基于自回归积分移动平均模型的妇女儿童医院门诊量预测
Prediction of women and Children's hospital outpatient numbers based on the autoregressive integrated moving average model.
作者信息
Lin Yan, Wan Chaomin, Li Sha, Xie Shina, Gan Yujing, Lu YuanHu
机构信息
Outpatient Department, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu 610091, China.
Department of Paediatrics, West China Second Hospital, Sichuan University, No. 20, 3rd Section of Renmin South Road, Chengdu 610041, PR China.
出版信息
Heliyon. 2023 Mar 27;9(4):e14845. doi: 10.1016/j.heliyon.2023.e14845. eCollection 2023 Apr.
OBJECTIVE
To evaluate the predictive value of the autoregressive integrated moving average (ARIMA) product seasonal model for the daily outpatient volume of paediatric internal medicine departments in hospitals.
METHODS
The daily outpatient volume of paediatric internal medicine recorded by the hospital information system of the Chengdu Women's and Children's Central Hospital from 1 January 2011 to 31 December 2020 was collected. Using the data from 1 January 2011 to 31 December 2019, the seasonal summation ARIMA model of the time product was established by fitting the tseries program in the R-3.6.3 software. The monthly outpatient volume from January to December 2020 was predicted, and the prediction effect was evaluated according to the mean absolute percentage error (MAPE) between the predicted value and the actual value.
RESULTS
The outpatient volume of paediatric internal medicine in the hospital from 2011 to 2019 showed an upward trend, with obvious seasonal fluctuations. The optimal model was the ARIMA model ([3,4], 1,2) × (1,1,0) 12, with an Akaike information criterion of 3116.656 and a Bayesian information criterion of 3217.412. The model's residual was a white noise sequence (x = 7.56, = 0.819), and the MAPE between the predicted value and the actual value of the model was 9.56%. Within a 95% confidence interval of the predicted value, the prediction accuracy of the model was high.
CONCLUSION
The ARIMA multiplicative seasonal model established in this study is suitable for the short-term prediction of the outpatient volume.
目的
评估自回归积分滑动平均（ARIMA）乘积季节模型对医院儿科内科每日门诊量的预测价值。
方法
收集成都市妇女儿童中心医院医院信息系统记录的2011年1月1日至2020年12月31日儿科内科的每日门诊量。利用2011年1月1日至2019年12月31日的数据，通过在R-3.6.3软件中拟合tseries程序，建立时间乘积的季节性求和ARIMA模型。预测2020年1月至12月的月门诊量，并根据预测值与实际值之间的平均绝对百分比误差（MAPE）评估预测效果。
结果
2011年至2019年该医院儿科内科门诊量呈上升趋势，有明显的季节性波动。最优模型为ARIMA模型（[3,4]，1,2）×（1,1,0）12，赤池信息准则为3116.656，贝叶斯信息准则为3217.412。该模型的残差为白噪声序列（χ = 7.56，P = 0.819），模型预测值与实际值的MAPE为9.56%。在预测值的95%置信区间内，模型的预测准确性较高。
结论
本研究建立的ARIMA乘积季节模型适用于门诊量的短期预测。
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