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The aim of this work is to design a selection algorithm for total allowable error (TEa) source using a graphic tool that, by integrating internal (IQC) and external (EQC) quality control performances, enables the laboratory to evaluate which TEa source better fits the test analytical performance.    Materials and methods  Two analytical performance indicators (bias and Sigma metrics) were estimated for 23 biochemistry tests during 2016. Bias was estimated on the EQC, and Sigma metrics was calculated through the results obtained in the IQC. The Sigma metrics was charted as a function of the bias (TEa%). Following the proposed algorithm (considering the hierarchy in the Milan 2014 consensus), the TEa was evaluated depending on two areas. One area in the chart was defined as the objective area in which the used TEa is the appropriate one for the analytical performance of the test under evaluation. For any test located outside this area, a performance re-evaluation was required using another source of TEa.    Results  In 19 out of 23 evaluated tests, the resulting analytical performance allowed for the selection of biologic variability as TEa source. In the four remaining cases, TEa sources of lesser hierarchy were selected.    Conclusion  The graphic tool designed together with the proposed algorithm enabled the laboratory to standardize the selection procedure of the most appropriate TEa for the test analytical performance.

Comprehensive evaluation of the internal and external quality control to redefine analytical quality goals