Cargando…
Practical application of Six Sigma management in analytical biochemistry processes in clinical settings
BACKGROUND: Six Sigma methodology with a zero‐defect goal has long been applied in commercial settings and was utilized in this study to assure/improve the quality of various analytes. METHODS: Daily internal quality control (QC) and external quality assessment data were collected and analyzed by ca...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6977137/ https://www.ncbi.nlm.nih.gov/pubmed/31774217 http://dx.doi.org/10.1002/jcla.23126 |
_version_ | 1783490443420368896 |
---|---|
author | Zhou, Bingfei Wu, Yi He, Hanlin Li, Cunyan Tan, Liming Cao, Youde |
author_facet | Zhou, Bingfei Wu, Yi He, Hanlin Li, Cunyan Tan, Liming Cao, Youde |
author_sort | Zhou, Bingfei |
collection | PubMed |
description | BACKGROUND: Six Sigma methodology with a zero‐defect goal has long been applied in commercial settings and was utilized in this study to assure/improve the quality of various analytes. METHODS: Daily internal quality control (QC) and external quality assessment data were collected and analyzed by calculating the sigma (σ) values for 19 analytes based on the coefficient of variation, bias, and total error allowable. Standardized QC sigma charts were established with these parameters. Quality goal index (QGI) analysis and root cause analysis (RCA) were used to discover potential problems for the analytes. RESULTS: Five analytes with σ ≥ 6 achieved world‐class performance, and only the Westgard rule (1(3s)) with one control measurement at two QC material levels (N2) per QC event and a run size of 1000 patient samples between QC events (R1000) was needed for QC. In contrast, more control rules (2(2s)/R(4s)/4(1s)) along with high N values and low R values were needed for quality assurance for five analytes with 4 ≤ σ < 6. However, the sigma levels of nine analytes were σ < 4 at one or more QC levels, and a more rigorous QC procedure (1(3s)/2(2s)/R(4s)/4(1s)/8(x) with N4 and R45) was implemented. The combination of QGI analysis and RCA further revealed inaccuracy or imprecision problems for these analytes with σ < 4 and discovered five aspects of potential causes considered for quality improvement. CONCLUSIONS: Six Sigma methodology is an effective tool for evaluating the performance of biochemical analytes and is conducive to quality assurance and improvement. |
format | Online Article Text |
id | pubmed-6977137 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-69771372020-01-28 Practical application of Six Sigma management in analytical biochemistry processes in clinical settings Zhou, Bingfei Wu, Yi He, Hanlin Li, Cunyan Tan, Liming Cao, Youde J Clin Lab Anal Research Articles BACKGROUND: Six Sigma methodology with a zero‐defect goal has long been applied in commercial settings and was utilized in this study to assure/improve the quality of various analytes. METHODS: Daily internal quality control (QC) and external quality assessment data were collected and analyzed by calculating the sigma (σ) values for 19 analytes based on the coefficient of variation, bias, and total error allowable. Standardized QC sigma charts were established with these parameters. Quality goal index (QGI) analysis and root cause analysis (RCA) were used to discover potential problems for the analytes. RESULTS: Five analytes with σ ≥ 6 achieved world‐class performance, and only the Westgard rule (1(3s)) with one control measurement at two QC material levels (N2) per QC event and a run size of 1000 patient samples between QC events (R1000) was needed for QC. In contrast, more control rules (2(2s)/R(4s)/4(1s)) along with high N values and low R values were needed for quality assurance for five analytes with 4 ≤ σ < 6. However, the sigma levels of nine analytes were σ < 4 at one or more QC levels, and a more rigorous QC procedure (1(3s)/2(2s)/R(4s)/4(1s)/8(x) with N4 and R45) was implemented. The combination of QGI analysis and RCA further revealed inaccuracy or imprecision problems for these analytes with σ < 4 and discovered five aspects of potential causes considered for quality improvement. CONCLUSIONS: Six Sigma methodology is an effective tool for evaluating the performance of biochemical analytes and is conducive to quality assurance and improvement. John Wiley and Sons Inc. 2019-11-27 /pmc/articles/PMC6977137/ /pubmed/31774217 http://dx.doi.org/10.1002/jcla.23126 Text en © 2019 The Authors. Journal of Clinical Laboratory Analysis published by Wiley Periodicals, Inc. 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 Zhou, Bingfei Wu, Yi He, Hanlin Li, Cunyan Tan, Liming Cao, Youde Practical application of Six Sigma management in analytical biochemistry processes in clinical settings |
title | Practical application of Six Sigma management in analytical biochemistry processes in clinical settings |
title_full | Practical application of Six Sigma management in analytical biochemistry processes in clinical settings |
title_fullStr | Practical application of Six Sigma management in analytical biochemistry processes in clinical settings |
title_full_unstemmed | Practical application of Six Sigma management in analytical biochemistry processes in clinical settings |
title_short | Practical application of Six Sigma management in analytical biochemistry processes in clinical settings |
title_sort | practical application of six sigma management in analytical biochemistry processes in clinical settings |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6977137/ https://www.ncbi.nlm.nih.gov/pubmed/31774217 http://dx.doi.org/10.1002/jcla.23126 |
work_keys_str_mv | AT zhoubingfei practicalapplicationofsixsigmamanagementinanalyticalbiochemistryprocessesinclinicalsettings AT wuyi practicalapplicationofsixsigmamanagementinanalyticalbiochemistryprocessesinclinicalsettings AT hehanlin practicalapplicationofsixsigmamanagementinanalyticalbiochemistryprocessesinclinicalsettings AT licunyan practicalapplicationofsixsigmamanagementinanalyticalbiochemistryprocessesinclinicalsettings AT tanliming practicalapplicationofsixsigmamanagementinanalyticalbiochemistryprocessesinclinicalsettings AT caoyoude practicalapplicationofsixsigmamanagementinanalyticalbiochemistryprocessesinclinicalsettings |