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首页> 外文期刊>Vox Sanguinis: International Journal of Blood Transfusion and Immunohaematology >Optimal collecting policy for apheresis platelets in a regional blood center
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Optimal collecting policy for apheresis platelets in a regional blood center

机译:最优收集政策apheresis血小板在一个地区血液中心

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Background and objectives Planning platelet collection and inventory must rely not only on adequate forecasts of transfusion demand but also sophisticated mathematical modeling techniques. This research aims to develop a better demand forecasting model of apheresis platelets and a mathematical programming model to determine the best target amounts of apheresis platelet collection. Materials and methods Time series data of apheresis platelets collected from donors and platelets supplied to hospitals daily in Taipei Blood Center from January 2014 to December 2015 was used to fit a forecasting model which combines a regression‐type model for formulating the deterministic trends and seasonal variation and an autoregressive moving average model (ARMA) for explaining remaining serial correlations. A seasonal autoregressive integrated moving average (SARIMA) model was also used for benchmarking the prediction performance. A linear programming model was then formulated to solve for the optimal daily target collection volumes that maximize the total social benefits. Results The time series model achieved good predictive power with a mean absolute percentage error less than 10%. The appropriateness of the proposed target collection volumes was also verified by using a simulation model, and the proportion of the total platelets requested by hospitals that can be filled by collected apheresis platelets can increase significantly by using the new policy. Conclusion The methods proposed in this study can be easily implemented to enhance the management efficiency of blood collecting and supplying of a blood center, and to decrease the costs of the blood outdates and shortages.
机译:背景和目标规划血小板收集和库存必须不仅依赖足够的输血需求的预测也复杂的数学建模技术。本研究旨在开发一个更好的需求apheresis血小板和预测模型数学规划模型来确定的最好的目标数量的apheresis血小板收集。数据收集的apheresis血小板捐献者和血小板供应给医院日常台北血液中心从2014年1月至12月2015年是使用适合的预测模型结合一个回归模型制定类型确定性趋势和季节性变化和一个自回归移动平均模型(ARMA)解释剩下的序列相关性。季节性自回归综合移动平均线SARIMA模型也用于基准测试预测性能。模型是制定解决的优化日常目标收集量整个社会福利最大化。时间序列模型取得了良好的预测能力平均绝对百分误差小于10%。组卷也验证了使用仿真模型和总数的比例血小板的医院,可以请求的由收集apheresis血小板通过使用新政策显著增加。结论:本研究中提出的方法很容易实现提高管理血液收集和提供的效率血液中心,降低的成本血液使废弃和短缺。

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