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Evaluation of the analytical performance of endocrine analytes using sigma metrics

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...

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Autores principales: Liu, Yanming, Cao, Yue, Liu, Xijun, Wu, Liangyin, Cai, Wencan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7843286/
https://www.ncbi.nlm.nih.gov/pubmed/32951270
http://dx.doi.org/10.1002/jcla.23581
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author Liu, Yanming
Cao, Yue
Liu, Xijun
Wu, Liangyin
Cai, Wencan
author_facet Liu, Yanming
Cao, Yue
Liu, Xijun
Wu, Liangyin
Cai, Wencan
author_sort Liu, Yanming
collection PubMed
description 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.
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spelling pubmed-78432862021-02-02 Evaluation of the analytical performance of endocrine analytes using sigma metrics Liu, Yanming Cao, Yue Liu, Xijun Wu, Liangyin Cai, Wencan J Clin Lab Anal Research Articles 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. John Wiley and Sons Inc. 2020-09-20 /pmc/articles/PMC7843286/ /pubmed/32951270 http://dx.doi.org/10.1002/jcla.23581 Text en © 2020 The Authors. Journal of Clinical Laboratory Analysis Published by Wiley Periodicals LLC This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Articles
Liu, Yanming
Cao, Yue
Liu, Xijun
Wu, Liangyin
Cai, Wencan
Evaluation of the analytical performance of endocrine analytes using sigma metrics
title Evaluation of the analytical performance of endocrine analytes using sigma metrics
title_full Evaluation of the analytical performance of endocrine analytes using sigma metrics
title_fullStr Evaluation of the analytical performance of endocrine analytes using sigma metrics
title_full_unstemmed Evaluation of the analytical performance of endocrine analytes using sigma metrics
title_short Evaluation of the analytical performance of endocrine analytes using sigma metrics
title_sort evaluation of the analytical performance of endocrine analytes using sigma metrics
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7843286/
https://www.ncbi.nlm.nih.gov/pubmed/32951270
http://dx.doi.org/10.1002/jcla.23581
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