ỨNG DỤNG PHƯƠNG PHÁP SIX SIGMA TRONG KHẢO SÁT VÀ ĐÁNH GIÁ HIỆU NĂNG MỘT SỐ XÉT NGHIỆM HÓA SINH TẠI BỆNH VIỆN ĐA KHOA BÀ RỊA

Abstract

Background: Effective quality management is a prerequisite for ensuring the reliability of results. The Six Sigma tool provides a quantitative methodology for evaluating the performance of individual assays based on three key parameters: total allowable error (TEa), bias, and coefficient of variation (CV). This study assessed the performance of routine biochemical assays on two automated analyzer systems, the AU 680 and DxC 700, using the Six Sigma scale, proposing an optimized QC strategy for each assay to enhance result reliability and concurrently optimize operational costs. Materials and Methods: This study employed a descriptive cross-sectional design conducted at the Laboratory Department of Ba Ria General Hospital from March to August 2025. The study focused on six specific serum biochemistry assays (urea, glucose, creatinine, total cholesterol, triglyceride, and HDL-c). Assays were selected based on the criteria of utilizing manufacturer-matched reagents, mandatory participation in Internal Quality Control (IQC) and External Quality Assessment (EQA) programs, and having at least 60 IQC data points over a three-month period. IQC and EQA data spanning six months were subsequently collected to calculate the Coefficient of Variation (CV%), bias% and the Sigma level established according to the CLIA 2019 criteria. Results: A total of 1,988 IQC results and 72 EQA results were analyzed. The majority of the assays demonstrated a CV within acceptable limits and a bias lower than the allowable total error (TEa). On the AU 680 analyzer system, triglyceride and HDL-c achieved ³6σ performance. In contrast, cholesterol, glucose, and creatinine levels were below 3σ, and urea was below 2σ. On the DxC 700 system, triglyceride and HDL-c maintained ³6σ performance; glucose and cholesterol ranged from 3 to 4σ; creatinine was between 2 and < 3σ; and urea remained below 2σ. Conclusions: Six Sigma enables the quantitative assessment of individual assay performance and guides appropriate Quality Control (QC) plan design. Through this study, triglyceride and HDL-c assays demonstrated excellent performance (world-class quality); cholesterol and glucose ranged from acceptable to poor depending on the instrument; while urea and creatinine require improvement. Applying the Sigma scale in conjunction with Westgard rules will enhance result reliability, optimize QC resources, and reduce operational costs