Disparities in geographic access to medical oncologists

Objective The objective of this study is to identify disparities in geographic access to medical oncologists at the time of diagnosis. Data Sources/Study Setting 2014-2016 Pennsylvania Cancer Registry (PCR), 2019 CMS Base Provider Enrollment File (BPEF), 2018 CMS Physician Compare, 2010 Rural-Urban Commuting Area Codes (RUCA), and 2015 Area Deprivation Index (ADI). Study Design Spatial regressions were used to estimate associations between geographic access to medical oncologists, measured with an enhanced two-step floating catchment area measure, and demographic characteristics. Data Collection/Extraction Methods Medical oncologists were identified in the 2019 CMS BPEF and merged with the 2018 CMS Physician Compare. Provider addresses were converted to longitude-latitude using OpenCage Geocoder. Newly diagnosed cancer patients in each census tract were identified in the 2014-2016 PCR. Census tracts were classified based on rurality and socioeconomic status using the 2010 RUCA Codes and the 2015 ADI. Principal Findings Large towns and rural areas were associated with spatial access ratios (SPARs) that were 6.29 lower (95% CI -16.14 to 3.57) and 14.76 lower (95% CI -25.14 to -4.37) respectively relative to urban areas. Being in the fourth ADI quartile (highest disadvantage) was associated with a 12.41 lower SPAR (95% CI -19.50 to -5.33) relative to the first quartile. The observed difference in a census tract's non-White population from the 25th (1.3%) to the 75th percentile (13.7%) was associated with a 13.64 higher SPAR (Coefficient = 1.10, 95% CI 11.89 to 15.29; p < 0.01), roughly equivalent to the disadvantage associated with living in the fourth ADI quartile, where non-White populations are concentrated. Conclusions Rurality and low socioeconomic status were associated with lower geographic access to oncologists. The negative association between area deprivation and geographic access is of similar magnitude to the positive association between larger non-White populations and access. Policies aimed at increasing geographic access to care should be cognizant of both rurality and socioeconomic status.