MU Reports

All quantitative measurements have inherent variation1.  Laboratories accredited to ISO 15189 must assess the level of uncertainty of their test results. The standard states “The laboratory shall determine the uncertainty of results, where relevant and possible. Uncertainty components which are of importance shall be taken into account.” 2. Guidance to the application of uncertainty of measurement (MU) is available from NRL1, 2, 3, 4.

Reporting MU 

The NRL has developed a system for estimating and reporting MU for quantitative assays based on a comparison of your laboratory’s QC results with those reported by other laboratories using the same QC sample/assay combination (peer group).The methodology for comparing MU is published and scientifically validated. The MU estimation accounts for the assay’s imprecision (random error) and bias (systematic error).  The imprecision is measured by calculating the standard deviation (SD) of the QC sample results over a defined period of time. The bias, expressed as a SD, is calculated by comparing the mean of the QC sample results with a weighted mean of all the QC sample results of the peer group. The imprecision and bias are combined to obtain a combined standard uncertainty.  This is multiplied by a factor of 2 to obtain an expanded uncertainty, which is the 95% confidence interval of the measurement.

To fulfil your regulatory requirements with ease, you can access free annual MU reports specific for your laboratory by downloading the order forms below:

​Download: 2019 NAT MU Order Form

Download: 2019 Serology MU Order Form

Download: How to Read MU Reports

References

  1. White GH, I Farrance. 2004. Uncertainty of measurement in quantitative medical testing - a laboratory implementation guide. Clin Biochem Rev: 25:S1-S24.

  2. International Standards Organization. Medical laboratories – Particular requirements for quality and competence, ISO/IEC 15189.2007: ISO, Geneva.

  3. Dimech W. et al. 2005. A proposed approach to estimating uncertainty of measurement in serological assays. Aust J Med Sci: 26: 58-64.

  4. Dimech W. et al. 2006. Calculating uncertainty of measurement for serology assays by use of precision and bias. Clin Chem: 52: 526-529.

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