Advancing health equity in cardiovascular care
Bibliographic record
Abstract
Unacceptable and complex yet also often unintended and unexpected health inequities exist in cardiovascular care and outcomes. While prevalent across health care, professionals involved in cardiovascular health care should know and address the sources of these inequalities in practice and policy. This editorial provides a primer to do so. Health equity is a principle underlying a commitment to reduce and even eliminate downstream disparities in and upstream determinants of health, including social and economic ones. Pursuing health equity means striving for the highest possible standard of health for all people, especially those at greatest risk of poor health outcomes. Accordingly, health equity is the state in which every person has a fair and just opportunity to realize their highest level of health.1 Unlike health equality, which refers to equal health care for everyone, health equity aims to adjust healthcare resources based on need. Thus, equity refers to fairness in healthcare outcomes regardless of any social determinants of health.1 Key social determinants of cardiovascular health include socioeconomic status, race and ethnicity, social support, culture and language, access to care, and residential environment.2 This also aligns with the notion that health has multiple determinants, including but beyond social determinants, such as genetic, behavioural, environmental, and physical factors.2,3 Accordingly, the health of people and communities is influenced by a myriad of physical, social, and economic conditions, including highly interrelated, clustered, and compounding social, cultural, and structural factors affecting individuals and communities. For example, educational attainment is strongly linked to individual and neighbourhood deprivation and low health literacy.4 People from low socioeconomic areas are more likely to undertake behaviour and have risk factors associated with cardiovascular disease, such as physical inactivity, smoking, diabetes, hypertension, and a high body mass index.4,5 Given upstream factors such as neighbourhood and household poverty and unequal access to education and health care are also associated with premature cardiovascular disease, patients from low socioeconomic areas, while at highest risk from multiple determinants, are ironically less likely to access and benefit from effective health care. The clustering of the multiple determinants of health leads to widespread and wide health disparities. There is extensive evidence of health disparities in cardiovascular health care, access, and outcomes, as illustrated by a recent editorial6 documenting disparities in cardiovascular mortality among Black and White men and women,7 between Hispanic and Asian adults and White adults,8 in atrial fibrillation care for people living in neighbourhoods with few socioeconomic resources,9 and even in the allocation of precious resources for heart transplantation for children.10 Again, these downstream disparities reflect upstream disparities linked to socioeconomic and environmental factors over the life course. Living in ‘redlined’ neighbourhoods (often characterized by having significant numbers of low-income residents) is associated with long-term adverse cardiovascular outcomes.11 In health care, high-income individuals with acute myocardial infarction have substantially better survival, are more likely to receive lifesaving revascularization, and have shorter hospital lengths of stay and fewer readmissions than low-income individuals.12 But in early life too, children who experience adversity are at higher risk of developing cardiovascular disease in young adulthood.13 Sex and gender are linked to disparities too. For example, in relation to ischaemic heart disease, women have higher morbidity and mortality rates than men and differ in the presentation of symptoms which may contribute to delays in diagnosis or appropriate treatment, where the gendered presentation of symptoms was not recognized by clinical staff, thus resulting in worse outcomes.14 Similarly, there are sex-related differences in the presentation and course of hypertension, with women having a more rapid increase in progressive blood pressure elevation than men, beginning as young as 30 years of age and persisting with aging.15 As the leading cause of death in women, the sex-specific mechanism for the development of cardiovascular disease has been poorly researched,16 and the lack of women’s representation in cardiovascular trials is a telling example of inequity in cardiovascular care.16 Thus, cardiovascular disease in women remains ‘understudied, under-recognized, underdiagnosed, and undertreated’ (p. 2385).16 To address health disparities, a tangible commitment to promoting diversity and inclusion is needed to advance health equity in cardiovascular care. Whether spanning race, ethnicity, culture, sex, gender, age, or geographical location—improving social justice for patients and preventing them and their families and communities from being marginalized is vital. There is a web of linked upstream and downstream barriers to equity in cardiovascular care and outcomes. The high cost of care, inadequate insurance coverage, and unavailable or limited provision of services and lack of culturally competent care, which are often themselves linked to race and ethnicity, sex and gender, age, poverty, low education and low health literacy, disability, job insecurity, and geographical location, result in delays in receiving appropriate care and inability to secure preventive services. For example, people with cardiovascular disease, particularly from marginalized communities, may face inequity in healthcare access, disparities in symptom recognition, bias in the provision of timely and optimal health care, and implicit bias among health professionals.17 Overcoming such barriers involves a change in thinking, feeling, and doing. The 2021 consensus study from the US National Academy of Medicine ‘The Future of Nursing 2020–2030: Charting a Path to Achieve Health Equity’18 offers recommendations for cardiovascular healthcare professionals to prioritize, including to: Address social determinants of health and provide effective, efficient, equitable, and accessible care for all across the care continuum, as well as identify the system facilitators and barriers to achieving this goal Employ a workforce that is diverse, including gender, race, and ethnicity, across all levels of education Provide the training, education, and competency development needed to prepare cardiovascular healthcare professionals to lead efforts to build a culture of health and health equity Conduct the research needed to identify or develop effective practices for eliminating gaps and disparities in health care To enable this depends on individual, professional, and institutional commitment and leadership. The American College of Cardiology19 notes that coordinated, collaborative efforts are the key to creating necessary policy changes to address health equity. Education for people, policymakers, and healthcare professionals and ensuring a diverse cardiovascular healthcare workforce are also keys to advancing health equity. Other steps to improve equity include ensuring disease management guidelines acknowledge the influence of social determinants of health on care and incorporate addressing these in updated versions.20 This is imperative as clinical practice is informed by guidelines. Just as guidelines are informed by research evidence, another important step is ensuring adequate representation of diverse, marginalized, and less privileged populations in research studies and clinical trials.21 In terms of implementation science, the American Heart Association22 provides a roadmap and checklist to help leverage implementation science to promote cardiovascular health equity. In an era of digital technology, digital health interventions have the potential to improve cardiovascular health care by obtaining continuous and actionable patient data, increasing access to care and decreasing delivery barriers and cost.23 However, marginalized and other equity-denied populations have lower access to digital health innovations and decreased representation in cardiovascular digital health trials; thus, there is a need to ensure health ‘techequity’.23 A major and pervasive barrier to health equity is low personal and organizational health literacy. Health literacy is a modifiable factor mediating the link between socioeconomic status and health disparities, and it is a better predictor of racial and ethnic health disparities than income and education.24 Healthcare professionals should avoid making health information unnecessarily complicated and use a variety of clear communication best practices to address inequities in education and higher health literacy.24 Cardiovascular healthcare professionals and this journal play an important role in raising awareness of cardiovascular healthcare disparities.25 Reporting study findings pertaining to these on a variety of topics is important; for instance, illness perceptions and health literacy being strongly associated with health-related quality of life and psychological distress,26 socioeconomic status affecting weight status through health-related lifestyles,27 socioeconomic status affecting cardiac rehabilitation participation,28 and factors affecting women’s participation in cardiovascular research.29 All cardiovascular health professionals should adhere to their professional and ethical codes of conduct to ensure the provision of fair and equal care to all. They have a major role to play in advocating for and advancing health equity in cardiovascular care, including prevention, disease management, and rehabilitation. This role includes raising awareness, providing information, disseminating knowledge, enhancing health literacy, correcting misconceptions, bolstering family/social support, mobilizing community assets, and promoting equity, diversity, and inclusion. To advance health equity in cardiovascular health care, we firstly need to be aware of and acknowledge potential health inequities and prioritize efforts to detect, understand, and reduce them through training, decision support, and peer networks. We have a professional, moral, and ethical duty to do this working in partnership with the patient, family, community, and others. In a rapidly changing healthcare landscape, which is often fragmented and disjointed, it is likely that an integrated care approach, which places the person/patient firmly at the centre, is collaborative, involves shared decision-making, and ensures continuity, will be the most effective means to advance health equity.30 But paramount to its success will be the establishment of trust.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.049 | 0.100 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.013 |
| Scholarly communication | 0.015 | 0.017 |
| Open science | 0.003 | 0.021 |
| Research integrity | 0.019 | 0.023 |
| Insufficient payload (model declined to judge) | 0.032 | 0.004 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".