Disparities in accessibility to oncology care centers in France

BackgroundAccess to health services plays a key role in cancer survival. Uneven distributions of populations and health facilities lead to geographical disparities. Location-allocation algorithms can address these disparities by finding new locations and capacities for health facilities. However, in oncology, opening new hospitals or moving them is difficult in practice, and should be handled carefully. MethodsWe propose a method to measure the spatial accessibility to oncology care and identify the hospitals to grow to reduce disparities. We first ran a clustering algorithm to automatically label the hospitals in terms of oncology specialization. Then, we computed an accessibility score to these hospitals for every population location. Finally, we introduced CAMION, an optimization algorithm based on Linear Programming that reduces disparities in oncology accessibility by identifying health facilities that should increase their capacities. ResultsWe demonstrate our algorithm in metropolitan France. The clustering step let us identify different oncology specialization levels for hospitals. Most of the population in metropolitan France lived in good accessibility areas, especially in large cities. Lower accessibility zones are often rural or suburban municipalities. The optimization algorithm effectively manages to identify hospitals to grow, based on current oncology specialization and accessibility scores. DiscussionThere is a tradeoff to be found by patients, between care center proximity and care center expertise, which is less likely to happen for patients living in good accessibility areas. The accessibility score is deliberately non-specific to cancer type but can be adapted to more precise pathologies. Our method is replicable in any country, given hospitals and population locations data. We developed a web application intended for healthcare professionals to let them to run the optimization algorithm with the desired parameters and visualize the results.