在西班牙I型EQA项目中,使用Schmidt-Launsbyn vs. Westgard方程估计六西格玛的影响。

IF 1.1 Q4 MEDICAL LABORATORY TECHNOLOGY
Advances in laboratory medicine Pub Date : 2025-07-02 eCollection Date: 2025-09-01 DOI:10.1515/almed-2025-0091
Fernando Marqués-García, Elisabeth González-Lao, Xavier Tejedor-Ganduxé, Beatriz Boned, Jorge Díaz-Garzón, Margarida Simón, Jose Vicente García-Lario, Carme Perich, María Pilar Fernández-Fernández, Luisa María Martínez-Sánchez, María Muñoz-Calero, Ricardo González-Tarancón, Pilar Fernández-Calle
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引用次数: 0

摘要

目标:六西格玛方法(SM)使用每百万机会的缺陷(DPMOs)来度量过程性能。SM传统上使用Westgard方程(WM),通过该方程间接计算dpmo。直接计算DPMOs的另一种方法是结合Schmidt-Launsbyn方程的z变换方法。SM在外部质量保证(EQA)项目中的实施是有限的,这阻碍了它们的评价。对两个方程得到的SM值进行了比较研究。材料和方法:根据一个I型EQA项目(SCR-EQA-SEQCML)的数据,采用Westgard方程和Z-transformation + Schmidt-Launsbyn方法(S-LM)两种方法估计Sigma值(SV)。对两种方法得到的SVs进行了比较。结果:根据EQA程序提供的949个值计算sv。结果表明,与S-LM相比,WM低估了SV,与是否去除异常值无关(2.9)(1.9)。这种低估是由于治疗偏差而不是不精确造成的。结论:与MW不同,S-LM调节偏倚,从而防止负SVs。S-LM不像MW那样受异常值的影响,并且在EQA程序中产生更稳健的SV估计。这保证了对结果的更精确的评估和方法/系统性能的分类。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Impact of six sigma estimated using the Schmidt-Launsbyn vs. the Westgard equation in the Spanish type I EQA program.

Impact of six sigma estimated using the Schmidt-Launsbyn vs. the Westgard equation in the Spanish type I EQA program.

Impact of six sigma estimated using the Schmidt-Launsbyn vs. the Westgard equation in the Spanish type I EQA program.

Impact of six sigma estimated using the Schmidt-Launsbyn vs. the Westgard equation in the Spanish type I EQA program.

Objectives: Six sigma methodology (SM) measures process performance using defects per million opportunities (DPMOs). SM has traditionally used the Westgard equation (WM), by which DPMOs are calculated indirectly. An alternative for directly calculate DPMOs is the Z-transformation method in combination with the Schmidt-Launsbyn equation. The implementation of SM in External Quality Assurance (EQA) programs is limited, which hampers their evaluation. A study was conducted to compare SM values obtained with the two equations.

Materials and methods: Sigma value (SV) was estimated based on data from a Type I EQA Program (SCR-EQA-SEQCML) using two methods: the Westgard equation, and the Z-transformation + Schmidt-Launsbyn method (S-LM). A comparison of the SVs obtained with the two methods was performed.

Results: SVs were calculated from 949 values provided by the EQA program. The results indicate that WM underestimates SV, as compared to S-LM, independently of whether outliers were removed (2.9) or not (1.9). This underestimation occurs as a result of treatment bias rather than imprecision.

Conclusions: Unlike MW, S-LM adjusts for bias, thereby preventing negative SVs. S-LM is not as influenced by outliers as MW and yields more robust SV estimates in EQA programs. This guarantees a more precise evaluation of results and classification of method/system performance.

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