BACKGROUND: As a cornerstone of quality management in the laboratory, External Quality Assessment (EQA) schemes are used to assess laboratory and analytical method performance. The characteristic function is used to describe the relation between the target concentration and the EQA standard deviation, which is an essential part of the evaluation process. The characteristic function is also used to compare the variability of different analytical methods.
METHODS: We fitted the characteristic function to data from the Belgian External Quality Assessment program for serum ethanol. Data included results from headspace gas chromatography and the enzymatic methods of Abbott, Roche, Siemens, and Ortho-Clinical Diagnostics. We estimated the characteristic function with weighted nonlinear regression. By introducing dummy variables, we rewrote the original formula of the characteristic function to assess statistical inference for comparing the variability of the different analytical methods.
RESULTS: The characteristic function fitted the data precisely. Comparison between methods showed that there was little difference between the estimated variability for low concentrations, and that the increase in SD with increasing target concentration was slower for Abbott and Roche than for the other methods.
CONCLUSIONS: The characteristic function can successfully be introduced in clinical schemes, although its applicability to fit the data should always be assessed. Because of its easy parameterization, it can be used to assess differences in performance between analytical methods and to assess laboratory performance. The characteristic function also offers an alternative framework for coefficients of variation to describe variability of analytical methods.
