1609 Background: Rural communities in the United States (US) experience persistent shortfalls accessing oncology care due to an uneven workforce distribution. Non-specific county-level metrics fail to pinpoint precisely where new oncologists can maximize impact. By adapting a maximal coverage algorithm to the ZIP code level, our study aims to provide a data-driven solution to physician placement by identifying high demand areas with significant unserved populations. Methods: We developed a model to simulate capacity-constrained maximal coverage expansion of oncology care with up to 500 oncologist placements per state, 40 kilometer catchment radii, and an assumption that one oncologist could cover up to 6,667 individuals over 55 years old (based on baseline US prevalence of 15 oncologists per 100,000 individuals over 55). We used physician data from the Doctors and Clinicians national downloadable file, geographical data from the US Census, and Rural-Urban Continuum Codes (RUCCs) to measure rurality. Outcomes measured included baseline state-level coverage, number of placements needed to achieve 90% state-level population coverage, and urban-rural placement differences. For continuous variables, the two-sample t-test was used for statistical significance. Results: Nationally, approximately 26 million additional individuals would gain coverage with 5,578 additional placements. 2,912 (52.2%) of the optimal ZIP codes were in rural counties. Placements provided a mean coverage of 4,684 people per physician. Median baseline state coverage was 67.8% (IQR 59.9%-77.1%), with 3 states having >90% coverage at baseline (Rhode Island, Connecticut, and New Jersey). To achieve 90% coverage, states required a median of 40 placements (IQR 18.25-63.25). Coverage gains per state were front-loaded with the first 25 oncologists in a state capturing on average 46.7% of all achievable gains. The states that required the greatest number of additional oncologists to achieve 90% coverage were: California (N=209), Florida (N=174), and Texas (N=163). The top five rural placements per state covered an average of 6,505 individuals while the top five urban placements per state covered an average of 6,220 individuals (p-value = 0.009). Conclusions: Our approach precisely identified underserved ZIP codes where oncologist placement would maximize access to care. Strategic placement of oncologists can lead to increased access to care, particularly for rural residents. These policies should initially be directed toward states and ZIP codes with the largest baseline gaps to maximize coverage and advance equitable healthcare access.
Crowley et al. (Wed,) studied this question.