Time Series Analysis by ARIMA Modeling to Forecast Amount of Inpatient
Xuetao Cao · Hospital Administration Journal of Chinese People's Liberation Army · 2007
Objective:To help general hospital managers to make decision with the trend of amount of inpatient. Methods:The author performed time series analysis with an ARIMA(0,1,1) (0,1,1) 12 model which used monthly amount of inpatient data of a large general hospital from 1995 to 2004,and tested the model against the da- ta in 2005.With the model,the managers can predict the trend and detect the abnormal changes in the amount of patient.Results:The average monthly amount of inpatient were 2 336±676.93,and the amount in March,April, June,July,September,November and December exceeded the average.The residuals sum of square by fitting an ARIMA model to the 1995-2004's amount of the inpatient was 2.810.The study set the prediction of the average monthly amount of inpatient (2 970±417.17) in 2005 as a target value,and the result showed that the actual a- mount of inpatient exceeded the target value by 26.12 percent.The model could further be used to picture a control chart for early warning.Conclusion:There is an increasing trend in the hospital's amount of inpatient as well as the monthly pattern.The ARIMA model is suitable to forecast general hospital amount of inpatient and to find abnormal changing of it.Our approach potentially has a high practical value for hospital managers in decision making.