Bias and measurement uncertainty: a duo rarely handled correctly

Bias (or its absence) and trueness are often considered the same thing and described as systematic error. At its simplest, bias is the difference between a value that is observed and one that is expected. If that expected value is a ‘known’ value, it is also a representation of its trueness. 

Bias is either constant across the measurement range or is influenced by the measurand value, so called proportional bias. Short- and long-term biases can be introduced through common laboratory activities including lot changes of reagents and calibrators. A solution may be to recalibrate the assay. Over calibration may itself introduce bias, and impact metrological traceability. 

Clinically significant bias should be eradicated by manufacturers and suppliers of methods. This is achieved by evidencing metrological traceability of the method (ISO/TS 20914:2019, 6.6). Ideally, calibration steps are documented and provided to laboratories through the instructions for use, although this is rarely realised. Despite removal of all clinically significant bias, the uncertainty of that correction (ubias) remains and is a source to be considered in the ISO/TS 20914:2019 framework. Absence of ubias data may have significant implications. Local ongoing quantification of bias is routinely achieved using certified reference material studies, external quality assessment (EQA) and internal quality control (IQC) peer review.