Identifying Changes in Demand for Perishable Products Using Statistical Process Control and Forecasting

Abstract

Fast and accurate identification of changes in demand is crucial in the management of blood products. Canadian Blood Services is planning a pilot project to apply pathogen reduction technology (PRT) to platelet production. This is expected to change hospital demand for platelets; however, the form of this change is unknown. Furthermore, a lag time exists between the identification of a supply-demand imbalance and the ability to address it, making it critical to have methods for accurately predicting demand. It was found that statistical process control methods were effective in detecting demand shifts of any form and that forecasting decreased the time to detection, with only slight increases in the false alarm rate. When the magnitude of the demand shift increased, the detection rate increased and the time to detection decreased. The results of this thesis will be useful in minimizing the patient impact of PRT.