|dc.description.abstract||Measurement uncertainty (MU) of results is one of the basic recommended and accepted statistical
methods in laboratory medicine, with which analytical and clinical evaluation of laboratory
test quality is assessed. Literature data indicate that the calculation of MU is not a simple process,
but that its assessment in daily laboratory practice should be reduced to routine and simple
presentation, understandable to both laboratory professionals and physicians. In order to achieve
this, it is necessary to understand the purpose of the test for which MU is to be determined.
Various suggestions have been given for presentation of MU as a quantitative indicator of the
quality of the final measurement result in the medical laboratory. Although MU refers to the final
measurement result, this metrological concept reflects the entire laboratory measurement process.
The data on estimated MU is used to interpret the measured numerical result, and represents
quantitatively the quality of the measurement itself, i.e. how different are the results of
multiple measurements of the analyte of interest in the same sample, as well as whether the
method of determination itself is subjected to significant random and systematic deviation.
Initially, in the metrological concept, the MU is viewed in relation to the true value of the analyte
of interest. However, the true value of the analyte measured in the biological fluid matrix of the
study population cannot be known. It is therefore considered the closest value obtained by the
perfect method, for which the bias and inaccuracy, as measures of systematic and random error,
are equal to zero, which is practically impossible to achieve in routine laboratory practice.
Although current standards require accredited medical laboratories to estimate MU, none of
these guidelines provide clear guidance on how this can be achieved in daily laboratory work.
This review examines literary data and documents dealing with MU issues, but also highlights
what additional terms and data should be considered when interpreting MU. This paper ultimately
draws attention, and once again points out, that a simpler solution is needed for this universal
concept to be formally and universally applicable in routine laboratory medicine practice.||en