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Evaluation of the analytical performance of endocrine analytes using sigma metrics

机译:利用SIGMA指标评估内分泌分析的分析性能

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Background (a) To evaluate the clinical performance of endocrine analytes using the sigma metrics (σ) model. (b) To redesign quality control strategies for performance improvement. Methods The sigma values of the analytes were initially evaluated based on the allowable total error (TEa), bias, and coefficient of variation (CV) at QC materials level 1 and 2 in March 2018. And then, the normalized QC performance decision charts, personalized QC rules, quality goal index (QGI) analysis, and root causes analysis (RCA) were performed based on the sigma values of the analytes. Finally, the sigma values were re‐evaluated in September 2018 after a series of targeted corrective actions. Results Based on the initial sigma values, two analytes (FT3 and TSH) with σ??6, only needed one QC rule (1 3S ) with N2 and R500 for QC management. On the other hand, seven analytes (FT4, TT4, CROT, E2, PRL, TESTO, and INS) with σ??4 at one QC material level or both needed multiple rules (1 3S /2 2S /R 4S /4 1S /10 X ) with N6 and R10‐500 depending on different sigma values for QC management. Subsequently, detailed and comprehensive RCA and timely corrective actions were performed on all the analytes base on the QGI analysis. Compared with the initial sigma values, the re‐evaluated sigma metrics of all the analytes increased significantly. Conclusions It was demonstrated that the combination of sigma metrics, QGI analysis, and RCA provided a useful evaluation system for the analytical performance of endocrine analytes.
机译:背景(a)使用Sigma度量(σ)模型来评估内分泌分析物的临床性能。 (b)重新设计绩效改进质量控制策略。方法2018年3月,QC材料等级1和2的允许总误差(茶),偏差和变异系数(CV)的允许总误差(CV),最初评估分析物的SIGMA值。然后,标准化的QC性能决策图表,基于分析物的Sigma值进行个性化QC规则,质量目标指数(QGI)分析和根本原因分析(RCA)。最后,在一系列有针对性的纠正措施之后,在2018年9月重新评估了SIGMA值。结果基于初始SIGMA值,两个分析物(FT3和TSH),具有σΔ&Δ6,仅需要一个QC规则(1 3s),N2和R500用于QC管理。另一方面,七个分析物(FT4,TT4,CROT,E2,PRL,Testo和Ins),其中一个QC材料水平或两条QC材料水平或两条QC的多项规则(1 3s / 2 2s / R 4s / 4 1s / 10 x)与N6和R10-500,具体取决于QC管理的不同SIGMA值。随后,对QGI分析的所有分析物进行详细和全面的RCA和及时的纠正措施。与初始SIGMA值相比,所有分析物的重新评估的SIGMA度量明显增加。结论证明SIGMA度量,QGI分析和RCA的组合为内分泌分析物的分析性能提供了有用的评价体系。

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