Application of six sigma metrics of routine enzymes for assessing the quality performance of biochemical analytes in the medical laboratory - A cross-sectional study

Background: Six sigma is a powerful quality management approach that enhances performance within the framework of Total Quality Management (TQM). In clinical laboratories, it provides a structured method to evaluate analytical precision and bias, thereby supporting continuous quality improvement and ensuring the reliability of results. Aims and Objectives: This study, conducted at the Clinical Biochemistry Department, aimed to calculate Sigma (σ) metrics for six routine enzyme parameters analyzed using the ERBA XL-640 analyzer from April to September 2023. For analytes with Sigma <3, the Quality Goal Index (QGI) was determined, followed by root cause analysis and implementation of corrective actions to design an appropriate Quality Control (QC) strategy. Materials and Methods: Daily Internal QC data for Level 1 (L1) and Level 2 (L2) controls and monthly External QC data over 6 months were analyzed. Mean, Standard Deviation, Coefficient of Variation, Bias%, Total Error, and Sigma metrics were calculated. For analytes with Sigma <3, QGI values were measured to distinguish between inaccuracy and imprecision. Results: Sigma values <3 were observed for aspartate aminotransferase, alanine aminotransferase (ALT), alkaline phosphatase, gamma-glutamyl transferase (GGT), amylase (AMY), and lipase at L1, while ALT and GGT showed Sigma >3 and <4 at L2. ALT had the highest Sigma value, and AMY the lowest. QGI indicated inaccuracy as the major contributor to poor performance. A QC strategy was designed based on Westgard and Cooper guidelines. Conclusion: Six Sigma effectively evaluates laboratory performance, identifies analytical deficiencies, and guides corrective actions. For parameters with Sigma <3, stringent and frequent QC is essential to maintain accuracy and ensure reliable reporting.