Changes in healthcare disparities
following the implementation
of a multifaceted quality
improvement initiative
Muriel Jean-Jacques, MD, MAPP
Stephen D. Persell, MD, MPH
Romana Hasnain-Wynia, PhD
Jason A. Thompson, BA
David W. Baker, MD, MPH
Northwestern University Feinberg School of Medicine
Division of General Internal Medicine
Funding Source: AHRQ
Introduction

Health information technology (HIT) based
interventions have been shown to improve
the quality of care.

The effects of HIT-based interventions on
health equity have been less well studied.
Quality and Equity

Studies have not found a consistent
association between higher quality and
greater equity.

Most studies of quality and equity have
focused on racial and ethnic health
disparities; however disparities by gender,
health insurance, and socioeconomic
status have been similarly pervasive.
Study Aim

To assess the effects of a multifaceted HIT
based quality improvement initiative on
disparities in the quality of ambulatory care
 Examine
disparities by race, gender, and
socioeconomic status
 Assess quality through adherence to process of
care and intermediate outcome measures
Study Setting

Academic GIM practice in Chicago

37 attendings: 25,000 patients annually

Electronic health record system since 2002

Quarterly feedback to MDs on quality
since 2006
Intervention: UPQUAL Study


Implemented February 1, 2008
Provider-directed components
 Point-of-care
electronic alerts
 Standardized reporting of medical or patient
exceptions
 Regular feedback on performance

Patient-directed components
 Outreach
to patients who reported financial barriers
 Educational outreach to patients who declined
recommended tests or therapies
Quality Measures
Coronary Heart Disease
•
•
•
•
Antiplatelet therapy
Lipid lowering therapy
Beta-blocker therapy
ACE inhibitor or ARB
Heart Failure
•
•
•
ACE inhibitor or ARB
Beta-blocker therapy
Anticoagulation for Afib
Hypertension
•
BP control
Diabetes Mellitus
•
•
•
•
•
Glycemic control (A1C<8)
LDL control (LDL<100)
BP control
ASA for primary prevention
Nephropathy screening or Rx
Prevention
•
•
•
•
•
Cervical cancer screening
Breast cancer screening
Colorectal cancer Screening
Pneumococcal vaccination
Osteoporosis screening or Rx
Data Source and Subjects

Data extracted from electronic health record
 Patient
characteristics
 Quality deficiency: measure not satisfied and no
exception documented

10,599 patients
 Eligible
for at least 1 quality measure
 ≥ 2 visits within 18 months of baseline or follow-up
assessments
 Black or white race
 Sample size by measure ranged from 102 to 6,322
Statistical Methods

Multivariate logistic regression model
for each measure:
 Dependent
variable: quality deficiency
 Main independent variables:
Race: recorded by registration staff
 Gender
 SES: from geocoding
 % families below federal poverty level in census
block group
 % high school graduates in census block group
 Other covariates: age, insurance

Statistical Methods

Ran logistic regression models using baseline vs.
follow-up data
 Baseline
– January 1, 2008
 Follow-up – January 1, 2009


Post-model estimation of the adjusted % of
patients by group with quality deficiencies for
each measure
Calculation of adjusted difference in quality by
group
Results: Racial Disparities
There were racial disparities for 4 of 18 measures at baseline
Worse
QOC
for black
patients
Better
QOC
for black
patients
Adjusted Difference (%)
15
11.2
10
7.5
5.5
5
0
0
0
thy
HD
a
C
rop
-5 let in
h
ep
te
N
a
l
tip
DM
n
-7.8
A
0
A
M
nD
i
<8
C
1
teo
s
O
-10
Baseline
Follow-up
0
ros
o
p
is
Results: Racial Disparities
At follow-up, disparities were no longer statistically
significant for 2 of 4 measures
Worse
QOC
for black
patients
Better
QOC
for black
patients
Adjusted Difference (%)
15
11.2
10
7.5
5.5
5
6.1
*
1.2
0
8
*
thy
HD
DM
a
C
p
n
-2.7
i
-5 let in
hro
<8
p
C
e
e
t
N
A1
pla
M
i
t
D
-7.8
An
teo
s
O
-10
Baseline
Follow-up
ros
o
p
is
Results: Gender Disparities
There were gender disparities for 7 of 15 measures at baseline
9.1
Worse
QOC
for
women
Better
QOC
for
women
Adjusted Difference (%)
10
8.1
7.4
5.6
5
2
0
0
0
0
0
0
thy
HD
DM
DM
DM
a
C
p
n
n
n
ro
Li
8i
Ai
h
r in
<
D
S
p
e
L
A
1C
ck
Ne
A
o
l
DM
B-b
id
Lip
-5
0
Rx
-5.9
-10
Baseline
Follow-up
0
C
CR
-3.1
Results: Gender Disparities
At follow-up, gender disparities were no longer
significant for 4 of 7 measures
Worse
QOC
for
women
Better
QOC
for
women
Adjusted Difference (%)
10
9.1
8.1
7.4
5
*
2 2.3
2.9
*
0.7
*
3.7
5.6
*
1.7
0
thy
HD
RC
DM
DM
DM
a
C
C
p
n
n
n
i
i
i
o
r
r in
-3.1
3.3
<8
-3.1
DL
SA
ph
-3.3
e
L
C
A
e
k
1
c
N
A
lo
M
b
-4.9
D
B
id
Lip
-5
Rx
-5.9
-10
Baseline
Follow-up
Results: Disparities by SES
Worse
QOC
for
patients
from
poor
areas
Adjusted Difference (%)
There were disparities by neighborhood level poverty
for 2 of 18 measures at baseline
14
12.1
12
10
8
6
*
4
2.7
5.2
3.6
2
0
oc
-bl
ke
HF
n
i
r
CS
R
C
B
Baseline
*
ing
n
e
cre
Follow-up
Results: Disparities by SES
There were disparities by neighborhood level education
for 2 of 18 measures at baseline
Better QOC
for
patients
from areas
with low
education
15
8.9
10
Adjusted Difference (%)
Worse QOC
for
patients
from areas
with low
education
6.1
5
0
-5
-10
-15
-20
oc
-bl
ke
HF
n
ri
B
-14.3
teo
s
O
ros
po
*
-25
-30
-35
-40
-33.2
Baseline
Follow-up
is
New Racial Disparities
 New disparities were apparent by race for 4 measures at
follow-up
6
3.3
4
1.7
2
0.8
er
ap
y
-7
n
-3.6
oc
ca
l
-5.9
eu
m
oc
th
AR
B
AC
E
or
-8
-3.8
Pn
-6
va
cc
in
at
io
in
C
Pa
p
y
m
og
-4
ra
ph
-2
HD
0
am
Better
QOC
for black
patients
7.4
8
M
Worse
QOC
for black
patients
Adjusted Difference (%)
10
Baseline
Follow-up
Other New Disparities
 New disparities were apparent for 1 measure by education
and 1 measure by gender at follow-up
Education
Gender
Better QOC
for women
and
patients
with lower
education
Adjusted Difference (%)
0
-1
BP control in DM
ACE or ARB therapy in HF
-2
-3
-3
-4
-5
-6
-7
-6.6
-8
-9
-8.2
-7.8
Conclusions

A generalized HIT-based QI initiative was
associated with significant improvements in
disparities by race, gender, and SES for some
but not all measures with baseline disparities.

No clear patterns emerged between the type of
measure and changes in disparities.
Strengths and Limitations
Strengths

Assessment of quality of
care for several chronic
diseases and types of
preventive care

Disparities assessed by
race, gender, SES

Models adjusted for
important covariates
including SES
Limitations

Single institution study

Race data not by selfreport

Many patients excluded
due to missing race

Limited power to detect
differences for some
measures
Implications

In evaluating QI efforts, it is important to
continuously monitor for health disparities to
identify areas where more targeted interventions
are needed:
 Measures
with persistent disparities
 Measures
with new disparities