Quantitative Application of Sigma Metrics in Medical Biochemistry

• Main Authors: Sunil Kumar Nanda, Lopamudra Ray
• Format: Article
• Language: English
• Published: JCDR Research and Publications Private Limited 2013-12-01
• Series: Journal of Clinical and Diagnostic Research
• Subjects: coefficient of variance; percentage bias; total allowable error
• Online Access: https://jcdr.net/articles/PDF/3700/11-%207292_E(C)_F(H)_PF1(PP)_PFA(H)_OLF.pdf

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.