Siegel C, Alexander M J, Lin S, Laska E
Med Care. 1986 May;24(5):407-17. doi: 10.1097/00005650-198605000-00004.
A statistical methodology based on the Cox proportional hazards model (a survival time analysis method), an alternative to the approach underlying DRGs, is presented. The method is used to obtain an estimate of the length-of-stay (LOS) distribution of a patient incorporating either patient-specific or hospital variables. A percentile of the distribution chosen to minimize prediction error serves as the assigned LOS. Absolute deviation is used as the loss function both to determine the choice of a predicted LOS and to examine how well the scheme works. Multiple assignment schemes may also be developed from this approach. The results of the method, tested on a national probability sample of 4,608 psychiatric patients treated in psychiatric units of general hospitals, suggest that with respect to average absolute deviation, the proposed methodology may provide a scheme that is superior to the present DRG scheme. For the sample, the average percent improvement obtained using the median of the estimated LOS distribution as the predicted LOS over the sample mean of the DRG group is 19%. A two assignment strategy results in average improvements over DRGs of 43%.
本文提出了一种基于Cox比例风险模型（一种生存时间分析方法）的统计方法，该方法可替代DRGs所依据的方法。该方法用于获取纳入患者特定变量或医院变量的患者住院时间（LOS）分布的估计值。选择分布的一个百分位数以最小化预测误差作为指定的LOS。绝对偏差用作损失函数，既用于确定预测LOS的选择，也用于检验该方案的效果。也可以从这种方法开发多种分配方案。该方法的结果在对4608名在综合医院精神科接受治疗的精神病患者的全国概率样本上进行了测试，结果表明，就平均绝对偏差而言，所提出的方法可能提供一种优于当前DRG方案的方案。对于该样本，使用估计的LOS分布的中位数作为预测LOS相对于DRG组样本均值获得的平均改进百分比为19%。一种双分配策略导致相对于DRGs的平均改进为43%。
