公立医院财务风险预警模型构建与应用探索

Research on Financial Risk Early Warning Model of Public Hospitals Based on Cluster Analysis

公立医院是我国的基础性服务行业,其安全持续的运行关系着国民与社会稳定。公立医院的生产经营活动面临许多不确定性,需要对财务风险进行有效地防控和预警。为此,本研究基于聚类分析的公立医院财务风险预警模型构建方法。从筹资、投资、运营、成长这四个角度入手,选取公立医院财务风险预警指标。根据各指标之间的线性关系,采用熵权法确定财务风险指标权重。基于聚类分析获取指标置信度,计算财务风险预警标准值。通过神经网络算法构建风险预警模型,对公立医院内的财务数据进行评分,实现数据的财务风险划分。实验结果表明,在本研究模型应用下能够对公立医院的多种财务风险进行分类,且预测精度较高,具有提前预警作用。

Public hospitals are a fundamental service industry in China,and the safe and sustainable operation is crucial for the stability of the nation and society.The production and operation activities of public hospitals havee many uncertainties,requiring effective prevention,control,and early warning of financial risks.To this end,research is conducted on the construction method of a financial risk warning model for public hospitals based on cluster analysis.Starting from the four perspectives of growth,it selects early warning indicators of financial risk of public hospitals from financing,investment,operation.According to the linear relationship between each index,the entropy weight method is used to determine the financial risk index weight.The index confidence was obtained based on cluster analysis,and the standard value of financial risk warning was calculated.The neural network algorithm is used to build a risk early warning model,score the financial data in public hospitals,and realize the financial risk division of the data.The experimental results show that the model can be used to classify various financial risks of public hospitals,the prediction accuracy is high,and it has the pre-withholding warning function.