|
|
 |
|
|
Addressing
Racial and Ethnic Disparities in the Context of
Medicaid Managed Care: A Six-State Demonstration
Project
Findings
- Overview
All
of the plans were able to obtain data on race/ethnicity
from their state Medicaid programs and link that
information to either membership files or HEDIS
data analysis files. This linkage allowed all
of the plans to generate quality of care reports
stratified by race/ethnicity.
The
plans varied somewhat in the data available for
analysis at baseline. As indicated in Table 2
below, most of the plans waited until calendar
year 2002 (reporting year 2003) data were available
in May or June of 2003 and used those data for
baseline analyses. Three plans did not analyze
data according to standard HEDIS definitions,
but were able to use the race/ethnicity data to
generate stratified quality of care reports in
“HEDIS-like” format. Conceptually, the measures
in these analyses were very similar to HEDIS measures,
focusing on measures of breast and cervical cancer
screening rates, prenatal care visit rates, and
laboratory testing rates for patients with diabetes.
The option of using “HEDIS-like” measures allowed
greater flexibility for plans to focus attention
on clinical areas that have previously been identified
as important, and allowed participation by plans
that were not yet NCQA-accredited and not routinely
participating in HEDIS.
Table
2. Baseline Data Sources
All
but one of the plans identified at least one significant
disparity in these baseline analyses. (In that
plan, an apparent disparity turned out to be a
problem in accuracy of claims data at some clinic
sites.) In 10 of the 12 plans finding a disparity,
more than one disparity was identified. The pattern
of baseline disparities is summarized in Table
3. (The absence of a check mark in a box does
not necessarily mean that data were analyzed and
no disparity found – as indicated earlier, some
plans did not analyze all of the HEDIS measures
at baseline.)
| |
|
|
+ |
+
|
|
|
+
|
+
|
+
|
|
|
|
|
|
|
+
|
+
|
|
+
|
+
|
+
|
|
|
|
|
|
|
|
|
|
+
|
+
|
|
+
|
+
|
|
|
|
|
|
|
|
|
+
|
+
|
|
+
|
|
+
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
+
|
|
|
|
|
|
|
|
|
|
|
|
|
+
|
|
|
|
|
|
|
|
+
|
|
|
|
|
|
|
|
|
|
|
|
|
+
|
|
|
|
|
|
|
+
|
|
|
|
|
|
|
+
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
+
|
|
|
|
|
|
|
|
|
|
|
|
|
|
+
|
|
|
|
|
|
|
+
|
+
|
+
|
|
|
|
|
|
|
|
|
|
+
|
|
|
|
|
+
|
|
|
|
|
Table
3. Pattern of Baseline Disparities by Plan
The
plans, in collaboration with their state Medicaid
programs and with project staff and consultants,
developed QI projects and specific objectives
for those projects with regard to reduction or
elimination of at least one of the disparities.
As shown in Table 4, the projects varied in terms
of target clinical condition, specific HEDIS measure(s),
and nature of the QI intervention(s). No two interventions
were exactly alike, although there was explicit
collaboration among plans in one of the States
so that those projects were much more similar
to each other than was the case elsewhere in the
project.
|
Health
Plan
|
HEDIS
Measure(s)
|
Clinical
Target
|
QI
Project(s)
|
|
A
|
HbA1C
& LDL-C control.
|
Increase
HbA1C &
LDL-C control rates for African-American
members by 5%.
|
Developed
a diabetes registry & physician profiles.
Requested
physicians use standardized diabetes flow
sheets for medical record documentation.
Established
a mechanism for obtaining lab results (HbA1c,
LDL-C) from hospitals to improve data completeness.
Established
a diabetes management program.
|
|
B
|
Comprehensive
Diabetes Measures.
|
Improve
HEDIS diabetes measures for African- American
members by 2.5% overall.
|
Members
enrolled in diabetes DM program from 6 practice
sites invited to participate in the Diabetes
Navigator Program.
Established
physician profiles and implemented educational
reminders for physicians regarding ADA Standards
of Care.
Members
received a series of educational tools and
reminders regarding diabetes standards of
care.
“Supermarket
tours” for members at high-risk.
|
|
C
|
HbA1C
& LDL-C Testing.
|
Increase
HbA1C testing rate from 68.9% to 71%;
Increase
LDL-C testing rate from 70.6% to 73%.
|
Used
Active Health System to send reminders to
providers & members.
Identified
issues with lab vendor regarding receipt
of lab data.
Conducted
diabetes case management and outreach activities.
|
|
D
|
HBA1C
& LDL-C Control.
|
Increase
the proportion of African-American and Hispanic
members with HBA1C and LDL levels in good
control.
|
Supplemented
existing Diabetes Disease Management Program
activities:
Collaboration
with a local health coalition to promote
Diabetes Detection;
Shared
aggregate data with physicians and provided
information packets that included race/ethnicity
statistics & culturally appropriate
information on nutrition;
Conducted
targeted member outreach & developed
educational materials that included race/ethnic
information related to diabetes.
|
|
E
|
Adult
Access to Preventive/
Ambulatory Care;
HbA1c
and
LDL-C Screening.
|
Increase
visits for Preventative and Ambulatory Services,
and HbA1c and LDL-C Diabetic measures in
the
African-American/ Hispanic population.
Achieve
50th percentile Medicaid benchmark
rates.
|
Provider
Data Sharing Program.
Promotion
of the Diabetic Control Network for all
eligible enrollees.
Interventions
targeting Hispanic & African-American
members including health promotion and outreach
activities.
CME
programs; cultural competency educational
events.
Active
Disease/Case Management Programs.
|
|
F
|
HbA1C
testing;
LDL-C screening;
CAHPS – Advise to Quit Smoking.
|
Increase
percentage of African-American members who
receive HbA1C and LDL-C testing by 10%;
Increase percent of members advised to quit
smoking by 10%.
|
Collaboration
with local African- American Health Coalition
to send targeted mailings to members covering
4 health topics.
|
|
G
|
CAHPS-
Advise to Quit Smoking.
HBA1c
testing.
LDL-C screening.
|
Increase
rate of
HBA1c testing
LDL-C screen in African- American members
with diabetes.
|
Collaboration
with local African-American Health Coalition
to send targeted mailings to members covering
2 health topics.
|
|
H
|
HBA1c
testing.
|
Increase
rate of HBA1c testing in African-American
members with diabetes.
|
Collaboration
with local African-American Health Coalition
to send targeted mailings to members covering
2 health topics.
|
|
I
|
Asthma
Measures-
A ppropriate Medications.
|
Improve
HEDIS rates for African-American members
to NCQA 2002 50th percentile
scores for asthma (60.8%).
|
Developed
a Home Visiting Program for members with
asthma that included member incentives for
participation.
Established
relationships with local community-based
organizations.
Conducted
an Asthma provider training.
Members
Health fairs.
|
|
J
|
Prenatal
and Postpartum Care.
|
Increase
proportion of postpartum visits occurring
within HEDIS specifications for Hispanic/Spanish
speaking members.
|
On-site
visits to Community Health Clinics to identify
best practices in providing prenatal care.
Implementation
of rapid cycle improvement projects in clinic
settings.
Development
of database to include prenatal and postpartum
care for member outreach.
|
|
K
|
Prenatal
&
Postpartum Care.
|
Increase
the % of African-American and Hispanic pregnant
women receiving prenatal visits within 2
weeks after enrollment;
Decrease
the number of antepartum hospital admissions;
Prospectively
identify high risk mom’s to be;
Increase
prenatal class attendance by 20%.
|
Conducted
medical record reviews to assess prenatal
and antepartum care
Hired
a Social Worker to work with high-risk members.
Contracted
with Matria Healthcare, Inc. to complete
high-risk assessments.
|
|
L
|
HEDIS-like
measures for Well Child Visits.
HEDIS
measures of Well Child Visits & Childhood
Immunizations.
|
Increase
rates of HEDIS Well Child Visits and Immunizations
for Hispanic members.
|
Developed
a culturally appropriate reminder postcard
for Hispanic/Spanish-speaking members.
|
|
M
|
Breast
& Cervical Cancer Screening.
|
Increase
HEDIS cervical and breast cancer screening
rates for Native American members by 3%
annually.
|
Reviewed
accuracy of claims/encounter data.
Established
process measures to improve data accuracy/
submission.
Initiated
contacts with local community agencies.
|
Table
4. Summary of QI Projects
Effects
of QI Initiatives on Disparities
Nine
of the thirteen plans were able to implement their
QI projects and carry through to at least some
form of follow-up evaluation. For most of the
plans, the follow-up analysis came in the form
of follow-up HEDIS analyses and reports (usually
2004 reports for the 2003 year). For one of the
plans, follow-up analyses involved measures and
data from quarterly or monthly reports on events
like prenatal care visits, childhood immunizations,
or laboratory tests for members with diabetes.
These analyses were useful to indicate whether
or not a QI project was “on track” but the plan
doing these analyses generally viewed them as
interim analyses rather than a final assessment
of project success.
Of
the eight plans reporting follow-up data that
had a disparity at baseline, it appears that two
(E, L) made clear progress toward the goal of
reducing or eliminating disparities observed at
baseline, and three other plans (B, C, I) made
measurable improvements in quality of care for
the target minority population without necessarily
reducing or eliminating a disparity.
Only
three plans (F, G, H) saw little or no change
in disparity in follow-up analyses. In four plans
(A, D, K, M) the short time frame of the project
did not allow for quantitative follow-up analyses.
(The scope of the project did not allow for detailed
analysis of reasons for the relative success of
different projects; such an analysis would probably
require a larger sample of projects in order to
make comparisons.)
In
three health plans (A, J, M), it became clear
that an apparent disparity at baseline was at
least partially a function of data completeness
and accuracy and not necessarily a reflection
of a true disparity in quality. Two of these plans
(A, M) made improvements in the data collection
and reporting process, and in both cases, the
apparent disparity was still seen in the more
accurate reports. The time taken to improve the
data collection and analysis processes inevitably
delayed the design and implementation of QI efforts,
but even in these two instances, the plans made
significant progress on the path toward quality
improvement and disparity reduction by improving
their measurement processes. Preliminary results
of the effects of QI initiatives in those two
plans will not be available until late fall of
2004 (after the publication date of this report).
(Back
to: Table of Contents)
|
