Trends in Health Care
Disparities in
Medicare Managed
Care
Sarah Hudson Scholle, MPH, DrPH
AcademyHealth
June 27, 2005
Acknowledgements
• Research Team
–
–
–
–
–
–
Sarah Hudson Scholle, DrPH, NCQA
Beth Virnig, PhD, University of Minnesota
Ann Chou, PhD, NCQA
Sarah Shih, MPH, NCQA
Russ Mardon, PhD, NCQA
Rich Mierzejewski, MA, NCQA
• Funded by the California Endowment
Background
• IOM: “ care should be safe, effective, patientcentered, timely, efficient, equitable”.
• Numerous reports of disparities in health care
and health outcomes, including previous studies
found disparities in Medicare managed care
• Quality has improved over time in Medicare
managed care: what about the disparities?
• The purpose of this study is to examine trends in
quality of care for blacks and whites in Medicare
managed care
Data Sources
• Medicare HEDIS data
– Health plans report member-level HEDIS data to NCQA
separately from plan-level data
– 1998 to 2003 measurement years
– Excluded plans where rates calculated from member-level
data did not agree with audited plan-level rates
• CMS enrollment file
– Age, sex, race/ethnicity, zip code, eligibility
– Race/ethnicity assigned at enrollment in Social Security
– Linked to HEDIS data using unique identifier (> 90% match)
• U.S. Census data
– Zip code matched to obtain median household income for
persons age 75-84
Medicare HEDIS® Measures
• Breast Cancer Screening (hybrid)
• Comprehensive Diabetes Care (hybrid)
– HgbA1c screening, Poor control of HgbA1c, Eye exam,
Nephropathy, Lipid screening, Lipid Control
• Cholesterol Management After Acute Cardiovascular
Event (hybrid)
– Lipid screening, Lipid Control
• Controlling High Blood Pressure (hybrid)
• Beta Blocker After Heart Attack (hybrid)
• Antidepressant Med Mgmt (admin only)
– Optimal Contacts, Acute Phase Treatment, Continuation Phase
Treatment
• Follow-up After Mental Health Hospitalization within 7 or
30 days (admin)
Study Group, 2003
Eligible Members
Measure
Plans
White
Black
Breast Cancer Screening
146
181,595
18,732
Comprehensive Diabetes Care
148
83,269
12,938
Cholesterol Management
145
24,454
2,060
Controlling High Blood Press.
141
46,292
7,237
Beta Blocker After Heart Attack
141
13,766
1,302
Antidepressant Med Mgmt
122
27,235
1,439
Follow-Up After MH Hosp
139
7,425
883
Analytic Approach: Trends over Time
• Research questions:
– Does performance differ by race?
– Does performance change over time?
– Does the rate of change in performance differ between
whites and blacks?
• Approach:
– Logistic regression analyses modeling each quality indicator
(met/not met)
– Controlling for patient age, sex, household income, region,
plan size
– Used a continuous variable to test for temporal correlation
Cholesterol Screening and Control –
Acute Cardiac Events
100.0%
90.0%
82.4%
80.0%
70.0%
70.9%
58.9%
69.5%
60.0%
53.7%
50.0%
40.0%
30.0%
Cholesterol
Screening
46.6%
Cholesterol
Control
47.0%
31.4%
20.0%
White
10.0%
Black
0.0%
1998
1999
2000
2001
Adjusted OR
Screening Control
Race:
0.638***
0.575***
Time:
1.439***
1.420***
Race*Time:
0.975
1.001
2002
2003
Cholesterol Screening and Control Diabetics
100.0%
93.2%
90.0%
80.0%
89.4%
Cholesterol
71.3% Screening
71.7%
70.0%
60.0%
50.0%
62.3%
62.5%
Cholesterol
Control
45.8%
40.0%
30.0%
33.7%
20.0%
White
10.0%
Black
0.0%
1999
2000
Adjusted OR
Screening
Race:
0.685***
Time:
1.816***
Race*Time:
0.993
2001
Control
0.653***
1.382***
1.031***
2002
2003
Diabetes HbA1c
Screening and Control
100%
90%
89.0%
78.1%
80%
70%
85.2%
71.3%
60%
50%
40%
44.0%
30%
20%
33.0%
HbA1c
Screening
29.2%
20.8%
10%
0%
1999
2000
2001
2002
HbA1c
Poor
Control§
2003
White
Adjusted OR
Race:
Time:
Race*Time:
Screen
0.748***
1.424***
1.011
Control
1.459***
0.825***
0.984
Black
§ Lower is better.
Beta Blocker & Blood Pressure
93.4%
100%
90%
80%
81.8%
70%
77.4%
87.7%
61.3%
60%
46.9%
50%
40%
56.0%
Beta
Blocker
High
Blood
Pressure
41.4%
30%
20%
10%
White
0%
1998
Adjusted OR
Race:
Time:
Race*Time:
1999
BBH
0.838**
1.626***
0.934*
HBP
0.782***
1.351***
1.002
2000
2001
2002
2003
Black
Antidepressant Medication
Management
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
67.1%
56.1%
59.5%
46.7%
45.9%
Acute
Phase
52.3% Continuation
38.5% Phase
32.1%
12.2%
12.4%
12.9%
12.0%
0%
2000
2001
2002
2003
Optimal
Contacts
2004
White
Adjusted OR
Race:
Time:
Race*Time:
Acute
Continuation
0.589***
0.544***
***
***
NS
NS
Contacts
1.024
NS
NS
Black
Follow Up After Mental Health
Hospitalization (30 Days)
100%
90%
80%
70%
60%
50%
58.2%
55.9%
40%
30%
46.2%
39.2%
20%
10%
0%
1998
Adjusted OR
Race:
Time:
Race*Time:
1999
2000
2001
2002
2003
White
0.537***
1.163***
1.028
Black
Breast Cancer Screening
100.0%
90.0%
80.0%
70.0%
60.0%
50.0%
40.0%
30.0%
20.0%
10.0%
0.0%
76.3%
76.3%
72.3%
1998
75.1%
1999
2000
2001
2002
2003
White
Adjusted OR
Race:
Time:
Race*Time:
0.911***
1.021***
1.030***
Black
Magnitude of Racial Disparity Differs
Adjusted
Odds Ratio
B-W Diff in
Adjusted
Rate
Blacks
gaining or
losing
Breast Cancer Screening
Diabetes HgbA1c screen
Diabetes LDL screen
0.91
0.75
0.69
1.2
3.2
3.8
+
Controlling High Blood Pressure
0.78
5.2
Beta Blocker after Heart Attack
0.84
5.7
-
Diabetes LDL control <130
Poor HgbA1c control§
Cardiac event : Chol Screening
Cardiac event: Chol Control
Depress Med Mgmt Acute Phase
Depress Med Mgmt Cont Phase
Follow Up after MH Hosp
0.65
1.46
0.64
0.58
0.59
0.54
0.54
9.0
11.6
11.5
15.8
11.0
13.8
12.0
+
§ Lower is better.
Conclusions
• Quality of care for Medicare managed care
beneficiaries is improving
• Black/white disparities remain for most
measures
• On most measures, the rate of
improvement is not different for blacks
and whites – the gap is not closing
• The amount of disparity varies: lower for
most screening measures, higher for
control and cardiac measures
Implications
• General efforts to improving quality are
not enough to reduce the racial gap
• Understand root causes that contribute to
disparities
• Develop and evaluate quality improvement
interventions that address racial
disparities specifically and within the
context of general QI
• Continue to monitor quality by race and
expand to include ethnicity and language