Abstract Background A sigma-metric run size nomogram is used to recommend quality control (QC) strategies to reduce patient risks. Herein, we aimed to evaluate the sigma performance of 8 enzymes and apply multistage bracketed statistical QC (SQC). Methods Sigma performance of alanine transaminase (ALT), aspartate transaminase (AST), gamma-glutamyl transferase (GGT), alkaline phosphatase (ALP), lactate dehydrogenase (LDH), creatine kinase (CK), amylase (AMY), and lipase (LIP) were determined. Daily workload of each test was estimated and expected reporting QC intervals were designed. Per the nomogram, "start-up" and "monitor" QC rules were determined from sigma performance. SQC was finally applied, followed by quality improvement. Results Sigma metrics were as follows: 5.26 (ALT), 4.80(AST), 5.25(GGT), 3.36(ALP), 4.71(LDH), 15.45(CK), 10.77(AMY), and 3.70 (LIP). "Start-up" rules were MR N2, MR N4, MR N2, MR N4, MR N4, 1:2.5 s N1, 1:3 s N1, and MR N4, and "monitor" QC rules were 1:2.5 s N1, 1:3 s N2, 1:2.5 s N1, MR N4, 1:3 s N2, 1:3 s N1, 1:3 s N1, MR N2 for 8 enzymes, respectively. Conclusion Multistage bracketed SQC is determined by sigma performance. Risk monitoring is significant during assaying to reduce patient risks and improve quality. Highlights • Sigma-metric run size nomogram is used for quality control (QC) to lower patient risks. • Multistage bracketed statistical QC (SQC) is estimated from sigma performance. • Risk monitoring is critical to reduce patient risks and improve quality. • The best method is to improve performance in tests with a low sigma performance. [ABSTRACT FROM AUTHOR]