International Journal of Health and Allied Sciences


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 Indices (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 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 6. Sodium, Chloride, Total T4, Beta-HCG and TSH were found to have Sigma < 2 indicating unacceptable performance. A significant 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.