摘要
目的探讨运用趋势分析的方法在血液质量控制中对血液成分关键指标进行评价。方法选取2023年1—12月贵州省血液中心采集和制备且抽检频次为每月1次的全血及成分血的质控数据,挑选与临床输血疗效相关的指标,采用图表结合界限设置的形式进行趋势分析。结果未能100%符合《全血及成分血质量要求》的关键指标有红细胞比容(hematocrit,Hct)、Ⅷ因子含量、血浆蛋白含量、血小板计数,但其每月质控抽检的数据结果满足符合率75%的质控范围;病毒灭活冰冻血浆亚甲蓝残留量项目质控抽检结果曲线距警戒限较远;单采血小板血小板含量项目有8次偏离数据(警戒限),冷沉淀凝血因子有5次偏离数据(警戒限)。结论依据不同血液成分选取相应关键指标进行连续性趋势分析,是及时发现异常、监测采供血过程稳定性的一种参考方法。
Objective To evaluate the key indexes of blood components in blood quality control by using trend analysis method.Methods The quality control data for whole blood and blood components supplied by the Guizhou Blood Center from January to December 2023 were selected,with a sampling frequency of once a month,selected indicators related to clinical blood transfusion efficacy and trend analysis combined charts with boundary settings.Results The key indicators that fail to 100%meet the"Whole Blood and Component Blood Quality Requirements"include hematocrit(Hct),factorⅧcontent,plasma protein content,and platelet count,but the data results of monthly quality control sampling test meet the quality control range of 75%compliance rate.The sampling curve of methylene blue residue in virus-inactivated frozen plasma was far away from the warning limit.There were 8 deviations from the data(warning limit)in the item of platelet content and 5 deviations from the data(warning limit)in the item of cryoprecipitate coagulation factor.Conclusion Selecting corresponding key indicators based on different blood components for continuous trend analysis,is a reference method for timely discovering abnormalities and monitoring the stability of the blood collection and supply process.
作者
曾迪
孙瑞
张玉敏
周晓泉
ZENG Di;SUN Rui;ZHANG Yumin;ZHOU Xiaoquan(Department of Quality Management,Guizhou Blood Center,Guiyang Guizhou 550002,China;Department of Business Information Management,Guizhou Blood Center,Guiyang Guizhou 550002,China)
出处
《中国卫生标准管理》
2024年第16期146-149,共4页
China Health Standard Management
关键词
血液成分
关键指标
趋势分析
质量控制
预防措施
影响因素
blood composition
key indicators
trend analysis
quality control
preventive measures
influential factors
