现代医院2024，Vol.24Issue(1)：14-19,6.DOI:10.3969/j.issn.1671-332X.2024.01.005
基于ARIMA与GM(1,1)模型的公立医院互联网门诊人次预测研究
Research on the prediction of internet outpatient visits in public hospitals based on ARIMA and GM(1,1)model
摘要
Abstract
Objective To understand the changing trend of Internet outpatient visits in public hospitals,and provide support for the development planning of Internet hospitals.Methods Using the data of Internet outpatient visits in a public hos-pital from January 2021 to June 2023,the ARIMA model and GM(1,1)model were constructed respectively.The mean absolute error(MAE)and root mean square error(RMSE)were used to evaluate the fitting effect,and the Internet outpatient visits from July to December 2023 were predicted based on the dominance model.Results ARIMA(1,2,1)model and GM(1,1)model were used to predict the number of return visits of Internet outpatient service.The average absolute errors were 369.86 and 978.84,and the root-mean-square errors were 479.49 and 1444.83,respectively.The ARIMA(0,1,0)model and GM(1,1)model were used to predict the number of Internet outpatient consultations.The average absolute errors were 297.23 and 369.62,and the root-mean-square errors were 413.61 and 496.30,respectively,indicating that the ARIMA model has a good prediction effect.The forecast results show that the predicted value of Internet outpatient visits in December 2023 is 14,831 cases,and the predicted value of consultation visits is 7461 cases.Conclusion The number of Internet outpatient visits in a public hospital will continue to rise from 2021 to 2023.Therefore,hospitals should fully realize the importance of Internet medical services,take ac-tive measures to continuously optimize the medical service model,and provide patients with high-quality,efficient and convenient Internet medical services.关键词
ARIMA/GM(1,1)/互联网/门诊人次/预测研究Key words
ARIMA/GM(1,1)/The internet/Outpatient visits/Prediction study分类
医药卫生引用本文复制引用
徐彦杰,辛亮,刘俊卿,李岩,李世云,王若臻,董恒磊..基于ARIMA与GM(1,1)模型的公立医院互联网门诊人次预测研究[J].现代医院,2024,24(1):14-19,6.基金项目
国家卫生健康委医院管理研究所《公立医院精细化管理与评价研究项目》(NIHA23JXH012) （NIHA23JXH012）
