Abstract：Objective To establish a differential autoregressive integrated moving average ( ARIMA ) model to predict the average length of stay in a tertiary hospital in Jiangsu Province and provide scientific reference for the allocation of medical resources.Methods Based on the average hospital stay data of a tertiary hospital in Jiangsu Province from January 2013 to June 2021, the ARIMA model was constructed by using R software to predict the average hospital stay in the hospital from July 2021 to May 2022, and to compare with the actual value to evaluate the prediction effect of the ARIMA model.Results The average length of stay of the hospital has been decreasing year by year since January 2013, and has certain seasonal characteristics. The best fitted ARIMA model is ARIMA ( 0, 1, 1 ) ( 0, 1, 1 ) 12 , with MAPE of 1.78% and RMSE of 0.24. In the prediction of ARIMA model, RMSE is 1.49, MAPE is 7.78%, and the prediction results are ideal.Conclusion ARIMA model has good prediction effect on the average length of stay in the hospital, and can be used for the shortterm prediction of the average length of stay in the hospital.
［1］TSAN Y T, CHEN D Y, LIU P Y, et al. The prediction of influenza-like illness and respiratory disease using LSTM and ARIMA［J］. Int J Environ Res Public Health, 2022, 19(3):1858.
［4］RGUIBI M A, MOUSSA N, MADANI A, et al. Forecasting covid-19 transmission with ARIMA and LSTM techniques in Morocco［J］. SN Comput Sci, 2022, 3(2):133.