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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]

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]