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Adjusting Quality Control Chart Limits for WBC, RBC, Hb, and PLT Counts to Reduce Daily Control Risks in Hospital Laboratory

机译:调整WBC,RBC,HB和PLT的质量控制图限制,以减少医院实验室的日常控制风险

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Background:To continuously improve medical quality and provide clinicians with more accurate blood test reports, this study collected blood quality control data in 2017 from a medical examination laboratory in a teaching level hospital located in Taoyuan City, Taiwan.Material and Methods:The quality control data were arranged and analyzed from daily complete blood count (CBC), including white blood cells (WBC), red blood cells (RBC), hemoglobin (Hb), and platelets (PLT) recorded by a laboratory blood analyzer. Using the empirical Bayesian method, we estimated the variation of concentrations of the last and current batches to establish a novel control chart with adjusted upper and lower limits for the current batch, and then compared results with the traditional Shewhart method. The average run length (ARL) and sensitivity of the empirical Bayesian method were explored.Results:The study found that ARL showed a qualified capability for the four blood routine tests when using the empirical Bayesian method. Compared to the Levey-Jennings control chart, the novel control chart presents an alert earlier when a deviation occurs and shows a fake alert later when there is no deviation.Conclusion:The parallel tests showed that the longer the time is, the better the test's proficiency. We concluded that the empirical Bayesian method could be applied effectively to improve the capability of daily control in CBC laboratory tests.? 2020 Liao et al.
机译:背景:为了不断提高医疗质量,并提供更准确的血液测试报告,从而在2017年从位于台湾桃园市的教学水平医院的体检实验室收集血质控制数据。材料和方法:质量控制数据被安排和分析,并从日常完整的血液计数(CBC),包括由实验室血液分析仪记录的白细胞(WBC),红细胞(RBC),血红蛋白(HB)和血小板(PLT)。使用经验贝叶斯方法,我们估计了最后一次和当前批次的浓度的变化,以建立新的控制图表,该图表与当前批次的调整高度和下限,然后用传统的削波方法进行比较结果。探讨了经验贝叶斯方法的平均运行长度(ARL)和敏感性。结果:研究发现,在使用经验贝叶斯方法时,ARL为四种血常试验表现出合格的能力。与levey-jennings控制图相比,新颖的控制图表在发生偏差时提前提醒警报并在没有偏差时显示假警报。结论:并行测试显示,时间越长,测试越长,测试越长熟练。我们得出结论,经验贝叶斯方法可以有效应用,以提高CBC实验室测试中的日常对照能力。 2020 Liao等人。

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