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Investigating Gender Differences in HEDIS Measures Related to Heart Disease. Ann F. Chou, PhD, MPH Carol S. Weisman, PhD Rosaly Correa-de-Araujo, MD, PhD Sarah H. Scholle, DrPH, MPH. Background. - PowerPoint PPT Presentation
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Investigating Gender Investigating Gender Differences in HEDIS Differences in HEDIS Measures Related to Measures Related to Heart DiseaseHeart Disease
Ann F. Chou, PhD, MPH
Carol S. Weisman, PhD
Rosaly Correa-de-Araujo, MD, PhD
Sarah H. Scholle, DrPH, MPH
BackgroundBackgroundBackgroundBackground
• Substantial literature documents gender disparities in guideline-indicated preventive and treatment services related to cardiovascular disease (CVD).
• Women may need more aggressive risk factor management than men due to differences in risk factors and symptom presentation.
CVD in Managed Care PopulationCVD in Managed Care PopulationCVD in Managed Care PopulationCVD in 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.
• Few studies that examined gender disparities in CVD-related care among managed care enrollees.
Study ObjectivesStudy ObjectivesStudy ObjectivesStudy Objectives
• To assess the reportability of CVD measures by gender (under existing specifications)
• To determine whether gender disparities in performance were evident within health plans
CVD-related HEDIS MeasuresCVD-related HEDIS MeasuresCVD-related HEDIS MeasuresCVD-related HEDIS Measures• Beta blocker treatment post acute myocardial
infarction (AMI)
• Persistence of beta blocker treatment post AMI
• Controlling high blood pressure
• Comprehensive diabetes care:– Cholesterol screening– LDL control <100 mg/dL
• Cholesterol management after acute cardiovascular event: – Cholesterol screening– LDL control <100 mg/dL
NCQA Sample Recruitment NCQA Sample Recruitment NCQA Sample Recruitment NCQA Sample Recruitment
• 289 Plans, varied by measure, that submit 2005 HEDIS performance data to NCQA were invited to participate in feasibility test.
• The final sample included 46 commercial health Plans, representing a national sample.
Participating Plan CharacteristicsParticipating Plan CharacteristicsParticipating Plan CharacteristicsParticipating Plan Characteristics
Plans in Study
• Profit status – For profit: 33 (73.3%)
– Not for profit: 12 (26.7%)
• Model type– Group: 2 (4.4%)
– IPA/Network: 25 (54.4%)
– Mixed Model: 19 (41.3%)
• Size* – <95,000 members: 16 (34.8%)
– 95,000+: 30 (65.2%)
All Others Reporting HEDIS
• Profit status – For profit: 169 (72.2%)
– Not for profit: 65 (27.8%)
• Model type– Group: 10 (4.1%)
– IPA/Network: 114 (46.9%)
– Mixed Model: 119 (49.0%)
• Size – <95,000 members: 141
(58.0%)
– 95,000+: 102 (42.0%)
Comparing Performance of Plans in Study Comparing Performance of Plans in Study v. All Other HEDIS-reporting Plansv. All Other HEDIS-reporting Plans
Comparing Performance of Plans in Study Comparing Performance of Plans in Study v. All Other HEDIS-reporting Plansv. All Other HEDIS-reporting Plans
Measures Average Performance
Plans in Study (%)
All other HEDIS
Plans (%)
t-test
Beta Blocker treatment 97.4 95.8 -2.08*
Persistence of beta blocker 69.0 67.0 -0.95
High blood pressure control 69.2 66.3 -2.42*
Cholesterol Screening-diabetes 92.4 90.7 -2.38*
LDL Control <100 – diabetes 41.9 39.9 -1.78
Cholesterol Screening-CVD event
83.7 81.3 -2.53*
LDL Control <100 – CVD event 53.7 50.4 -2.02*
• Descriptive statistics
• Calculation of disparities score (male-female difference)
• T- and chi-square tests to determine significance of the gender difference
MethodsMethodsMethodsMethods
Sample and Reportability of Gender Sample and Reportability of Gender Stratified Data Stratified Data
Sample and Reportability of Gender Sample and Reportability of Gender Stratified Data Stratified Data
Measures Commercial PlansOverall Male Female
Beta Blocker treatment 46 19 17
Persistence of beta blocker 46 13 13
High blood pressure control 46 45 45
Cholesterol Screening-diabetes 46 46 46
LDL Control <100 – diabetes 46 46 46
Cholesterol Screening-CVD event
46 36 36
LDL Control <100 – CVD event 46 35 35
Performance Rates by GenderPerformance Rates by GenderPerformance Rates by GenderPerformance Rates by Gender
Measures Performance Rates in % t-Test
N overall Male Female t p-value
Beta Blocker treatment
44 97.4 95.4 93.1 1.79 0.09
Persistence of beta blocker
37 69.0 70.8 70.1 0.33 0.75
High blood pressure control
46 69.2 69.0 69.2 -0.28 0.78
Cholesterol Screening-diabetes
46 92.4 92.9 91.7 2.70 0.75
LDL Control <100 – diabetes
46 41.9 44.4 38.8 8.14 <.0001
Cholesterol Screening-CVD event
44 83.7 84.2 81.6 2.82 0.008
LDL Control <100 – CVD event
44 53.7 56.4 47.1 6.38 <.0001
Distribution of Disparity ScoresDistribution of Disparity ScoresDistribution of Disparity ScoresDistribution of Disparity Scores
N Mean Std. Deviation
Minimum Maximum
Beta Blocker treatment 17 1.8 4.2 -3.3 10.0
Persistence of beta blocker
13 0.7 8.3 -11.9 12.6
High blood pressure control
45 -0.2 4.8 -10.9 8.4
Cholesterol Screening-diabetes
46 1.1 2.8 -5.9 8.2
LDL Control <100 – diabetes
46 5.6 4.6 -3.9 16.9
Cholesterol Screening-CVD event
36 2.5 5.4 -8.6 16.4
LDL Control <100 – CVD event
35 9.3 8.4 -3.4 31.8
Magnitude of Gender Disparities Magnitude of Gender Disparities Magnitude of Gender Disparities Magnitude of Gender Disparities
Measures N Plan Disparity ±5%: N (%)
Favor Women Favor Men
Beta Blocker treatment 17 0 (0) 4 (23.5)
Persistence of beta blocker 13 2 (15.4) 4 (30.8)
High blood pressure control 45 9 (20.0) 8 (17.8)
Cholesterol Screening-diabetes 46 1 (2.2) 2 (4.3)
LDL Control <100 – diabetes 46 0 (0) 25 (54.3)
Cholesterol Screening-CVD event
36 3 (8.3) 9 (25.0)
LDL Control <100 – CVD event 35 0 (0) 22 (62.9)
ConclusionConclusionConclusionConclusion
• Reporting of CVD measures based on gender is feasible for most measures.
• Differences in plan performance by gender were noted for 3 of the 7 CVD measures.
Discussion Discussion Discussion Discussion
• The CVD measures demonstrated a large range in disparity score among plans. LDL control for those with a history of CVD ranged from 3.4 in favor of women to 31.8 in favor of men in commercial plans.
• Denominator size limited adequate assessment for several CVD measures.
ImplicationsImplicationsImplicationsImplications
• Consumers/patients
• Providers
• Health plans
Acknowledgements Acknowledgements Acknowledgements Acknowledgements
• The Agency for Healthcare Research and Quality and the American Heart Association provided funding support for this research.
• NCQA staff provided data management and administrative support.