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Background: We developed a new practical tool and applied it to assess the performance of 14 biochemical assays and designed risk-based statistical quality control (SQC) procedures.
Methods: Two graphs were combined to develop the new tool. Data points of assays were plotted on the tool to determine their sigma performance and the risk-based SQC procedures. The quality goal index (QGI) was also calculated for quality improvement.
Results: Among 14 assays, total bilirubin, direct bilirubin, alanine aminotransferase, creatine kinase, and gammaglutamyl transferase achieved 6-sigma performance, the recommended SQC procedure was 13s rule (n = 2) with a run size of 1,000 patient samples. Triglycerides was 5-sigma quality and could be controlled with 13s/22s/R4s multi-rule procedure (n = 2) with a run size of 450. Uric acid, creatinine, total cholesterol, and aspartate aminotransferase obtained 4-sigma quality and could be controlled using 13s/22s/R4s/41s multi-rule procedure (n = 4) with run size of 200. The performance for urea, alkaline phosphatase, amylase, and lactate dehydrogenase was 3-sigma and 13s/22s/R4s/41s/6X multi-rule procedure (n = 6) with run size of 45 was recommended. The QGI for assays with sigma quality below 6.0 were all less than 0.8.
Conclusions: The developed tool can be used to simplify laboratory practices in assessing analytical performance and designing SQC procedures.
DOI: 10.7754/Clin.Lab.2022.220215
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