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Predicting Nursing Home Financial Distress Using the Altman Z-Score

机译:使用Altman Z分数预测护理家庭财务困境

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摘要

This article uses a modified Altman Z-score to predict financial distress within the nursing home industry. The modified Altman Z-score model uses multiple discriminant analysis (MDA) to examine multiple financial ratios simultaneously to assess a firm’s financial distress. This study utilized data from Medicare Cost Reports, LTCFocus, and the Area Resource File. Our sample consisted of 167 268 nursing home-year observations, or an average of 10 454 facilities per year, in the United States from 2000 through 2015. The independent financial variables, liquidity, profitability, efficiency, and net worth were entered stepwise into the MDA model. All of the financial variables, with the exception of net worth, significantly contributed to the discriminating power of the model. K-means clustering was used to classify the latent variable into 3 categorical groups: distressed, risk-of-financial distress, and healthy. These findings will provide policy makers and practitioners another tool to identify nursing homes that are at risk of financial distress.
机译:本文使用改进的altman z-score来预测护理家庭行业内的财务困境。修改的Altman Z-Score模型使用多种判别分析(MDA)来同时检查多个财务比率,以评估公司的财务困境。本研究利用来自Medicare成本报告,LTCFoCus和区域资源文件的数据。我们的样本由2000年至2015年的美国167名268名护理家庭观测,或平均每年10个454个设施。独立的财务变量,流动性,盈利,效率和净值逐步进入MDA模型。除净值外,所有的金融变量明显促成了模型的辨别力。 K-means聚类用于将潜在变量分类为3个分类群体:痛苦,财务风险,健康。这些调查结果将为政策制定者和从业者提供另一个工具,用于识别受到财务困境的风险的护理家庭。

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