Application of Sigma metrics in the quality control strategies of immunology and protein analytes

Abstract

Background Six Sigma (6σ) is an efficient laboratory management method. We aimed to analyze the performance of immunology and protein analytes in terms of Six Sigma. Methods Assays were evaluated for these 10 immunology and protein analytes: Immunoglobulin G (IgG), Immunoglobulin A (IgA), Immunoglobulin M (IgM), Complement 3 (C3), Complement 4 (C4), Prealbumin (PA), Rheumatoid factor (RF), Anti streptolysin O (ASO), C‐reactive protein (CRP), and Cystatin C (Cys C). The Sigma values were evaluated based on bias, four different allowable total error (TEa) and coefficient of variation (CV) at QC materials levels 1 and 2 in 2020. Sigma Method Decision Charts were established. Improvement measures of analytes with poor performance were recommended according to the quality goal index (QGI), and appropriate quality control rules were given according to the Sigma values. Results While using the TEaNCCL, 90% analytes had a world‐class performance with σ>6, Cys C showed marginal performance with σ<4. While using minimum, desirable, and optimal biological variation of TEa, only three (IgG, IgM, and CRP), one (CRP), and one (CRP) analytes reached 6σ level, respectively. Based on σNCCL that is calculated from TEaNCCL, Sigma Method Decision Charts were constructed. For Cys C, five multi‐rules (13s/22s/R4s/41s/6X, N = 6, R = 1, Batch length: 45) were adopted for QC management. The remaining analytes required only one QC rule (13s, N = 2, R = 1, Batch length: 1000). Cys C need to improve precision (QGI = 0.12). Conclusions The laboratories should choose appropriate TEa goals and make judicious use of Sigma metrics as a quality improvement tool.

The Evaluation of the Quality Performance of Biochemical Analytes in Clinical Biochemistry Laboratory Using Six Sigma Matrices

“…Through the incorporation of both bias and coefficient of variation (CV) in a laboratory's performance, the sigma offers an objective means of evaluating and comparing laboratory quality. The three parameters that form the basis of sigma analysis are bias, CV%, and total allowable error (TEa) [ 5 ]. The total allowable error represents the laboratory's deviation from the true concentration of an analyte from the reported concentration in a patient's sample, which should be within the limit to consider the result as reliable [ 5 ].…”

“…The three parameters that form the basis of sigma analysis are bias, CV%, and total allowable error (TEa) [ 5 ]. The total allowable error represents the laboratory's deviation from the true concentration of an analyte from the reported concentration in a patient's sample, which should be within the limit to consider the result as reliable [ 5 ]. Bias is the systematic difference between the average value and the true value [ 6 ].…”