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Measurement uncertainty for practical use
Abdurrahman Coskun1, Elvar Theodorsson2, Wytze P Oosterhuis3
1EFLM Task and Finish Group on Practical Approach to Measurement Uncertainty, Milan, Italy; School of Medicine, Department of Medical Biochemistry, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey.
Summary
Clinical laboratories can simplify measurement uncertainty calculations by using a pragmatic approach. This method focuses on influential factors and commutable quality control materials for accurate patient test results.
Area of Science:
- Clinical Laboratory Science
- Measurement Science
Background:
- Accreditation standards (ISO/IEC 17025:2017, ISO 15189:2012) mandate measurement uncertainty calculations in clinical laboratories.
- Existing guidelines (CLSI EP29, Nordest 537, ISO 20914:2019) offer methods but are often perceived as too complex for routine application.
Purpose of the Study:
- To describe a pragmatic and utilitarian approach for calculating measurement uncertainty in clinical laboratories.
- To outline the advantages and disadvantages of this simplified method.
Main Methods:
- Focus on incorporating the most influential factors affecting patient test results into uncertainty calculations.
- Utilize results from analyzing the same internal quality control material (if commutable) or pooled/split patient samples.
- This approach is suitable for scenarios involving multiple laboratories or diverse measuring systems for the same measurand.
Main Results:
- The proposed approach aims to enhance the practical application of measurement uncertainty in high-workload clinical settings.
- It offers a more accessible method compared to complex, guideline-based calculations.
- The effectiveness and limitations of this utilitarian approach are discussed.
Conclusions:
- A pragmatic approach to measurement uncertainty calculation is feasible and beneficial for clinical laboratories.
- This method addresses the challenges posed by high workload and measurand heterogeneity.
- Accurate calculation of measurement uncertainty is crucial for reliable patient test results.
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