Abstract:
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 (13S ) 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 (13S /22S /R4S /41S /10X ) 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.
journal_name
J Clin Lab Analjournal_title
Journal of clinical laboratory analysisauthors
Liu Y,Cao Y,Liu X,Wu L,Cai Wdoi
10.1002/jcla.23581subject
Has Abstractpub_date
2020-09-20 00:00:00pages
e23581eissn
0887-8013issn
1098-2825pub_type
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