Background: In a network of laboratories analytical variability between instruments, even of the same type, may exist for reasons beyond the control of laboratory staff. Controlling variability is a prerequisite for the application of shared reference ranges and for ensuring the transferability of patient test results. Controlling variability requires a robust, non-conventional quality system to detect poor performance of analysers that are geographically distant. Essential to this quality system is a set of well-defined quality specifications. Methods: The approach used in our study started with (1) selection of a model for quality specifications based on biological variation; the 'three-level model' (TLM) was selected on the basis of its flexibility to accommodate various levels of analytical performance; (2) determination of the performance characteristics of the 71 analytes measured in core biochemistry in terms of imprecision and bias; (3) defining quality requirements in the form of imprecision, bias and total error for 71 analytes measured routinely in core biochemistry; and (4) developing software to assist a consistent wide application of the quality specifications and to monitor analytical indices to the common quality specifications. Results: In this paper we describe how we have implemented this model across our network. Forty-six of the 71 analytes in our core laboratory repertoire were allocated to the TLM. We were able to demonstrate equivalence of results on all analysers, for 42 out of 46 analytes allocated to this model. Conclusions: We propose that other networked laboratories should investigate the suitability of this quality system for use in their network.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.