Cover: Mapping the Gaps

Mapping the Gaps

Gender Differences in Preventive Cardiovascular Care Among Managed Care Members in Four Metropolitan Areas

Published in: Women's Health Issues (2018). doi:10.1016/j.whi.2018.04.008

Posted on Aug 24, 2018

by Chloe E. Bird, Michael Manocchia, Brooke Tomblin, Peggy Payne, Mahesh Kulakodlu, Emily Iacolo, Allen Fremont


Prior research documents gender gaps in cardiovascular risk management, with women receiving poorer quality routine care on average, even in managed care systems. Although population health management tools and quality improvement efforts have led to better overall care quality and narrowing of racial/ethnic gaps for a variety of measures, we sought to quantify persistent gender gaps in cardiovascular risk management and to assess the performance of routinely used commercial population health management tools in helping systems narrow gender gaps.


Using 2013 through 2014 claims and enrollment data from more than 1 million members of a large national health insurance plan, we assessed performance on seven evidence-based quality measures for the management of coronary artery disease and diabetes mellitus, a cardiac risk factor, across and within four metropolitan areas. We used logistic regression to adjust for region, demographics, and risk factors commonly tracked in population health management tools.


Low-density lipoprotein (LDL) cholesterol control (LDL < 100 mg/dL) rates were 5 and 15 percentage points lower for women than men with diabetes mellitus (p < .0001), and coronary artery disease (p < .0001), respectively. Adjusted analyses showed women were more likely to have gaps in LDL control with an odds ratio of 1.31 (95% confidence interval, 1.27-1.38) in diabetes mellitus and 1.88 (95% confidence interval, 1.65-2.10) in coronary artery disease.


Given our findings that gender gaps persist across both clinical and geographic variation, we identified additional steps health plans can take to reduce disparities. For measures where gaps have been consistently identified, we recommend that gender-stratified quality reporting and analysis be used to complement widely used algorithms to identify individuals with unmet needs for referral to population health and wellness behavior support programs.

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