Health Equity最新文献

Purpose: In 2020, the National Kidney Foundation (NKF) and the American Society of Nephrology (ASN) convened a Task Force to recommend an evidence-based race-free approach to estimated glomerular filtration rate (eGFR). After the rigorous review of more than 20 approaches, the NKF/ASN Task Force published the final report that recommended the implementation of the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI 2021) equation for eGFR using creatine and expanded utilization of cystatin C testing. The purpose of this manuscript is to provide a comprehensive overview of the evolution of eGFR equations, and an overview of the Task Force deliberations and recommendations. For over two decades, the equation recommended to calculate eGFR included a race coefficient to adjust for data that suggested that American adults with African ancestry had consistently higher serum creatinine levels.

Methods: We will provide a discussion illustrating why the 2021 CKD EPI equations are the most equitable solution to eGFR. We will also provide an overview of the current implementation status and best practices for the new equations. Lastly, we will discuss how deployment of the new equations is an important step toward eliminating significant disparities in CKD care which disproportionately affect communities of color.

Results: Removing race from the algorithm used to assess kidney function is most equitable. Since race is a social construct, its use in clinical algorithms has facilitated health disparities in Black/African American people, Hispanic/Latino people, and other racial and ethnic minority groups-those who are already disproportionately impacted by diabetes, hypertension, and kidney disease. In turn, these same individuals experience significant inequities in kidney health care including reduced access to nephrology care, home dialysis, and kidney transplant.

Conclusions: Adoption of the race-free 2021 CKD-EPI eGFR equations will have life changing implications for kidney health. It will aid in appropriate referral, identification, diagnosis, treatment, and management of kidney disease and transplantation services/options. The outcomes of widespread implementation of the new equations coupled with system change quality improvement interventions such as the kidney profile will lead to more equitable outcomes and begin to address the crippling disparities in early, appropriate testing for CKD.

Introduction: Perinatal Mood and Anxiety Disorders (PMADs) are the most common complications during the perinatal period. There is limited understanding of the gaps between need and provision of comprehensive health services for childbearing people, especially among racialized populations.

Methods: The Giving Voice to Mothers Study (GVtM; n=2700), led by a multistakeholder, Steering Council, captured experiences of engaging with perinatal services, including access, respectful care, and health systems' responsiveness across the United States. A patient-designed survey included variables to assess relationships between race, care provider type (midwife or doctor), and needs for psychosocial health services. We calculated summary statistics and tested for significant differences across racialized groups, subsequently reporting odds ratios (ORs) for each group.

Results: Among all respondents, 11% (n=274) reported unmet needs for social and mental health services. Indigenous women were three times as likely to have unmet needs for treatment for depression (OR [95% confidence interval, CI]: 3.1 [1.5-6.5]) or mental health counseling (OR [95% CI]: 2.8 [1.5-5.4]), followed by Black women (OR [95% CI]: 1.8 [1.2-2.8] and 2.4 [1.7-3.4]). Odds of postpartum screening for PMAD were significantly lower for Latina women (OR [95% CI]=0.6 [0.4-0.8]). Those with midwife providers were significantly more likely to report screening for anxiety or depression (OR [95% CI]=1.81 [1.45-2.23]) than those with physician providers.

Discussion: We found significant unmet need for mental health screening and treatment in the United States. Our results confirm racial disparities in referrals to social services and highlight differences across provider types. We discuss barriers to the integration of assessments and interventions for PMAD into routine perinatal services.

Implications: We propose incentivizing reimbursement schema for screening and treatment programs; for community-based organizations that provide mental health and social services; and for culture-centered midwife-led perinatal and birth centers. Addressing these gaps is essential to reproductive justice.

Introduction: Despite their dynamic, socially constructed, and imprecise nature, both race and gender are included in common risk calculators used for clinical decision-making about statin therapy for atherosclerotic cardiovascular disease (ASCVD) prevention.

Methods and materials: We assessed the effect of manipulating six different race-gender categories on ASCVD risk scores among 90 Black transgender women.

Results: Risk scores varied by operationalization of race and gender and affected the proportion for whom statins were recommended.

Discussion: Race and gender are social constructs underpinning racialized and gendered health inequities. Their rote use in ASCVD risk calculators may reinforce and perpetuate existing inequities.

Background: Promoting anti-racism in medicine entails naming racism as a contributor to health inequities and being intentional about changing race-based practices in health care. Unscientific assumptions about race have led to the proliferation of race-based coefficients in clinical algorithms. Identifying and eliminating this practice is a critical step to promoting anti-racism in health care. The New York City Department of Health and Mental Hygiene (NYC-DOHMH) formed the Coalition to End Racism in Clinical Algorithms (CERCA), a health system consortium charged with eliminating clinical practices and policies that perpetuate racism.

Objective: This article describes the process by which an academic medical center guided by the NYC-DOHMH tackled race-based clinical algorithms.

Methods: Multiple key interested parties representing department chairs, hospital leaders, researchers, legal experts, and clinical pathologists were convened. A series of steps ensued, including selecting a specific clinical algorithm to address, conducting key informant interviews, reviewing relevant literature, reviewing clinical data, and identifying alternative and valid algorithms.

Key outcomes: Given the disproportionately higher rates of chronic kidney disease risk factors, estimated glomerular filtration rate (eGFR) was prioritized for change. Key informant interviews revealed concerns about the clinical impact that removing race from the equation would have on patients, potential legal implications, challenges of integrating revised algorithms in practice, and aligning this change in clinical practice with medical education. This collaborative process enabled us to tackle these concerns and successfully eliminate race as a coefficient in the eGFR algorithm.

Conclusions: CERCA serves as a model for developing academic and public health department partnerships that advance health equity and promote anti-racism in practice. Lessons learned can be adapted to identify, review, and remove the use of race as a coefficient from other clinical guidelines.

Introduction: Despite mounting evidence that the inclusion of race and ethnicity in clinical prediction models may contribute to health disparities, existing critical appraisal tools do not directly address such equity considerations.

Objective: This study developed a critical appraisal tool extension to assess algorithmic bias in clinical prediction models.

Methods: A modified e-Delphi approach was utilized to develop and obtain expert consensus on a set of racial and ethnic equity-based signaling questions for appraisal of risk of bias in clinical prediction models. Through a series of virtual meetings, initial pilot application, and an online survey, individuals with expertise in clinical prediction model development, systematic review methodology, and health equity developed and refined this tool.

Results: Consensus was reached for ten equity-based signaling questions, which led to the development of the Critical Appraisal for Racial and Ethnic Equity in Clinical Prediction Models (CARE-CPM) extension. This extension is intended for use along with existing critical appraisal tools for clinical prediction models.

Conclusion: CARE-CPM provides a valuable risk-of-bias assessment tool extension for clinical prediction models to identify potential algorithmic bias and health equity concerns. Further research is needed to test usability, interrater reliability, and application to decision-makers.

The Veterans Health Administration uses equity- and evidence-based principles to examine, correct, and eliminate use of potentially biased clinical equations and predictive models. We discuss the processes, successes, challenges, and next steps in four examples. We detail elimination of the race modifier for estimated kidney function and discuss steps to achieve more equitable pulmonary function testing measurement. We detail the use of equity lenses in two predictive clinical modeling tools: Stratification Tool for Opioid Risk Mitigation (STORM) and Care Assessment Need (CAN) predictive models. We conclude with consideration of ways to advance racial health equity in clinical decision support algorithms.