Robust parametric indirect estimates of the expected cost of a hospital stay with covariates and censored data

Authors

  • Isabella Locatelli,

    Corresponding author
    • Institute for Social and Preventive Medicine, Centre Hospitalier Universitaire Vaudois and University of Lausanne, CH 1010 Lausanne, Switzerland
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  • Alfio Marazzi

    1. Institute for Social and Preventive Medicine, Centre Hospitalier Universitaire Vaudois and University of Lausanne, CH 1010 Lausanne, Switzerland
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Correspondence to: Isabella Locatelli, Institute for Social and Preventive Medicine, Centre Hospitalier Universitaire Vaudois and University of Lausanne, route de la Corniche 10, CH 1010 Lausanne, Switzerland.

E-mail: Isabella.Locatelli@chuv.ch

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. Copyright © 2012 John Wiley & Sons, Ltd.

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