Maisoon Amarni, Kamal Dumaidi, Sara Abbadi, Nataly Fakhouri, Amer Al-Jawabreh
BACKGROUND: Reliable analytical performance is vital for accurate diagnosis in clinical chemistry laboratories. Quality control (QC) strategies must be customized to assess performance, meet regulatory standards, and optimize resource use. This study evaluated the analytical performance of 3 routine analytes, blood-urea nitrogen (BUN), creatinine, and glucose using Sigma metrics, visualized through the Method Decision Chart (MDC), Quality Goal Index (QGI), and Operating Specifications (OPSpecs) charts, to recommend appropriate internal quality control (IQC) procedures at 3 levels (L1, L2, L3). METHODS: A 6-month retrospective analysis (June-November 2024) was performed in an ISO 15189:2022 accredited primary health care laboratory in Jenin District, Palestine. Internal QC and External Quality Assessment Scheme data were used to calculate the coefficient of variation (%CV), %bias, and Sigma values across all IQC levels, applying CLIA total allowable error limits. For analytes with Sigma <4, QGI ratios differentiated between imprecision, inaccuracy, or combined error sources. MDC and OPSpecs charts guided the selection of Westgard QC rules. RESULTS: Glucose demonstrated excellent performance (σ > 6), allowing a simplified IQC protocol (1-3.5s, N3, R1). Creatinine showed moderate performance (σ = 3.1-13.6) requiring multirule application (2 of 3-2s, R4s) at Level 2. BUN displayed poor Sigma values (σ < 4), with QGI analysis indicating alternating imprecision and inaccuracy; OPSpecs recommended full multirule implementation and root-cause investigation. CONCLUSION: The combined use of Sigma metrics, QGI, MDC, and OPSpecs charts offers an effective, risk-based QC framework enabling early detection, continuous monitoring, and timely correction of analytical errors in ISO 15189-certified laboratories.