title: The geography of hospital admission in a national health service with patient choice.
abstract: Each year about 20% of the 10 million hospital inpatients in Italy get admitted to hospitals outside the Local Health Authority of residence. In this paper we carefully explore this phenomenon and estimate gravity equations for 'trade' in hospital care using a Poisson pseudo-maximum likelihood method. Consistency of the PPML estimator is guaranteed under the null of independence provided that the conditional mean is correctly specified. In our case we find that patients' flows are affected by network autocorrelation. We correct for it by relying upon spatial filtering. Our results suggest that the gravity model is a good framework for explaining patient mobility in most of the examined diagnostic groups. We find that the ability to restrain patients' outflows increases with the size of the pool of enrollees. Moreover, the ability to attract patients' inflows is reduced by the size of pool of enrollees for all LHAs except for the very big LHAs. For LHAs in the top quintile of size of enrollees, the ability to attract inflows increases with the size of the pool.
authors.affiliation: Dipartimento di Scienze Economiche, Università di Bologna, HEDG and CHILD, Piazza Scaravilli 2, Bologna, Italy. d.fabbri@unibo.it
authors.forename: Daniele
authors.initials: D
authors.lastname: Fabbri
authors.forename: Silvana
authors.initials: S
authors.lastname: Robone
mesh_terms: D002755:Choice Behavior; D005843:Geography; D015285:Hospital-Patient Relations; D006761:Hospitals / Q000706:statistics & numerical data*; D006801:Humans; D007558:Italy; D016013:Likelihood Functions; D017059:Models, Econometric; D009313:National Health Programs / Q000706:statistics & numerical data*; D010343:Patient Admission / Q000706:statistics & numerical data*; D016012:Poisson Distribution; D014195:Travel / Q000706:statistics & numerical data