Application of Arima Model to outpatient attendance data in Kiruddu General Hospital of Uganda

Abstract

Time series analysis is considered an essential topic in statistics, where it is usually used to study the future behavior of the series at a determined time. It may be stationary or non-stationary. In the time series model, the Autoregressive integrated moving average (ARIMA) model is used. The main objective of the study was to carry out the application of the Arima model to outpatient attendance data in Kiruddu general hospital in Uganda between 2012 and 2019. The ARIMA model was used to predict the number of outpatient visits Accurate forecasting of the number of outpatient visits in tertiary hospitals is beneficial for determining future staff needs and locating the hospital's budget. Hospitals in Uganda are always overwhelmed by the unexpectedly high Outpatient Department (OPD) attendance. This reason underpins this study where OPD attendance data from 2012 to 2019 as can be seen in Appendix A was gathered for developing an adequate time series model and forecasting attendance. Several time series models including AR, MA, ARMA, and ARIMA were fitted to the data. It was revealed that the most adequate model for the data was the seasonal ARIMA (2, 1, 1). Also, there will be an increase in OPD attendance at the hospital in the next 5 years. It is recommended that for the hospital to prepare adequately, the forecasted figures should be relied upon in planning its activities