A comparison study of outpatient visits forecasting effect between ARIMA with seasonal index and SARIMA

Abstract

This paper delineates a case study analyzing and forecasting of the outpatient visits frequency of a hospital in Zhengzhou, China. By evaluating the annual out-patient data throughout the year of 2015, this paper applies the “Day” as timescale and carries out the experiment so as to forecast the number of visiting patients with the impact of the “Week” taken into consideration. Two models are used separately: the Autoregressive Integrated Moving Average (ARIMA) with seasonal index and the Seasonal Autoregressive Integrated Moving Average (SARIMA). Based on the empirical findings from the comparison of the fitting effect and forecasting effect of the above two models, it is clear that SARIMA reaches a satisfactory outcome: it displays optimum indexes. Therefore it is preferable to deploy the SARIMA model to proceed a forecasting of outpatient visits for medical institutions. Meanwhile the paper also aims to provide management of medical institution with theory grounds of working and personnel arrangement and insight so as to make a prompt and reasonable contingency plan when it comes to sudden disease.