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Background: To demonstrate the utility of sigma metrics towards assessing the quality of processes, and optimization of statistical quality control rules in a high-volume clinical laboratory, in a two-phase quality improvement project. Methods: In the 損re� period, the sigma score was assessed across 25 routine high-volume assay parameters in our laboratory, comprising of 20 clinical chemistry and 5 immunoassay methods. Measures were taken to improve the analytical quality of low sigma score parameters within a 6-month period. Another sigma metric analysis was then performed in the 損ost� period to examine any measurable improvement. Results: The average sigma metric increased from 6.4? to 9.2?. Out of 25 analytes, 17 showed a significant improvement, defined as an increase in the sigma metric by greater than 1.0. Conclusions: The changes in sigma metric had a significant positive impact on the DPMO and reinforced the reliability of our test results. It showed that our quality control processes can be streamlined and simplified further, to optimize the frequency of internal quality control, while still maintaining the same level of error detection and analytical quality assurance. The analysis also provided additional benefits of achieving lesser errors, fewer sample reruns and troubleshooting, and improved turnaround time, for better clinician and patient satisfaction
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Background: Six sigma is a process of quality measurement and improvement program used in industries. Sigma metrics can be used effectively in laboratory services as total testing process has multiple steps and error can occur anywhere. The present study was undertaken to evaluate the quality of the analytical performance of clinical chemistry laboratory by calculating sigma metrics. Methods: The study was conducted in the clinical biochemistry laboratory of Karwar Institute of Medical Sciences, Karwar. Sigma metrics of 15 parameters with automated chemistry analyzer, transasia XL 640, electrolytes with Roche electrolyte analyzer and thyroid hormones with Maglumi were analyzed. Results: Sigma values <3 for Urea, ALT, BD, BT, Ca, creatinine (L1) and urea, AST, BD (L2), sodium, potassium and T4 were observed. Sigma lies between 3-6 for Glucose, AST, cholesterol, uric acid, total protein (L1) and ALT, cholesterol, BT, calcium, creatinine and glucose (L2), chloride, T3,TSH.Sigma was more than 6 for Triglyceride, ALP, HDL, albumin (L1) and TG, uric acid, ALP, HDL, albumin, total protein (L2). Conclusion: Sigma metrics helps to assess analytical methodologies and augment laboratory performance. It acts as a guide for planning quality control strategy. It can be a self assessment tool regarding the functioning of clinical laboratory.
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Objective To explore the differences of using different analytic quality requirements in the comparable validation of blood cell analysis multi-system range test comparable schemes for establishing appropriate analysis quality standards for laboratory.Methods According to WS/T 407-2012 Guideline for Comparability Verification of Quantitative Results in Medical Institution,the range test comparable method was established.According to different sources of analytic quality requirements from the WS/T 406-2012 Analysis Quality Requirements of Clinical Hematological Detection Routine Items,the US Clinical Laboratory Improvement Amendment (88),GB/T 20470-2006 Requirements of External Quality Assessment for Clinical Laboratories and biological variations,corresponding analysis quality requirements standard was designed.Results With the standards designed by using WS/T 406-2012,CLIA′-88 and GB/T 20470-2006 as the analysis quality requirements,only the comparison results of low concentration levels in 3 items of HBC,PLT and HCT were not passed,while other results all were passed;all results passed the consistency verification by suitably revising the analytic quality requirements of low value concentrations.With the biological variations as the analysis quality requirement,the comparison results in WBC three concentration levels,and HBG high and low concentration levels were passed,but other results were not passed.Conclusion The biological variations analytical quality requirements are relative demanding.Using WS/T 406-2012 Analysis Quality Requirements of Clinical Hematological Detection Routine Items and GB/T 20470-2006 Requirements of External Quality Assessment for Clinical Laboratories,fully considering the suitability of low concentration quality requirements and formulating appropriate analysis quality standards of laboratory are the important contents of laboratory comparable validation scheme.
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Objective To study on the application of biological variation total allowable error in quality management of serum lipid detection .Methods The σ score ,quality goal index (QGI) ,priority improvement measures and performance evaluation of lipid accuracy criteria were evaluated ,including cholesterol (CHOL) ,triglyceride (TG) ,high density lipoprotein (HDL‐C) ,low density lipoprotein (LDL‐C) ,which included in the standard of accuracy of the Ministry of Health in 2015 .The reason for unsatisfactory re‐sults of cholesterol (CHOL) test were analyzed .Results Based on the three levels of quality specifications derived in biological var‐iation ,when the total allowable error was located at an appropriate level ,the σ score of TG ,HDL‐C ,LDL‐C reached 6 ,it was not re‐quired for improvement .While the score of CHOL performance analysis was poor ,accuracy was required to give priority to impro‐ving .When the total allowable error reached the best level ,only the σ score of TG achieved “good” in the four items ,improvement of precision was needed .When the total allowable error was located at the lowest level ,the σ score of TG ,HDL‐C ,LDL‐C was grea‐ter than 6 ,the score of performance analysis reached the “excellent” .The σ score of CHOL (2 .9) had been closen to 3σ ,accuracy was required to be corrected .Conclusion The biological variation derived total allowable error is easy to meet the requirements of the quality management in serum lipid determination by current technologies and methods .The theory of 6σ quality can reflect the performance of detection indexes ,and improve the quality of analysis effectively .