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Quantitative Application of Sigma Metrics in Medical Biochemistry

机译:Sigma度量标准在医学生物化学中的定量应用

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摘要

>Introduction: Laboratory errors are result of a poorly designed quality system in the laboratory. Six Sigma is an error reduction methodology that has been successfully applied at Motorola and General Electric. Sigma (σ) is the mathematical symbol for standard deviation (SD). Sigma methodology can be applied wherever an outcome of a process has to be measured. A poor outcome is counted as an error or defect. This is quantified as defects per million (DPM). A six sigma process is one in which 99.999666% of the products manufactured are statistically expected to be free of defects. Six sigma concentrates, on regulating a process to 6 SDs, represents 3.4 DPM (defects per million) opportunities. It can be inferred that as sigma increases, the consistency and steadiness of the test improves, thereby reducing the operating costs. We aimed to gauge performance of our laboratory parameters by sigma metrics.>Objectives: Evaluation of sigma metrics in interpretation of parameter performance in clinical biochemistry.>Material and Methods: The six month internal QC (October 2012 to march 2013) and EQAS (external quality assurance scheme) were extracted for the parameters-Glucose, Urea, Creatinine, Total Bilirubin, Total Protein, Albumin, Uric acid, Total Cholesterol, Triglycerides, Chloride, SGOT, SGPT and ALP. Coefficient of variance (CV) were calculated from internal QC for these parameters. Percentage bias for these parameters was calculated from the EQAS. Total allowable errors were followed as per Clinical Laboratory Improvement Amendments (CLIA) guidelines. Sigma metrics were calculated from CV, percentage bias and total allowable error for the above mentioned parameters.>Results: For parameters - Total bilirubin, uric acid, SGOT, SGPT and ALP, the sigma values were found to be more than 6. For parameters – glucose, Creatinine, triglycerides, urea, the sigma values were found to be between 3 to 6. For parameters – total protein, albumin, cholesterol and chloride, the sigma values were found to be less than 3.>Conclusion: ALP was the best performer when it was gauzed on the sigma scale, with a sigma metrics value of 8.4 and chloride had the least sigma metrics value of 1.4.
机译:>简介:实验室错误是由于实验室质量体系设计不当造成的。六西格码(Six Sigma)是一种减少错误的方法,已成功应用于摩托罗拉和通用电气。 Sigma(σ)是标准差(SD)的数学符号。 Sigma方法论可应用于必须测量过程结果的任何地方。不良结果被视为错误或缺陷。量化为每百万缺陷数(DPM)。六个sigma工艺是这样一种工艺,据统计,其中99.999666%的产品在生产中均无缺陷。将6个sigma集中到一个6 SD的过程中,代表3.4 DPM(百万个缺陷)的机会。可以推断,随着sigma的增加,测试的一致性和稳定性得到改善,从而降低了运营成本。我们旨在通过sigma指标来评估实验室参数的性能。>目标:评估sigma指标以解释临床生物化学中的参数性能。>材料和方法:六个月内提取QC(2012年10月至2013年3月)和EQAS(外部质量保证体系)的参数-葡萄糖,尿素,肌酐,总胆红素,总蛋白,白蛋白,尿酸,总胆固醇,甘油三酸酯,氯化物,SGOT,SGPT和ALP。从内部QC计算出这些参数的方差系数(CV)。这些参数的百分比偏差由EQAS计算得出。根据临床实验室改进修正案(CLIA)指南,遵循总允许误差。从上述参数的CV,偏差百分比和总允许误差中计算出Sigma指标。>结果:对于参数-总胆红素,尿酸,SGOT,SGPT和ALP,发现sigma值为大于6。对于参数-葡萄糖,肌酐,甘油三酸酯,尿素,发现sigma值在3到6之间。对于参数-总蛋白质,白蛋白,胆固醇和氯化物,发现sigma值小于3。 >结论:以sigma量度衡量的ALP表现最佳,sigma指标值为8.4,氯化物的sigma指标值为1.4。

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