Disparities in spatial access to neurological care in Appalachia: A cross-sectional health services analysis

indicating a lack of better options in addition to the noted high coverage of Care Compare. Also, we included all physician practice locations, as no variable exists in Care Compare by which to restrict to primary practice location, which could have overestimated physician density in certain areas. We used nationwide quintiles for better representation of the true area socioeconomic deprivation of the study area. Only a single tract in the study area existed in the lowest socioeconomic deprivation quintile, which resulted in NAs in our tabulated ADI results. However, using study area-specific quantiles would have underestimated the widespread socioeconomic deprivation in Appalachia, indicating that nation-based ADI quantiles were optimal. We used 2010 distance matrix and population data due to availability and accuracy. In a supplementary analysis of 2010–2019 population change, we found that there was little concern for differential misclassification (Supplementary Materials). Euclidean distance matrices tend to overestimate access to care, particularly for urban areas, as they do not account for the complexity of road networks and other transit modalities, such as urban rail. Although we acknowledge that it would be ideal to account for complex transportation matrices, this requires exponentially more computational and memory requirements, which was not feasible for a census tract-level analysis. Future work may consider using advanced routing methods to build more representative travel matrices. In addition, for 82 or 0.33% of census tracts in the study area, RUCA codes were unavailable. For the 82 missing values, 78 were non-Appalachian tracts, 4 were Appalachian, and overall SPARs were close to 1 for each of the FCA methods. Due to only a small proportion of missing values, significant differential effects due to missingness were exceedingly unlikely. Finally, our supplementary construction of a geographic access measure for primary care providers displayed that our neurologist SPARs were not simply identifying areas with poor overall spatial access to providers (Supplementary Fig. S3). Though there was moderate to strong Spearman correlation between neurologist and primary care provider SPARs, visual inspection showed substantial differences. For example, SPARs for primary care providers in Appalachian metro areas, such as Knoxville, TN and Charleston, WV were substantially higher than SPARs for neurologists in the same areas, revealing the utility of directly studying spatial access to neurologists.