Sigma metrics in quality control- An innovative tool

Abstract

The clinical laboratory in today’s world is a rapidly evolving field which faces a constant pressure to produce quick and reliable results. Sigma metric is a new tool which helps to reduce process variability, quantitate the approximate number of analytical errors, and evaluate and guide for better quality control (QC) practices.To analyze sigma metrics of 16 biochemistry analytes using ERBA XL 200 Biochemistry analyzer, interpret parameter performance, compare analyzer performance with other Middle East studies and modify existing QC practices.This study was undertaken at a clinical laboratory for a period of 12 months from January to December 2020 for the following analytes: albumin (ALB), alanine amino transferase (SGPT), aspartate amino transferase (SGOT), alkaline phosphatase (ALKP), bilirubin total (BIL T), bilirubin direct (BIL D), calcium (CAL), cholesterol (CHOL), creatinine (CREAT), gamma glutamyl transferase (GGT), glucose (GLUC), high density lipoprotein (HDL), triglyceride (TG), total protein (PROT), uric acid (UA) and urea. The Coefficient of variance (CV%) and Bias % were calculated from internal quality control (IQC) and external quality assurance scheme (EQAS) records respectively. Total allowable error (TEa) was obtained using guidelines Clinical Laboratories Improvement Act guidelines (CLIA). Sigma metrics was calculated using CV%, Bias% and TEa for the above parameters. It was found that 5 analytes in level 1 and 8 analytes in level 2 had greater than 6 sigma performance indicating world class quality. Cholesterol, glucose (level 1 and 2) and creatinine level 1 showed >4 sigma performance i.e acceptable performance. Urea (both levels) and GGT (level 1) showed <3 sigma and were therefore identified as the problem analytes. Sigma metrics helps to assess analytic methodologies and can serve as an important self assessment tool for quality assurance in the clinical laboratory. Sigma metric evaluation in this study helped to evaluate the quality of several analytes and also categorize them from high performing to problematic analytes, indicating the utility of this tool. In conclusion, parameters showing lesser than 3 sigma need strict monitoring and modification of quality control procedure with change in method if necessary.

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

“…Values for TEa were extracted from RIQAS SOTA 2021 and CLIA 2024. As indicated in Tables 1, 2, the performance of the analytes was graded into six categories based on the sigma level: world-class (sigma ≥ 6), excellent (5 ≤ sigma < 6), good (4 ≤ sigma < 5), marginal (3 ≤ sigma < 4), poor (2 ≤ sigma < 3), and unacceptable (sigma < 2) [12]. Table 3 shows the sigma values in terms of six grades and the analytes falling under those categories for both level 1 and level 2 IQC data.…”

“…Analytes were categorized as world-class, excellent, good, marginal, poor, and unacceptable based on their sigma values. The integration of Six Sigma methodology into clinical biochemistry laboratories has been extensively explored in previous studies [ 11 , 12 ]. The review by Westgard et al demonstrated that Six Sigma metrics provide a robust framework to analyze laboratory errors and optimize the QC rules as per the performance of the laboratory tests [ 14 ].…”