Abstract：Objective To analyze and predict the demand of regular medical consumables in the future through application of time
series analysis method of seasonal factors in the management of regular consumables in the department. Methods Multiple seasonal
autoregressive integrated moving average (ARIMA) model was used to predict the monthly usage of a brand syringe in a department
of a hospital in Beijing from January 2014 to December 2018. Results The MAPE of ARIMA (0, 1, 2) (0, 1, 1)12 model was 5.308,
which controlled in tolerance interval, and the prediction result was close to the actual generated value. Conclusion ARIMA (0, 1,
2) (0, 1, 1)12 model could accurately predict regular medical consumables in the short-term, and apply it to the hospital consumables
management information system. The system realizes the reasonable control of the hospital consumables, and provide a reliable basis
for funding budget applications.
白玲，郭晓伟，马莉. 基于ARIMA乘积季节模型的科室级常规耗材需求量预测研究[J]. 中国医疗设备, 2021, 36(1): 123-126.
BAI Ling, GUO Xiaowei, MA Li. Research on Demand Prediction of Regular Medical Consumables at Department Level
Based on Multiple Seasonal ARIMA Model. China Medical Devices, 2021, 36(1): 123-126.
