[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-seo-427961-105":3,"detail-sidebar-cat-0-en-105":85,"doc-detail-427961-en":135},{"code":4,"msg":5,"data":6},0,"ok",{"site_id":7,"language":8,"slug":9,"title":10,"keywords":11,"description":12,"schema_data":13,"social_meta":78,"head_meta":80,"extra_data":82,"updated_unix":84},105,"en","upstream-drivers-of-receiving-care-in-minority-serving-hospitals-a-cross-sectional-study-using-mcbs-data","UPSTREAM DRIVERS OF RECEIVING CARE IN MINORITY-SERVING HOSPITALS - A CROSS-SECTIONAL STUDY USING MCBS DATA","","Racial separation of care contributes to health disparities, yet little is known about factors upstream of receiving care in minority-serving hospitals (MSHs) or how these differ by race/ethnicity. Cross-sectional analyses of MCBS data (2010-2019) contrasted MSH hospitalization versus non-MSH, evaluating race/ethnicity and insurance, neighborhood disadvantage (SDI), and regional residential racial segregation with individual and regional covariates. In fully adjusted models, race/ethnicity, dual-eligible status, neighborhood disadvantage, and residential segregation were independently associated with MSH hospitalization, with stronger effects for Black versus White patients in least/most disadvantaged and segregated contexts. Findings support further research on site-of-care determinants and investment in MSHs while addressing socio-structural influences like neighborhood disadvantage and segregation.",{"@graph":14,"@context":77},[15,34,56],{"@type":16,"itemListElement":17},"BreadcrumbList",[18,23,27,31],{"item":19,"name":20,"@type":21,"position":22},"https://docshare.wps.com","Home","ListItem",1,{"item":24,"name":25,"@type":21,"position":26},"https://docshare.wps.com/document/","Document",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/document/research-report/","Research & 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is the study’s main question about minority-serving hospitals?","Question",{"text":63,"@type":64},"The study examines upstream drivers of receiving care in minority-serving hospitals and whether associations differ by race/ethnicity.","Answer",{"name":66,"@type":61,"acceptedAnswer":67},"What data and study design were used?",{"text":68,"@type":64},"The analysis uses cross-sectional MCBS data from 2010 to 2019, comparing hospitalizations in minority-serving hospitals versus not.",{"name":70,"@type":61,"acceptedAnswer":71},"Which factors were independently associated with hospitalization in MSHs?",{"text":72,"@type":64},"Race/ethnicity, dual-eligible status, neighborhood disadvantage (SDI), and residential segregation were independently associated with MSH hospitalization in fully adjusted models.",{"name":74,"@type":61,"acceptedAnswer":75},"What do the results imply for future research and policy?",{"text":76,"@type":64},"The findings suggest further research on determinants of site of care and the need to invest in minority-serving hospitals while addressing socio-structural drivers such as neighborhood disadvantage and residential segregation.","https://schema.org",{"og:url":32,"og:type":79,"og:title":10,"og:site_name":45,"og:description":12},"article",{"robots":81,"canonical":32},"index,follow",{"doc_id":83,"site_id":7},427961,1790741578,{"code":4,"msg":86,"data":87},"success",[88,92,96,100,105,110,115,119,124,127,131],{"id":22,"doc_module":4,"doc_module_name":25,"category_name":89,"show_sort_weight":90,"slug":91},"Story & 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IN  \nMINORITY-SERVING HOSPITALS: A  \nCROSS-SECTIONAL STUDY USING MCBS DATA  \nLouisa Holaday1, Alina Kung1, Yingtong Chen2,  \nKaren McKendrick1, Bian Liu1, and Albert Siu2, 1. Icahn School of Medicine at Mount Sinai, New York, New York, United States, 2. Icahn School of Medicine at Mount Sinai, new york, New York, United States  \nIntro: Racial separation of care contributes to racial disparities in health. Little is known about upstream drivers of receiving care in a minority-serving hospital (MSH) and differences by race/ethnicity. Methods: Cross-sectional analysis of MCBS data (2010-2019) with binary outcome of hospitalization in MSH versus not. Exposures of interest were individual race/ethnicity and insurance; neighborhood disadvantage (SDI); and regional residential racial segregation. We included individual and regional covariates. In fully adjusted models, we tested whether race/ethnicity modified the association between SDI or residential segregation and hospitalization in MSH. Results: Among 8,735 hospitalizations, race/ethnicity (aOR 3.19 for Black vs. White patients; 95% Confidence Interval (CI): 2.60-3.91; P \u003C 0.001); dual-eligible status (aOR: 1.30, 95% CI: 1.05-1.60; P \u003C 0.05), neighborhood disadvantage (aOR for most disadvantaged versus least: 2.03, 95% CI: 1.56-2.63, P \u003C 0 .001); and residential  \nsegregation (aOR for high segregation versus low: 2.99, 95%  \nCI: 1.98-4.52; P \u003C 0.001) were independently associated with hospitalization in MSH. In the least disadvantaged or segregated areas, all patients were unlikely to be hospitalized in MSH; however, in the most disadvantaged or segregated areas, White patients had only a small increase in odds ofMSH hospitalization while Black patients had a very large increase (P for interaction terms = 0.001 and 0.04, respectively) . Conclusion: Our findingson differences by race/ethnicity suggest a need for further research on factors driving site of care, to address the upstream  \n1096 Innovation in Aging, 2025, Vol. 9, No. S2  \nsocio-structural determinants of health, and to invest in minority-serving hospitals given the practical challenges of eliminating neighborhood disadvantage and residential segregation.","cbCaijmqSaeoukOs","https://ap.wps.com/l/cbCaijmqSaeoukOs","pdf",1893478,"English","# Introduction\n# Methods\n# Results\n# Conclusion","[{\"question\":\"What is the study’s main question about minority-serving hospitals?\",\"answer\":\"The study examines upstream drivers of receiving care in minority-serving hospitals and whether associations differ by race/ethnicity.\"},{\"question\":\"What data and study design were used?\",\"answer\":\"The analysis uses cross-sectional MCBS data from 2010 to 2019, comparing hospitalizations in minority-serving hospitals versus not.\"},{\"question\":\"Which factors were independently associated with hospitalization in MSHs?\",\"answer\":\"Race/ethnicity, dual-eligible status, neighborhood disadvantage (SDI), and residential segregation were independently associated with MSH hospitalization in fully adjusted models.\"},{\"question\":\"What do the results imply for future research and policy?\",\"answer\":\"The findings suggest further research on determinants of site of care and the need to invest in minority-serving hospitals while addressing socio-structural drivers such as neighborhood disadvantage and residential segregation.\"}]","UPSTREAM DRIVERS OF RECEIVING CARE IN MINORITY-SERVING HOSPITALS - A CROSS-SECTIONAL STUDY USING MCBS DATA | PDF",1790645308]