Predictive Analysis of Outpatient Volumes of a First-class Grade A General Hospital through ARIMA Models

Abstract

AbstractObjectives. To explore the effect of ARIMA (Auto Regressive Integrated Moving Average) models in predicting the outpatient volume, the short-term prediction of the outpatient volume of a hospital, and to provide a basis for hospital management decisions related to outpatient volume. Methods. Extract the outpatient data for the period between January 2010 and March 2014 from the information system of a first-class grade A general hospital. The time series modeler in PASW (Predictive Analytics Software) was used in combination with ARIMA models, the model effect was evaluated, and the outpatient volumes for the next 2 years were predicted. Results. The number of outpatients during 2010–2013 amounted to 3.036 million, with an annual average growth rate of 24.07%. (Male/female ratio 0.81/1, mean age 40.36 ± 19.32, internal/external medicine ratio 1.35/1.) Based on the outpatient volume during 2010–2013, the predicted value of the outpatient volume in the first quarter of 2014 had a relative error of 4...