ad4a3b-725b-479e-bd24-d99a7854f012/2777-1
00:17:57.426 --> 00:18:00.311
really banking on.
Let's build a marketplace of models where

b0ad4a3b-725b-479e-bd24-d99a7854f012/2777-2
00:18:00.311 --> 00:18:03.148
we may have built a model that works.
It's using fire data.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2794-0
00:18:03.148 --> 00:18:05.199
Hey,
let's make it available in some sort of

b0ad4a3b-725b-479e-bd24-d99a7854f012/2794-1
00:18:05.199 --> 00:18:08.390
marketplace for other organizations to
leverage and deploy into their

b0ad4a3b-725b-479e-bd24-d99a7854f012/2794-2
00:18:08.390 --> 00:18:09.028
organizations.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2799-0
00:18:09.028 --> 00:18:11.028
They don't have to start from scratch
again.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2815-0
00:18:11.028 --> 00:18:14.481
The key there is the data has to look the
same and that's why the embrace of fire

b0ad4a3b-725b-479e-bd24-d99a7854f012/2815-1
00:18:14.481 --> 00:18:15.028
is important.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2852-0
00:18:15.788 --> 00:18:18.582
The marketplace,
actually this comes kind of full circle

b0ad4a3b-725b-479e-bd24-d99a7854f012/2852-1
00:18:18.582 --> 00:18:21.426
to an earlier conversation,
which is earlier part of this

b0ad4a3b-725b-479e-bd24-d99a7854f012/2852-2
00:18:21.426 --> 00:18:24.171
conversation,
which is maybe instead of having a one to

b0ad4a3b-725b-479e-bd24-d99a7854f012/2852-3
00:18:24.171 --> 00:18:26.573
2% margin as a healthcare delivery
organization,

b0ad4a3b-725b-479e-bd24-d99a7854f012/2852-4
00:18:26.573 --> 00:18:30.348
you're getting out of the data center
business, but you're getting into the.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2867-0
00:18:30.348 --> 00:18:33.592
Software development LLM.
Business and you can license out the

b0ad4a3b-725b-479e-bd24-d99a7854f012/2867-1
00:18:33.592 --> 00:18:35.188
model that you create to other.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2890-0
00:18:35.348 --> 00:18:39.410
Organizations to buy and that can
generate a new revenue stream and

b0ad4a3b-725b-479e-bd24-d99a7854f012/2890-1
00:18:39.410 --> 00:18:43.950
therefore demonstrate the profitability
or ROI of investing in fire care to

b0ad4a3b-725b-479e-bd24-d99a7854f012/2890-2
00:18:43.950 --> 00:18:44.428
comment.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2920-0
00:18:44.688 --> 00:18:47.711
Yeah, absolutely.
I think that is an aspiration for a lot

b0ad4a3b-725b-479e-bd24-d99a7854f012/2920-1
00:18:47.711 --> 00:18:52.038
of organizations. You know, to your point,
every every health system is looking to

b0ad4a3b-725b-479e-bd24-d99a7854f012/2920-2
00:18:52.038 --> 00:18:55.895
diversify some revenue streams and
looking at things like innovation as a

b0ad4a3b-725b-479e-bd24-d99a7854f012/2920-3
00:18:55.895 --> 00:18:58.918
place to do that.
And I and absolutely I think I can see.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2934-0
00:18:58.918 --> 00:19:01.567
A world now that again,
this is where I do think fire going to

b0ad4a3b-725b-479e-bd24-d99a7854f012/2934-1
00:19:01.567 --> 00:19:02.408
become so important.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2947-0
00:19:02.408 --> 00:19:07.728
It's really hard to do that if you have
to retrain the data on every organization.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2952-0
00:19:07.728 --> 00:19:08.768
They're not even just retrain.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2955-0
00:19:08.768 --> 00:19:10.168
You actually have to extract the data.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2963-0
00:19:11.198 --> 00:19:13.678
Individually because the data's not
structured the same.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2992-0
00:19:14.068 --> 00:19:16.639
But if we can embrace a standard like
fire,

b0ad4a3b-725b-479e-bd24-d99a7854f012/2992-1
00:19:16.639 --> 00:19:21.432
there's an opportunity to eliminate that
step and kind of allow the scale of kind

b0ad4a3b-725b-479e-bd24-d99a7854f012/2992-2
00:19:21.432 --> 00:19:23.068
of that marketplace to grow.

b0ad4a3b-725b-479e-bd24-d99a7854f012/2994-0
00:19:24.638 --> 00:19:24.918
Quickly.

b0ad4a3b-725b-479e-bd24-d99a7854f012/3016-0
00:19:25.228 --> 00:19:28.796
So I have kind of one doozy of a follow
up question.

b0ad4a3b-725b-479e-bd24-d99a7854f012/3016-1
00:19:28.796 --> 00:19:32.028
As we approach the end of this podcast
episode.

b0ad4a3b-725b-479e-bd24-d99a7854f012/3031-0
00:19:32.468 --> 00:19:37.344
We've covered fire, have covered cloud,
we've covered a wide range of of topics

b0ad4a3b-725b-479e-bd24-d99a7854f012/3031-1
00:19:37.344 --> 00:19:38.868
within those two buckets.

b0ad4a3b-725b-479e-bd24-d99a7854f012/3042-0
00:19:40.438 --> 00:19:42.721
You know,
but everyone knows about GEICO garbage in,

b0ad4a3b-725b-479e-bd24-d99a7854f012/3042-1
00:19:42.721 --> 00:19:43.238
garbage out.

b0ad4a3b-725b-479e-bd24-d99a7854f012/3069-0
00:19:44.958 --> 00:19:49.200
How what measures is northwestern
medicine taking to ensure that your data

b0ad4a3b-725b-479e-bd24-d99a7854f012/3069-1
00:19:49.200 --> 00:19:53.838
is clean, that you have normalized data,
aggregated data, deduplicated data that?

b0ad4a3b-725b-479e-bd24-d99a7854f012/3062-0
00:19:50.318 --> 00:19:50.518
Yeah.

b0ad4a3b-725b-479e-bd24-d99a7854f012/3089-0
00:19:54.148 --> 00:19:58.155
You know as much as these, you know,
embracing these larger models and the

b0ad4a3b-725b-479e-bd24-d99a7854f012/3089-1
00:19:58.155 --> 00:20:00.933
integrations.
They're only as good as the data that

b0ad4a3b-725b-479e-bd24-d99a7854f012/3089-2
00:20:00.933 --> 00:20:01.948
they're trained on.

b0ad4a3b-725b-479e-bd24-d99a7854f012/3096-0
00:20:01.948 --> 00:20:03.868
So how to ensure that you have clean data?

b0ad4a3b-725b-479e-bd24-d99a7854f012/3093-0
00:20:02.268 --> 00:20:02.468
Yeah.

b0ad4a3b-725b-479e-bd24-d99a7854f012/3102-0
00:20:04.508 --> 00:20:06.308
Yeah, it's it's a huge challenge.

b0ad4a3b-725b-479e-bd24-d99a7854f012/3138-0
00:20:06.418 --> 00:20:10.496
Can't pretend that we have the answer,
but we are focusing on data quality as

b0ad4a3b-725b-479e-bd24-d99a7854f012/3138-1
00:20:10.496 --> 00:20:14.836
part of our strategy and kind of building
it upfront as the data lands and the the

b0ad4a3b-725b-479e-bd24-d99a7854f012/3138-2
00:20:14.836 --> 00:20:17.607
data lake,
how do we build the right kind of quality

b0ad4a3b-725b-479e-bd24-d99a7854f012/3138-3
00:20:17.607 --> 00:20:19.698
tests and scripts and compare that data?

b0ad4a3b-725b-479e-bd24-d99a7854f012/3154-0
00:20:21.268 --> 00:20:24.228
To kind of the source of truth data to
make sure we have completeness and

b0ad4a3b-725b-479e-bd24-d99a7854f012/3154-1
00:20:24.228 --> 00:20:24.588
accuracy.

b0ad4a3b-725b-479e-bd24-d99a7854f012/3175-0
00:20:24.588 --> 00:20:29.452
I actually think this could be an
opportunity for llms to really help us.

b0ad4a3b-725b-479e-bd24-d99a7854f012/3175-1
00:20:29.452 --> 00:20:33.988
Is llms have the opportunity to help with
the normalization of data.

b0ad4a3b-725b-479e-bd24-d99a7854f012/3198-0
00:20:34.338 --> 00:20:36.782
Right.
If you look at individual hospitals,

b0ad4a3b-725b-479e-bd24-d99a7854f012/3198-1
00:20:36.782 --> 00:20:40.281
medication data, right,
there's there's thousands of rows just

b0ad4a3b-725b-479e-bd24-d99a7854f012/3198-2
00:20:40.281 --> 00:20:43.058
for this, for one, medication for Tylenol,
right?

b0ad4a3b-725b-479e-bd24-d99a7854f012/3235-0
00:20:43.058 --> 00:20:46.855
Thousands of rolls of different
variations of Tylenol and LLM might be

b0ad4a3b-725b-479e-bd24-d99a7854f012/3235-1
00:20:46.855 --> 00:20:49.636
really useful to say, hey,
I'm looking for Tylenol.

b0ad4a3b-725b-479e-bd24-d99a7854f012/3235-2
00:20:49.636 --> 00:20:52.738
I I'm going to read through all those.
I'm going to pick,

b0ad4a3b-725b-479e-bd24-d99a7854f012/3235-3
00:20:52.738 --> 00:20:56.802
find those thousand rows rather than
having to individually map row to row.

b0ad4a3b-725b-479e-bd24-d99a7854f012/3235-4
00:20:56.802 --> 00:20:57.818
I think that could.

b0ad4a3b-725b-479e-bd24-d99a7854f012/3252-0
00:20:57.858 --> 00:21:00.854
Be a really promising next step for how
LL Ms.

b0ad4a3b-725b-479e-bd24-d99a7854f012/3252-1
00:21:00.854 --> 00:21:03.658
Enable kind of AI at scale on an old
scale.

b0ad4a3b-725b-479e-bd24-d99a7854f012/3267-0
00:21:04.018 --> 00:21:06.997
Something we're starting to explore and
have didn't done it internally,

b0ad4a3b-725b-479e-bd24-d99a7854f012/3267-1
00:21:06.997 --> 00:21:07.618
but we haven't.

b0ad4a3b-725b-479e-bd24-d99a7854f012/3282-0
00:21:08.058 --> 00:21:11.423
Kind of operationalized it yet,
but we're looking forward to kind of

b0ad4a3b-725b-479e-bd24-d99a7854f012/3282-1
00:21:11.423 --> 00:21:13.618
taking that tactic as we as we move
forward.

b0ad4a3b-725b-479e-bd24-d99a7854f012/3289-0
00:21:14.398 --> 00:21:15.438
Thank you, Danny.

b0ad4a3b-725b-479e-bd24-d99a7854f012/3304-0
00:21:15.438 --> 00:21:19.068
I have no more questions for you,
but I'd like to offer you an opportunity

b0ad4a3b-725b-479e-bd24-d99a7854f012/3304-1
00:21:19.068 --> 00:21:20.278
to speak to our audience.

b0ad4a3b-725b-479e-bd24-d99a7854f012/3310-0
00:21:20.438 --> 00:21:23.838
You they've just been listening to this
conversation about using.

b0ad4a3b-725b-479e-bd24-d99a7854f012/3316-0
00:21:25.388 --> 00:21:26.508
Fire as a gateway to Gen.

b0ad4a3b-725b-479e-bd24-d99a7854f012/3319-0
00:21:26.508 --> 00:21:26.588
AI.

b0ad4a3b-725b-479e-bd24-d99a7854f012/3324-0
00:21:26.588 --> 00:21:28.948
Any final words of Wis?

b0ad4a3b-725b-479e-bd24-d99a7854f012/3333-0
00:21:28.948 --> 00:21:32.608
Parting words of wisdom that you'd like
to impart upon your peers across the

b0ad4a3b-725b-479e-bd24-d99a7854f012/3333-1
00:21:32.608 --> 00:21:32.988
country.

b0ad4a3b-725b-479e-bd24-d99a7854f012/3356-0
00:21:33.888 --> 00:21:36.088
Yeah. I mean,
I think the one thing is that

b0ad4a3b-725b-479e-bd24-d99a7854f012/3356-1
00:21:36.088 --> 00:21:39.888
traditionally fire is thought of as a
information exchange standard, right?

b0ad4a3b-725b-479e-bd24-d99a7854f012/3360-0
00:21:40.048 --> 00:21:41.328
And that's what it's built for, right?

b0ad4a3b-725b-479e-bd24-d99a7854f012/3365-0
00:21:41.328 --> 00:21:43.128
API calls to exchange information.

b0ad4a3b-725b-479e-bd24-d99a7854f012/3391-0
00:21:43.568 --> 00:21:47.740
I think growing and we're seeing this
from from big platforms like the cloud

b0ad4a3b-725b-479e-bd24-d99a7854f012/3391-1
00:21:47.740 --> 00:21:50.287
providers,
the idea of fire for a persistence,

b0ad4a3b-725b-479e-bd24-d99a7854f012/3391-2
00:21:50.287 --> 00:21:52.888
how do we also persist the data in a data
lake?

b0ad4a3b-725b-479e-bd24-d99a7854f012/3395-0
00:21:52.888 --> 00:21:54.408
Build an analytics platform.

b0ad4a3b-725b-479e-bd24-d99a7854f012/3407-0
00:21:54.408 --> 00:21:59.008
Build a platform by which we can model
create models off of fire based data.

b0ad4a3b-725b-479e-bd24-d99a7854f012/3416-0
00:21:59.208 --> 00:22:00.488
I think is the growing trend.

b0ad4a3b-725b-479e-bd24-d99a7854f012/3422-0
00:22:00.728 --> 00:22:03.568
So if you aren't, you know,
well versed on fire.

b0ad4a3b-725b-479e-bd24-d99a7854f012/3428-0
00:22:04.018 --> 00:22:04.818
And are interested.

b0ad4a3b-725b-479e-bd24-d99a7854f012/3434-0
00:22:04.818 --> 00:22:07.058
I would definitely take it from both
lenses. Think about it.

b0ad4a3b-725b-479e-bd24-d99a7854f012/3472-0
00:22:07.058 --> 00:22:11.276
How how can fire be useful for to me for
exchanging data with with other

b0ad4a3b-725b-479e-bd24-d99a7854f012/3472-1
00:22:11.276 --> 00:22:15.898
organizations other entities but also how
to use it for kind of as an analytics

b0ad4a3b-725b-479e-bd24-d99a7854f012/3472-2
00:22:15.898 --> 00:22:20.694
data model and and hope that the industry
buys into the vision as we do in that we

b0ad4a3b-725b-479e-bd24-d99a7854f012/3472-3
00:22:20.694 --> 00:22:21.098
see it.

b0ad4a3b-725b-479e-bd24-d99a7854f012/3478-0
00:22:21.098 --> 00:22:22.138
Kind of grow in its adoption.

b0ad4a3b-725b-479e-bd24-d99a7854f012/3487-0
00:22:23.618 --> 00:22:25.098
Thank you, Danny.

b0ad4a3b-725b-479e-bd24-d99a7854f012/3506-0
00:22:25.098 --> 00:22:27.746
That for our listeners has been Danny
Sama,

b0ad4a3b-725b-479e-bd24-d99a7854f012/3506-1
00:22:27.746 --> 00:22:31.418
the VP and Chief Digital executive of
Northwestern Medicine.

b0ad4a3b-725b-479e-bd24-d99a7854f012/3509-0
00:22:31.418 --> 00:22:32.778
Danny, I appreciate your time.

b0ad4a3b-725b-479e-bd24-d99a7854f012/3511-0
00:22:32.778 --> 00:22:33.698
Thank you for joining us.

b0ad4a3b-725b-479e-bd24-d99a7854f012/3515-0
00:22:33.948 --> 00:22:34.828
Thank you for having me.