Travel distance is one of the most important drivers determining how patients choose hospitals. As an aid to defining proximity hospitals or hospitals with a wide reach (and thereby comparing hospitals’ attractiveness), we present a method to numerically measure, for a given hospital, the distance beyond which no patient is expected to choose the hospital for treatment by using a new approach in random utility models (RUMs); the utility maximization used to derive RUMs is released for a certain level of utility that we called the utility-threshold. The measured distance is called the wingspan of the hospital.

To illustrate, 3 hospitals from the Hérault Department of France (CHU Montpellier, CH Béziers and Clinique le Millénaire) were considered for asthma patients’ admissions in 2009. As expected, CHU Montpellier is the one with the largest spatial wingspan.

For estimation, Monte Carlo Markov chain (MCMC) methods are used.

discrete choice models, hospital attractiveness, Bayesian inference, MCMC methods.