Institute for Social and Preventive Medicine, Centre Hospitalier Universitaire Vaudois and University of Lausanne, Route de la Corniche 10, CH 1010 Lausanne, Switzerland.
Stat Med. 2013 Jun 30;32(14):2457-66. doi: 10.1002/sim.5701. Epub 2012 Dec 5.
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.
我们考虑了一类患者（例如，诊断相关组）的住院费用的均值估计问题，该费用是患者特征的函数。统计分析受到成本分布的不对称性、成本变量的删失可能性和异常值的发生的影响。这些问题在文献中经常分别处理，并且仍然缺乏一种能够为所有问题提供联合解决方案的方法。已经提出了间接程序，将持续时间分布的估计与给定持续时间的条件成本的估计相结合。我们提出了这种方法的参数版本，允许成本分布存在不对称和删失，并提供了一种在存在极端值时稳健的平均成本估计量。此外，新方法考虑了协变量信息。
