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

TitreRobust parametric indirect estimates of the expected cost of a hospital stay with covariates and censored data.
Publication TypeJournal Article
Year of Publication2013
AuthorsLocatelli, I, Marazzi, A
JournalStat Med
Volume32
Issue14
Pagination2457-66
Date Published2013 Jun 30
DOI10.1002/sim.5701
ISSN1097-0258
Mots-clésAnalysis of Variance, Biostatistics, Computer Simulation, Costs and Cost Analysis, Data Interpretation, Statistical, Diagnosis-Related Groups, Hospital Costs, Humans, Length of Stay, Models, Statistical, Monte Carlo Method
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.

Alternate URL

http://www.ncbi.nlm.nih.gov/pubmed/23212933?dopt=Abstract

Alternate JournalStat Med
Citation Key / SERVAL ID3354
PubMed ID23212933

                         

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