精神疾病患者经济负担分析及预测

范  馨  月1; 2

精神疾病患者经济负担分析及预测

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 550025；2.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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