Abstract
Travel distance is one of the most important drivers of patients' decision. In this work, we present a modeling of spatial number of patients' admissions for hospitals. Thereby, we numerically measure the effect of distance on the probability of choosing a hospital, allowing subsequently comparison of hospitals attractiveness related to the distance, by using a spatial Bayesian binomial hierarchical model. For estimation, we used Markov chains Monte Carlo (MCMC) methods.