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Welcome to Healthy Data Podcast.
We are here today with Yair Saperstein,

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the founder and CEO of Avvo,
a Health tech startup and a clinical

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informatics and internal medicine
physician practicing as a per diem

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hospitalist at Mount Sinai Health System.

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Yair, thank you for joining us today.

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Thank you. It's a pleasure to be here.

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For those who don't know,
Mount Sinai Health System is

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headquartered in New York, NY,
in Midtown Manhattan,

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with 2800 beds and 12 hospitals staffed
by 6300 primary providers who see an

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additional one and a half million annual
outpatient visits through Mount Sinai.

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For everyone's information,
Mount Sinai is an epic EHR health system.

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So today we're gonna be talking about
capacity and throughput and leveraging

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technology to improve both. Yair,
I'd like to ask you to start first just

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with a bit of an add.

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Anecdote.
You are a practicing physician at a large

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health system in New York City,
and you encountered a problem that you

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then went on to solve with Evo.
Could you tell us about the genesis of

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this business idea and then you know what
it is?

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But how did you see a problem as a
physician and then what did you do to

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solve it?

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Yeah,
so the story actually starts when I was

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in residency and at the time I really
wanted to be a whole person. You know,

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for me as a practicing doc,
I was pegged as you are a doc and this is

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your whole life, you know?
But I really wanted to be able to have

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dinner with my family.
I wanted to be able to go for a walk.

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Walks. I'm a whole person.
And so I wanted something that would give

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me efficiency to be a whole person.
Simultaneously, though, I'm a doc, right?

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I wanted to be a good clinician.
I wanted to be able to deliver value to

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my patients.
And the best way to do that was with

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quality.
And how can I have efficiency with

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quality? Those kinds of things didn't.

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There were either the quality systems,
like best practice alerts,

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Yeah.

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but there were so many that I I got
overwhelmed, right?

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It's like with all these alerts.
And then on the other side is like the

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efficiency plays,
but the efficiency plays were like, yeah,

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OK.

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we'll do an 80% good enough job.
It's like, no,

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I'm trying to really do as well as I can.

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And so I really wanted the ability to
have those two together as an individual

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clinician, as an individual physician,
you know,

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Fast forward a little bit and I became
chief resident.

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I was involved on the quality side and
you know,

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I started to think more from a system
perspective.

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I actually was an informatics liaison to
be able to help.

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Install the new Epic system as we were
transitioning where I was chief resident

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over to to our Epic system and so really
got more of an overview on the system

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side.
I had also just completed my MPH in

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hospital policy and management, right?
So more of like this.

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Broader holistic looking down umbrella
perspective on from a system side more

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than as an individual physician to
complement that with you know what do we

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need as a system and what would be
important from a system level where it

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was really much more about OK.

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Make sure that our physicians,
our clinicians are happy, obviously,

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right. So if they're burning out,
we got to solve that.

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But we also need from our system side,
the financial ROI to be able to keep us

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afloat, right, keep us going up and up.
And so thinking creatively about these

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different ways of putting those two
together.

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Which actually is a larger macro
perspective of what my micro perspective

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as an individual clinician was.
And from that came out Evo and Evo as a

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tool, right?
Evo as a platform is this melding of the

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two like quality and efficiency and the
way that we do it in a word.

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Is that we have a back end clinical AI
apps builder and so this builder,

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we kind of call it an operating system
for building clinical AI apps is able to

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solve these different problems.
You want to solve physician burnout.

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You have an app for that.
You want to be able to solve your

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throughput and capacity.

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We'll talk about that.
We have an app for that.

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And over this time,
over the last bunch of years, right,

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as I've been interacting with various
other health systems through our progress

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as a company, right,
with my company hat on,

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really have heard from the leading health
systems and the issues that are.

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Being faced, you know,
through all of these systems and heard

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some of the resonance of what people are
facing and what the systems are facing,

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where one of the major things that I've
been hearing about is capacity.

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How do we solve our capacity problems?
How do we improve throughput?

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How do we allow for more patients to get
in by getting more patients out?

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And so thinking about the.

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Aspect of how to solve that from a
broader perspective and the clinical AI

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apps that can help with that is something
that's definitely been on my mind for the

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last for the last bunch of time.

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So here you covered a lot of different
issues right now.

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We're going to drill into one of them,
but let me just recapitulate for our

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listeners.
We talked about quality of care,

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efficiency and delivery of care,
physician satisfaction and burnout and

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capacity and throughput.
I'd like to start with quality of care.

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I understand that there are society
guidelines and best.

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Practices put out by the Association of
whatever American, the AP.

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There are many different associations,
pulmonary, cardiac,

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and they have best practices and you have
content aggregators to summarize the

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guidelines and then integrate them into
the EHR to.

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Tee them up for clinicians to provide
more standard care.

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If that's not accurate,
please just clarify how are you

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addressing quality of care?

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Yeah, so similar dual perspective, right?
So everyone and their friends are all

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using AI scribes,
and if you're not using an AI scribe,

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well, get on the bandwagon already.
The thing is that AI scribes have

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difficulty in integrating quality.

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Into the overall workflow because it's
really contingent on whatever I'm saying.

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So there's no easy way to be able to
guide me into a proper direction.

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The best place to be able to guide is in
the chart summarization piece, right?

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Before I see a patient,
I normally do chart review and when I go

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through my chart review,
I'll take a look at the.

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Notes and labs and meds,
whatever my role is, right?

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OK.

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I'll do this as an outpatient doc.
I'll do this as a hospitalist.

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OK.

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I'll do this as a consultant to be able
to review the church, whatever it is.

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And then for me,
I need to synthesize that and think about,

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OK,
what is the proper thing that I need to

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do regardless of where that's coming from?
Is it a society guideline?

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And is it coming from a guideline
aggregator?

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Is it coming from utilization management?
And if I should admit or discharge the

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patient, right,
wherever that decision point is,

7a348fe0-4a18-47ea-828a-6cef1df75f23/1056-3
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I'm getting it from a reliable source,
which is going to guide me.

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And sometimes that source is something
that I've learned beforehand and then I'm

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just incorporating whatever I need to do.

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In order to actually have decision
support, right,

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the way that people think about it is
alerts in the EHR based on things that

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are going on in the EHR.
But if there was some way that I can have

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it in the context of my chart
summarization so that whenever I'm

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opening up my chart summarizer or what we
call chart assist,

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then I'm able to get the decision support
together with that chart assist.

7a348fe0-4a18-47ea-828a-6cef1df75f23/1162-0
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Here's the summary of your patient.
Here's our recommendations of what you

7a348fe0-4a18-47ea-828a-6cef1df75f23/1162-1
00:07:35.953 --> 00:07:38.725
might want to do,
and here's a pre-drafted note that

7a348fe0-4a18-47ea-828a-6cef1df75f23/1162-2
00:07:38.725 --> 00:07:41.392
actually incorporates both of them
together. Well,

7a348fe0-4a18-47ea-828a-6cef1df75f23/1162-3
00:07:41.392 --> 00:07:45.576
all of a sudden then I have the ability
to really drive forward in my path that

7a348fe0-4a18-47ea-828a-6cef1df75f23/1162-4
00:07:45.576 --> 00:07:48.610
I'm doing right,
because I'm getting more efficiency as a

7a348fe0-4a18-47ea-828a-6cef1df75f23/1162-5
00:07:48.610 --> 00:07:51.382
clinician,
but with the guidance of decision support

7a348fe0-4a18-47ea-828a-6cef1df75f23/1162-6
00:07:51.382 --> 00:07:51.591
and.

7a348fe0-4a18-47ea-828a-6cef1df75f23/1210-0
00:07:51.711 --> 00:07:55.640
The workflow that I prefer right?
Because I want to do this,

7a348fe0-4a18-47ea-828a-6cef1df75f23/1210-1
00:07:55.640 --> 00:08:00.794
it saves me time. And on the Avo side,
we show that we can actually reduce node

7a348fe0-4a18-47ea-828a-6cef1df75f23/1210-2
00:08:00.794 --> 00:08:06.077
bloat by doing it this way in addition to
improving quality in addition to saving

7a348fe0-4a18-47ea-828a-6cef1df75f23/1210-3
00:08:06.077 --> 00:08:09.620
time, right?
So like this triple aim of having quality

7a348fe0-4a18-47ea-828a-6cef1df75f23/1210-4
00:08:09.620 --> 00:08:11.231
that is true quality for.

7a348fe0-4a18-47ea-828a-6cef1df75f23/1260-0
00:08:11.231 --> 00:08:15.232
The patient reflected in documentation
and then time efficiency gains for

7a348fe0-4a18-47ea-828a-6cef1df75f23/1260-1
00:08:15.232 --> 00:08:17.989
clinicians.
But regardless of the specific answer,

7a348fe0-4a18-47ea-828a-6cef1df75f23/1260-2
00:08:17.989 --> 00:08:22.098
it's thinking creatively about how to
actually put the effective content of

7a348fe0-4a18-47ea-828a-6cef1df75f23/1260-3
00:08:22.098 --> 00:08:25.612
what you want to do into a workflow that
people will respond to.

7a348fe0-4a18-47ea-828a-6cef1df75f23/1260-4
00:08:25.612 --> 00:08:28.694
And people used to think, well,
if you have a hard stop,

7a348fe0-4a18-47ea-828a-6cef1df75f23/1260-5
00:08:28.694 --> 00:08:30.911
if you have an alert, that's gonna force.

7a348fe0-4a18-47ea-828a-6cef1df75f23/1321-0
00:08:31.031 --> 00:08:33.656
to go in whatever direction you want,
that'll work.

7a348fe0-4a18-47ea-828a-6cef1df75f23/1321-1
00:08:33.656 --> 00:08:37.594
And they realize that people are just
writing QWERTY as an answer to whatever

7a348fe0-4a18-47ea-828a-6cef1df75f23/1321-2
00:08:37.594 --> 00:08:41.229
it is, like, hey, this is a hard stop,
you must respond. QWERTY, enter.

7a348fe0-4a18-47ea-828a-6cef1df75f23/1321-3
00:08:41.229 --> 00:08:44.865
And then people are ignoring those hard
stops because there's too many.

7a348fe0-4a18-47ea-828a-6cef1df75f23/1321-4
00:08:44.865 --> 00:08:47.742
And instead people want an easy pass.
We're in New York,

7a348fe0-4a18-47ea-828a-6cef1df75f23/1321-5
00:08:47.742 --> 00:08:50.671
so it probably won't say Sunshine Pass
like in the South.

7a348fe0-4a18-47ea-828a-6cef1df75f23/1368-0
00:08:50.911 --> 00:08:55.262
Right that people want an easy pass to be
able to actually go down and once you're

7a348fe0-4a18-47ea-828a-6cef1df75f23/1368-1
00:08:55.262 --> 00:08:58.197
on that easy pass route,
then you can get whatever your

7a348fe0-4a18-47ea-828a-6cef1df75f23/1368-2
00:08:58.197 --> 00:09:01.552
recommendations are or advertisements
right in the car example.

7a348fe0-4a18-47ea-828a-6cef1df75f23/1368-3
00:09:01.552 --> 00:09:05.484
But the right path that you wanna go to,
maybe not the best corollary with

7a348fe0-4a18-47ea-828a-6cef1df75f23/1368-4
00:09:05.484 --> 00:09:08.891
advertisements, right?
But the proper path of where you wanna go

7a348fe0-4a18-47ea-828a-6cef1df75f23/1368-5
00:09:08.891 --> 00:09:10.831
cuz you're already on that easy path.

7a348fe0-4a18-47ea-828a-6cef1df75f23/1370-0
00:09:10.871 --> 00:09:11.111
Yes.

7a348fe0-4a18-47ea-828a-6cef1df75f23/1409-0
00:09:11.551 --> 00:09:15.334
So you're looking to reduce provider
variability,

7a348fe0-4a18-47ea-828a-6cef1df75f23/1409-1
00:09:15.334 --> 00:09:20.403
improve throughput by making more
valuable and less frequent BPAS,

7a348fe0-4a18-47ea-828a-6cef1df75f23/1409-2
00:09:20.403 --> 00:09:26.304
and then reducing friction between case
managers and clinicians and trying to

7a348fe0-4a18-47ea-828a-6cef1df75f23/1409-3
00:09:26.304 --> 00:09:31.071
help providers better adhere to best
practices. Is that right?

7a348fe0-4a18-47ea-828a-6cef1df75f23/1428-0
00:09:31.591 --> 00:09:35.431
Yeah,
so so once one specific example right for

7a348fe0-4a18-47ea-828a-6cef1df75f23/1428-1
00:09:35.431 --> 00:09:41.911
throughput and this is really where right
at the the best value can be found so.

7a348fe0-4a18-47ea-828a-6cef1df75f23/1425-0
00:09:42.231 --> 00:09:42.391
M.

7a348fe0-4a18-47ea-828a-6cef1df75f23/1452-0
00:09:56.711 --> 00:09:56.871
Yeah.

7a348fe0-4a18-47ea-828a-6cef1df75f23/1459-0
00:09:59.071 --> 00:09:59.191
OK.

7a348fe0-4a18-47ea-828a-6cef1df75f23/1465-0
00:10:02.671 --> 00:10:02.791
OK.

7a348fe0-4a18-47ea-828a-6cef1df75f23/1468-0
00:10:02.831 --> 00:10:02.871
I.

7a348fe0-4a18-47ea-828a-6cef1df75f23/1511-0
00:10:02.831 --> 00:10:06.193
Basically,
case managers would use these guidelines

7a348fe0-4a18-47ea-828a-6cef1df75f23/1511-1
00:10:06.193 --> 00:10:10.331
to help determine if the patient,
let's say, discharged, right?

7a348fe0-4a18-47ea-828a-6cef1df75f23/1511-2
00:10:10.331 --> 00:10:14.469
So an admitted patient,
are they eligible for discharge or not?

7a348fe0-4a18-47ea-828a-6cef1df75f23/1511-3
00:10:14.469 --> 00:10:19.318
If they match the criteria that are in
the care guideline criteria, right,

7a348fe0-4a18-47ea-828a-6cef1df75f23/1511-4
00:10:19.318 --> 00:10:22.551
that's OK, yeah,
they match each of these things.

7a348fe0-4a18-47ea-828a-6cef1df75f23/1558-0
00:10:22.831 --> 00:10:27.334
They're stable, they're able to walk,
they they're they don't have abnormal

7a348fe0-4a18-47ea-828a-6cef1df75f23/1558-1
00:10:27.334 --> 00:10:32.371
labs and each of the criteria specific to
their disease states, to their conditions,

7a348fe0-4a18-47ea-828a-6cef1df75f23/1558-2
00:10:32.371 --> 00:10:36.046
and if they match well,
then they are eligible for discharge,

7a348fe0-4a18-47ea-828a-6cef1df75f23/1558-3
00:10:36.046 --> 00:10:38.831
right?
And those guidelines that arbitrator is

7a348fe0-4a18-47ea-828a-6cef1df75f23/1558-4
00:10:38.831 --> 00:10:42.031
trusted by health systems and by
insurance companies.

7a348fe0-4a18-47ea-828a-6cef1df75f23/1621-0
00:10:42.831 --> 00:10:44.911
Now,
the way that happens for me as a

7a348fe0-4a18-47ea-828a-6cef1df75f23/1621-1
00:10:44.911 --> 00:10:48.251
hospitalist, right?
So let's go back in time a little bit is

7a348fe0-4a18-47ea-828a-6cef1df75f23/1621-2
00:10:48.251 --> 00:10:52.576
I would show up at an interdisciplinary
rounds and the case manager would say,

7a348fe0-4a18-47ea-828a-6cef1df75f23/1621-3
00:10:52.576 --> 00:10:56.244
is the patient ready for discharge?
And I would say, I don't know,

7a348fe0-4a18-47ea-828a-6cef1df75f23/1621-4
00:10:56.244 --> 00:10:58.982
the patient's still sick.
And then it's OK, well,

7a348fe0-4a18-47ea-828a-6cef1df75f23/1621-5
00:10:58.982 --> 00:11:02.431
should I get the discharge paperwork
ready? I'll let you know.

7a348fe0-4a18-47ea-828a-6cef1df75f23/1664-0
00:11:02.511 --> 00:11:02.871
The patient.

7a348fe0-4a18-47ea-828a-6cef1df75f23/1678-0
00:11:02.991 --> 00:11:04.876
Better.
And then there's this whole back and

7a348fe0-4a18-47ea-828a-6cef1df75f23/1678-1
00:11:04.876 --> 00:11:07.976
forth because they're taking a look at
the guidelines where the patient's

7a348fe0-4a18-47ea-828a-6cef1df75f23/1678-2
00:11:07.976 --> 00:11:10.322
actually matching as they're cross
checking everything,

7a348fe0-4a18-47ea-828a-6cef1df75f23/1678-3
00:11:10.322 --> 00:11:13.631
which takes them a long time if they
actually go through it. For me, I'm like,

7a348fe0-4a18-47ea-828a-6cef1df75f23/1678-4
00:11:13.631 --> 00:11:15.517
hey,
I would just thought that the patient's

7a348fe0-4a18-47ea-828a-6cef1df75f23/1678-5
00:11:15.517 --> 00:11:17.904
sick and I'll let you know.
And then this afternoon, oh,

7a348fe0-4a18-47ea-828a-6cef1df75f23/1678-6
00:11:17.904 --> 00:11:20.879
everything's actually resolved. Yeah,
we can discharge. Unfortunately,

7a348fe0-4a18-47ea-828a-6cef1df75f23/1678-7
00:11:20.879 --> 00:11:22.471
it's already Friday afternoon and the.

7a348fe0-4a18-47ea-828a-6cef1df75f23/1738-0
00:11:22.831 --> 00:11:25.273
You know,
shelter's not going to take the packet

7a348fe0-4a18-47ea-828a-6cef1df75f23/1738-1
00:11:25.273 --> 00:11:28.962
and we got to wait until Monday.
That's a longer length of stay and it's,

7a348fe0-4a18-47ea-828a-6cef1df75f23/1738-2
00:11:28.962 --> 00:11:31.404
you know,
that's repetitive across the different

7a348fe0-4a18-47ea-828a-6cef1df75f23/1738-3
00:11:31.404 --> 00:11:33.846
patients across their disease states.
Over here,

7a348fe0-4a18-47ea-828a-6cef1df75f23/1738-4
00:11:33.846 --> 00:11:37.734
what we do is we partnered with MCG to be
able to take their content into the

7a348fe0-4a18-47ea-828a-6cef1df75f23/1738-5
00:11:37.734 --> 00:11:41.273
overall workflow so that when I open up
my chart summarization, right,

7a348fe0-4a18-47ea-828a-6cef1df75f23/1738-6
00:11:41.273 --> 00:11:42.071
my chart assist.

7a348fe0-4a18-47ea-828a-6cef1df75f23/1785-0
00:11:42.431 --> 00:11:45.729
In the morning,
when I'm pre-rounding on my patients as a

7a348fe0-4a18-47ea-828a-6cef1df75f23/1785-1
00:11:45.729 --> 00:11:49.709
hospitalist or as a case manager,
it will automatically summarize the

7a348fe0-4a18-47ea-828a-6cef1df75f23/1785-2
00:11:49.709 --> 00:11:52.609
patient's information compared to the MCG
content,

7a348fe0-4a18-47ea-828a-6cef1df75f23/1785-3
00:11:52.609 --> 00:11:55.452
tell you if the patient's eligible for
discharge.

7a348fe0-4a18-47ea-828a-6cef1df75f23/1785-4
00:11:55.452 --> 00:11:59.830
If the patient is eligible for discharge,
pre-draft you a discharge summary.

7a348fe0-4a18-47ea-828a-6cef1df75f23/1785-5
00:11:59.830 --> 00:12:01.991
It means that the hospitalist and the.

7a348fe0-4a18-47ea-828a-6cef1df75f23/1832-0
00:12:02.151 --> 00:12:05.723
Case manager on the same page.
That's how to get patients out

7a348fe0-4a18-47ea-828a-6cef1df75f23/1832-1
00:12:05.723 --> 00:12:10.333
appropriately because you suddenly reduce
that variation and the back and forth

7a348fe0-4a18-47ea-828a-6cef1df75f23/1832-2
00:12:10.333 --> 00:12:15.001
between these different parties and then
allow for the patients to be discharged

7a348fe0-4a18-47ea-828a-6cef1df75f23/1832-3
00:12:15.001 --> 00:12:19.207
appropriately, reducing length of stay,
improving throughput and thereby

7a348fe0-4a18-47ea-828a-6cef1df75f23/1832-4
00:12:19.207 --> 00:12:22.031
improving capacity.
So it's a specific use case.

7a348fe0-4a18-47ea-828a-6cef1df75f23/1877-0
00:12:22.031 --> 00:12:27.174
To solve that ROI with the same idea,
right? It's the same structural framework.

7a348fe0-4a18-47ea-828a-6cef1df75f23/1877-1
00:12:27.174 --> 00:12:31.301
It's the same scaffolding.
You're doing patient data extraction,

7a348fe0-4a18-47ea-828a-6cef1df75f23/1877-2
00:12:31.301 --> 00:12:36.127
checking against a knowledge source and
having the AI take the patient data

7a348fe0-4a18-47ea-828a-6cef1df75f23/1877-3
00:12:36.127 --> 00:12:41.271
against the knowledge source to see where
it matches and then producing outputs.

7a348fe0-4a18-47ea-828a-6cef1df75f23/1888-0
00:12:41.551 --> 00:12:46.957
or orders as appropriate with a specific
eye towards utilization management of the

7a348fe0-4a18-47ea-828a-6cef1df75f23/1888-1
00:12:46.957 --> 00:12:48.911
example of the MCG guidelines.

7a348fe0-4a18-47ea-828a-6cef1df75f23/1938-0
00:12:48.591 --> 00:12:52.114
And when I'd like to,
I think some of our listeners might be

7a348fe0-4a18-47ea-828a-6cef1df75f23/1938-1
00:12:52.114 --> 00:12:56.793
interested in learning about some of the
clinical outcomes of implementing these

7a348fe0-4a18-47ea-828a-6cef1df75f23/1938-2
00:12:56.793 --> 00:12:59.855
interventions.
Would I be correct to say that you've

7a348fe0-4a18-47ea-828a-6cef1df75f23/1938-3
00:12:59.855 --> 00:13:03.667
seen improved HCAP scores,
better guideline medication adherence,

7a348fe0-4a18-47ea-828a-6cef1df75f23/1938-4
00:13:03.667 --> 00:13:08.231
savings at one site in the millions of
dollars, reduced admissions delays and.

7a348fe0-4a18-47ea-828a-6cef1df75f23/1945-0
00:13:08.431 --> 00:13:11.751
Improved time saving and is it not
accurate?

7a348fe0-4a18-47ea-828a-6cef1df75f23/1986-0
00:13:11.871 --> 00:13:15.795
That is, yeah.
And we've seen it across these different

7a348fe0-4a18-47ea-828a-6cef1df75f23/1986-1
00:13:15.795 --> 00:13:19.719
ROI trackers.
So in addition to all the things that you

7a348fe0-4a18-47ea-828a-6cef1df75f23/1986-2
00:13:19.719 --> 00:13:23.433
mentioned,
I had mentioned we saw reduced note bloat

7a348fe0-4a18-47ea-828a-6cef1df75f23/1986-3
00:13:23.433 --> 00:13:28.197
in addition by eliminating copy forward,
which is good for quality,

7a348fe0-4a18-47ea-828a-6cef1df75f23/1986-4
00:13:28.197 --> 00:13:31.351
significant time reduction in
documentation.

7a348fe0-4a18-47ea-828a-6cef1df75f23/2032-0
00:13:31.911 --> 00:13:35.702
So, right,
it's across different areas where you'll

7a348fe0-4a18-47ea-828a-6cef1df75f23/2032-1
00:13:35.702 --> 00:13:39.201
see these improvements,
obviously cost savings,

7a348fe0-4a18-47ea-828a-6cef1df75f23/2032-2
00:13:39.201 --> 00:13:43.138
better medication adherence, right,
as you mentioned,

7a348fe0-4a18-47ea-828a-6cef1df75f23/2032-3
00:13:43.138 --> 00:13:48.387
decreased admission delays, right.
So across the spectrum where we have

7a348fe0-4a18-47ea-828a-6cef1df75f23/2014-0
00:13:45.431 --> 00:13:45.511
I.

7a348fe0-4a18-47ea-828a-6cef1df75f23/2032-4
00:13:48.387 --> 00:13:51.231
shown significant ROI with these tools.

7a348fe0-4a18-47ea-828a-6cef1df75f23/2023-0
00:13:50.831 --> 00:13:50.871
I.

7a348fe0-4a18-47ea-828a-6cef1df75f23/2088-0
00:13:51.391 --> 00:13:55.975
And then the nice thing about it is when
people first started implementing AI in

7a348fe0-4a18-47ea-828a-6cef1df75f23/2088-1
00:13:55.975 --> 00:14:00.277
health systems, it was a like, OK,
we have to get this in because everybody

7a348fe0-4a18-47ea-828a-6cef1df75f23/2088-2
00:14:00.277 --> 00:14:03.616
else has it. You know,
we have to get this in because it's

7a348fe0-4a18-47ea-828a-6cef1df75f23/2088-3
00:14:03.616 --> 00:14:06.559
something which seems to have a
significant impact.

7a348fe0-4a18-47ea-828a-6cef1df75f23/2063-0
00:14:06.511 --> 00:14:06.631
OK.

7a348fe0-4a18-47ea-828a-6cef1df75f23/2088-4
00:14:06.559 --> 00:14:10.748
But now we're at a point of, OK,
we want to get these tools in because we

7a348fe0-4a18-47ea-828a-6cef1df75f23/2088-5
00:14:10.748 --> 00:14:11.031
want.

7a348fe0-4a18-47ea-828a-6cef1df75f23/2107-0
00:14:11.231 --> 00:14:16.006
Significant financial ROI. In addition,
where are we going to see this ROI that

7a348fe0-4a18-47ea-828a-6cef1df75f23/2107-1
00:14:16.006 --> 00:14:19.111
the system will pay for itself over the
first year?

7a348fe0-4a18-47ea-828a-6cef1df75f23/2151-0
00:14:17.671 --> 00:14:23.376
So, Yair, I'd like to pivot.
We we only have about a few more minutes

7a348fe0-4a18-47ea-828a-6cef1df75f23/2151-1
00:14:23.376 --> 00:14:28.511
left in this episode,
and I want to pivot to the idea of being

7a348fe0-4a18-47ea-828a-6cef1df75f23/2151-2
00:14:28.511 --> 00:14:33.809
an entrepreneurial provider.
So health systems across the United

7a348fe0-4a18-47ea-828a-6cef1df75f23/2151-3
00:14:33.809 --> 00:14:37.151
States have incubators where they try to.

7a348fe0-4a18-47ea-828a-6cef1df75f23/2198-0
00:14:37.231 --> 00:14:42.424
Invest in startup ideas and generate new
revenue streams for the health system by

7a348fe0-4a18-47ea-828a-6cef1df75f23/2198-1
00:14:42.424 --> 00:14:45.527
holding an equity stake in these startups.
Also,

7a348fe0-4a18-47ea-828a-6cef1df75f23/2198-2
00:14:45.527 --> 00:14:50.594
health systems have providers like you
who see problems in the health system as

7a348fe0-4a18-47ea-828a-6cef1df75f23/2198-3
00:14:50.594 --> 00:14:54.584
they're delivering care that they have
ideas for how to solve.

7a348fe0-4a18-47ea-828a-6cef1df75f23/2198-4
00:14:54.584 --> 00:14:56.991
So I'd like to ask you to speak about.

7a348fe0-4a18-47ea-828a-6cef1df75f23/2247-0
00:14:57.071 --> 00:15:01.444
Both those topics separately.
One is if a health system executive is

7a348fe0-4a18-47ea-828a-6cef1df75f23/2247-1
00:15:01.444 --> 00:15:06.325
listening to this episode right now,
how would you advise them to respond to

7a348fe0-4a18-47ea-828a-6cef1df75f23/2247-2
00:15:06.325 --> 00:15:11.269
providers in their own system who have
identified problems and identify would

7a348fe0-4a18-47ea-828a-6cef1df75f23/2247-3
00:15:11.269 --> 00:15:15.960
like to experiment with possible
solutions to improve the problems facing

7a348fe0-4a18-47ea-828a-6cef1df75f23/2247-4
00:15:15.960 --> 00:15:16.911
them every day?

7a348fe0-4a18-47ea-828a-6cef1df75f23/2250-0
00:15:17.031 --> 00:15:17.511
Start there.

7a348fe0-4a18-47ea-828a-6cef1df75f23/2296-0
00:15:18.271 --> 00:15:22.972
Yeah. So when I was in residency,
I was in SUNY downstate.

7a348fe0-4a18-47ea-828a-6cef1df75f23/2296-1
00:15:22.972 --> 00:15:28.071
And one of my favorite things about it
was that the leadership,

7a348fe0-4a18-47ea-828a-6cef1df75f23/2296-2
00:15:28.071 --> 00:15:34.605
the executives were so supportive of my
ideas to be able to guide me to the right

7a348fe0-4a18-47ea-828a-6cef1df75f23/2296-3
00:15:34.605 --> 00:15:38.111
people who can help to the right
resources.

7a348fe0-4a18-47ea-828a-6cef1df75f23/2345-0
00:15:38.111 --> 00:15:43.147
I was able to work with the CMIO at Kings
County Hospital doing electives and then

7a348fe0-4a18-47ea-828a-6cef1df75f23/2345-1
00:15:43.147 --> 00:15:47.091
later as an informatics liaison to be
able to help install Epic.

7a348fe0-4a18-47ea-828a-6cef1df75f23/2345-2
00:15:47.091 --> 00:15:51.884
And there was so much that I learned
along the way because of the support that

7a348fe0-4a18-47ea-828a-6cef1df75f23/2345-3
00:15:51.884 --> 00:15:55.646
I got. Fast forward and we were actually,
once I started Avo,

7a348fe0-4a18-47ea-828a-6cef1df75f23/2345-4
00:15:55.646 --> 00:15:57.831
the first company in Elemental Labs.

7a348fe0-4a18-47ea-828a-6cef1df75f23/2336-0
00:15:57.631 --> 00:15:57.671
I.

7a348fe0-4a18-47ea-828a-6cef1df75f23/2388-0
00:15:58.031 --> 00:16:01.498
In Mount Sinai.
So when that started as an incubator,

7a348fe0-4a18-47ea-828a-6cef1df75f23/2388-1
00:16:01.498 --> 00:16:06.507
we were the first company to go through
and we were learning together, right,

7a348fe0-4a18-47ea-828a-6cef1df75f23/2388-2
00:16:06.507 --> 00:16:10.552
how to be able to support these ideas
that are coming through.

7a348fe0-4a18-47ea-828a-6cef1df75f23/2388-3
00:16:10.552 --> 00:16:15.433
Not that I was a doc at Mount Sinai and
being supported from inside that we

7a348fe0-4a18-47ea-828a-6cef1df75f23/2388-4
00:16:15.433 --> 00:16:17.231
actually applied externally.

7a348fe0-4a18-47ea-828a-6cef1df75f23/2379-0
00:16:17.071 --> 00:16:17.111
I.

7a348fe0-4a18-47ea-828a-6cef1df75f23/2436-0
00:16:17.551 --> 00:16:24.166
To be able to join Elementa and I had to
be a path that was very explicit about

7a348fe0-4a18-47ea-828a-6cef1df75f23/2436-1
00:16:24.166 --> 00:16:30.698
like how we would chart this out because
I was per diem at Mount Sinai, right,

7a348fe0-4a18-47ea-828a-6cef1df75f23/2436-2
00:16:30.698 --> 00:16:35.329
even at the time.
And so we had to figure out that path

7a348fe0-4a18-47ea-828a-6cef1df75f23/2418-0
00:16:32.631 --> 00:16:33.111
Mhm.

7a348fe0-4a18-47ea-828a-6cef1df75f23/2436-3
00:16:35.329 --> 00:16:37.231
that we would navigate.

7a348fe0-4a18-47ea-828a-6cef1df75f23/2490-0
00:16:37.231 --> 00:16:41.440
Exactly what I could do and couldn't do
within that context of the path.

7a348fe0-4a18-47ea-828a-6cef1df75f23/2490-1
00:16:41.440 --> 00:16:45.937
So I think a couple things to call out.
Number one is being supportive of the

7a348fe0-4a18-47ea-828a-6cef1df75f23/2490-2
00:16:45.937 --> 00:16:50.493
physicians and of the clinicians that
have these ideas will allow them to feel

7a348fe0-4a18-47ea-828a-6cef1df75f23/2468-0
00:16:48.911 --> 00:16:48.951
I.

7a348fe0-4a18-47ea-828a-6cef1df75f23/2490-3
00:16:50.493 --> 00:16:55.221
empowered to make the real changes that
we're seeing. So support your clinicians,

7a348fe0-4a18-47ea-828a-6cef1df75f23/2472-0
00:16:51.471 --> 00:16:51.511
I.

7a348fe0-4a18-47ea-828a-6cef1df75f23/2490-4
00:16:55.221 --> 00:16:56.951
support your physicians #2 is.

7a348fe0-4a18-47ea-828a-6cef1df75f23/2481-0
00:16:55.631 --> 00:16:55.671
I.

7a348fe0-4a18-47ea-828a-6cef1df75f23/2539-0
00:16:57.151 --> 00:17:00.966
Make sure to handle the conflict of
interest needs. Well, you know,

7a348fe0-4a18-47ea-828a-6cef1df75f23/2539-1
00:17:00.966 --> 00:17:04.614
that was something which was a little bit
difficult to navigate,

7a348fe0-4a18-47ea-828a-6cef1df75f23/2539-2
00:17:04.614 --> 00:17:08.879
but especially they were super helpful
for me to, you know, figure out, OK,

7a348fe0-4a18-47ea-828a-6cef1df75f23/2539-3
00:17:08.879 --> 00:17:12.245
what was OK for me?
What should be handled by others within

7a348fe0-4a18-47ea-828a-6cef1df75f23/2539-4
00:17:12.245 --> 00:17:15.332
my company?
What was I allowed to do or not? You know,

7a348fe0-4a18-47ea-828a-6cef1df75f23/2539-5
00:17:15.332 --> 00:17:16.791
could we join this or not?

7a348fe0-4a18-47ea-828a-6cef1df75f23/2579-0
00:17:16.991 --> 00:17:22.327
At different times to just to make sure
that everything was was clear and I took

7a348fe0-4a18-47ea-828a-6cef1df75f23/2579-1
00:17:22.327 --> 00:17:27.466
their guidance and was super appreciative
for that guidance to make sure that

7a348fe0-4a18-47ea-828a-6cef1df75f23/2579-2
00:17:27.466 --> 00:17:32.671
everything was in line. Third is you know,
thinking from a system perspective.

7a348fe0-4a18-47ea-828a-6cef1df75f23/2636-0
00:17:32.991 --> 00:17:36.653
There is money opportunity, right?
It's like if companies are going to do

7a348fe0-4a18-47ea-828a-6cef1df75f23/2636-1
00:17:36.653 --> 00:17:40.167
well and you have equity stake in these
companies, well, that's great.

7a348fe0-4a18-47ea-828a-6cef1df75f23/2636-2
00:17:40.167 --> 00:17:43.583
Then you're able to do well from
continuing to do what you're doing,

7a348fe0-4a18-47ea-828a-6cef1df75f23/2636-3
00:17:43.583 --> 00:17:47.790
just inculcating this idea of innovation.
And it's not just that you are innovative,

7a348fe0-4a18-47ea-828a-6cef1df75f23/2636-4
00:17:47.790 --> 00:17:51.403
which itself has a lot of value,
but also the financial returns that are

7a348fe0-4a18-47ea-828a-6cef1df75f23/2636-5
00:17:51.403 --> 00:17:52.591
possible. So with those.

7a348fe0-4a18-47ea-828a-6cef1df75f23/2672-0
00:17:52.991 --> 00:17:57.825
I would say definitely from my side
within the vendor perspective,

7a348fe0-4a18-47ea-828a-6cef1df75f23/2672-1
00:17:57.825 --> 00:18:03.165
it was amazing to be able to have these
experiences and to go through the

7a348fe0-4a18-47ea-828a-6cef1df75f23/2672-2
00:18:03.165 --> 00:18:08.577
elemental labs in Mount Sinai and in
general to be supported by the health

7a348fe0-4a18-47ea-828a-6cef1df75f23/2672-3
00:18:08.577 --> 00:18:11.031
systems that we were working with.

7a348fe0-4a18-47ea-828a-6cef1df75f23/2706-0
00:18:11.351 --> 00:18:16.225
Both from my time as a in residency and
then and then beyond and then from a

7a348fe0-4a18-47ea-828a-6cef1df75f23/2706-1
00:18:16.225 --> 00:18:20.150
system level perspective,
like there's a lot of gain that can

7a348fe0-4a18-47ea-828a-6cef1df75f23/2706-2
00:18:20.150 --> 00:18:23.759
happen there. So it's not just a service,
it's you know,

7a348fe0-4a18-47ea-828a-6cef1df75f23/2706-3
00:18:23.759 --> 00:18:26.671
you can do good and do well at the same
time.

7a348fe0-4a18-47ea-828a-6cef1df75f23/2755-0
00:18:26.271 --> 00:18:29.015
Right.
So it sounds like you health system may

7a348fe0-4a18-47ea-828a-6cef1df75f23/2755-1
00:18:29.015 --> 00:18:33.803
benefit from supporting providers who'd
like to start their own solutions both by

7a348fe0-4a18-47ea-828a-6cef1df75f23/2755-2
00:18:33.803 --> 00:18:38.299
having equity and successful start-ups
and generating cash flow that way and

7a348fe0-4a18-47ea-828a-6cef1df75f23/2755-3
00:18:38.299 --> 00:18:43.028
also introducing solutions for providers
at their health system to problems that

7a348fe0-4a18-47ea-828a-6cef1df75f23/2755-4
00:18:43.028 --> 00:18:45.831
exist.
So kind of improving provider retention.

7a348fe0-4a18-47ea-828a-6cef1df75f23/2801-0
00:18:46.111 --> 00:18:50.363
And all the different issues we've
covered today from quality to efficiency

7a348fe0-4a18-47ea-828a-6cef1df75f23/2801-1
00:18:50.363 --> 00:18:53.944
to to improve profitability.
We are approaching the end of this

7a348fe0-4a18-47ea-828a-6cef1df75f23/2801-2
00:18:53.944 --> 00:18:58.141
podcast episode. So final question, Yair,
I'd like to ask if looking back,

7a348fe0-4a18-47ea-828a-6cef1df75f23/2801-3
00:18:58.141 --> 00:19:02.449
is there if you could have one wish of
something you could change or looking

7a348fe0-4a18-47ea-828a-6cef1df75f23/2801-4
00:19:02.449 --> 00:19:05.191
forward if there's one thing you'd like
to have?

7a348fe0-4a18-47ea-828a-6cef1df75f23/2848-0
00:19:05.871 --> 00:19:08.912
You know,
you think health system leadership could

7a348fe0-4a18-47ea-828a-6cef1df75f23/2848-1
00:19:08.912 --> 00:19:13.504
help you with or help providers if
they're looking to improve throughput and

7a348fe0-4a18-47ea-828a-6cef1df75f23/2848-2
00:19:13.504 --> 00:19:16.545
improve outcomes and improve efficiency.
You know,

7a348fe0-4a18-47ea-828a-6cef1df75f23/2848-3
00:19:16.545 --> 00:19:21.256
what's kind of the one thing that you
would either like differently or like in

7a348fe0-4a18-47ea-828a-6cef1df75f23/2848-4
00:19:21.256 --> 00:19:25.431
the future or one kind of take away for
our exec leadership audience?

7a348fe0-4a18-47ea-828a-6cef1df75f23/2849-0
00:19:26.111 --> 00:19:26.351
Today.

7a348fe0-4a18-47ea-828a-6cef1df75f23/2888-0
00:19:27.391 --> 00:19:30.561
Yeah.
Biggest take away is kind of like your

7a348fe0-4a18-47ea-828a-6cef1df75f23/2888-1
00:19:30.561 --> 00:19:34.154
last point,
which is listen to your physicians and

7a348fe0-4a18-47ea-828a-6cef1df75f23/2888-2
00:19:34.154 --> 00:19:39.790
clinicians on the ground to be able to
synthesize the things that are important

7a348fe0-4a18-47ea-828a-6cef1df75f23/2868-0
00:19:35.991 --> 00:19:36.111
OK.

7a348fe0-4a18-47ea-828a-6cef1df75f23/2888-3
00:19:39.790 --> 00:19:43.031
and the way that things are actually
working.

7a348fe0-4a18-47ea-828a-6cef1df75f23/2926-0
00:19:43.231 --> 00:19:47.929
Which you don't always get to experience
unless you're actually in the trenches.

7a348fe0-4a18-47ea-828a-6cef1df75f23/2926-1
00:19:47.929 --> 00:19:51.526
And then with that you're going to be
able to understand, OK,

7a348fe0-4a18-47ea-828a-6cef1df75f23/2926-2
00:19:51.526 --> 00:19:56.282
what are the real problems and you know
what's going on and with the capacity and

7a348fe0-4a18-47ea-828a-6cef1df75f23/2926-3
00:19:56.282 --> 00:19:58.951
throughput examples, right?
It's like if the.

7a348fe0-4a18-47ea-828a-6cef1df75f23/2957-0
00:20:12.671 --> 00:20:12.711
I.

7a348fe0-4a18-47ea-828a-6cef1df75f23/3010-0
00:20:12.871 --> 00:20:17.126
10 rounds and it's like, OK, cool.
Like would it help to get something which

7a348fe0-4a18-47ea-828a-6cef1df75f23/3010-1
00:20:17.126 --> 00:20:21.547
would be able to be like an arbitrator
that has the guidelines that can help be

7a348fe0-4a18-47ea-828a-6cef1df75f23/2972-0
00:20:19.831 --> 00:20:20.311
Mhm.

7a348fe0-4a18-47ea-828a-6cef1df75f23/3010-2
00:20:21.547 --> 00:20:24.641
present there?
And then it's like you have something to

7a348fe0-4a18-47ea-828a-6cef1df75f23/3010-3
00:20:24.641 --> 00:20:28.841
disagree about as opposed to just
disagreeing like that can help solve that

7a348fe0-4a18-47ea-828a-6cef1df75f23/3010-4
00:20:28.841 --> 00:20:31.991
problem as one example, right?
But the key is listening.

7a348fe0-4a18-47ea-828a-6cef1df75f23/3018-0
00:20:32.751 --> 00:20:36.311
Listening to your clinicians, that's, uh,
that's the secret.