ConsultGLP

Top down approaches of Measurement Uncertainty

With regards to the subject of measurement uncertainty (MU) evaluation for chemical, microbiological and medical testing laboratories, I have been strongly advocating the holistic “top-down”  approaches which consider the test method performance as a whole, making use of the routine quality control (QC) and method validation data, instead of the time consuming and clumsy step-by-step ISO GUM “bottom-up” approach which study the uncertainty contributions in each and every step of the laboratory analysis before summing up for the expanded uncertainty of the method.

Indeed, the top-down MU approach evaluates the overall variability of the analytical process in question.

Your ISO 17025 accredited laboratory should have a robust laboratory quality management control system in place, and carrying out regular laboratory control check sample analyses on each and every test method. This is your routine practice to ensure the reliability and accuracy of the test results reported to the end users.

Over time, you would have collected a wealth of such QC information data on the performance of all your test methods. They are sitting around in your LIMS or other computer system.  Furthermore, you would have carried out your method validation or verification in your laboratory practice.  What you really need to do is to re-organize all these QC data to your benefits with the help of a PC or laptop computer.

Of course, the top-down approaches like GUM have certain limitations, such as the possible mismatching of your sample matrices against the laboratory reference check samples, or relatively unstable reference materials. But these issues have been addressed by various top-down methods with an addition of the uncertainty contribution in actual sample analysis.

I list below some good references of the top-down approaches which are widely practiced by our US and EU peers. In Asia, I reckon China CNAS is probably the only national accreditation body leading the local testing industry in adopting these approaches. The other national accreditation bodies seem to be slow in promoting this noble subject for whatever reason.

• ISO 21748:2010 Guidance for the use of repeatability, reproducibility and trueness estimates in measurement uncertainty estimation
•  ISO 11352:2012 Water quality — Estimation of measurement uncertainty based on validation and quality control data
•  ISO 11095:1996 (2012) Linear calibration using reference materials
•  ISO 19036:2006 Microbiology of food and animal feeding stuffs — Guidelines for the estimation of measurement uncertainty for quantitative determinations Amd1:2009: Measurement uncertainty for low counts
•  BS 8496:2007 Water quality. Enumeration of micro-organisms in water samples

• ASTM D6299-08 Applying statistical quality assurance and control charting techniques to evaluate analytical measurement system performance
• ASTM D2554-07 Estimating and monitoring the uncertainty of test results of a test method in a single laboratory using a control sample program
•  ASTM E2093-05 Optimizing controlling and reporting test method uncertainty from multiple workstations in the same laboratory organization
• EuroLab Technical Report No. 1/2006 Guide to the Evaluation of Measurement Uncertainty for Quantitative Test Results
•  NORDIC Technical Report TR 537 Edition 3.1 Handbook for Calculation of Measurement Uncertainty in Environmental Laboratories
• A2LA G108 – Guidelines for Estimating Uncertainty for Microbiological Counting Methods
• CNAS-GL34:2013 基于质控数据环境检测测量不确定度评定指南 Guidance for measurement uncertainty evaluation based on quality control data in environmental testing