a063df5a-124c-428e-bb07-4da24531b175/20-0
00:00:03.130 --> 00:00:05.488
Women and children service line for the
system. Kendra,
a063df5a-124c-428e-bb07-4da24531b175/20-1
00:00:05.488 --> 00:00:07.130
thank you so much for joining us today.
a063df5a-124c-428e-bb07-4da24531b175/24-0
00:00:07.200 --> 00:00:08.240
I'm very excited to be here.
a063df5a-124c-428e-bb07-4da24531b175/28-0
00:00:08.240 --> 00:00:09.240
Thank you for having me.
a063df5a-124c-428e-bb07-4da24531b175/51-0
00:00:09.610 --> 00:00:12.477
Yeah.
So we have a wide set of issues that
a063df5a-124c-428e-bb07-4da24531b175/51-1
00:00:12.477 --> 00:00:17.144
we're going to be discussing today,
all pertaining to data surprises,
a063df5a-124c-428e-bb07-4da24531b175/51-2
00:00:17.144 --> 00:00:18.610
healthy data, podcast.
a063df5a-124c-428e-bb07-4da24531b175/75-0
00:00:19.370 --> 00:00:25.219
I'd like to ask you to start us off with
a conversation or description of how data
a063df5a-124c-428e-bb07-4da24531b175/75-1
00:00:25.219 --> 00:00:28.530
the current state of data at Memorial
Hermann.
a063df5a-124c-428e-bb07-4da24531b175/90-0
00:00:28.690 --> 00:00:34.126
What kind of issues are arising from
clean or lack of clean data at Memorial
a063df5a-124c-428e-bb07-4da24531b175/90-1
00:00:34.126 --> 00:00:34.690
Hermann?
a063df5a-124c-428e-bb07-4da24531b175/130-0
00:00:35.200 --> 00:00:37.452
Well,
I think I could definitely speak to what
a063df5a-124c-428e-bb07-4da24531b175/130-1
00:00:37.452 --> 00:00:40.327
is the state of Theta for all maternal
health and you know,
a063df5a-124c-428e-bb07-4da24531b175/130-2
00:00:40.327 --> 00:00:43.872
not just within my organization,
but I also do a lot of work at the state
a063df5a-124c-428e-bb07-4da24531b175/130-3
00:00:43.872 --> 00:00:47.417
of Texas level and so significant
opportunity to really understand what's
a063df5a-124c-428e-bb07-4da24531b175/130-4
00:00:47.417 --> 00:00:48.040
happening in.
a063df5a-124c-428e-bb07-4da24531b175/174-0
00:00:48.150 --> 00:00:50.931
Population.
We know maternal health is population
a063df5a-124c-428e-bb07-4da24531b175/174-1
00:00:50.931 --> 00:00:53.546
health,
so how do we get data that's relevant,
a063df5a-124c-428e-bb07-4da24531b175/174-2
00:00:53.546 --> 00:00:56.660
actionable and timely,
so we can really steer the ship.
a063df5a-124c-428e-bb07-4da24531b175/174-3
00:00:56.660 --> 00:01:01.054
We know we have opportunities to improve
our maternal mortality and morbidity,
a063df5a-124c-428e-bb07-4da24531b175/174-4
00:01:01.054 --> 00:01:04.280
but where is the data that really helps
us other than we?
a063df5a-124c-428e-bb07-4da24531b175/180-0
00:01:04.280 --> 00:01:05.390
Have a problem.
a063df5a-124c-428e-bb07-4da24531b175/186-0
00:01:05.510 --> 00:01:07.110
How do we fix this problem?
a063df5a-124c-428e-bb07-4da24531b175/192-0
00:01:07.110 --> 00:01:08.870
And so how do we find the data?
a063df5a-124c-428e-bb07-4da24531b175/195-0
00:01:08.910 --> 00:01:10.470
How do we clean that data?
a063df5a-124c-428e-bb07-4da24531b175/200-0
00:01:10.590 --> 00:01:13.630
There's multiple different sources of
this to really create.
a063df5a-124c-428e-bb07-4da24531b175/207-0
00:01:14.320 --> 00:01:15.920
A story so we know where we can go and
prove.
a063df5a-124c-428e-bb07-4da24531b175/217-0
00:01:17.610 --> 00:01:19.930
So what are some of I like to?
a063df5a-124c-428e-bb07-4da24531b175/237-0
00:01:19.930 --> 00:01:23.040
I think it's most helpful for our
listeners if you walk us through a
a063df5a-124c-428e-bb07-4da24531b175/237-1
00:01:23.040 --> 00:01:25.609
particular use case,
I think many listeners may say yes,
a063df5a-124c-428e-bb07-4da24531b175/237-2
00:01:25.609 --> 00:01:26.690
you know this resonates.
a063df5a-124c-428e-bb07-4da24531b175/257-0
00:01:26.690 --> 00:01:31.426
We do have an issue with mortality
morbidity relating to maternal health,
a063df5a-124c-428e-bb07-4da24531b175/257-1
00:01:31.426 --> 00:01:33.730
but we don't really know what to do.
a063df5a-124c-428e-bb07-4da24531b175/277-0
00:01:33.730 --> 00:01:37.860
What are the different data sources
you're trying to reconcile and what are
a063df5a-124c-428e-bb07-4da24531b175/277-1
00:01:37.860 --> 00:01:42.370
some of the challenges in trying to have
actionable real time insights to improve?
a063df5a-124c-428e-bb07-4da24531b175/279-0
00:01:43.060 --> 00:01:43.340
Maternal health.
a063df5a-124c-428e-bb07-4da24531b175/281-0
00:01:43.610 --> 00:01:43.730
Off.
a063df5a-124c-428e-bb07-4da24531b175/316-0
00:01:44.090 --> 00:01:46.634
Well,
I think what the current state is and we
a063df5a-124c-428e-bb07-4da24531b175/316-1
00:01:46.634 --> 00:01:50.639
think of what are our data sources and I
think you know, Data's A1280 kg,
a063df5a-124c-428e-bb07-4da24531b175/316-2
00:01:50.639 --> 00:01:54.210
like we say, a clinical side,
I'm an L&D nurse by background.
a063df5a-124c-428e-bb07-4da24531b175/346-0
00:01:54.210 --> 00:01:56.854
So data is a newer place for us.
As clinicians,
a063df5a-124c-428e-bb07-4da24531b175/346-1
00:01:56.854 --> 00:02:01.370
we know we have our EMR which in Memorial
Hermann we currently converted to EPIC.
a063df5a-124c-428e-bb07-4da24531b175/369-0
00:02:01.610 --> 00:02:05.553
So we have EMR data,
we have administrative coding data which
a063df5a-124c-428e-bb07-4da24531b175/369-1
00:02:05.553 --> 00:02:09.050
is really where a lot of our reporting is
coming from.
a063df5a-124c-428e-bb07-4da24531b175/374-0
00:02:09.050 --> 00:02:11.050
So CMS is now really moving towards.
a063df5a-124c-428e-bb07-4da24531b175/379-0
00:02:11.800 --> 00:02:12.920
Our severe maternal morbidity.
a063df5a-124c-428e-bb07-4da24531b175/383-0
00:02:13.430 --> 00:02:14.910
Diagnostic codes.
a063df5a-124c-428e-bb07-4da24531b175/406-0
00:02:14.990 --> 00:02:18.330
That's all claims data.
There was just a recent article that came
a063df5a-124c-428e-bb07-4da24531b175/388-0
00:02:15.080 --> 00:02:15.280
Mm hmm.
a063df5a-124c-428e-bb07-4da24531b175/406-1
00:02:18.330 --> 00:02:21.670
out by Popeue that said that really it's
only about 65% accurate.
a063df5a-124c-428e-bb07-4da24531b175/430-0
00:02:22.040 --> 00:02:26.871
So how did we take the ICD 10 code,
which is really where all the claims data
a063df5a-124c-428e-bb07-4da24531b175/430-1
00:02:26.871 --> 00:02:27.800
is coming from?
a063df5a-124c-428e-bb07-4da24531b175/431-0
00:02:27.800 --> 00:02:28.560
The billing data.
a063df5a-124c-428e-bb07-4da24531b175/448-0
00:02:28.560 --> 00:02:33.522
The reportable data is coming from,
but then how do we use our epic to give
a063df5a-124c-428e-bb07-4da24531b175/448-1
00:02:33.522 --> 00:02:34.240
us reports?
a063df5a-124c-428e-bb07-4da24531b175/482-0
00:02:34.240 --> 00:02:38.323
That's gonna give us some good
information and mix that together within
a063df5a-124c-428e-bb07-4da24531b175/482-1
00:02:38.323 --> 00:02:42.461
the state of Texas and is coming to
theaters near a lot of us across the
a063df5a-124c-428e-bb07-4da24531b175/482-2
00:02:42.461 --> 00:02:45.807
nation as levels of care.
And that's where we are gonna be
a063df5a-124c-428e-bb07-4da24531b175/482-3
00:02:45.807 --> 00:02:46.600
designated as.
a063df5a-124c-428e-bb07-4da24531b175/496-0
00:02:47.400 --> 00:02:51.266
Organization at what level of care and
what is the acuity level of moms and
a063df5a-124c-428e-bb07-4da24531b175/496-1
00:02:51.266 --> 00:02:52.080
neonatal babies?
a063df5a-124c-428e-bb07-4da24531b175/512-0
00:02:52.630 --> 00:02:57.068
Even the NICU that you can take care of
that requires a significant amount of
a063df5a-124c-428e-bb07-4da24531b175/512-1
00:02:57.068 --> 00:02:57.750
case review.
a063df5a-124c-428e-bb07-4da24531b175/527-0
00:02:58.110 --> 00:03:02.410
So that's another, you know,
data source that is based on real
a063df5a-124c-428e-bb07-4da24531b175/527-1
00:03:02.410 --> 00:03:05.960
obstruction,
which I think as clinicians that's our
a063df5a-124c-428e-bb07-4da24531b175/527-2
00:03:05.960 --> 00:03:06.710
preference.
a063df5a-124c-428e-bb07-4da24531b175/535-0
00:03:06.710 --> 00:03:08.750
We really want to dig into that case.
a063df5a-124c-428e-bb07-4da24531b175/544-0
00:03:08.750 --> 00:03:10.950
We want to understand all the variables.
a063df5a-124c-428e-bb07-4da24531b175/545-0
00:03:11.110 --> 00:03:12.190
What happened?
a063df5a-124c-428e-bb07-4da24531b175/552-0
00:03:12.430 --> 00:03:16.750
So how do we take the administrative data,
the EMR data?
a063df5a-124c-428e-bb07-4da24531b175/563-0
00:03:17.560 --> 00:03:22.600
And the abstracted data and create one
source of truth that we can really guide.
a063df5a-124c-428e-bb07-4da24531b175/571-0
00:03:23.110 --> 00:03:25.710
Our teams to move improvement.
a063df5a-124c-428e-bb07-4da24531b175/576-0
00:03:25.710 --> 00:03:28.110
So that's the work that we're doing right
now.
a063df5a-124c-428e-bb07-4da24531b175/583-0
00:03:28.110 --> 00:03:31.190
It's really trying to pull that together
to create one source.
a063df5a-124c-428e-bb07-4da24531b175/620-0
00:03:31.800 --> 00:03:34.762
Yeah.
And I understand that it's been difficult
a063df5a-124c-428e-bb07-4da24531b175/620-1
00:03:34.762 --> 00:03:39.267
to get clinicians to buy into that
administrative coding data and to get
a063df5a-124c-428e-bb07-4da24531b175/620-2
00:03:39.267 --> 00:03:43.833
them to trust the claims data because
there may be a lack of trust in the
a063df5a-124c-428e-bb07-4da24531b175/620-3
00:03:43.833 --> 00:03:45.560
validity of that payer data.
a063df5a-124c-428e-bb07-4da24531b175/633-0
00:03:45.560 --> 00:03:50.200
How are you overcoming that kind of
skepticism on the part of clinicians?
a063df5a-124c-428e-bb07-4da24531b175/654-0
00:03:50.420 --> 00:03:53.219
We have to know our data and I think
that's, you know,
a063df5a-124c-428e-bb07-4da24531b175/654-1
00:03:53.219 --> 00:03:57.239
whether you're on the clinical side or
you're on the on the tech side is we've
a063df5a-124c-428e-bb07-4da24531b175/654-2
00:03:57.239 --> 00:03:58.460
really got to review it.
a063df5a-124c-428e-bb07-4da24531b175/660-0
00:03:58.460 --> 00:03:59.700
We've got to get dirty with it.
a063df5a-124c-428e-bb07-4da24531b175/665-0
00:03:59.700 --> 00:04:01.220
You got to get your hands in the data.
a063df5a-124c-428e-bb07-4da24531b175/685-0
00:04:01.220 --> 00:04:04.603
So what we have found,
we are seeing the same thing within our
a063df5a-124c-428e-bb07-4da24531b175/685-1
00:04:04.603 --> 00:04:07.180
administrative data that's also being
reported.
a063df5a-124c-428e-bb07-4da24531b175/700-0
00:04:07.540 --> 00:04:10.470
Our validity is a little bit better as
far as reliability,
a063df5a-124c-428e-bb07-4da24531b175/700-1
00:04:10.470 --> 00:04:14.492
but I mean you're really looking at about
80% of that because the administrative
a063df5a-124c-428e-bb07-4da24531b175/700-2
00:04:14.492 --> 00:04:14.740
data.
a063df5a-124c-428e-bb07-4da24531b175/721-0
00:04:15.440 --> 00:04:19.150
Has a tendency to overcode history of,
so that's what we're seeing is when we're
a063df5a-124c-428e-bb07-4da24531b175/721-1
00:04:19.150 --> 00:04:22.080
getting triggered from mom that had a
very severe complication.
a063df5a-124c-428e-bb07-4da24531b175/767-0
00:04:22.750 --> 00:04:27.108
Based on a coding we're looking back and
realizing she has a history of some
a063df5a-124c-428e-bb07-4da24531b175/767-1
00:04:27.108 --> 00:04:31.862
cardiomyopathy or a history of stroke and
then that pops up as a trigger and that's
a063df5a-124c-428e-bb07-4da24531b175/767-2
00:04:31.862 --> 00:04:36.559
what we're publicly reporting and that's
where we lose the trust of our clinicians
a063df5a-124c-428e-bb07-4da24531b175/767-3
00:04:36.559 --> 00:04:38.200
and our program managers and.
a063df5a-124c-428e-bb07-4da24531b175/791-0
00:04:38.200 --> 00:04:41.915
Our nursing abstractors at the site
saying, hey, our data's not right.
a063df5a-124c-428e-bb07-4da24531b175/791-1
00:04:41.915 --> 00:04:45.578
So we've got to take those triggers.
We've got to abstract and really
a063df5a-124c-428e-bb07-4da24531b175/791-2
00:04:45.578 --> 00:04:46.310
understand it.
a063df5a-124c-428e-bb07-4da24531b175/808-0
00:04:46.310 --> 00:04:50.397
And then we have to visualize it,
make it digestible and bring it back to
a063df5a-124c-428e-bb07-4da24531b175/808-1
00:04:50.397 --> 00:04:52.550
the teams into a product that they can.
a063df5a-124c-428e-bb07-4da24531b175/812-0
00:04:53.750 --> 00:04:54.230
Actually mute.
a063df5a-124c-428e-bb07-4da24531b175/814-0
00:04:54.230 --> 00:04:54.830
So very labor intensive.
a063df5a-124c-428e-bb07-4da24531b175/823-0
00:04:56.000 --> 00:04:56.560
So.
a063df5a-124c-428e-bb07-4da24531b175/832-0
00:04:57.160 --> 00:05:00.248
But to have the move forward to using our
EMR to do some of that cleaning
a063df5a-124c-428e-bb07-4da24531b175/832-1
00:05:00.248 --> 00:05:01.040
abstraction for us.
a063df5a-124c-428e-bb07-4da24531b175/851-0
00:05:01.670 --> 00:05:06.435
So as all of our listeners will know,
there are two main buckets of analytic of
a063df5a-124c-428e-bb07-4da24531b175/851-1
00:05:06.435 --> 00:05:07.030
reporting.
a063df5a-124c-428e-bb07-4da24531b175/860-0
00:05:07.030 --> 00:05:11.339
There's analytical and operational.
The analytical often people associate
a063df5a-124c-428e-bb07-4da24531b175/860-1
00:05:11.339 --> 00:05:11.630
with.
a063df5a-124c-428e-bb07-4da24531b175/888-0
00:05:13.100 --> 00:05:17.316
Historical chart reviews and claims
reviews for something that happened
a063df5a-124c-428e-bb07-4da24531b175/888-1
00:05:17.316 --> 00:05:21.707
potentially months ago and operational
something that happens real time is
a063df5a-124c-428e-bb07-4da24531b175/888-2
00:05:21.707 --> 00:05:23.580
actionable at the point of care.
a063df5a-124c-428e-bb07-4da24531b175/900-0
00:05:25.260 --> 00:05:29.020
Have you any experience working with fire
or is that on your road map at all?
a063df5a-124c-428e-bb07-4da24531b175/907-0
00:05:29.640 --> 00:05:30.560
Well, we definitely have.
a063df5a-124c-428e-bb07-4da24531b175/928-0
00:05:30.560 --> 00:05:34.783
And so I think we we use fire more from
an operational efficiency perspective
a063df5a-124c-428e-bb07-4da24531b175/928-1
00:05:34.783 --> 00:05:38.680
where we're thinking, OK, hey,
where do we have barriers for discharge?
a063df5a-124c-428e-bb07-4da24531b175/955-0
00:05:38.680 --> 00:05:43.549
So how do we build that into our Emrs to
flag a a mom that has already shown me
a063df5a-124c-428e-bb07-4da24531b175/955-1
00:05:43.549 --> 00:05:45.800
some signs or changes in vital signs?
a063df5a-124c-428e-bb07-4da24531b175/975-0
00:05:45.800 --> 00:05:49.781
Or maybe there's some delays that are
already occurring so that way we can
a063df5a-124c-428e-bb07-4da24531b175/975-1
00:05:49.781 --> 00:05:53.232
mitigate that quickly.
Just really to ensure efficiency decrease
a063df5a-124c-428e-bb07-4da24531b175/975-2
00:05:53.232 --> 00:05:54.240
our length of stay.
a063df5a-124c-428e-bb07-4da24531b175/991-0
00:05:55.000 --> 00:05:58.592
But we're really wanting to do is how do
we actually use fire and look at safe
a063df5a-124c-428e-bb07-4da24531b175/991-1
00:05:58.592 --> 00:06:00.320
postpartum hemorrhage risk assessment.
a063df5a-124c-428e-bb07-4da24531b175/1017-0
00:06:01.570 --> 00:06:06.882
How do we know a mom truly is at risk for
hemorrhage and utilizing that technology
a063df5a-124c-428e-bb07-4da24531b175/1017-1
00:06:06.882 --> 00:06:11.618
to alert these teams to increase the
awareness to really monitor that mom
a063df5a-124c-428e-bb07-4da24531b175/1017-2
00:06:11.618 --> 00:06:12.130
closely?
a063df5a-124c-428e-bb07-4da24531b175/1020-0
00:06:13.730 --> 00:06:14.050
Got it.
a063df5a-124c-428e-bb07-4da24531b175/1044-0
00:06:14.050 --> 00:06:18.970
So I think that there's a if there's a
real time risk of hemorrhage,
a063df5a-124c-428e-bb07-4da24531b175/1044-1
00:06:18.970 --> 00:06:24.530
you're looking at using these reports to
prevent bad outcomes and the target.
a063df5a-124c-428e-bb07-4da24531b175/1072-0
00:06:25.940 --> 00:06:29.958
You can't monitor every single woman who
delivers for being at high risk for a
a063df5a-124c-428e-bb07-4da24531b175/1072-1
00:06:29.958 --> 00:06:33.212
postpartum hemorrhage,
but you're kind of identifying the ideal
a063df5a-124c-428e-bb07-4da24531b175/1072-2
00:06:33.212 --> 00:06:35.500
target population where the care gap may
be.
a063df5a-124c-428e-bb07-4da24531b175/1089-0
00:06:35.500 --> 00:06:41.230
Have you had any success in reducing the
rates of postpartum hemorrhage because of
a063df5a-124c-428e-bb07-4da24531b175/1089-1
00:06:41.230 --> 00:06:44.060
these risk assessments and the analytics?
a063df5a-124c-428e-bb07-4da24531b175/1094-0
00:06:44.450 --> 00:06:45.850
Provided by fire in real time.
a063df5a-124c-428e-bb07-4da24531b175/1125-0
00:06:46.250 --> 00:06:48.717
Not yet,
but we are looking at is really the
a063df5a-124c-428e-bb07-4da24531b175/1125-1
00:06:48.717 --> 00:06:53.102
maternal early warning and so that's the
analysis that we're doing right now or
a063df5a-124c-428e-bb07-4da24531b175/1125-2
00:06:53.102 --> 00:06:56.172
what are the signs,
the vital signs that a mom has that
a063df5a-124c-428e-bb07-4da24531b175/1125-3
00:06:56.172 --> 00:07:00.009
really has subtle changes that are
increasing her risk for morbidity,
a063df5a-124c-428e-bb07-4da24531b175/1125-4
00:07:00.009 --> 00:07:01.050
what we're looking.
a063df5a-124c-428e-bb07-4da24531b175/1153-0
00:07:01.050 --> 00:07:03.518
At right now is.
What is that impact on ICU?
a063df5a-124c-428e-bb07-4da24531b175/1153-1
00:07:03.518 --> 00:07:06.479
So how soon can we identify a change in a
vital sign,
a063df5a-124c-428e-bb07-4da24531b175/1153-2
00:07:06.479 --> 00:07:10.153
whether it's a mom's heart rate,
her mean arterial blood pressure,
a063df5a-124c-428e-bb07-4da24531b175/1153-3
00:07:10.153 --> 00:07:12.730
or even just some of the hypertension
disease?
a063df5a-124c-428e-bb07-4da24531b175/1164-0
00:07:13.360 --> 00:07:15.742
What are those warnings that are going to
prevent her from going to the ICU for
a063df5a-124c-428e-bb07-4da24531b175/1164-1
00:07:15.742 --> 00:07:15.920
early?
a063df5a-124c-428e-bb07-4da24531b175/1166-0
00:07:16.310 --> 00:07:16.470
OK.
a063df5a-124c-428e-bb07-4da24531b175/1197-0
00:07:17.260 --> 00:07:22.104
Hi Kendra I think you mentioned that you
are A6 Sigma black belt and there have
a063df5a-124c-428e-bb07-4da24531b175/1181-0
00:07:21.330 --> 00:07:21.690
Yeah.
a063df5a-124c-428e-bb07-4da24531b175/1197-1
00:07:22.104 --> 00:07:26.706
been different reports that have offer
conflicting insights and you've been
a063df5a-124c-428e-bb07-4da24531b175/1197-2
00:07:26.706 --> 00:07:28.340
working to reconcile those.
a063df5a-124c-428e-bb07-4da24531b175/1203-0
00:07:28.340 --> 00:07:31.260
Would you mind elaborating upon your
efforts there?
a063df5a-124c-428e-bb07-4da24531b175/1210-0
00:07:32.550 --> 00:07:33.910
You know, we'll just stay with epic.
a063df5a-124c-428e-bb07-4da24531b175/1238-0
00:07:33.910 --> 00:07:36.556
I mean,
there's some really great product there
a063df5a-124c-428e-bb07-4da24531b175/1238-1
00:07:36.556 --> 00:07:40.469
and there's some good reporting.
I think what happens is if we have so
a063df5a-124c-428e-bb07-4da24531b175/1238-2
00:07:40.469 --> 00:07:43.665
much data that's coming out and the
definitions conflict,
a063df5a-124c-428e-bb07-4da24531b175/1238-3
00:07:43.665 --> 00:07:46.310
So what populations are we actually
looking at?
a063df5a-124c-428e-bb07-4da24531b175/1245-0
00:07:46.310 --> 00:07:47.950
How are these reports written?
a063df5a-124c-428e-bb07-4da24531b175/1264-0
00:07:48.390 --> 00:07:52.408
But how are we gonna use them?
That is our biggest struggle is not only
a063df5a-124c-428e-bb07-4da24531b175/1264-1
00:07:52.408 --> 00:07:56.761
just having the consistency and the
cleanness of the data, but having to use,
a063df5a-124c-428e-bb07-4da24531b175/1264-2
00:07:56.761 --> 00:07:57.430
for example.
a063df5a-124c-428e-bb07-4da24531b175/1278-0
00:07:58.080 --> 00:08:00.480
With severe maternal morbidity,
which is a very important measure and
a063df5a-124c-428e-bb07-4da24531b175/1278-1
00:08:00.480 --> 00:08:01.920
definition for those severe complications.
a063df5a-124c-428e-bb07-4da24531b175/1283-0
00:08:01.990 --> 00:08:02.990
It's her mom's.
a063df5a-124c-428e-bb07-4da24531b175/1293-0
00:08:02.990 --> 00:08:07.503
There are three definitions that we have
to report and have to educate our teams
a063df5a-124c-428e-bb07-4da24531b175/1293-1
00:08:07.503 --> 00:08:07.670
on.
a063df5a-124c-428e-bb07-4da24531b175/1313-0
00:08:08.070 --> 00:08:11.339
So you have three different reports
coming out with three different
a063df5a-124c-428e-bb07-4da24531b175/1313-1
00:08:11.339 --> 00:08:14.270
numerators, 3 different denominators,
different definitions.
a063df5a-124c-428e-bb07-4da24531b175/1318-0
00:08:14.270 --> 00:08:15.710
What do you do with that?
a063df5a-124c-428e-bb07-4da24531b175/1322-0
00:08:15.750 --> 00:08:17.310
What do you act on that?
a063df5a-124c-428e-bb07-4da24531b175/1338-0
00:08:17.310 --> 00:08:21.879
So it's taking a step back,
aligning that up strategically to create
a063df5a-124c-428e-bb07-4da24531b175/1338-1
00:08:21.879 --> 00:08:24.990
one system of truth that our teams can
act on.
a063df5a-124c-428e-bb07-4da24531b175/1341-0
00:08:25.980 --> 00:08:26.380
Got it.
a063df5a-124c-428e-bb07-4da24531b175/1388-0
00:08:26.380 --> 00:08:30.972
So it sounds like there's an issue that
we covered at the beginning of this
a063df5a-124c-428e-bb07-4da24531b175/1388-1
00:08:30.972 --> 00:08:33.933
discussion about whether data is clean or
dirty,
a063df5a-124c-428e-bb07-4da24531b175/1388-2
00:08:33.933 --> 00:08:38.645
but it's also possible to have fully
accurate data in three different reports
a063df5a-124c-428e-bb07-4da24531b175/1388-3
00:08:38.645 --> 00:08:43.056
that conflict with each other,
because even though the data is accurate,
a063df5a-124c-428e-bb07-4da24531b175/1388-4
00:08:43.056 --> 00:08:43.660
the defin.
a063df5a-124c-428e-bb07-4da24531b175/1395-0
00:08:43.780 --> 00:08:45.260
'S conflicting aren't standardized.
a063df5a-124c-428e-bb07-4da24531b175/1412-0
00:08:45.300 --> 00:08:49.679
And so that presents a challenge for
healthcare providers who are looking to
a063df5a-124c-428e-bb07-4da24531b175/1412-1
00:08:49.679 --> 00:08:52.180
have one golden record and source of
truth.
a063df5a-124c-428e-bb07-4da24531b175/1447-0
00:08:53.140 --> 00:08:55.926
Correct.
And then if it was April 30 and then if
a063df5a-124c-428e-bb07-4da24531b175/1419-0
00:08:53.770 --> 00:08:54.810
Have you been?
a063df5a-124c-428e-bb07-4da24531b175/1447-1
00:08:55.926 --> 00:08:59.507
you're having reporting issues or
workflow entry issues or the
a063df5a-124c-428e-bb07-4da24531b175/1447-2
00:08:59.507 --> 00:09:03.940
documentation's not done in the right
place, it's not gonna feed your report.
a063df5a-124c-428e-bb07-4da24531b175/1459-0
00:09:04.100 --> 00:09:09.803
So how are we're documenting the workload
is so essential in the success and the
a063df5a-124c-428e-bb07-4da24531b175/1459-1
00:09:09.803 --> 00:09:11.140
clean data process.
a063df5a-124c-428e-bb07-4da24531b175/1461-0
00:09:12.770 --> 00:09:13.650
Is there?
a063df5a-124c-428e-bb07-4da24531b175/1481-0
00:09:15.420 --> 00:09:20.916
Can you walk us through what the what
kind of interventions you've been working
a063df5a-124c-428e-bb07-4da24531b175/1481-1
00:09:20.916 --> 00:09:24.900
on to improve documentation workflow at
Memorial Hermann?
a063df5a-124c-428e-bb07-4da24531b175/1511-0
00:09:25.540 --> 00:09:29.625
So as a six figure black belt,
one of the projects we had as we did our
a063df5a-124c-428e-bb07-4da24531b175/1511-1
00:09:29.625 --> 00:09:34.220
epic conversion is we've really had to
analyze our data all across the spectrum.
a063df5a-124c-428e-bb07-4da24531b175/1516-0
00:09:34.700 --> 00:09:37.740
What are the reports doing process
mapping?
a063df5a-124c-428e-bb07-4da24531b175/1537-0
00:09:38.020 --> 00:09:42.014
Understanding the data going,
we call go to Gimba which is going and
a063df5a-124c-428e-bb07-4da24531b175/1537-1
00:09:42.014 --> 00:09:46.180
working with those clinicians at the
frontline to look at the workflow.
a063df5a-124c-428e-bb07-4da24531b175/1539-0
00:09:46.700 --> 00:09:48.100
How are they documenting?
a063df5a-124c-428e-bb07-4da24531b175/1543-0
00:09:48.220 --> 00:09:49.300
Where are they doing it?
a063df5a-124c-428e-bb07-4da24531b175/1550-0
00:09:49.300 --> 00:09:52.060
What makes sense to workflow and how does
that documentation?
a063df5a-124c-428e-bb07-4da24531b175/1555-0
00:09:52.960 --> 00:09:54.320
Feed into the reporting.
a063df5a-124c-428e-bb07-4da24531b175/1559-0
00:09:54.750 --> 00:09:55.550
The revenue.
a063df5a-124c-428e-bb07-4da24531b175/1569-0
00:09:55.630 --> 00:09:59.270
The charge drops and all of the output
that are required.
a063df5a-124c-428e-bb07-4da24531b175/1574-0
00:09:59.310 --> 00:10:01.710
What we're finding is a significant
amount of variation there.
a063df5a-124c-428e-bb07-4da24531b175/1592-0
00:10:02.810 --> 00:10:08.170
So we've had to really do some work to
standardize documentation.
a063df5a-124c-428e-bb07-4da24531b175/1598-0
00:10:08.320 --> 00:10:09.680
Standardized template.
a063df5a-124c-428e-bb07-4da24531b175/1623-0
00:10:09.750 --> 00:10:14.482
Standardized order sets and workflows and
then kind of reconfigure how we're
a063df5a-124c-428e-bb07-4da24531b175/1623-1
00:10:14.482 --> 00:10:18.476
working in the application,
then going back to the reporting and
a063df5a-124c-428e-bb07-4da24531b175/1623-2
00:10:18.476 --> 00:10:22.470
analytics to to redesign and reprogram
what those workflows are.
a063df5a-124c-428e-bb07-4da24531b175/1660-0
00:10:23.160 --> 00:10:25.615
Many of our listeners may be thinking,
you know,
a063df5a-124c-428e-bb07-4da24531b175/1660-1
00:10:25.615 --> 00:10:29.523
we've tried to implement standardized
checklists and standardized procedures,
a063df5a-124c-428e-bb07-4da24531b175/1660-2
00:10:29.523 --> 00:10:33.080
but there's been a lot of pushback from
different kinds of clinicians.
a063df5a-124c-428e-bb07-4da24531b175/1677-0
00:10:33.080 --> 00:10:36.485
The one physician says, well,
this is the way we did it in residency
a063df5a-124c-428e-bb07-4da24531b175/1677-1
00:10:36.485 --> 00:10:38.360
and the other one does it differently.
a063df5a-124c-428e-bb07-4da24531b175/1699-0
00:10:38.360 --> 00:10:42.142
And then this nurse was trained on this
for at that institution and then left and
a063df5a-124c-428e-bb07-4da24531b175/1699-1
00:10:42.142 --> 00:10:45.970
came to this institution and wants to do
it that way because it worked over there.
a063df5a-124c-428e-bb07-4da24531b175/1699-2
00:10:45.970 --> 00:10:46.800
How do you handle?
a063df5a-124c-428e-bb07-4da24531b175/1716-0
00:10:47.930 --> 00:10:51.846
Cultural change as you're trying to make
sure that you're following standard
a063df5a-124c-428e-bb07-4da24531b175/1716-1
00:10:51.846 --> 00:10:53.930
processes to improve the quality of data.
a063df5a-124c-428e-bb07-4da24531b175/1727-0
00:10:54.560 --> 00:10:58.760
And therefore improve patient health with
actionable real time insights.
a063df5a-124c-428e-bb07-4da24531b175/1756-0
00:10:59.100 --> 00:11:02.886
We would be very intentional with this as
an organization with almost 32,
a063df5a-124c-428e-bb07-4da24531b175/1756-1
00:11:02.886 --> 00:11:05.854
000 deliveries,
we have 10 campuses and I always think of
a063df5a-124c-428e-bb07-4da24531b175/1756-2
00:11:05.854 --> 00:11:07.900
us as a star track enterprise starships.
a063df5a-124c-428e-bb07-4da24531b175/1765-0
00:11:07.900 --> 00:11:10.660
Everybody's got a different,
different kind of ship.
a063df5a-124c-428e-bb07-4da24531b175/1774-0
00:11:10.660 --> 00:11:12.500
They're running where a plurist model.
a063df5a-124c-428e-bb07-4da24531b175/1782-0
00:11:12.500 --> 00:11:15.140
So we've got a global 4 academic facility.
a063df5a-124c-428e-bb07-4da24531b175/1786-0
00:11:15.140 --> 00:11:16.140
We've got quite a physician.
a063df5a-124c-428e-bb07-4da24531b175/1817-0
00:11:16.140 --> 00:11:18.961
We have employee positions,
so we really had to create an
a063df5a-124c-428e-bb07-4da24531b175/1817-1
00:11:18.961 --> 00:11:22.949
organizational structure and governance.
That way we were collaboratively working
a063df5a-124c-428e-bb07-4da24531b175/1817-2
00:11:22.949 --> 00:11:25.186
together.
So we have what we call a perinatal
a063df5a-124c-428e-bb07-4da24531b175/1817-3
00:11:25.186 --> 00:11:27.860
quality collaborative within the
organization we have.
a063df5a-124c-428e-bb07-4da24531b175/1819-0
00:11:27.860 --> 00:11:28.840
We meet every month.
a063df5a-124c-428e-bb07-4da24531b175/1834-0
00:11:29.070 --> 00:11:33.102
Where we bring all of this together,
we have work groups and so stakeholder
a063df5a-124c-428e-bb07-4da24531b175/1834-1
00:11:33.102 --> 00:11:33.950
analysis is key.
a063df5a-124c-428e-bb07-4da24531b175/1855-0
00:11:33.950 --> 00:11:38.933
We've got to have the right folks at the
table and leading conversation and
a063df5a-124c-428e-bb07-4da24531b175/1855-1
00:11:38.933 --> 00:11:42.670
collaborating,
so we're not wanting to be authoritative.
a063df5a-124c-428e-bb07-4da24531b175/1882-0
00:11:43.070 --> 00:11:47.021
We as the hospital organization,
I'm not managing physician practice,
a063df5a-124c-428e-bb07-4da24531b175/1882-1
00:11:47.021 --> 00:11:51.593
but we've got to come to some consensus.
And so it's working to consensus in the
a063df5a-124c-428e-bb07-4da24531b175/1882-2
00:11:51.593 --> 00:11:53.230
best evidence based practice.
a063df5a-124c-428e-bb07-4da24531b175/1892-0
00:11:54.440 --> 00:11:57.480
And taking that to the right governance
structures for approval.
a063df5a-124c-428e-bb07-4da24531b175/1919-0
00:11:57.910 --> 00:12:00.640
Once those are approved,
then we put those in place for
a063df5a-124c-428e-bb07-4da24531b175/1919-1
00:12:00.640 --> 00:12:04.344
standardizing them and then doing that
education, Pete as well as auditing.
a063df5a-124c-428e-bb07-4da24531b175/1919-2
00:12:04.344 --> 00:12:05.270
We've got to audit.
a063df5a-124c-428e-bb07-4da24531b175/1936-0
00:12:05.270 --> 00:12:07.886
We've got to bring that back to our
quality and assurance performance
a063df5a-124c-428e-bb07-4da24531b175/1936-1
00:12:07.886 --> 00:12:10.651
improvement committees or the quality
committees to make sure that we are
a063df5a-124c-428e-bb07-4da24531b175/1936-2
00:12:10.651 --> 00:12:11.510
managing that standard.
a063df5a-124c-428e-bb07-4da24531b175/1969-0
00:12:12.100 --> 00:12:15.457
As you mentioned Kendra,
at the start of this discussion,
a063df5a-124c-428e-bb07-4da24531b175/1969-1
00:12:15.457 --> 00:12:19.451
you are the Chair of the data committee
at the state level in Texas.
a063df5a-124c-428e-bb07-4da24531b175/1969-2
00:12:19.451 --> 00:12:23.907
And I think you have had some experience
with reluctancy of different health
a063df5a-124c-428e-bb07-4da24531b175/1969-3
00:12:23.907 --> 00:12:25.180
systems to share data.
a063df5a-124c-428e-bb07-4da24531b175/1986-0
00:12:26.610 --> 00:12:28.783
At the,
either with the state or with each other,
a063df5a-124c-428e-bb07-4da24531b175/1986-1
00:12:28.783 --> 00:12:30.130
would you care to elaborate on?
a063df5a-124c-428e-bb07-4da24531b175/1994-0
00:12:30.210 --> 00:12:32.276
Obviously,
some patients are getting care well
a063df5a-124c-428e-bb07-4da24531b175/1994-1
00:12:32.276 --> 00:12:34.210
system and moving to another health
system.
a063df5a-124c-428e-bb07-4da24531b175/2008-0
00:12:34.450 --> 00:12:37.467
Different.
How do you how do you get kind of an
a063df5a-124c-428e-bb07-4da24531b175/2008-1
00:12:37.467 --> 00:12:40.610
accurate record of 1 mother coming in to
deliver?
a063df5a-124c-428e-bb07-4da24531b175/2010-0
00:12:42.250 --> 00:12:42.450
And how?
a063df5a-124c-428e-bb07-4da24531b175/2018-0
00:12:42.680 --> 00:12:45.360
The different data sharing issues playing
into that.
a063df5a-124c-428e-bb07-4da24531b175/2032-0
00:12:45.570 --> 00:12:49.788
One, I think we're just not.
I think we're not getting a good story of
a063df5a-124c-428e-bb07-4da24531b175/2032-1
00:12:49.788 --> 00:12:51.570
moms working across the state.
a063df5a-124c-428e-bb07-4da24531b175/2035-0
00:12:51.730 --> 00:12:54.050
I think we're also struggling.
a063df5a-124c-428e-bb07-4da24531b175/2069-0
00:12:54.130 --> 00:12:58.173
I think Epic truly with the my chart have
been the best interoperability that we've
a063df5a-124c-428e-bb07-4da24531b175/2069-1
00:12:58.173 --> 00:13:01.447
been able to find so far.
I think even just within Houston and some
a063df5a-124c-428e-bb07-4da24531b175/2069-2
00:13:01.447 --> 00:13:05.297
of the work we're doing, to your point,
women go to different organizations all
a063df5a-124c-428e-bb07-4da24531b175/2069-3
00:13:05.297 --> 00:13:05.730
the time.
a063df5a-124c-428e-bb07-4da24531b175/2075-0
00:13:05.810 --> 00:13:07.610
I'm going to go to what's ever easier.
a063df5a-124c-428e-bb07-4da24531b175/2081-0
00:13:07.610 --> 00:13:08.530
I'm going to go to the Ed.
a063df5a-124c-428e-bb07-4da24531b175/2082-0
00:13:08.530 --> 00:13:09.330
That's fastest.
a063df5a-124c-428e-bb07-4da24531b175/2085-0
00:13:09.370 --> 00:13:10.570
Not necessarily the same.
a063df5a-124c-428e-bb07-4da24531b175/2090-0
00:13:11.280 --> 00:13:14.000
It's changing that with,
you know whether it's HIPAA.
a063df5a-124c-428e-bb07-4da24531b175/2115-0
00:13:15.270 --> 00:13:20.402
Rules, whether it's organizational,
reluctancy and protectivity of client
a063df5a-124c-428e-bb07-4da24531b175/2115-1
00:13:20.402 --> 00:13:25.950
data as well as nobody wants to to to all
the things nobody wants to have their
a063df5a-124c-428e-bb07-4da24531b175/2115-2
00:13:25.950 --> 00:13:28.030
information used against them.
a063df5a-124c-428e-bb07-4da24531b175/2126-0
00:13:28.390 --> 00:13:33.718
So even at the state level with the state
is reluctant to have their data
a063df5a-124c-428e-bb07-4da24531b175/2126-1
00:13:33.718 --> 00:13:34.510
publicized.
a063df5a-124c-428e-bb07-4da24531b175/2151-0
00:13:34.510 --> 00:13:38.655
I know there was an article that just
recently came out with Pro Publica that
a063df5a-124c-428e-bb07-4da24531b175/2151-1
00:13:38.655 --> 00:13:41.950
there's just this reluctance to be being
seen in a bad light.
a063df5a-124c-428e-bb07-4da24531b175/2154-0
00:13:41.950 --> 00:13:43.550
So everybody's very protective.
a063df5a-124c-428e-bb07-4da24531b175/2173-0
00:13:43.790 --> 00:13:46.955
Of the information and again adding in
PIPA,
a063df5a-124c-428e-bb07-4da24531b175/2173-1
00:13:46.955 --> 00:13:52.230
well it just adds a little bit more
difficulty in exchange of information.
a063df5a-124c-428e-bb07-4da24531b175/2182-0
00:13:52.630 --> 00:13:55.870
So there's political barriers,
economic barriers.
a063df5a-124c-428e-bb07-4da24531b175/2190-0
00:13:57.370 --> 00:14:00.170
To share to getting interoperability
across health systems.
a063df5a-124c-428e-bb07-4da24531b175/2214-0
00:14:01.730 --> 00:14:06.594
And clinicians are just trying to provide
care and it's difficult to exchange data
a063df5a-124c-428e-bb07-4da24531b175/2214-1
00:14:06.594 --> 00:14:10.930
in a way that is in the best interest of
the patient is what I'm hearing.
a063df5a-124c-428e-bb07-4da24531b175/2215-0
00:14:10.970 --> 00:14:12.530
Correct. Absolutely.
a063df5a-124c-428e-bb07-4da24531b175/2245-0
00:14:12.690 --> 00:14:16.713
Now you mentioned that automating data
collection reporting would potentially
a063df5a-124c-428e-bb07-4da24531b175/2245-1
00:14:16.713 --> 00:14:20.065
add value and potentially if you could
automate data collection,
a063df5a-124c-428e-bb07-4da24531b175/2245-2
00:14:20.065 --> 00:14:22.850
maybe you could overcome some of those
interoperable.
a063df5a-124c-428e-bb07-4da24531b175/2258-0
00:14:23.200 --> 00:14:26.653
Ability challenges.
Have you had any experience working on
a063df5a-124c-428e-bb07-4da24531b175/2258-1
00:14:26.653 --> 00:14:29.520
the automation of data collection and
reporting?
a063df5a-124c-428e-bb07-4da24531b175/2272-0
00:14:30.280 --> 00:14:32.320
Well,
I think we're trying to I think just take
a063df5a-124c-428e-bb07-4da24531b175/2272-1
00:14:32.320 --> 00:14:33.680
them within my own organization.
a063df5a-124c-428e-bb07-4da24531b175/2307-0
00:14:33.680 --> 00:14:37.937
That's exactly what we're trying to do
when we're looking at how do we automate
a063df5a-124c-428e-bb07-4da24531b175/2307-1
00:14:37.937 --> 00:14:42.088
data collection and abstraction just for
all of our state recording is that's
a063df5a-124c-428e-bb07-4da24531b175/2307-2
00:14:42.088 --> 00:14:45.600
where we're really trying to do this at a
pilot level internally.
a063df5a-124c-428e-bb07-4da24531b175/2321-0
00:14:45.720 --> 00:14:48.840
How do we utilize the EMR with the claims
data to audit?
a063df5a-124c-428e-bb07-4da24531b175/2325-0
00:14:48.840 --> 00:14:50.800
We're building something we're calling
the motherboard.
a063df5a-124c-428e-bb07-4da24531b175/2350-0
00:14:51.240 --> 00:14:55.863
So how do we take this motherboard
feeding automatically and doing some
a063df5a-124c-428e-bb07-4da24531b175/2350-1
00:14:55.863 --> 00:14:58.560
minimal abstraction to complete the story?
a063df5a-124c-428e-bb07-4da24531b175/2352-0
00:14:58.680 --> 00:15:00.080
And then we have a final.
a063df5a-124c-428e-bb07-4da24531b175/2367-0
00:15:00.230 --> 00:15:02.444
Product.
But we're also looking at how do we do
a063df5a-124c-428e-bb07-4da24531b175/2367-1
00:15:02.444 --> 00:15:03.550
that at the state level?
a063df5a-124c-428e-bb07-4da24531b175/2396-0
00:15:03.550 --> 00:15:08.302
Now California has done that well in this
in this population where you like in the
a063df5a-124c-428e-bb07-4da24531b175/2396-1
00:15:08.302 --> 00:15:12.652
Emrs are automatically reporting.
There's some automation particularly with
a063df5a-124c-428e-bb07-4da24531b175/2396-2
00:15:12.652 --> 00:15:15.285
epic,
with the Vermont Oxford Network and the
a063df5a-124c-428e-bb07-4da24531b175/2396-3
00:15:15.285 --> 00:15:16.430
neonatal population.
a063df5a-124c-428e-bb07-4da24531b175/2421-0
00:15:16.550 --> 00:15:21.301
So I think there's pockets of it.
The biggest opportunity in my perspective
a063df5a-124c-428e-bb07-4da24531b175/2421-1
00:15:21.301 --> 00:15:26.490
is how do we take what the piloting that
has been done and these piloting pilot in
a063df5a-124c-428e-bb07-4da24531b175/2421-2
00:15:26.490 --> 00:15:26.990
pockets.
a063df5a-124c-428e-bb07-4da24531b175/2426-0
00:15:27.760 --> 00:15:29.280
And how do we learn from those?
a063df5a-124c-428e-bb07-4da24531b175/2432-0
00:15:29.790 --> 00:15:31.870
To see how can we fill that up.
a063df5a-124c-428e-bb07-4da24531b175/2435-0
00:15:32.660 --> 00:15:33.020
Got it.
a063df5a-124c-428e-bb07-4da24531b175/2479-0
00:15:33.020 --> 00:15:35.248
Yeah.
The biggest opportunity is to scale
a063df5a-124c-428e-bb07-4da24531b175/2479-1
00:15:35.248 --> 00:15:39.596
little instances where it worked and see
if you spread it across the organization
a063df5a-124c-428e-bb07-4da24531b175/2479-2
00:15:39.596 --> 00:15:43.255
and that's when you might use your
position at the chair of the data
a063df5a-124c-428e-bb07-4da24531b175/2479-3
00:15:43.255 --> 00:15:47.339
committee at the state level or the
difference governance committees at each
a063df5a-124c-428e-bb07-4da24531b175/2479-4
00:15:47.339 --> 00:15:48.770
individual healthcare deli.
a063df5a-124c-428e-bb07-4da24531b175/2481-0
00:15:48.860 --> 00:15:49.260
System.
a063df5a-124c-428e-bb07-4da24531b175/2496-0
00:15:50.730 --> 00:15:54.208
We've covered a lot of different topics,
kind of approaching the end of this
a063df5a-124c-428e-bb07-4da24531b175/2496-1
00:15:54.208 --> 00:15:54.930
podcast episode.
a063df5a-124c-428e-bb07-4da24531b175/2499-0
00:15:54.930 --> 00:15:56.730
We've been moving quickly. We covered.
a063df5a-124c-428e-bb07-4da24531b175/2506-0
00:15:58.970 --> 00:16:01.810
Challenges with data being clean.
a063df5a-124c-428e-bb07-4da24531b175/2545-0
00:16:02.200 --> 00:16:06.713
Challenges with providers trusting the
data challenges of trying to get the data
a063df5a-124c-428e-bb07-4da24531b175/2545-1
00:16:06.713 --> 00:16:10.947
in real time so it provides actionable
insights and value to clinicians and
a063df5a-124c-428e-bb07-4da24531b175/2545-2
00:16:10.947 --> 00:16:14.680
patients when they're interacting with
each other in an encounter.
a063df5a-124c-428e-bb07-4da24531b175/2571-0
00:16:14.920 --> 00:16:19.733
Challenges with try to reconcile
different reports and then challenges and
a063df5a-124c-428e-bb07-4da24531b175/2571-1
00:16:19.733 --> 00:16:24.931
interoperability and automation for our
listeners who are also experiencing some
a063df5a-124c-428e-bb07-4da24531b175/2571-2
00:16:24.931 --> 00:16:26.920
of these same challenges. What?
a063df5a-124c-428e-bb07-4da24531b175/2582-0
00:16:28.210 --> 00:16:31.478
Is one word of advice.
If there you would potentially even give
a063df5a-124c-428e-bb07-4da24531b175/2582-1
00:16:31.478 --> 00:16:32.090
to yourself.
a063df5a-124c-428e-bb07-4da24531b175/2589-0
00:16:32.720 --> 00:16:35.080
A year ago or two years ago.
a063df5a-124c-428e-bb07-4da24531b175/2607-0
00:16:35.080 --> 00:16:38.994
What do you wish that you knew then that
you know now that may help some of our
a063df5a-124c-428e-bb07-4da24531b175/2607-1
00:16:38.994 --> 00:16:42.760
listeners as they're beginning to go down
the journey that you have been on.
a063df5a-124c-428e-bb07-4da24531b175/2625-0
00:16:43.680 --> 00:16:45.837
The most important thing I have learned
so far,
a063df5a-124c-428e-bb07-4da24531b175/2625-1
00:16:45.837 --> 00:16:49.520
whether it's in my own organization and
at the state level, if alignment is true.
a063df5a-124c-428e-bb07-4da24531b175/2647-0
00:16:50.160 --> 00:16:55.269
So we've got to line up with Cnf and the
external reporting measures and we're
a063df5a-124c-428e-bb07-4da24531b175/2647-1
00:16:55.269 --> 00:16:58.760
financially impact us.
We have to start from the top.
a063df5a-124c-428e-bb07-4da24531b175/2665-0
00:16:58.760 --> 00:17:05.400
That is how we get the resources and the
time to do this work and to get this data
a063df5a-124c-428e-bb07-4da24531b175/2665-1
00:17:05.400 --> 00:17:05.880
clean.
a063df5a-124c-428e-bb07-4da24531b175/2669-0
00:17:06.200 --> 00:17:08.320
It's very important. And So what we.
a063df5a-124c-428e-bb07-4da24531b175/2681-0
00:17:09.200 --> 00:17:12.639
Have found the most valuable in these
conversations is where we gonna make
a063df5a-124c-428e-bb07-4da24531b175/2681-1
00:17:12.639 --> 00:17:12.960
impact.
a063df5a-124c-428e-bb07-4da24531b175/2685-0
00:17:13.870 --> 00:17:15.870
Start very simple.
a063df5a-124c-428e-bb07-4da24531b175/2688-0
00:17:16.070 --> 00:17:17.470
What are we trying to do?
a063df5a-124c-428e-bb07-4da24531b175/2693-0
00:17:17.630 --> 00:17:18.750
What's our objective?
a063df5a-124c-428e-bb07-4da24531b175/2697-0
00:17:18.790 --> 00:17:20.150
Let's focus on mortality.
a063df5a-124c-428e-bb07-4da24531b175/2705-0
00:17:20.150 --> 00:17:23.150
Let's focus on morbidity decrease like
the state.
a063df5a-124c-428e-bb07-4da24531b175/2711-0
00:17:23.190 --> 00:17:25.030
How do we get the data to get there?
a063df5a-124c-428e-bb07-4da24531b175/2743-0
00:17:25.030 --> 00:17:29.392
What does the story we need and what is
the financial impact and that was the
a063df5a-124c-428e-bb07-4da24531b175/2743-1
00:17:29.392 --> 00:17:33.977
biggest piece is when we lined that all
the way up with our supplemental funding,
a063df5a-124c-428e-bb07-4da24531b175/2743-2
00:17:33.977 --> 00:17:35.430
our CMS, our IQR measures.
a063df5a-124c-428e-bb07-4da24531b175/2753-0
00:17:35.590 --> 00:17:39.430
Well, when you paint that picture,
there's a lot of monetary impact here.
a063df5a-124c-428e-bb07-4da24531b175/2758-0
00:17:39.510 --> 00:17:41.030
Not as well as just the impact of.
a063df5a-124c-428e-bb07-4da24531b175/2766-0
00:17:42.040 --> 00:17:43.320
The the lives of these moms and these
babies.
a063df5a-124c-428e-bb07-4da24531b175/2783-0
00:17:44.230 --> 00:17:50.267
And that was how we were able to get the
resources and the time to do this at a
a063df5a-124c-428e-bb07-4da24531b175/2783-1
00:17:50.267 --> 00:17:51.550
meaningful level.
a063df5a-124c-428e-bb07-4da24531b175/2836-0
00:17:52.160 --> 00:17:55.429
Got this.
So if you present a financial argument of
a063df5a-124c-428e-bb07-4da24531b175/2836-1
00:17:55.429 --> 00:17:58.194
return on investment to C-Suite
executives,
a063df5a-124c-428e-bb07-4da24531b175/2836-2
00:17:58.194 --> 00:18:02.908
then there may be an opportunity to
allocate resources in time in order to
a063df5a-124c-428e-bb07-4da24531b175/2836-3
00:18:02.908 --> 00:18:07.873
invest in these interventions to improve
the quality of data where it's needed
a063df5a-124c-428e-bb07-4da24531b175/2836-4
00:18:07.873 --> 00:18:10.010
when it's needed, how it's needed.
a063df5a-124c-428e-bb07-4da24531b175/2842-0
00:18:10.690 --> 00:18:12.970
And not just the speechwrit executive.
a063df5a-124c-428e-bb07-4da24531b175/2847-0
00:18:12.970 --> 00:18:13.730
Also to our legislature.
a063df5a-124c-428e-bb07-4da24531b175/2851-0
00:18:13.930 --> 00:18:15.730
And legislative as well.
a063df5a-124c-428e-bb07-4da24531b175/2881-0
00:18:15.770 --> 00:18:19.151
All right. Well, for our listeners,
this has been Kendra folh,
a063df5a-124c-428e-bb07-4da24531b175/2881-1
00:18:19.151 --> 00:18:23.284
the program director of Women's and
children's servicen for Memorial Hermann
a063df5a-124c-428e-bb07-4da24531b175/2881-2
00:18:23.284 --> 00:18:25.967
Kendra.
I'd like to thank you so much for joining
a063df5a-124c-428e-bb07-4da24531b175/2881-3
00:18:25.967 --> 00:18:26.450
us today.
a063df5a-124c-428e-bb07-4da24531b175/2883-0
00:18:26.820 --> 00:18:28.100
Thank you so much for having me.
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