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Left Behind: Mapping Gaps in Healthcare Access for Racial Minorities

Shuyue Zhang
Scarsdale High School, Scarsdale, USA
​​​Publication date: November 20, 2025
​DOI: http://doi.org/10.34614/JIYRC2025II64
ABSTRACT 
Despite all its wealth, America is faced with persistent racial and geographic disparities in healthcare access. Structural racism, underfunding of safety-net programs, and uneven policy incentives have left many communities concentrated with racial and ethnic minorities without a consistent source of care. New York State serves as an excellent model of such disparities, given its diversity. The decentralized nature of the U.S. healthcare system shapes local decision-makers as crucial stakeholders in interventions, yet there is a lack of granular models that pinpoint problematic hotspot regions and can guide local policymaking. To address this gap, this project examines the intersection of race and access to primary care providers (PCP) across New York State using publicly available data. Rather than re-establishing known correlations between race and healthcare access, this study uses these relationships as an identification tool to pinpoint specific tracts where interventions are most urgently needed. With bivariate choropleth mapping and census tract-level spatial analyses, mapping identifies disparities in urban sites such as the Bronx, Buffalo, and Rochester, as well as ubiquitous shortages in upstate rural areas. Findings report a significant association between minority concentration and self-reported barriers to care, like treatment delay and lack of a usual provider. Mapping results also identify bright spots wherein locally competent systems counteract disadvantage, offering lessons for policy interventions and targeted resource distribution. Beyond informing policies for tract-level intervention like augmented clinic networks, provider incentives, and community-based outreach, the study offers a replicable model for revealing health equity disparities and mobilizing local stakeholders to address them through data-driven policy.

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  • Information
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