Quality Measurement and Gender
Differences in Managed Care Populations
with Chronic Diseases
Ann F. Chou
Carol Weisman
Arlene Bierman
Sarah Hudson Scholle
Background
• Institute of Medicine (IOM) outlined 6
attributes of health care:
– Health care should be “safe, effective, patientcentered, timely, efficient, equitable.”
• There are many reports of disparities in
health care and health outcomes (IOM,
Unequal Treatment).
• Overall health care quality has improved
over time but it has not improved for all
patient subgroups.
2
© NCQA, 2007
Background: Disparities in Care for
Cardiovascular Disease (CVD)
• Substantial literature documents
gender differences in guideline
indicated services and treatment.
• Women may need more aggressive
risk factor management than men
due to differences in risk factors and
symptoms presentation.
3
© NCQA, 2007
Managed Care Population
• A significant portion of the US
population receives care through
managed care organizations, where
the quality of care may be more
uniform.
• In particular, there are few studies
that examined disparities among
commercially managed care
enrollees.
4
© NCQA, 2007
Objective
• To examine possible gender and
racial disparities in meeting quality
performance indicators for
cholesterol screening and control
among commercial health plans and
in commercial and Medicare
managed care populations of
patients with chronic conditions
5
© NCQA, 2007
HEDIS®
• Healthcare Effectiveness Data and
Information Set (HEDIS®) is a set of
standardized performance
measures designed to ensure that
purchasers and consumers have the
information to reliably compare the
performance of managed health
care plans.
6
© NCQA, 2007
MEASURING QUALITY OF CARE
FOR HEART DISEASE
HEDIS Measures:
– Comprehensive diabetes care
• Screening for Cholesterol
• Good control of cholesterol (LDL <100 mg/dL)
– Cholesterol management after acute
cardiovascular event
• Cholesterol screening
• Good control of cholesterol (LDL <100 mg/dL)
7
© NCQA, 2007
Study Population
• Submissions from Commercial plans (2005)
– 46 plan level submissions
– 31 member level data submissions, including 11,813
patients
– Geocoding and surname analysis used to estimate race,
ethnicity and socio-economic status (SES)
– Participating plans are larger, higher performing
• Submissions from Medicare plans (2004)
– 96,055 patients from 148 health plans
– Race obtained from CMS enrollment data, geocoding
used to estimate SES
8
© NCQA, 2007
Analytic Approach
• Member Level
– Hierarchical Generalized Linear Modeling (HGLM):
HEDIS outcomes were modeled as functions of
gender, controlling for other socio-demographic
characteristics at the first level, and plan’s clustering
effect at the second level
– Adjusted rates were calculated
• Plan Level
– Descriptive statistics
– Calculation of disparities score (male-female
difference)
– T-test to determine significance of the gender
difference in performance rates
9
© NCQA, 2007
Results
Gender and Racial/Ethnic
Disparities in Medicare
Managed Care Populations
with Diabetes Mellitus
10
© NCQA, 2007
Sample Description
Characteristic
Medicare Population
(%)
Age:
• <65
• 65+
12.2
87.8
Gender:
• Male
• Female
Race:
50.3
49.7
• White
86.6
• African American
13.4
11
© NCQA, 2007
HGLM Results: Odds Ratios
Cholesterol
Screening
LDL control
<100 mg/dL
Female
/Male
1.06
0.75*
African American
/White
0.67*
0.69*
Enrolled in plans with
>20% minority members
0.81
0.93
HEDIS Outcomes
* Denotes statistical significance at p≤0.05
12
© NCQA, 2007
Adjusted Rates for Gender and Race
100
90
80
Cholesterol screening
AA Female
70
Wht Female
AA Men
60
Wht Men
LDL Control <100
50
40
30
13
© NCQA, 2007
Results
Gender Differences in Quality
Measures Among Commercially
Insured Patients
14
© NCQA, 2007
Sample Characteristics
Characteristics
Gender (women)
%
44.2
Race/Ethnicity
• African American
8.5
• Latino
7.7
• White/other
74.6
Low SES
10.3
Age
•Age 65 and older
6.7
•45-64 years
72.6
15
© NCQA, 2007
Unadjusted Rates: Cholesterol Measures
Characteristics
Diabetes Management
Screening
LDL Control
Cholesterol
Management
Screening
LDL Control
%
t-test
%
t-test
%
t-test
%
t-test
• Female
91.6
2.13*
37.7
6.04*
76.8
2.53*
45.3
6.22*
• Male
92.7
Gender
43.3
79.9
55.0
African American
• Female
90.6
• Male
87.7
-1.39
29.9
2.03*
36.1
65.7
-0.24
64.2
34.2
1.55
44.8
White
• Female
91.5
• Male
93.2
2.84*
39.4
44.9
5.05*
77.6
80.8
2.32*
46.2
5.31*
55.4
* Denotes statistical significance at p≤0.05
16
© NCQA, 2007
HGLM Results: Odds Ratios
Diabetes
Management
Covariate
Cholesterol
Management
Cholesterol
screening
LDL
Control
Cholesterol
screening
LDL
Control
Female
/Male
0.88
0.81*
0.88*
0.72*
African American
/White
0.69*
0.74*
0.88
0.71*
Latino
/White
1.13
0.73*
0.79*
0.87
Low SES
/High SES
0.85
0.83*
0.77*
0.75*
Age 65+
/(<65)
1.10
1.52*
1.03
1.26*
* Denotes statistical significance at p≤0.05
17
© NCQA, 2007
WOMEN LESS LIKELY CONTROL CHOLESTEROL;
AFRICAN-AMERICAN WOMEN EVEN LESS LIKELY
Cholesterol Control <100 mg/dl for Commercial CVD sample
70
Unadjusted Rate (%)
60
White Males
9.2
50
White Females
African-American Males
21.2
40
10.6
African-American Females
30
20
18
© NCQA, 2007
Results
Gender Differences in Quality
Measures Cross a Sample of
Health Plans
19
© NCQA, 2007
Plans Characteristics
Measures
N (%)
Medicare Plans
(N=148)
Commercial Plans
(N=46)
53 (35.8)
12 (26.1)
Staff/Group Model
63 (42.6)
2 (4.3)
IPA/Network
79 (53.4)
25 (54.3)
Mixed Model
6 (4.0)
19 (41.3)
Midwest
40 (27.0)
13 (28.3)
Northeast
38 (25.7)
11 (23.9)
South
33 (22.3)
15 (21.7)
West
37 (25.0)
7 (15.2)
Not for Profit
Health Plan Model
Region
20
© NCQA, 2007
Overall Performance of Plans
Measures
Commercial Plans
Medicare Plans
Male
Female
Male
Female
Cholesterol Screeningdiabetes
92.9
91.7
90.9
91.8*
Lipid Control – diabetes
44.4
38.8*
44.4
38.0*
Cholesterol ScreeningCVD event
84.2
81.6
81.1
79.5*
Lipid Control – CVD event
56.4
47.1*
52.1
43.6*
21
© NCQA, 2007
MORE THAN HALF OF HEALTH PLANS SHOW DISPARITY
FAVORING MEN ON CHOLESTEROL CONTROL
70
60
COMMERCIAL PLANS (%)
Striking disparities for
cholesterol control
50
40
30
20
10
0
BP Control
Cholesterol
Screening
(Diabetes)
Cholesterol
Control (<100)
(Diabetes)
Favors Women
Cholesterol
Screening
(CVD)
Cholesterol
Control (<100)
(CVD)
Favors Men
22
© NCQA, 2007
MORE THAN HALF OF HEALTH PLANS SHOW DISPARITY
FAVORING MEN ON CHOLESTEROL CONTROL
80
70
MEDICARE PLANS (%)
Striking disparities for
cholesterol control
60
50
40
30
20
10
0
BP Control
Cholesterol
Screening
(Diabetes)
Cholesterol
Control (<100)
(Diabetes)
Favors Women
Cholesterol
Screening
(CVD)
Cholesterol
Control (<100)
(CVD)
Favors Men
23
© NCQA, 2007
Conclusion
• Clinically important and statistically
significant gender differences and
racial/ethnic disparities in LDL control
measures in those with chronic conditions
• African-American and poor women at
greatest disadvantage from additive effect
of race, gender, socioeconomic status
• More than half of health plans have gender
disparity of 5 percentage points or more for
LDL control
• Differences persist despite fairly equitable
access to care. This is concerning given
these are populations with high risk due to
the presence of co-morbidities
24
© NCQA, 2007
Limitations
• Lack of information on patient
clinical, behavioral, and attitudinal
characteristics. Results were consistent
after adjusting for region, SES and
plan clustering
• No information on patterns of
utilization and providers
25
© NCQA, 2007
Recommendations for Quality Improvement
• Inform consumers about disparities and
encourage active role in demanding
high quality care
• Educate physicians about the patterns of
gender disparities in CVD care and
encourage for active management with
patients as partners
• Engage employers, purchasers and
health plans in promoting focus on
disparities in quality improvement
26
© NCQA, 2007
Recommendations for Policy and Research
•
•
•
•
Build consideration of gender, racial/ethnic, and
socioeconomic differences into quality
improvement interventions, with incentives for
health plans and providers to identify, address and
monitor potential disparities in CVD care
Gain consensus on the methods for collecting,
examining, and reporting on key population-wide
health measures by gender, racial/ethnic, and
socioeconomic characteristics
Improve training in the area of women’s health for
the health care workforce
Fund further research to disentangle influence of
physician and patient factors on outcomes
27
© NCQA, 2007
Acknowledgements
• Funded by the Agency for
Healthcare Research and Quality,
American Heart Association, the
California Endowment
• NCQA staff for support in project
and data management
28
© NCQA, 2007