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首页> 外文期刊>Journal of Clinical and Diagnostic Research >Evaluation of Quality Assurance in a New Clinical Chemistry Laboratory by Six Sigma Metrics
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Evaluation of Quality Assurance in a New Clinical Chemistry Laboratory by Six Sigma Metrics

机译：六西格玛度量值在新的临床化学实验室中评估质量保证

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Six sigma is a new tool in quality assurance widely applied in several industrial quality control processes including health care industry, especially in clinical laboratories.Aim: To evaluate retrospectively the quality in a new clinical biochemistry laboratory and to take corrective measures to improve the analytical performance on sigma scale.Materials and Methods: This study was undertaken in a new clinical biochemistry laboratory at a Government tertiary care level hospital for a period of six months from February to July 2018. Imprecision (CV) calculated from the Bio-Rad Internal Quality Controls (IQC) of both normal (L1) and abnormal (L2) levels for 16 most common analytes were run on Beckman Coulter AU5800 analyser and inaccuracy (peer bias) calculated from the Bio-Rad External Quality Assurance Scheme (EQAS). The Allowable Total Error (TEa) values taken from CLIA and Biological Variation (for D BIL) guidelines and authors calculated sigma metrics from the standard sigma equation, S(s)=(TEa-bias)/CV. Windows 7, MS Excel was used for statistical analyses.Results: Authors got a similar sigma value for both the level of controls. Nine parameters out of 16, (albumin, aspartate transaminase, total cholesterol, creatinine, glucose, total protein, urea, phosphorus and calcium) are of sigma metrics =3.0 and 4 parameters (alanine transaminase, alkaline phosphatase, total bilirubin and uric acid) have s =5. Amylase had a s of =5 and only two out of 16 tests (direct bilirubin and HDL-C) achieved a sigma value of 6.Conclusion: Further steps were taken to implement QC strategies to improve the sigma metrics as per Westgard and Cooper guidelines.
机译：6 sigma是质量保证的新工具，已广泛应用于包括卫生保健行业在内的多个工业质量控制流程中，特别是在临床实验室。目标：回顾性评估新的临床生化实验室的质量并采取纠正措施以提高质量材料和方法：本研究在政府三级护理医院的新临床生物化学实验室中进行，历时6个月，从2018年2月至2018年7月。不精确度（CV）由在Beckman Coulter AU5800分析仪上运行了16种最常见分析物的正常（L1）和异常（L2）水平的Bio-Rad内部质量控制（IQC），并通过Bio-Rad外部质量保证计划（ EQAS）。取自CLIA和Biological Variation（for D BIL）准则的允许总误差（TEa）值，作者根据标准sigma公式S（s）=（TEa-bias）/ CV计算出sigma度量。 Windows 7，MS Excel用于统计分析。结果：作者在两个控件级别上都获得了相似的sigma值。 16个参数中的9个参数（白蛋白，天冬氨酸转氨酶，总胆固醇，肌酐，葡萄糖，总蛋白质，尿素，磷和钙）的sigma指标= 3.0和4个参数（丙氨酸转氨酶，碱性磷酸酶，总胆红素和尿酸） s = 5。淀粉酶截至= 5，并且16个测试中只有两个测试（直接胆红素和HDL-C）的sigma值为6。结论：采取了进一步的步骤来实施质量控制策略，以改善Westgard和的sigma指标。库珀指南。

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