精神疾病患者经济负担分析及预测
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引用本文:范 馨 月1,2.精神疾病患者经济负担分析及预测[J].经济数学,2019,(1):79-83
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作者单位
范 馨 月1,2 (1.贵州大学 贵州省公共大数据重点实验室, 贵州 贵阳 5500252.贵州大学 数学与统计学院贵州 贵阳 550025) 
中文摘要:对某精神疾病的专科医院患者数量及费用进行分析,采用径向基函数(RBF)神经网络模型对精神疾病患者的看病费用进行拟合及预测,并比较该预测模型与BP神经网络的预测效果.将贵州省某精神类疾病的专科医院2015年1月-2016年12月医院HIS系统中的病人处方数据作为训练集,建立BP模型、RBF神经网络模型.分别对2017年1月1日-2017年1月16日病人用以精神类疾病看病费用情况进行预测.RBF神经网络模型均能够较好地拟合和预测精神类疾病患者看病费用,可以为医院管理者了解本院精神病患者看病费用的变化趋势提供依据,为制定精神病患者疾病负担的相关政策提供数据支撑.
中文关键词:精神疾病  统计分析  RBF神经网络
 
Analysis and Prediction of Economic Burden of Mental Patients
Abstract:The number and cost of patients in a specialist hospital of a mental disease were analyzed. The radial basis function (RBF) neural network model was used to fit and predict the cost of the patients with mental illness, and the prediction results of the prediction model and the BP neural network were compared. The patients' prescription data in the hospital HIS system of a psychiatric hospital of Guizhou province from January 2015 to December 2016 were used as the training set, and the BP model and RBF neural network model were established. The patients' mental illness expenses were predicted from January 1 to 16, 2017. The RBF neural network model can better fit and predict the cost of patients with mental disease. It can provide the basis for the hospital managers to understand the change trend of the hospital psychiatric patients' medical expenses, and provide data support for the related policies of the disease burden of mental patients.
keywords:mental illness  statistical analysis  RBF neural network
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