Introduction- Analytical quality is a prerequisite for the clinical laboratory, but it can be difficult to assess it. Sigma metrics is an objective way to measure and quantify quality. It combines total allowable error (TEa), bias and precision. TEa for an analyte is obtained from literature and can vary based on the source of data used such as Biological Variation data or Clinical Laboratory Improvement Amendments (CLIA) guidelines. Hence, we conducted this study to highlight the importance of TEa goals. The objective of our study was to calculate and compare sigma metrics of 16 clinical chemistry assays using TEa data from various sources. Methodology- Precision is expressed as coefficient of variation (%CV) and Bias was calculated from target mean provided by the manufacturer and lab mean. Sources of TEa used are Biological Variability (Desirable, Optimal & Minimum) and CLIA (Old Guidelines & New proposed guidelines 2019). Sigma metric was calculated by formula “Sigma metric= (TEa-Bias)/Precision”. Results- Triglyceride both the levels showed sigma>6, with TEa biological variability desirable and old CLIA guidelines while Amylase showed sigma >3 with Biological variability minimum and old CLIA guidelines whereas, it showed sigma <2 with the Biological variability optimal & New CLIA guidelines. Conclusion- Sigma metrics as a quality assurance tool should be periodically used to monitor changes in assay quality. Laboratories need to improve their performance to reach the desired quality goals. Inconsistent TEa targets from different independent sources can create a dilemma and should be chosen based on assay performance. We found Biological Variability TEa values to be too demanding for routine performance whereas; old CLIA guidelines can be considered lenient.
