Application of the six sigma model to evaluate the analytical performance of serum lipid analytes and design quality control strategies: A multi-centre study

BackgroundThe six sigma model is widely used in laboratory quality management. For the first time, this study introduced total allowable error (TEa) from WS/T403-2024 and 'desirable' biological variation (BV) as dual quality goals to evaluate serum lipid analytes in six laboratories and develop individualized quality control (QC) strategies.MethodsWe collected internal quality control (IQC) and external quality assessment (EQA) data to calculate sigma values for each serum lipid analyte. Normalized sigma method decision charts were employed, and the Westgard sigma rule flow chart with batch size plus the quality goal index (QGI) guided individualized QC strategies and improvement plans.ResultsUnder the same quality goal, different QC concentrations produced varying sigma values. Sigma values also differed significantly between the two quality goals. When WS/T403-2024 was applied, all analytes except triglycerides (TGs) showed lower sigma values than under 'desirable' BV. Normalized sigma method decision charts effectively highlighted these differences. Based on the Westgard sigma rule flow chart with batch size and QGI, individualized QC strategies were created, and priority improvement measures were proposed for analytes with sigma values below six.ConclusionsThe six sigma model is a valuable tool for laboratory quality management, guiding laboratories to enhance the detection capabilities of serum lipid analytes through targeted QC strategies and improvement measures.