ARIMA model in blood supply prediction of multi blood components
10.13303/j.cjbt.issn.1004-549x.2021.07.022
- VernacularTitle:ARIMA模型在多种成分血拟合供血预测中的研究
- Author:
Yanyan LIU
1
;
Jing FAN
1
Author Information
1. Tianjin Blood Center, Tianjin 300110, China
- Publication Type:Journal Article
- Keywords:
ARIMA model;
blood component;
blood supply;
fitting prediction
- From:
Chinese Journal of Blood Transfusion
2021;34(7):759-763
- CountryChina
- Language:Chinese
-
Abstract:
【Objective】 To establish an ARIMA model to fit the distributed units of four blood components from 2010 to 2018 in Tianjin and test the fitting degree, so as to predict the future issuing units of these blood products, and provide scientific basis for the blood center to formulate blood collection and donor recruitment plan. 【Methods】 The monthly distributed data of blood components from 2010 to 2019 were sorted out to establish the ARIMA model. The model identification, parameter estimation and test of the distributed data concerning red cells, plasma, apheresis platelet and white cells from January 2010 to December 2019 were performed to determine the optimal model using Eviews 10.0 software. Considering the obvious trend and seasonality of data, the seasonal model was chosen to predict the issuing of four blood products in January to December 2019, and the fitting degree was tested by comparing with the actual value. 【Results】 The ARIMA model residual autocorrelation function and partial autocorrelation function of four blood components showed that the regression residuals of each product had the same variance. The predicted value of supply was basically within 95% CI, and the curve trend of model fitting value and actual value was basically consistent, The average relative errors of red cells, plasma, apheresis platelets and white cells were 6.19%, 5.08%, 1.72% and 7.17%, respectively. 【Conclusion】 ARIMA model can appropriately fit the change trend of blood supply in Tianjin, which is helpful to understand the clinical requirements in the near future, provide the basis for blood collection, recruitment and inventory management.
