title: Robust parametric indirect estimates of the expected cost of a hospital stay with covariates and censored data.
abstract: We consider the problem of estimating the mean hospital cost of stays of a class of patients (e.g., a diagnosis-related group) as a function of patient characteristics. The statistical analysis is complicated by the asymmetry of the cost distribution, the possibility of censoring on the cost variable, and the occurrence of outliers. These problems have often been treated separately in the literature, and a method offering a joint solution to all of them is still missing. Indirect procedures have been proposed, combining an estimate of the duration distribution with an estimate of the conditional cost for a given duration. We propose a parametric version of this approach, allowing for asymmetry and censoring in the cost distribution and providing a mean cost estimator that is robust in the presence of extreme values. In addition, the new method takes covariate information into account.
authors.affiliation: Institute for Social and Preventive Medicine, Centre Hospitalier Universitaire Vaudois and University of Lausanne, Route de la Corniche 10, CH 1010 Lausanne, Switzerland. Isabella.Locatelli@chuv.ch
authors.forename: Isabella
authors.initials: I
authors.lastname: Locatelli
authors.forename: Alfio
authors.initials: A
authors.lastname: Marazzi
mesh_terms: D000704:Analysis of Variance; D056808:Biostatistics; D003198:Computer Simulation; D003365:Costs and Cost Analysis / Q000706:statistics & numerical data; D003627:Data Interpretation, Statistical; D003953:Diagnosis-Related Groups / Q000191:economics; D017721:Hospital Costs / Q000706:statistics & numerical data*; D006801:Humans; D007902:Length of Stay / Q000191:economics*; D015233:Models, Statistical; D009010:Monte Carlo Method