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  • Author or Editor: Phiroz E. Tarapore x
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Sudheesha Perera, Shawn L. Hervey-Jumper, Praveen V. Mummaneni, Ernest J. Barthélemy, Alexander F. Haddad, Dario A. Marotta, John F. Burke, Andrew K. Chan, Geoffrey T. Manley, Phiroz E. Tarapore, Michael C. Huang, Sanjay S. Dhall, Dean Chou, Katie O. Orrico, and Anthony M. DiGiorgio

OBJECTIVE

This study attempts to use neurosurgical workforce distribution to uncover the social determinants of health that are associated with disparate access to neurosurgical care.

METHODS

Data were compiled from public sources and aggregated at the county level. Socioeconomic data were provided by the Brookings Institute. Racial and ethnicity data were gathered from the Centers for Disease Control and Prevention Wide-ranging Online Data for Epidemiologic Research. Physician density was retrieved from the Health Resources and Services Administration Area Health Resources Files. Catchment areas were constructed based on the 628 counties with neurosurgical coverage, with counties lacking neurosurgical coverage being integrated with the nearest covered county based on distances from the National Bureau of Economic Research’s County Distance Database. Catchment areas form a mutually exclusive and collectively exhaustive breakdown of the entire US population and licensed neurosurgeons.

Socioeconomic factors, race, and ethnicity were chosen as independent variables for analysis. Characteristics for each catchment area were calculated as the population-weighted average across all contained counties. Linear regression analysis modeled two outcomes of interest: neurosurgeon density per capita and average distance to neurosurgical care. Coefficient estimates (CEs) and 95% confidence intervals were calculated and scaled by 1 SD to allow for comparison between variables.

RESULTS

Catchment areas with higher poverty (CE = 0.64, 95% CI 0.34–0.93) and higher prime age employment (CE = 0.58, 95% CI 0.40–0.76) were significantly associated with greater neurosurgeon density. Among categories of race and ethnicity, catchment areas with higher proportions of Black residents (CE = 0.21, 95% CI 0.06–0.35) were associated with greater neurosurgeon density. Meanwhile, catchment areas with higher proportions of Hispanic residents displayed lower neurosurgeon density (CE = −0.17, 95% CI −0.30 to −0.03). Residents of catchment areas with higher housing vacancy rates (CE = 2.37, 95% CI 1.31–3.43), higher proportions of Native American residents (CE = 4.97, 95% CI 3.99–5.95), and higher proportions of Hispanic residents (CE = 2.31, 95% CI 1.26–3.37) must travel farther, on average, to receive neurosurgical care, whereas people living in areas with a lower income (CE = −2.28, 95% CI −4.48 to −0.09) or higher proportion of Black residents (CE = −3.81, 95% CI −4.93 to −2.68) travel a shorter distance.

CONCLUSIONS

Multiple factors demonstrate a significant correlation with neurosurgical workforce distribution in the US, most notably with Hispanic and Native American populations being associated with greater distances to care. Additionally, higher proportions of Hispanic residents correlated with fewer neurosurgeons per capita. These findings highlight the interwoven associations among socioeconomics, race, ethnicity, and access to neurosurgical care nationwide.