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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
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摘要 目的了解公立医院互联网门诊人次的变化趋势,为互联网医院的发展规划提供支持。方法利用某公立医院2021年1月—2023年6月互联网门诊人次数据,分别构建ARIMA模型和GM(1,1)模型,采用平均绝对误差(MAE)和均方根误差(RMSE)评价拟合效果,基于优势模型预测2023年7—12月互联网门诊人次。结果通过ARIMA(1,2,1)模型和GM(1,1)模型对互联网门诊的复诊人次进行预测,平均绝对误差分别为369.86和978.84,均方根误差分别为479.49和1444.83;通过ARIMA(0,1,0)模型和GM(1,1)对互联网门诊咨询人次进行预测,平均绝对误差分别为297.23和369.62,均方根误差分别为413.61和496.30,表明ARIMA模型的预测效果较好。预测结果显示,2023年12月互联网门诊的复诊人次预测值为14831例,咨询人次预测值为7461例。结论2021—2023年某公立医院互联网门诊人次呈持续上升趋势。因此,医院应充分认识到互联网医疗服务的重要性,积极采取措施,不断优化医疗服务模式,为患者提供优质、高效、便捷的互联网医疗服务。 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 hospital 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 active measures to continuously optimize the medical service model,and provide patients with high-quality,efficient and convenient Internet medical services.
作者 徐彦杰 辛亮 刘俊卿 李岩 李世云 王若臻 董恒磊 XU Yanjie;XIN Liang;LIU Junqing;LI Yan;LI Shiyun;WANG Ruozhen;DONG Honglei(Tianjin Medical University Cancer Institute&Hospital,National Clinical Research Center for Cancer,Tianjin Key Laboratory of Cancer Prevention and Therapy,Tianjin’s Clinical Research Center for Cancer,Tianjin 300060,China)
出处 《现代医院》 2024年第1期14-19,共6页 Modern Hospitals
基金 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)。
关键词 ARIMA GM(1 1) 互联网 门诊人次 预测研究 ARIMA GM(1,1) The internet Outpatient visits Prediction study
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