期刊文献+

基于数据挖掘及自回归积分移动平均模型预测的医用耗材库存智能化管理研究

Research on the value of data mining in intelligent management of medical consumables inventory
下载PDF
导出
摘要 目的:基于自回归积分移动平均(ARIMA)构建医用耗材ARIMA模型,为医用耗材库存管理中的各项决策提供技术支持。方法:采用数据挖掘技术中的时间序列分析方法对医用耗材库存进行预测,通过构建医用耗材ARIMA模型分析医用耗材库存变化趋势,预测未来一段时间内医用耗材库存可能出现的结果。选取2018-2021年医院医用耗材每月库存数据,根据2018年1月至2021年7月医院医用耗材每月的库存数据构建医用耗材ARIMA模型,对2021年8-12月的医用耗材每月库存数据进行模型验证和数据预测。结果:建立的医用耗材最优模型为ARIMA(5,1,2)(1,1,1),模型平均绝对误差为7.46%;采用该模型预测2021年8-12月的医用耗材库存量与实际医用耗材库存量比较接近,平均绝对百分比误差(MAPE)为2.075%,模型拟合效果较好。结论:基于数据挖掘技术构建的医用耗材ARIMA模型,可指导决策者根据预测值对医用耗材进行采购,一定程度上降低医用耗材积压率和断货率,减少客观因素引起的医用耗材损耗率。 Objective:Based on the Autoregressive Integral Moving Average(ARIMA),the ARIMA model of medical consumables was constructed to provide technical support for the decision-making of medical consumables inventory management.Methods:Medical consumables inventory was predicted based on time series analysis method in data mining technology.The change trend of medical consumables inventory was analyzed by constructing ARIMA model and the possible outcome of medical consumables inventory in the future period was predicted.Based on the monthly inventory data of hospital medical consumables from 2018 to 2021,the ARIMA model of medical consumables was constructed according to the monthly inventory data of hospital medical consumables from January 2018 to July 2021,and the model verification and data prediction were carried out on the monthly inventory data of medical consumables from August to December 2021.Results:The optimal model of medical consumables was ARIMA(5,1,2)(1,1,1),and the average absolute error of the model was 7.46%.The inventory of medical consumables predicted using this model from August to December 2021 was close to the actual inventory,with an average absolute percentage error(MAPE)of 2.075%.The model had a good fitting effect.Conclusion:The ARIMA model of medical consumables based on data mining technology can guide the decision-makers to purchase medical consumables according to the predicted value,reduce the backlog and out-of-stock rate of medical consumables to a certain extent,and reduce the loss rate of medical consumables caused by objective factors.
作者 徐嘉彬 傅歆 刘林 高述桥 XU Jia-bin;FU Xin;LIU Lin(Department of Medical Engineering,Wuhan Central Hospital,Wuhan 430014,China;不详)
出处 《中国医学装备》 2023年第11期143-146,共4页 China Medical Equipment
关键词 数据挖掘 自回归积分移动平均(ARIMA)模型 医用耗材库 智能化管理 Data mining Autoregressive integrated moving average(ARIMA)model Medical consumables warehouse Intelligent management
  • 相关文献

参考文献11

二级参考文献114

共引文献67

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部