Health Equity最新文献

{"title":"Preferences and Perspectives of Black Male Barbershop Patrons on Receiving Health Care in Nontraditional Settings","authors":"Sarah Chong, Brittany Huynh, Stephanie Wong, Temesgen Woldeyesus, Melvin Faulks, Kenneth El-Amin, Jabari Thibeaux, Joseph Lewis, Robert Harlin, Mario Carter, Ramy Shatara, Crystal Zhou, A. Oni‐Orisan","doi":"10.1089/heq.2023.0157","DOIUrl":"https://doi.org/10.1089/heq.2023.0157","url":null,"abstract":"Introduction: Non-Hispanic Black men experience a disproportionate rate of morbidity and mortality from hypertension, cardiovascular disease, and other chronic conditions in the United States. Studies have demonstrated the efficacy of community-based health outreach in settings not traditionally utilized for health care. Understanding how potential future participants view health care services in nontraditional settings is a necessary step to ascertain the success of these interventions in the real world. Our study objective was to explore the preferences of Black male barbershop patrons regarding health care-provided services in these nontraditional settings. Methods: We recruited patrons of a Black-owned barbershop in the San Francisco Bay Area. Study participants were asked to complete a survey assessing individual attitudes and preferences toward the idea of receiving health care services in traditional and nontraditional settings. Results: Among non-Hispanic Black males (n=17), 81% agreed or strongly agreed that they would prefer to receive health care in traditional clinics. Receiving care at the pharmacy (56% agreed or strongly agreed) and the patient's own home (53% agreed or strongly agreed) were the next most preferred locations. A minority of participants agreed or strongly agreed that they preferred to receive health care in nontraditional settings: 47% for barbershops, 19% for churches, and 6% for grocery stores. Discussion: Participants expressed preference for traditional over nontraditional settings, despite listing barriers that may be addressed, in part, by nontraditional settings. One potential reason for this is simply a lack of familiarity. Establishing and normalizing nontraditional clinical settings may allow for enhanced acceptance within Black communities, ultimately increasing health care access.","PeriodicalId":36602,"journal":{"name":"Health Equity","volume":"38 7","pages":"835 - 842"},"PeriodicalIF":2.7,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139023382","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Past Is Prologue: Dismantling Colonial Legacies to Advance Black Health Equity in the United States","authors":"Sirry M. Alang, Chelsey R. Carter, Oni Blackstock","doi":"10.1089/heq.2023.0226","DOIUrl":"https://doi.org/10.1089/heq.2023.0226","url":null,"abstract":"","PeriodicalId":36602,"journal":{"name":"Health Equity","volume":"55 11","pages":""},"PeriodicalIF":2.7,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139015946","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effects of Race and Gender Classifications on Atherosclerotic Cardiovascular Disease Risk Estimates for Clinical Decision-Making in a Cohort of Black Transgender Women.","authors":"Tonia Poteat, Elle Lett, Ashleigh J Rich, Huijun Jiang, Andrea L Wirtz, Asa Radix, Sari L Reisner, Alexander B Harris, Jowanna Malone, William G La Cava, Catherine R Lesko, Kenneth H Mayer, Carl G Streed","doi":"10.1089/heq.2023.0066","DOIUrl":"10.1089/heq.2023.0066","url":null,"abstract":"<p><strong>Introduction: </strong>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.</p><p><strong>Methods and materials: </strong>We assessed the effect of manipulating six different race-gender categories on ASCVD risk scores among 90 Black transgender women.</p><p><strong>Results: </strong>Risk scores varied by operationalization of race and gender and affected the proportion for whom statins were recommended.</p><p><strong>Discussion: </strong>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.</p>","PeriodicalId":36602,"journal":{"name":"Health Equity","volume":"7 1","pages":"803-808"},"PeriodicalIF":2.6,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10698798/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138810605","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Promoting Anti-Racism in Clinical Practice: Lessons Learned in the Process of Removing the Race Coefficient from the Estimated Glomerular Filtration Rate Algorithm.","authors":"Carla Boutin-Foster, Camille A Clare, Jameela Yusuff, Moro Salifu","doi":"10.1089/heq.2023.0095","DOIUrl":"https://doi.org/10.1089/heq.2023.0095","url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Objective: </strong>This article describes the process by which an academic medical center guided by the NYC-DOHMH tackled race-based clinical algorithms.</p><p><strong>Methods: </strong>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.</p><p><strong>Key outcomes: </strong>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.</p><p><strong>Conclusions: </strong>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.</p>","PeriodicalId":36602,"journal":{"name":"Health Equity","volume":"7 1","pages":"782-789"},"PeriodicalIF":2.7,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10698764/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138810622","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"<i>Health Equity</i> Journal: Special Issue Guest Editorial.","authors":"Michelle Morse, Adriana Joseph, Chandra Ford, Ruqaiijah Yearby, Nichola Davis","doi":"10.1089/heq.2023.29038.mmo","DOIUrl":"https://doi.org/10.1089/heq.2023.29038.mmo","url":null,"abstract":"","PeriodicalId":36602,"journal":{"name":"Health Equity","volume":"7 1","pages":"761-763"},"PeriodicalIF":2.7,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10698763/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138810591","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Critical Appraisal for Racial and Ethnic Equity in Clinical Prediction Models Extension: Development of a Critical Appraisal Tool Extension to Assess Racial and Ethnic Equity-Related Risk of Bias for Clinical Prediction Models.","authors":"Shazia M Siddique, Corinne V Evans, Michael Harhay, Eric S Johnson, Jaya Aysola, Gary E Weissman, Nikhil K Mull, Emilia Flores, Harald Schmidt, Kelley Tipton, Brian Leas, Jennifer S Lin","doi":"10.1089/heq.2023.0035","DOIUrl":"https://doi.org/10.1089/heq.2023.0035","url":null,"abstract":"<p><strong>Introduction: </strong>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.</p><p><strong>Objective: </strong>This study developed a critical appraisal tool extension to assess algorithmic bias in clinical prediction models.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusion: </strong>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.</p>","PeriodicalId":36602,"journal":{"name":"Health Equity","volume":"7 1","pages":"773-781"},"PeriodicalIF":2.7,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10698767/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138810601","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Eliminating Algorithmic Racial Bias in Clinical Decision Support Algorithms: Use Cases from the Veterans Health Administration.","authors":"Justin M List, Paul Palevsky, Suzanne Tamang, Susan Crowley, David Au, William C Yarbrough, Amol S Navathe, Craig Kreisler, Ravi B Parikh, Jessica Wang-Rodriguez, J Stacey Klutts, Paul Conlin, Leonard Pogach, Esther Meerwijk, Ernest Moy","doi":"10.1089/heq.2023.0037","DOIUrl":"10.1089/heq.2023.0037","url":null,"abstract":"<p><p>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.</p>","PeriodicalId":36602,"journal":{"name":"Health Equity","volume":"7 1","pages":"809-816"},"PeriodicalIF":2.7,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10698768/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138810616","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Race Correction and Algorithmic Bias in Atrial Fibrillation Wearable Technologies.","authors":"Beza Merid, Vanessa Volpe","doi":"10.1089/heq.2023.0034","DOIUrl":"https://doi.org/10.1089/heq.2023.0034","url":null,"abstract":"<p><p>Stakeholders in biomedicine are evaluating how race corrections in clinical algorithms inequitably allocate health care resources on the basis of a misunderstanding of race-as-genetic difference. Ostensibly used to intervene on persistent disparities in health outcomes across different racial groups, these troubling corrections in risk assessments embed essentialist ideas of race as a biological reality, rather than a social and political construct that reproduces a racial hierarchy, into practice guidelines. This article explores the harms of such race corrections by considering how the technologies we use to account for disparities in health outcomes can actually innovate and amplify these harms. Focusing on the design of wearable digital health technologies that use photoplethysmographic sensors to detect atrial fibrillation, we argue that these devices, which are notoriously poor in accurately functioning on users with darker skin tones, embed a subtle form of race correction that presupposes the need for explicit adjustments in the clinical interpretation of their data outputs. We point to research on responsible innovation in health, and its commitment to being responsive in addressing inequities and harms, as a way forward for those invested in the elimination of race correction.</p>","PeriodicalId":36602,"journal":{"name":"Health Equity","volume":"7 1","pages":"817-824"},"PeriodicalIF":2.7,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10698766/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138810673","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Z60.5/(En)Coded.","authors":"Ryan J Petteway","doi":"10.1089/heq.2023.0033","DOIUrl":"10.1089/heq.2023.0033","url":null,"abstract":"","PeriodicalId":36602,"journal":{"name":"Health Equity","volume":"7 1","pages":"790-792"},"PeriodicalIF":2.6,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10698783/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138810686","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Self-Fulfilling Process of Clinical Race Correction: The Case of Eighth Joint National Committee Recommendations.","authors":"Leah C Savage, Aaron Panofsky","doi":"10.1089/heq.2023.0064","DOIUrl":"10.1089/heq.2023.0064","url":null,"abstract":"<p><p>There is growing attention to how unfounded beliefs about biological differences between racial groups affect biomedical research and health care, in part, through race adjustment in clinical tools. We develop a case study of the Eighth Joint National Committee (JNC 8)'s 2014 Evidence-Based Guideline for the Management of High Blood Pressure in Adults, which recommends a distinct initial hypertension treatment for Black versus nonblack patients. We analyze the historical context, study design, and racialized findings of the Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial (ALLHAT) that informed development of the guideline. We argue that ALLHAT's racialized outcomes emanated from a poor and artificial study design and analysis weakened by implicit assumptions about race as biological. We show that the acceptance and utilization of ALLHAT for race correction arises from its historical context within the \"inclusion-and-difference paradigm\" and its indication of the inefficacy of angiotensin-converting-enzyme inhibitors for Black patients, which follows from the enduring, yet, refuted slavery hypertension hypothesis. We demonstrate that the JNC 8 guideline displays the self-fulfilling process of racial reasoning: presuppositions about racial differences inform the design and interpretation of research, which then conceptually reinforce ideas about racial differences leading to differential medical treatment. We advocate for the abolition of race adjustment and the integration of structural competency, biocritical inquiry, and race-conscious medicine into biomedical research and clinical medicine to disrupt the use of race as a proxy for ancestry, environment, and social treatment and to address the genuine determinants of racialized disparities in hypertension.</p>","PeriodicalId":36602,"journal":{"name":"Health Equity","volume":"7 1","pages":"793-802"},"PeriodicalIF":2.6,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10698797/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138810685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}