西格玛-度量分析评价使用RCA和QGI在印度南部临床生物化学实验室的分析过程的质量管理

S. Nilakantam, Kusuma Kasapura Shivashankar, Akila Prashant, Melanahalli Dayananda, Suma M. Nataraj, Namratha G Dayananda
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引用次数: 0

摘要

本研究旨在通过西格玛-度量分析尽早发现实验室错误,并评价分析过程的质量管理。方法:收集认可实验室在罗氏Cobas6000和e411上运行的31项生化参数的IQC和EQC数据,计算Sigma-metrics和质量目标指数(QGI)。结果:近13种化学分析物在Sigma bbb6 (cid:1)下表现为世界级水平,大部分免疫测定参数在Sigma > (cid:1) 6下表现为边缘性水平。钠、氯化物、总T4、β - hcg和TSH的Sigma < 2表明表现不佳。在进行根本原因分析后,西格玛计量分析有了显著的改善。结论:西格玛计量分析了生物化学各分析过程的质量管理。通过根本原因分析和质量目标指标的计算,找出分析结果不佳的地方。在RCA和QGI的帮助下,我们计划通过减少QC运行的频率来增加资源管理。
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Sigma-Metric Analysis to Evaluate Quality Management of Analytical Processes Using RCA and QGI in a Clinical Biochemistry Laboratory, South India
Introduction : This study aimed to identify laboratory errors at the earliest through Sigma-metric analysis and to evaluate quality management of analytical processes. Methods : Sigma-metrics and Quality Goal Index (QGI) were calculated by harvesting the IQC and EQC data of an accredited laboratory for 31 biochemical parameters run on Roche Cobas6000 and e411. Those with Sigma (cid:1) 2 were further analysed by applying the various Westgard rules, as suggested Results : Nearly 13 chemistry analytes showed world-class performance with Sigma > 6 and most of the immunoassay parameters showed marginal performance with sigma > 2 (cid:1) 6. Sodium, Chloride, Total T4, Beta-HCG and TSH were found to have Sigma < 2 indicating unacceptable performance. A signi fi cant improvement was observed in the Sigma-metrics analysis after performing the root cause analysis Conclusion : Sigma-metric analyses the quality management of various analytical processes in biochemistry. The poor assay performance will be picked up by the Root cause analysis and Quality Goal Indices calculation. With the help of RCA and QGI, we plan to increase the resource management by decreasing the frequency of QC runs.
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