Affiliation:
1. Automation and Portfolio Solutions, QuidelOrtho Corporation , Rochester, NY , United States
2. Valumetrix, QuidelOrtho Corporation , Upavon , United Kingdom
Abstract
Abstract
Background
Sigma metrics have been adapted for the clinical laboratory to incorporate observed accuracy, precision, and total error allowed. The higher the Sigma level for a process, the better performance that process has. A limitation of studies assessing Sigma metrics is that they are performed on a small number of well-controlled systems.
Methods
An algorithm was developed to extract QC data and derive the Sigma metric for 115 analytes from sites connected to the QuidelOrtho E-Connectivity® database. The median of these results was then used to derive the Sigma metric for each assay.
Results
In this analysis, 79 out of 115 (68.7%) of the assays assessed achieved 6 Sigma or better and 98 out of 115 (85.2%) achieved 5 Sigma or better.
Conclusions
This study has demonstrated a methodology that can be used to condense Sigma metrics from hundreds of analyzers into a single metric of assay quality. Because these analyzers are running in working laboratories from around the world, this analysis can serve as a baseline for understanding the assay performance achieved in the presence of variabilities such as lab-to-lab, instrument-to-instrument, material handling, environmental conditions, and reagent lot. The significant number of assays demonstrating high Sigma levels did so despite this variation. The ability of the methods reported here to include hundreds of analyzers represents a novel approach for assessing Sigma metrics in clinical laboratories.
Publisher
Oxford University Press (OUP)
Cited by
2 articles.
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