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Analysis of Patient Information: An Empirical Modeling Approach

机译:患者信息分析:一种经验造型方法

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With rising costs and increasing complexities, many hospitals seek to better understand the intricate details of their operations. Increasingly, these organizations have a strong desire to accurately predict the resources required to effectively treat their patient load. This research investigates patient length-of-stay in a hospital neurological unit using an empirical modeling approach. Factors significantly affecting patient length of stay were identified and used to construct a regression model. The predictive model provides hospital decision makers with a compact tool to input what-if scenarios and predict future patient treatment lengths, thus, allowing the hospital to properly allocate resources.
机译:随着成本上涨和复杂性越来越多,许多医院寻求更好地了解其运营的复杂细节。这些组织越来越强烈地愿意准确预测有效治疗患者负荷所需的资源。本研究通过经验建模方法调查患者在医院神经系统中的患者长度。鉴定并用于构建回归模型的显着影响患者的住宿时间的因素。预测模型为医院决策者提供了一个紧凑的工具,可以输入什么方案并预测未来的患者治疗长度,从而允许医院正确地分配资源。

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