Prediction on clinical platelet demand in Suzhou based on ARIMA model / 中国输血杂志

ABSTRACT

【Objective】 To establish an ARIMA model suitable for clinical platelet demand prediction in Suzhou, which can be used as reference to predict future clinical platelet demand and provide scientific basis for platelet collection, preparation, stock management and clinical deployment for blood banks, so as to achieve the maximum balance between platelets supply and demand . 【Methods】 The data of platelet consumption in Suzhou from 2009 to 2019 were collected and analyzed by SPSS 26 software, Time series analysis method was used to establish the ARIMA model. The model was further optimized through model identification, parameter estimation and optimal model test, and then used to predict clinical platelet consumption from January to November 2020. The predicted value was compared with the actual value to verify the prediction effect of the model. 【Results】 The optimal model for the prediction of platelet clinical demand was ARIMA (0, 1, 1) (0, 1, 1) 12. The ACF autocorrelation function value and PACF partial autocorrelation function value of the residuals were within 95% CI. Meanwhile, the LJUNG BOX test was 13.982 (P>0.05), indicating that there was no autocorrelation in the residuals. The trend of the curve between the predicted and actual value was basically the same(except for February 2020), and the predicted values were within 95% CI, with the average relative error of 7.22%, which was lower than 10%, showing good prediction effect. 【Conclusion】 ARIMA model can be used for short-term prediction of clinical platelets demand in Suzhou, and can provide basis for reasonable collection, preparation and deployment of platelets.