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| Prediction of ARIMA model based on R language on average length of stay |
| Guo Zaijin1,2, Zhou Luojing2 |
1 School of Public Health, Yangzhou University, Yangzhou 225009,China;
2 Management Institute, North Jiangsu People′s Hospital, Yangzhou 225001, China |
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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.
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Received: 14 May 2022
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