Departamento Universitário de Saúde Pública, Faculdade de Ciências Médicas, Universidade Nova de Lisboa, Campo dos Mártires da Pátria 130, 1169-056, Lisbon, Portugal.
Eur J Health Econ. 2013 Oct;14(5):715-23. doi: 10.1007/s10198-012-0416-5. Epub 2012 Aug 5.
Inpatient length of stay (LOS) is an important measure of hospital activity, but its empirical distribution is often positively skewed, representing a challenge for statistical analysis. Taking this feature into account, we seek to identify factors that are associated with HIV/AIDS through a hierarchical finite mixture model. A mixture of normal components is applied to adult HIV/AIDS diagnosis-related group data (DRG) from 2008. The model accounts for the demographic and clinical characteristics of the patients, as well the inherent correlation of patients clustered within hospitals. In the present research, a normal mixture distribution was fitted to the logarithm of LOS and it was found that a model with two-components had the best fit, resulting in two subgroups of LOS: a short-stay subgroup and a long-stay subgroup. Associated risk factors for both groups were identified as well as some statistical differences in the hospitals. Our findings provide important information for policy makers in terms of discharge planning and the efficient management of LOS. The presence of "atypical" hospitals also suggests that hospitals should not be viewed or treated as homogenous bodies.
住院患者的住院时间（LOS）是衡量医院活动的一个重要指标，但其实证分布往往呈正偏态，这给统计分析带来了挑战。考虑到这一特点，我们试图通过分层有限混合模型来确定与 HIV/AIDS 相关的因素。混合正态分量适用于 2008 年成人 HIV/AIDS 诊断相关组（DRG）数据。该模型考虑了患者的人口统计学和临床特征，以及医院内患者固有的相关性。在本研究中，对 LOS 的对数进行了正态混合分布拟合，发现两分量模型拟合效果最好，从而产生了 LOS 的两个亚组：短住亚组和长住亚组。确定了这两个亚组的相关风险因素，以及医院之间的一些统计学差异。我们的研究结果为决策者在出院计划和 LOS 的有效管理方面提供了重要信息。“非典型”医院的存在也表明，不应该将医院视为同质的整体。
