Optimizing Laboratory Quality with Sigma Metrics: Application of CLIA 2024 Total Allowable Error Guidelines

Background- Statistical quality control continues to serve as the cornerstone for ensuring the accuracy and reliability of laboratory investigations. The current research aimed to evaluate the performance of biochemistry parameters using Six Sigma metrics in light of revised CLIA (Clinical Laboratory Improvement Amendments) total allowable error (TEa) 2024 guidelines, to guide the application of appropriate quality control strategies. Methods- Quality control data for 20 chemistry parameters analyzed on the Fully Automated Biochemistry analyzer were evaluated using Six Sigma methodology. Internal quality control (IQC) and external quality assessment scheme (EQAS) data from December 2023 to May 2024 were collected. Coefficient of variation (%), bias (%) and TEa based on CLIA and Ricos biological variation guidelines were used to calculate sigma metrics. All quality control data were entered and analyzed using Microsoft Excel (Microsoft Corporation, Redmond, WA, USA). Results- The laboratory showed excellent (≥6 sigma) performance for direct bilirubin and HDL-cholesterol. Albumin, alkaline phosphatase, aspartate transaminase, cholesterol, glucose, iron, potassium, total iron binding capacity and triglycerides achieved minimum sigma performance standard (>3) at one level. However, the other chemistry parameters did not meet the minimum sigma performance standard across all assay range. Conclusion- The laboratories need to reassess the performance of various biochemical parameters to redefine quality control protocols as the CLIA 2024 guidelines have tightened the total allowable error goals.