Discrepancies in Sigma Metrics Driven by Total Allowable Error Variability: Implications for QC Strategy and Laboratory Efficiency

Abstract

Background: Sigma methodology has become a valuable tool in clinical laboratories for assessing analytical performance and optimizing QC. However, the choice of total allowable error (TEa) sources significantly influences sigma calculation outcomes and can lead to inconsistent quality classifications. In this study, we aimed to evaluate how different TEa guidelines impact sigma metrics and internal quality control (IQC) strategies in order to highlight the need for harmonization in TEa selection. Methods: A prospective observational study was conducted over 3 months (April–June 2025) in the Clinical Biochemistry Laboratory at Bechir Hamza Children’s Hospital. Sigma metrics were calculated for 14 routine analytes at 2 QC levels (level 1 and level 2) using internal and external QC data. Three TEa sources were used: CLIA 2025 (regulatory-based), Randox International Quality Assessment Scheme (RIQAS; peer group-based), and European Federation of Laboratory Medicine (EFLM; biological variation-based). IQC procedures were adapted based on Westgard sigma rules and flowcharts. Results: Substantial variability in sigma metrics was observed across the 3 TEa guidelines. The same analyte could be classified as “world-class” under EFLM but “unacceptable” under RIQAS. Electrolytes (sodium, potassium, chloride) consistently exhibited poor performance across all guidelines. Visual tools, including radar and sigma charts, confirmed discrepancies. These differences significantly influenced the selection and complexity of IQC procedures. Conclusions: The choice of TEa guideline exerts a critical influence on sigma metrics and subsequent IQC planning. Current inconsistencies highlight the urgent need for standardized TEa criteria that are both clinically meaningful and practically achievable. Harmonization would improve comparability, optimize laboratory resources, and support evidence-based quality management in clinical laboratories.