Quality Control Validation, Application of Sigma Metrics, and Performance Comparison between Two Biochemistry Analyzers in a Commercial Veterinary Laboratory

Abstract

A review of the literature pertinent to interpretation of biochemistry data and quality control (QC) and proficiency testing data from 2 biochemistry analyzers was used to determine clinical quality requirements for biochemistry assays, characterize the performance of and calculate sigma metrics for the analytes run on the 2 analyzers, and perform QC validation in order to determine the needs for statistical QC for each analyzer. Quality requirements suitable for the analytes based on the needs of the authors' laboratory are presented. These requirements may or may not be appropriate for other laboratories, depending on the needs of the clients, species, and equipment performance capability. The majority of the analytes were easily controlled using the 13s control rule, with a sigma metric approaching or exceeding 6 and with a high probability of error detection and a low probability of false rejection. Some analytes could not be controlled using the 13s rule, and additional control rules with a greater number of control data points were required. There were differences between performances of the 2 analyzers. The findings in the present study emphasize the need for QC specific for the analyte and the clinical decision level and the need for separate QC validation on every instrument.