Related Experiment Video
Updated: May 21, 2025

Split Point Analysis and Uncertainty Quantification of Thermal-Optical Organic/Elemental Carbon Measurements
Published on: September 7, 2019
Evaluation of Measurement Uncertainty in Clinical Chemistry and its Comparison With Analytical Performance
Nishtha Wadhwa1, Kiran Bhat1, Mansi Kalsi1
1Biochemistry, Himalayan Institute of Medical Sciences, Dehradun, IND.
Abstract:
Introduction To evaluate the variability in values reported by a clinical laboratory, it is important to assess the measurement uncertainty (MU). Furthermore, verifying that the estimated MU aligns with relevant analytical performance specifications (APS) is essential. Previous research has indicated variability in how laboratories estimate and apply MU, with some failing to meet APS, potentially affecting clinical decision-making. Additionally, factors such as differences in instrumentation, reagent quality, and calibration protocols may contribute to regional variations in MU, emphasizing the need for a systematic evaluation. This study aimed to determine the MU of 31 measurands and compare it with the APS available in the literature to assess whether our measuring systems can meet these APS. Methods The study was conducted in the Clinical Biochemistry Laboratory of the Himalayan Institute of Medical Sciences, Dehradun, India. The measuring systems in our laboratory are Beckman Coulter DxC 700 AU (Beckman Coulter, Inc., Brea, California, United States), Beckman Coulter UniCel DxI 800 (Beckman Coulter, Inc.,), and bioMérieux VIDAS (bioMérieux SA, Marcy-l'Étoile, France). The 'top-down' approach which uses internal quality control data and calibrator information was used for the estimation of MU. The formula used was: u result =√(u cal 2 + u Rw 2+ u bias 2). Objectively derived APS available in the literature were utilized to determine the allowable MU. Results A total of 24 measurands exhibited uncertainty estimates below the minimum APS limits. However, serum lactate dehydrogenase (LD), creatine kinase (CK), alkaline phosphatase (ALP), sodium, chloride, glucose, and ferritin showed MU higher than the minimum APS. The calibrator uncertainties (ucal) for ALP (4.7), LD (5.45), CK (11.06), and Ferritin (23.2) were significantly high, contributing to their elevated MU estimates. Additionally, the minimum APS for serum chloride (0.74) and sodium (0.40) were particularly stringent and could not be met. Conclusion The evaluation of MU provides objective insights into the quality of measurement systems and, its comparison, against set APS, supports the applicability of laboratory results in clinical decision-making. Failing to meet APS can lead to misdiagnosis, treatment errors, and patient safety risks. It may also hinder ISO 15189 accreditation and increase retesting costs.
Related Concept Videos
Uncertainty: Overview
Data Validation
Key parameters for method validation include:
Uncertainty in Measurement: Accuracy and Precision
Uncertainty in Measurement: Reading Instruments
Accuracy and Precision
Instrument Calibration
Analytical Balance Calibration
An analytical balance measures mass and requires regular calibration to...

