基于SARIMA模型的血小板需求预测：优化血库资源配置和临床供应。

IF 1.4 4区医学 Q4 HEMATOLOGY

Transfusion Clinique et Biologique Pub Date : 2025-05-01 DOI:10.1016/j.tracli.2025.03.005

Wang Feng , Xu Wen-long , Xu Zhi-guo , Wang Yun , Yang Hai-ying , Chen Yi-zhu , Lv Ke , Shi Lei

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引用次数: 0

摘要

背景：随着医疗技术的进步和人口的老龄化，单供血小板输注的治疗效果显著，对其的需求正在增加。然而，由于血小板的保质期短，且缺乏大规模储备，因此准确的需求预测对于血库库存管理、资源分配和临床供应至关重要。目的：通过时间序列分析，特别是SARIMA模型，预测血小板需求趋势，为血库优化资源配置，提高临床供应效率提供科学依据。方法：收集湖州市中心血站2015年1月至2023年12月A型血机的月度汇总数据。通过分析这些数据，构建SARIMA模型来预测2024年上半年的血小板需求。结果：SARIMA(0,1,1)(0,1,1)12模型在拟合优度和贝叶斯信息准则（BIC）检验方面表现最好，能准确预测血小板需求。预测结果显示，2024年上半年的实际月供应量在预测的95%置信区间内，平均相对误差为3.61%。结论：SARIMA模型能有效预测血小板需求，为血库优化库存管理和临床供应提供实用工具。未来的研究应进一步探索优化和改进，以更好地服务于临床需求和资源管理。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Platelet demand forecasting based on the SARIMA model: optimizing blood bank resource allocation and clinical supply

Background

With advances in medical technology and an aging population, the demand for single-donor platelet transfusions is increasing because of their significant therapeutic effects. However, the short shelf-life of platelets and the lack of large-scale reserves make accurate demand forecasting crucial for blood bank inventory management, resource allocation and clinical supply.

Objective

This study aims to forecast platelet demand trends via time series analysis, specifically the SARIMA model, to provide scientific evidence for blood banks, optimize resource allocation and improve clinical supply efficiency.

Methods

Monthly aggregate data from type A BPC units supplied by Huzhou Central Blood Station from January 2015 to December 2023 were collected. By analyzing these data, a SARIMA model was constructed to predict platelet demand in the first half of 2024.

Results

The SARIMA(0,1,1)(0,1,1)₁₂ model performed best in terms of goodness of fit and Bayesian information criterion (BIC) tests and accurately predicted platelet demand. The predicted results revealed that the actual monthly supply in the first half of 2024 was within the 95% confidence interval of the forecast, with a mean relative error of 3.61%.

Conclusion

The SARIMA model effectively predicts platelet demand, providing a practical tool for blood banks to optimize inventory management and clinical supply. Future research should explore further optimizations and improvements to better serve clinical needs and resource management.

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来源期刊

Transfusion Clinique et Biologique 医学-免疫学

CiteScore

2.50

自引率

11.80%

发文量

234

审稿时长

36 days

期刊介绍： Transfusion Clinique et Biologique, the official journal of the French Society of Blood Transfusion (SFTS): - an aid to training, at a European level - the only French journal indexed in the hematology and immunology sections of Current Contents Transfusion Clinique et Biologique spans fundamental research and everyday practice, with articles coming from both sides. Articles, reviews, case reports, letters to the editor and editorials are published in 4 editions a year, in French or in English, covering all scientific and medical aspects of transfusion: immunology, hematology, infectious diseases, genetics, molecular biology, etc. And finally, a convivial cross-disciplinary section on training and information offers practical updates. Readership: "Transfusers" are many and various: anesthetists, biologists, hematologists, and blood-bank, ICU and mobile emergency specialists...