Mapping disparities in head and neck cancer care: Geospatial analysis of social vulnerability and healthcare access in the US.

Abstract

e23112 Background: Ensuring equitable access to head and neck (H&N) cancer care across the US is vital for optimal patient outcomes. This study explores the impact of social vulnerability on disparities in access to H&N multidisciplinary specialist care by US region and metro status. Methods: Oncologists and a subset of H&N cancer specialist practice locations were extracted from the National Provider Index, American Society of Clinical Oncology, and US News and World Report. Travel time using the fastest transportation mode from population-weighted county centroids to the nearest H&N cancer specialist (surgical, radiation, or medical oncologist) was computed using Travel Time API. Cancer data were obtained from United States Cancer Statistics and Surveillance, Epidemiology, and End Results (SEER). Regression analysis assessed impact of aspects of social vulnerability from the Social Vulnerability Index (SVI) on travel time. A disparity index incorporating travel time, county-level H&N cancer incidence, and SVI was developed to quantify disparities at the county-level. Results: In total, 18,241 medical, 6,387 radiation, and 2,564 surgical oncologists were identified, of which 346 medical, 308 radiation, and 453 surgical oncologists self-identified as H&N specialists. Regression analysis indicated that low household income and lack of insurance within counties significantly increased travel time ( p < .001) after controlling for US region, metro status, cancer rate, and other county-level factors. The disparity index identified counties with highest and lowest disparity (Table 1). Conclusions: Key findings highlight specific counties with higher vulnerability, primarily rural counties in the West and Southeast, and underscores the influence of social vulnerability on access to care. After accounting for US region and metro status, aspects of social vulnerability still predict travel time, with low household income and lack of insurance being the most impactful. Identified disparities in care may provide targets for interventions and policies aimed at reducing access inequalities, such as outreach programs and allocation of resources to underserved areas. [Table: see text]