Increasing Equity While Improving the Quality of Care

Abstract

This review summarizes racial and ethnic disparities in the quality of cardiovascular care—a challenge given the fragmented nature of the health care delivery system and measurement. Health equity for all racial and ethnic groups will not be achieved without a substantially different approach to quality measurement and improvement. The authors adapt a tool frequently used in quality improvement work—the driver diagram—to chart likely areas for diagnosing root causes of disparities and developing and testing interventions. This approach prioritizes equity in quality improvement. The authors demonstrate how this approach can be used to create interventions that reduce systemic racism within the institutions and professions that deliver health care; attends more aggressively to social factors related to race and ethnicity that affect health outcomes; and examines how hospitals, health systems, and insurers can generate effective partnerships with the communities they serve to achieve equitable cardiovascular outcomes.

The disparate impact of the coronavirus disease-2019 (COVID-19) pandemic and widely publicized violence against Black, Latino, and Asian Americans have drawn attention to longstanding injustices faced by people of color in the United States. Among these injustices are well-documented persistent disparities in health outcomes and the quality of care (1,2). Cardiovascular diseases (CVDs) and related conditions remain among the most common causes of premature morbidity and mortality, so racial and ethnic disparities in CVD outcomes play a prominent role in reducing the length and quality of life among Black, Latino, Asian and Pacific Islanders, and Indigenous Americans (3–5). Improvements in cardiovascular care have reduced age-adjusted mortality from CVD overall, although the gains have stalled during the past decade, and racial and ethnic disparities persist (Figure 1) (6). For some conditions like heart failure, declines in mortality have plateaued while racial gaps have persisted or even widened, erasing earlier gains (Figure 2) (7).

FIGURE 1. Trends in CVD Mortality by Race and Ethnicity.

Deaths per 100,000 attributable to cardiovascular disease (CVD) (International Classification of Diseases-Tenth Revision) cause of death codes 100–178). Authors’ analysis of CDC WONDER Online Database (46). AI/AN = American Indian/Alaskan Native.

FIGURE 2. Trends in HF-Related CVD Mortality by Age and Race.

Deaths per 100,000. Authors’ analysis of CDC WONDER Online Database (46).

CVD = cardiovascular disease; HF = heart failure.

Cardiovascular specialists have been at the fore-front of measuring and improving the quality of care. Evidence-based guidelines, registries, quality measures, and quality improvement (QI) programs like Get With The Guidelines have improved clinical decisions related to prevention, risk factor reduction, and effective management of chronic CVD (8). In addition, the field has improved the timeliness, consistency, and reliability of acute care. For example, the Door-to-Balloon Alliance used a single metric (door-to-balloon time) tied to a specific clinical goal (minimizing myocardial injury) to motivate and sustain the challenging work of re-engineering care protocols and setting up the communications systems that enable teams to achieve timely delivery of a highly effective intervention (coronary revascularization) (9).

How can the health care enterprise extend this quality improvement work to achieve equity in CVD outcomes? Answering this question requires a deep understanding of the complex web of clinical and social risk factors as well as inequities in the quality of care that drive racially and ethnically disparate CVD outcomes. The epidemiological factors and their relationship to CVD outcomes have been extensively documented by past research and in this special issue.

This paper highlights efforts to reduce inequities in the quality of cardiovascular care, building on insights from recent scholarship on the effects of structural racism in the broader society and also within medicine (10). Structural (or systemic) racism refers not to the impact of individual biases, but instead to the overt and insidious ways that racism has been woven into the policies, management, and practices of American institutions. For example, medical apartheid, a term coined by Harriet Washington, established a hierarchical system by which people of color, and especially Black and Indigenous people of color (BIPOC) were denied health care, experimented upon, and excluded from medical education (11). Several leading health care organizations including the American Heart Association (AHA) have acknowledged that people of color face social conditions that perpetuate inequities in quality of care, health care outcomes, and representation in the health professions and in medical science (12,13).

Recent research suggests that health equity for all racial and ethnic groups will not be achieved without an approach to quality measurement and improvement that acknowledges systemic racism at multiple levels and uses the methods and tools of QI to dismantle systemic racism in health care (10). Interventions are needed that both improve processes of care and also reduce systemic racism within the institutions and professions that deliver health care. These interventions attend more aggressively to social factors related to race and ethnicity that impact health outcomes. They also require an enabling environment: hospitals, health systems, and payors that counteract systemic racism by forging effective and aligned partnerships with the communities they serve.

MULTIPLE FACTORS CONTRIBUTE TO RACIAL AND ETHNIC DISPARITIES

Disparities in clinical risk factors, such as hypertension, diabetes, hyperlipidemia, and obesity, and in behavioral risk factors, such as diet, exercise, and tobacco use, contribute significantly to disparate outcomes. Yet, differences in clinical risk factors do not fully account for observed disparities in CVD outcomes. Even among people with the same clinical risk factors, morbidity and mortality are higher among Black and Hispanic people compared with White people (14). Nor are racial and ethnic disparities in CVD outcomes explained by genetic factors. Genetic factors can modify individual susceptibility to disease, alter risk for progression, and affect responsiveness to medications, but these genetic associations are small. Furthermore, they are swamped by heterogeneity of genotypic variation within and between the coarsely-labeled racial and ethnic groupings assigned and used in research and practice. Focusing on genetic factors distracts from the socially and historically patterned impact of race and racism on health and health care (15,16).

Discussion of racial and ethnic disparities in CVD outcomes frequently turns to disparities in social and economic conditions. The AHA provides a CVD-specific conceptual framework for classifying these factors within 6 domains: socioeconomic position (eg, wealth and income, education, employment/occupational status), race and ethnicity, culture and language, social supports, access to care, and the residential environment (17). Longstanding geographic segregation based on race, ethnicity, and socioeconomic factors is deeply intertwined with U.S. geography, as the maps in Figures 3A to 3F illustrate. Aggregating groups based on existing census categories masks considerable heterogeneity within populations and geographies. Considerations of race, ethnicity, and many individual features that define socioeconomic position are incomplete without an understanding of the adverse exposures and strengths present in the communities within which people live, work, and play (18).

FIGURE 3. Disparities in Age- and Sex-Standardized Cardiovascular Mortality in U.S. Counties, 2016–2018.

Counties categorized into quintiles based on whole-population cardiovascular disease mortality per 100,000; the number of counties in each category is in parentheses. (A) All race/ethnicities; (B) Black (non-Hispanic); (C) White (non-Hispanic); (D) Hispanic; (E) American Indian and Alaskan Native; (F) Asian and Pacific Islander. Authors’ analysis of Interactive Atlas of Heart Disease and Stroke (47).

MEASURING AND IMPROVING QUALITY AND EQUITY OF CARE FOR CARDIOVASCULAR CONDITIONS

Population-level reports on CVD mortality exist, but a systematic summary of the quality of cardiovascular care in the United States is difficult to produce because of the fragmented nature of our health care system. Research studies, registries, accreditation, and measurement for accountability occur within specific delivery organizations (eg, Veterans Affairs, hospitals, managed care organizations) or insured populations (eg, Medicare, Medicaid, commercial). The challenge to producing a coherent picture of CVD quality is compounded when trying to stratify results by race and ethnicity because standardized data on race and ethnicity are not routinely collected.

We identified 1,309 citations from a PubMed search for the years 2000–2020 using the key words “cardiovascular disease,” “racial ethnic disparities,” and “quality of care.” We focused on the 103 reviews published between 2010 and 2020. Among those, we selected recent papers in the 15 areas that have been the focus of measurement and QI efforts. Table 1 provides a high-level summary of the findings. Blacks/African Americans had poorer quality than the group with the best quality in all areas. Hispanics had worse quality in 8 areas, Asian Americans’ and Pacific Islanders’ care was worse in 2 areas, and Native Americans’ care in 1 (most studies fail to obtain adequate sample sizes to include this group in stratified analyses).

TABLE 1.

Racial and Ethnic Disparities in the Quality of Care

Quality Measure Construct With Demonstrated Racial/Ethnic Disparities	Clinical Population(s) Measured	Comparator Group With Highest Quality (Reference)a	Racial/Ethnic Groups Included in Studies and With Lower Quality Relative to Reference Group	Ref. #
Health outcomes, intermediate outcomes, risk factors
Mortality after hospitalization for AMI, PTCA, CABG surgery	AMI	White	AA	(24,49)
Blood pressure control	HTN	White	AA, Hispanic	(22,50)
Diabetes/glycemic control	HTN, DM, CAD	AAPI	White, AA, Hispanic	(51)
Obesity/nutrition	HTN, DM, CAD, CHF	AAPI	White, AA, Hispanic	(52)
Physical activity/sedentary behavior	General pediatric	White	AA, Hispanic, other	(53)
Tobacco use	General adults	Hispanic	Native Americans, White, AA, AAPI	(53,54)
Processes of care, procedure use
Medication adherence	HTN,CHF	White	AA, Hispanic	(50)
Involvement of a cardiologist	CHF (inpatient)	White	AA	(55)
Revascularization after AMI	CAD	White	AA, Hispanic, Native Americans	(20,56)
Cardiac resynchronization therapy	CHF	White	AA, Hispanic	(23)
Left ventricular assist device/Heart transplant	CHF (end-stage)	White	AA (heart transplant more likely than among whites, but worse outcomes)	(57)
Hospital readmissions	AMI, CHF	White	AA	(58)
Hospitalization rates	CHF, CAD	White	AA, Hispanic, AAPI	(59)

^aAmong groups compared using the indicated measures. Not all groups were included in all studies.

AA = African American; AAPI = Asian American/Pacific Islander; AMI = acute myocardial infarction; CAD = coronary artery disease; CHF = congestive heart failure; DM = diabetes mellitus; HTN = hypertension.

The studies were based on a variety of measures in different populations and settings making it difficult to summarize the magnitude of disparities. Nevertheless, the disparities are striking (19). For example, Black persons >40 years of age with diabetes have a lower rate of blood pressure control than their White counterparts (39.1% vs 53.1%). Black persons with diabetes have a much higher rate of lower extremity amputations compared with White patients (60.9 vs 26.8 per 1,000). Black patients >40 years of age are more likely than White patients to die after hospital admission for CABG (33.6 vs 24.9 per 1,000 hospital admissions). Asian Americans admitted for AMI are more likely to die than Whites (60.4 vs 50.5 per 1,000 hospital admissions). If admitted for CHF, Hispanics and Asian Americans are less likely than White Americans to die (21.9, 26.1, and 31.3 per 1,000 respectively). In contrast, compared with White patients admitted for AMI, Hispanic patients have the same likelihood of death (50.4 vs 50.5 per 1,000). Data on quality for Native Americans are scant, but demonstrate that they are less likely than White patients to undergo coronary catheterization (OR: 0.32) and PCI (OR: 0.43) after AMI or CABG if diabetic (OR: 0.48) (20).

Clinical management of CVD risk factors also reveals disparities. For example, rates of physical inactivity are 38.3% in African Americans vs 40.1% in Hispanics, and 26.3% in White adults (21). A different pattern emerges for tobacco use with the highest rates of lifetime use among American Indian or Alaskan Natives and Whites (75.9%), while use among African Americans (58.4%) and Hispanics (56.7%) is lower. Hypertension treatment rates were 73.9%, 70.8%, and 60.7% and hypertension control rates were 42.9%, 36.9%, and 31.2% for Whites, Blacks, and Hispanics, respectively (22). New technologies are also subject to racial and ethnic disparities. A study of cardiac resynchronization therapy (CRT) showed that CRT-eligible Black (OR: 0.84) and Hispanic (OR: 0.83) patients were less likely to receive CRT with defibrillation than were White patients (23).

Some areas have few disparities by race or ethnicity, suggesting that disparities can be reduced within organized QI programs. Among hospitals that voluntarily report to the Get With The Guidelines Program on Stroke, between 2017 and 2018, 11 measures showed no substantial differences in quality between White, Black, and Hispanic patients (24). Of these measures, 9 were related to medication management and 2 to making lifestyle recommendations. A retrospective study comparing quality for 1.7 million White and Asian-American patients admitted for acute ischemic stroke showed better quality for Asian Americans on some measures such as rehabilitation and intensive statin use, but lower quality on others such as likelihood of receiving intravenous tissue plasminogen activator, more frequent complications after tissue plasminogen activator, and functional outcomes (25).

Although insurance coverage is important for access to care, it is not sufficient to eliminate disparities. In a large national population defined by insurance coverage, the Centers for Medicare and Medicaid Services Office of Minority Health examined racial and ethnic disparities in the Medicare Advantage (MA) population (approximately one-third of all Medicare beneficiaries). Table 2 shows substantial racial/ethnic disparities on 4 cardiovascular quality measures among MA members whose insurance coverage includes care coordination (26). Despite the millions of members enrolled in MA, few of the hundreds of individual contracting MA insurance plans had sufficient numbers of enrollees to reliably stratify reporting on quality differences among racial and ethnic groups. Stratification in local geographic areas using multipayer data may yield more usable data.

TABLE 2.

The Percent of Medicare Advantage Enrollees Receiving Care for 4 Cardiovascular Quality Measures by Race and Ethnicity, 2018

Measure	White	Black	Asian or Pacific Islander	Hispani
Controlling high blood pressure	75.7	65.1a	72.4a	66.8a
Continuous beta-blocker post-heart attack	92.3	87.5a	90.8a	88.3a
Statin use in patients with CVD	78.8	76.8a	81.5a	78.7
Statin adherence among patients with CVD	80.3	69.9a	80.9a	72.4a

Values are %. Data extracted from Martino et al (60).

^aP < 0.05 compared with Whites.

CVD = cardiovascular disease.

CENTERING EQUITY IN QUALITY IMPROVEMENT TO DISMANTLE STRUCTURAL RACISM

To visualize the drivers of inequities for those working to improve quality, we created an Equity-Centered Quality Improvement Model (Central Illustration) that explicitly maps the many influences within and outside of health care that contribute to inequitable patient outcomes. It highlights the key levers for achieving equitable cardiovascular outcomes by organizing the major underpinnings of racial and ethnic disparities in health care. These include factors that perpetuate inequities, such as structural features of care delivery organizations (for example, location and workforce), clinical care processes, and external influences on organizations and clinicians, such as regulations, financial incentives from insurance and payment, and other community factors.

CENTRAL ILLUSTRATION. An Equity-Centered Quality Improvement Model.

This model maps the contributors to inequitable patient outcomes. The model recognizes that clinicians and patients interact within a structure that enables clinicians to provide care (processes) to patients (27). Cardiovascular outcomes are the results achieved and can be characterized as intermediate (eg, blood pressure control) or final (eg, premature mortality). The model highlights the role of insurance benefits and payment policies that contribute to variations in quality, access, and equity at both the community and health system levels. Access to care and patient experience are major levers for reducing disparities in care. Figure based on Schneider et al (48).

The Donabedian framework of structure, process, and outcomes underpins this model (27). Donabedian viewed the interaction between a clinician and a patient (the “dyad”) as the primary building block for understanding health care quality. Clinicians and patients interact within a structure—the institutions, professionals, workforce, teams, and equipment that enable clinicians to provide care to patients. The delivery of care is a set of processes. High quality is achieved when the right health services are delivered to the right person at the right time every time. Cardiovascular outcomes are the results achieved and can be characterized as intermediate (eg, blood pressure control) or final (eg, death from CVD, including premature mortality). Measurement systems sometimes rely on processes of care (ie, readmissions) to serve as proxies for health outcomes.

The model emphasizes the role of insurance benefits and payment differentials that contribute to variations in quality, access, and equity at both the community and health system levels. Structural racism is complicated and multifactorial. Decades of economic and social divestment from minority-predominant communities have created and reinforced a wealth gap between BIPOC and White populations in America. Many issues, such as segregation in unequal housing and education, discrimination in employment, and environmental policies, cannot be addressed by health care organizations alone, but as a major and sometimes dominant employer in many communities, they can play an important role in community improvement through community benefit investments. Policies that disenfranchise the poor have a greater impact on BIPOC, including lack of benefits such as health insurance and paid sick leave (28,29).

The model highlights the importance of access to care and patient experience as major levers for reducing disparities in care. The twelve states that declined Medicaid expansion (Alabama, Florida, Georgia, Kansas, Mississippi, North Carolina, South Carolina, South Dakota, Tennessee, Texas, Wisconsin, and Wyoming) have higher rates of CVD mortality and are disproportionately home to large numbers of Black Americans (Figure 3B), Hispanic Americans (Figure 3D), and Indigenous Americans (Figure 3E). BIPOC with lower incomes and inadequate insurance often must seek care from public facilities far from home with limited transportation options.

Racism in medical research and discriminatory treatment approaches continue to fuel doubt about the motives of health professionals. Discrimination against patients, both historical and ongoing, breeds and reinforces mistrust of the health care system. Without trust, patients may not participate actively in care plans, adhere to treatment recommendations, or sustain lifestyle changes. Reducing discriminatory interactions with patients and families and enhancing access to care can increase the trustworthiness of institutions and professionals.

Disparities persist because delivery systems have not been intentionally designed to eliminate racial and ethnic differences in outcomes. Instead, delivery systems have placed patients in inequitably resourced care settings with limited workforce diversity, failed to achieve meaningful coordination, and propagated technical and interpersonal biases in care. The safety net institutions that serve people of color with the highest health risks are among the least well resourced. For example, the Indian Health Service has been grossly underfunded and understaffed, with poor access to cardiovascular specialty services. Interpreter services are frequently inadequate for patients with limited English proficiency (30). Within institutions, BIPOC are under-represented in professional and management positions, limiting the perspectives available to leadership. Biases also exist in equipment (pulse oximeters that fail to account for pigmentation differences) and in technical aspects of care, such as guidelines and treatment protocols or clinical laboratory test algorithms that incorporate race without a supporting evidence base (calculated renal clearance [estimated glomerular filtration rate] and pulmonary function testing) (31).

Racial and ethnic disparities in the application of diagnosis and treatment guidelines are well summarized in a recent review (32). Clinical judgment and effective decisions are at the core of high-quality processes of care. Poor decisions produce poor quality through delays in diagnosis, uneven and biased adherence to treatment guidelines, and delayed referrals of patients for appropriate consultations and procedures. Persistent racial bias affecting clinical decisions has been documented in studies using videotaped encounters and clinical vignettes as well as in qualitative studies that explore clinical decision processes (33,34). Implicit biases and the ways that negative stereotypes perpetuate racial and ethnic disparities were central to findings and recommendations of the Institute of Medicine 2003 report Unequal Treatment (2).

MOVING FROM AWARENESS TO ACTION

The disparities documented in this paper and efforts to address them are not new. Although we have seen improvement in some areas, the level of progress is not sufficient. We need to move from awareness to action that produces results.

Physicians, other health professionals, and health care systems can reduce racial and ethnic disparities in cardiovascular mortality and other outcomes if they simultaneously and intentionally address both quality and equity. As a recent AHA statement on structural racism noted, health care can address attitudes and beliefs (13). Awareness is a key factor. Until recently, the majority of individuals in the United States were unaware that health disparities exist by race and ethnicity (35). Many more are unaware of the impact of structural racism on health. Efforts that educate and elevate the discussion and awareness related to structural racism will be essential.

Based upon the Robert Wood Johnson Foundation’s Roadmap to Advance Health Equity, we propose a Roadmap to Advance Cardiovascular Health Equity that offers a useful framework and set of steps (36,37) and is consistent with prominent national proposals (38,39). Table 3 outlines the 5 steps of the Roadmap to Advance Cardiovascular Health Equity that may occur simultaneously: 1) create a culture of equity; 2) identify disparities; 3) diagnose root causes of disparities; 4) design and implement care interventions to advance cardiovascular health equity; and 5) design clinical performance reporting and payment systems to support and incentivize advancing cardiovascular health equity. Explicitly integrating quality and equity will be critical to ensure that the necessary attention and resources are garnered to enable these efforts to succeed.

TABLE 3.

Roadmap to Advance Cardiovascular Health Equity

Create a culture of equity Prioritize advancing health equity by incorporating into the organization’s mission statement, dashboards, and leadership compensation package Ensure that every worker (senior leaders, middle management, frontline clinicians and staff, nonclinical employees) knows how to advance health equity in their daily jobs Conduct implicit bias training Identify and eliminate organizational structures that bias against marginalized populations Create c-suite level Chief Equity Officer and adequately resourced equity team Diversify employees in the health care organization and represented voices on decision-making bodies Partner with patients and community organizations to advance cardiovascular health equity As an anchor institution in a community use purchasing, partnerships, policies, and recruitment to advance equity

Identify disparities Stratify clinical performance data by race and ethnicity Use geospatial analysis tools to identify geographically based assets and opportunities to reduce disparities

Diagnose root causes of disparities Identify and examine drivers of disparities in collaboration with patients, communities, and frontline clinicians and staff (eg, differential monitoring of blood pressure, medication affordability, dietary suggestions that are not culturally tailored) Recognize the role of place including the built and social environments (eg, no safe place to exercise; segregated housing from redlining; social networks, community experiences, level of trust in institutions)

Design and implement care interventions to advance cardiovascular health equity Interventions are intentionally designed to address the root causes driving the disparities Interventions can be designed for patients, communities, providers/care teams, health care organizations, and public policies. Example interventions include: Increase home blood pressure monitoring with enhanced broadband access Create community sites for blood pressure monitoring Use generic medications Create safe spaces in the community for exercise Culturally tailor dietary recommendations Imbed best practice alerts or prescribing algorithms in the electronic health record Provide implicit bias training to physicians Develop financing options for medications Improve ease and accessibility of collecting blood samples for laboratory tests Follow implementation science best practices Continuously evaluate results and adjust interventions as needed

Design clinical performance reporting and payment systems to support and incentivize advancing cardiovascular health equity Intentionally design performance reporting and payment systems to support and incentivize care delivery systems that advance cardiovascular health equity Publicly report metrics that measure cardiovascular disparities (eg, clinical performance measures stratified by race and ethnicity) Reward reducing disparities, improving performance, meeting absolute quality thresholds, and high performance in relation to benchmarks Consider both social risk adjustment and stratification of measures by social risk in reporting measures and adjusting payment to ensure that safety net organizations are not unfairly penalized while being held accountable

Creating a culture of equity means prioritizing equity in a way that has not been previously accomplished in most health systems. Prioritizing equity in this framework means bringing equity into every analysis and decision—asking not just whether an institution is improving effectiveness and safety on average overall but whether those gains are being realized by each group served by the delivery system. Organizations that evaluate all decisions through an equity lens (eg, purchasing, partnerships, policies, providers) will be more likely to recruit hire, train, and invest in communities in ways that also enhance organizational performance (40).

Identifying disparities involves analyzing both clinical data and geospatial data on race, ethnicity, and social risk factors. In analyzing clinical data, aggregating across all insurance types will be necessary to obtain adequate sample sizes in most organizations. Geospatial analysis, using tools such as the CDC Social Vulnerability Index (41) or the Social Deprivation Index (42), can identify areas with greater disparities as well as the local community infrastructure available to support healthy lifestyles.

Diagnosing root causes of disparities may include identifying persons who are at risk of poor health outcomes and are less engaged in health care, because either access is challenging or they have previously experienced discrimination in clinical settings. For example, an effective disparities reduction intervention for hypertension might identify patients with no measurement of blood pressure in the past year or 2 coupled with outreach by a community health worker. Medication adherence measures could identify persons who could benefit from medication but have not received it (43).

Designing interventions should take a broader perspective than modifying care for patients while they are in a clinical care setting. Tailoring solutions to patients and their communities may involve actively engaging patients and community health workers in developing and evaluating interventions. For example, patients knowledgeable about cultural practices, such as diets, or neighborhood resources, such as grocery stores, housing, transportation, and schools (which can be mapped using geospatial tools), religious and other community-supporting institutions can codesign interventions that are far more likely to be effective than those designed without such perspectives. Examples such as West Side United in the Chicago area demonstrate the power of bringing hospital and community partners together (44).

Awareness of how systemic racism affects outcomes is crucial to delivering care that is technically correct and interpersonally trustworthy. Clinical performance measurement systems must identify and monitor disparities in care. Quality of care reporting and payment systems must use data on disparities to motivate the work necessary to reduce racial and ethnic disparities in care and outcomes (45).

Concerted efforts to reduce disparities will require sustained attention and resources over years with many cycles of intervention, monitoring, and refinement of interventions. Sustaining these efforts and the culture of equity will require payment systems and other enabling policies that support and incentivize advancing health equity. Clinicians ready to engage in reducing health disparities should have the technical assistance and resources that enable them to do so successfully. Health care organizations, payors, and policymakers can create a virtuous cycle that increases equity and reinforces the culture of equity by identifying and celebrating successful models of care and care teams that reduce disparities.

CONCLUSIONS

Although cardiovascular medicine has partially reduced racial and ethnic disparities in health outcomes, persistent racial and ethnic gaps in processes and outcomes of care are an ongoing tragedy. Intentionally advancing cardiovascular health equity is an integral part of improving the quality of care. The Equity-Centered Quality Improvement Model and Roadmap to Advance Cardiovascular Health Equity provide practical guidance to improve the measurement and analysis of quality problems and the implementation of care interventions and policies that reduce racial and ethnic disparities in outcomes. Setting explicit organizational goals for equity should reflect emerging understandings of structural racism and engage people from local communities. Policy-makers, payers, and accreditors must align financial incentives to reward those who tackle this insidious problem. Change is possible. Seizing the equity initiative today will offer hope to future generations and accelerate further reductions in CVD morbidity and mortality.

HIGHLIGHTS.

• Racial and ethnic disparities in cardiovascular care that contribute to premature morbidity and mortality were reduced, but may be resurgent.

• Multiple factors, including structural racism, impede equitable care and adversely impact outcomes.

• Quality improvement programs are more effective when they address drivers of inequities both within and outside of health care systems.

ABBREVIATIONS AND ACRONYMS

BIPOC

Black, indigenous, and people of color

MA

Medicare Advantage

QI

quality improvement