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Racism has resulted in significant disproportionality and disparity in the US child welfare system. Being Black is not an inherent risk factor for child abuse and neglect yet Black children are almost twice as likely to be victims of substantiated abuse and neglect claims compared to other racial groups. Addressing the disproportionality within the child welfare system due to systemic racism falls squarely under the purview of bioethics. In this paper, we briefly review the impact of racism on child welfare. We then discuss some ethical considerations that mandatory healthcare reporters should think through when determining whether to report potential abuse and neglect. Specifically, we discuss the need for a broader consideration of what constitutes harm. We then present a hypothetical composite case to illuminate where and how bias can enter the process of referral to child protective services (CPS). We encourage thoughtful reporting with consideration of social and historical context and alternative explanations for worrisome findings. We recommend using evidence, avoiding assumptions by seeking clarification from families and ensuring internal consistency. When contemplating CPS referral, medical providers should feel empowered to ask questions if there is concern for potential bias. The ultimate goal is to protect children from harm. If there are clear safety concerns—they must be addressed. However, in the many cases where the safety concern is less tangible, we need to expand our considerations of the harms that can befall children, especially children of color. [ABSTRACT FROM AUTHOR]

The COVID‐19 pandemic has had a disproportionate impact on the health of Black Americans, Latinx or Hispanic Americans, and American Indians. These disparities are deeply unjust, in part, because they are the causal result of racism at both the interpersonal and structural levels. This paper argues, however, that establishing a causal connection between racism and health disparities is not the only way to explain the injustice of these disparities. The COVID‐19 health disparities are arguably unjust because health equity is a "free‐standing" demand of justice, an obligation of reparative justice, a remedy to structural injustice, and part of dismantling pernicious racial concepts. Identifying multiple accounts of injustice may lower the evidentiary bar for our normative claims and help us to identify alternative policy pathways for ending health inequity. [ABSTRACT FROM AUTHOR]

Introduction: Healthcare organisations serve clients from diverse Indigenous and other ethnic and racial groups on a daily basis, and require appropriate client-centred systems and services for provision of optimal healthcare. Despite advocacy for systems-level approaches to cultural competence, the primary focus in the literature remains on competency strategies aimed at health promotion initiatives, workforce development and student education. This paper aims to bridge the gap in available evidence about systems approaches to cultural competence by systematically mapping key concepts, types of evidence, and gaps in research. Methods: A literature search was completed as part of a larger systematic search of evaluations and measures of cultural competence interventions in health care in Canada, the United States, Australia and New Zealand. Seventeen peer-reviewed databases, 13 websites and clearinghouses, and 11 literature reviews were searched from 2002 to 2015. Overall, 109 studies were found, with 15 evaluating systems-level interventions or describing measurements. Thematic analysis was used to identify key implementation principles, intervention strategies and outcomes reported. Results: Twelve intervention and three measurement studies met our inclusion criteria. Key principles for implementing systems approaches were: user engagement, organisational readiness, and delivery across multiple sites. Two key types of intervention strategies to embed cultural competence within health systems were: audit and quality improvement approaches and service-level policies or strategies. Outcomes were found for organisational systems, the client/practitioner encounter, health, and at national policy level. Discussion and implications: We could not determine the overall effectiveness of systems-level interventions to reform health systems because interventions were context-specific, there were too few comparative studies and studies did not use the same outcome measures. However, examined together, the intervention and measurement principles, strategies and outcomes provide a preliminary framework for implementation and evaluation of systems-level interventions to improve cultural competence. Identified gaps in the literature included a need for cost and effectiveness studies of systems approaches and explication of the effects of cultural competence on client experience. Further research is needed to explore the extent to which cultural competence improves health outcomes and reduces ethnic and racially-based healthcare disparities. [ABSTRACT FROM AUTHOR]

This paper examines how an overseas medical student can improve the life of a kamlari, an indentured servant girl in Nepal. I argue that physicians and students should not only provide care for the health and well-being of patients but also act to ameliorate the suffering of their patients, particularly when patients' social, cultural, economic, and political vulnerabilities overshadow their immediate clinical needs. I also address the point that medical schools need to offer courses on health advocacy and activism in order to promote health equity and social justice for all. [ABSTRACT FROM AUTHOR]

Background: Health care organizations need to be responsive to the needs of increasingly diverse patient populations. We compared the contents of six publicly available approaches to organizational responsiveness to diversity. The central questions addressed in this paper are: what are the most consistently recommended issues for health care organizations to address in order to be responsive to the needs of diverse groups that differ from the majority population? How much consensus is there between various approaches?Methods: We purposively sampled six approaches from the US, Australia and Europe and used qualitative textual analysis to categorize the content of each approach into domains (conceptually distinct topic areas) and, within each domain, into dimensions (operationalizations). The resulting classification framework was used for comparative analysis of the content of the six approaches.Results: We identified seven domains that were represented in most or all approaches: organizational commitment, empirical evidence on inequalities and needs, a competent and diverse workforce, ensuring access for all users, ensuring responsiveness in care provision, fostering patient and community participation, and actively promoting responsiveness. Variations in the operationalization of these domains related to different scopes, contexts and types of diversity. For example, approaches that focus on ethnic diversity mostly provide recommendations to handle cultural and language differences; approaches that take an intersectional approach and broaden their target population to vulnerable groups in a more general sense also pay attention to factors such as socio-economic status and gender.Conclusions: Despite differences in labeling, there is a broad consensus about what health care organizations need to do in order to be responsive to patient diversity. This opens the way to full scale implementation of organizational responsiveness in healthcare and structured evaluation of its effectiveness in improving patient outcomes. [ABSTRACT FROM AUTHOR]

Background: Annually since 2010, the University of Wisconsin Population Health Institute and the Robert Wood Johnson Foundation have produced the County Health Rankings--a "population health checkup" for the nation's over 3,000 counties. The purpose of this paper is to review the background and rationale for the Rankings, explain in detail the methods we use to create the health rankings in each state, and discuss the strengths and limitations associated with ranking the health of communities. Methods: We base the Rankings on a conceptual model of population health that includes both health outcomes (mortality and morbidity) and health factors (health behaviors, clinical care, social and economic factors, and the physical environment). Data for over 30 measures available at the county level are assembled from a number of national sources. Z-scores are calculated for each measure, multiplied by their assigned weights, and summed to create composite measure scores. Composite scores are then ordered and counties are ranked from best to worst health within each state. Results: Health outcomes and related health factors vary significantly within states, with over two-fold differences between the least healthy counties versus the healthiest counties for measures such as premature mortality, teen birth rates, and percent of children living in poverty. Ranking within each state depicts disparities that are not apparent when counties are ranked across the entire nation. Discussion: The County Health Rankings can be used to clearly demonstrate differences in health by place, raise awareness of the many factors that influence health, and stimulate community health improvement efforts. The Rankings draws upon the human instinct to compete by facilitating comparisons between neighboring or peer counties within states. Since no population health model, or rankings based off such models, will ever perfectly describe the health of its population, we encourage users to look to local sources of data to understand more about the health of their community. [ABSTRACT FROM AUTHOR]

Introduction Accurate measurement of health inequities is indispensable to track progress or to identify needs for health equity policy interventions. A key empirical task is to measure the extent to which observed inequality in health - a difference in health - is inequitable. Empirically operationalizing definitions of health inequity has generated an important question not considered in the conceptual literature on health inequity. Empirical analysis can explain only a portion of observed health inequality. This paper demonstrates that the treatment of unexplained inequality is not only a methodological but ethical question and that the answer to the ethical question - whether unexplained health inequality is unfair - determines the appropriate standardization method for health inequity analysis and can lead to potentially divergent estimates of health inequity. Methods We use the American sample of the 2002-03 Joint Canada/United States Survey of Health and measure health by the Health Utilities Index (HUI). We model variation in the observed HUI by demographic, socioeconomic, health behaviour, and health care variables using Ordinary Least Squares. We estimate unfair HUI by standardizing fairness, removing the fair component from the observed HUI. We consider health inequality due to factors amenable to policy intervention as unfair. We contrast estimates of inequity using two fairness- standardization methods: direct (considering unexplained inequality as ethically acceptable) and indirect (considering unexplained inequality as unfair). We use the Gini coefficient to quantify inequity. Results Our analysis shows that about 75% of the variation in the observed HUI is unexplained by the model. The direct standardization results in a smaller inequity estimate (about 60% of health inequality is inequitable) than the indirect standardization (almost all inequality is inequitable). Conclusions The choice of the fairness-standardization method is ethical and influences the empirical health inequity results considerably. More debate and analysis is necessary regarding which treatment of the unexplained inequality has the stronger foundation in equity considerations. [ABSTRACT FROM AUTHOR]