Deriving proper measurement uncertainty from Internal Quality Control data: An impossible mission?

Ferruccio Ceriotti

Research output: Contribution to journalArticle

Abstract

Measurement uncertainty (MU) is a “non-negative parameter characterizing the dispersion of the quantity values being attributed to a measurand, based on the information used”. In the clinical laboratory the most convenient way to calculate MU is the “top down” approach based on the use of Internal Quality Control data. As indicated in the definition, MU depends on the information used for its calculation and so different estimates of MU can be obtained. The most problematic aspect is how to deal with bias. In fact bias is difficult to detect and quantify and it should be corrected including only the uncertainty derived from this correction. Several approaches to calculate MU starting from Internal Quality Control data are presented. The minimum requirement is to use only the intermediate precision data, provided to include 6 months of results obtained with a commutable quality control material at a concentration close to the clinical decision limit. This approach is the minimal requirement and it is convenient for all those measurands that are especially used for monitoring or where a reference measurement system does not exist and so a reference for calculating the bias is lacking. Other formulas including the uncertainty of the value of the calibrator, including the bias from a commutable certified reference material or from a material specifically prepared for trueness verification, including the bias derived from External Quality Assessment schemes or from historical mean of the laboratory are presented and commented. MU is an important parameter, but a single, agreed upon way to calculate it in a clinical laboratory is not yet available.

Original languageEnglish
Pages (from-to)37-40
JournalClinical Biochemistry
Volume57
DOIs
Publication statusPublished - 2018

Keywords

  • Bias
  • Imprecision
  • Internal Quality Control
  • Measurement uncertainty

ASJC Scopus subject areas

  • Clinical Biochemistry

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