Application of ARIMA seasonal product model to predicting the number of outpatient and emergency department visits for childhood pneumonia
YANG Lei1, WU Wen-hua2, REN Quan3, WANG Yan-jie1, LIU Zao-ling1
1. School of Public Health, Xinjiang Medical University, Xinjiang, Urumqi 830054, China; 2. Center for Medical Information, the First Affiliated Hospital of Xinjiang Medical University,Urumqi, Xinjiang 830011, China; 3. Urumqi Weather Bureau, Urumqi, Xinjiang 830002, China
Abstract：Objective To explore the application of autoregressive integrated moving average (ARIMA) seasonal product model to forecasting the number of outpatient and emergency department visits for childhood pneumonia, and to provide a scientific basis for the rational utilization of medical resources. Methods We collected the data regarding the number of monthly outpatient and emergency department visits for childhood pneumonia from two tertiary comprehensive hospitals in Urumqi City from 2011 to 2016. R 3.4.1 software was used for model identification, parameter estimation and verification. ARIMA seasonal product model was established to fit the number of monthly outpatient and emergency department visits for childhood pneumonia from January 2011 to June 2016, and the prediction effect was evaluated through checking the average relative error between the predicted and actual values by using the monthly data from July to December in 2016. Results The ARIMA (0,1,2) (1,1,0)12 model was the best prediction model, with an average relative error of 9.82%. Conclusions ARIMA seasonal product model has better fitting and short-term prediction effect, which can provide references for hospitals to rationally utilize medical resources.
杨蕾, 吴文华, 任泉, 王艳杰, 刘早玲. ARIMA季节乘积模型在儿童肺炎门急诊人次预测中的应用[J]. 实用预防医学, 2019, 26(1): 33-35.
YANG Lei, WU Wen-hua, REN Quan, WANG Yan-jie, LIU Zao-ling. Application of ARIMA seasonal product model to predicting the number of outpatient and emergency department visits for childhood pneumonia. , 2019, 26(1): 33-35.
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2019, Vol. 26 
