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Uncertainty in Measurement and Total Error: Tools for Coping with Diagnostic Uncertainty
1Department of Clinical Chemistry and Department of Clinical and Experimental Medicine, Linköping University, SE-581 85 Linköping, Sweden.
Clinics in Laboratory Medicine
|February 4, 2017
Summary
Laboratory medicine uses error and uncertainty methods to reduce diagnostic uncertainty. New metrology standards will integrate both approaches, improving laboratory collaboration and diagnostic accuracy.
Area of Science:
- Clinical Laboratory Science
- Metrology
- Biostatistics
Background:
- Laboratory medicine aims to reduce diagnostic uncertainty but faces challenges from various influencing factors.
- Historically, error and uncertainty methods have been viewed as incompatible in laboratory settings.
- Evolving metrology standards are poised to bridge this gap.
Purpose of the Study:
- To explore the integration of error and uncertainty methods in laboratory medicine.
- To highlight the theoretical advantages of Bayesian statistics and the law of propagation of uncertainty in diagnostics.
- To advocate for the recognition of both error and uncertainty methods for calculating diagnostic uncertainty.
Main Methods:
- Review of current metrology guidelines, including the Guide to the Expression of Uncertainty in Measurement (GUM) and the International Vocabulary of Metrology (VIM).
- Theoretical comparison of frequentist and Bayesian statistical approaches in the context of diagnostic medicine.
- Analysis of the compatibility and application of error and uncertainty methodologies.
Main Results:
- Upcoming metrology standards will incorporate both error and uncertainty quantification methods.
- Bayesian statistics and the law of propagation of uncertainty offer theoretical advantages for diagnostic uncertainty.
- Frequentist statistics remain widely practiced despite theoretical limitations in this context.
Conclusions:
- Integrating error and uncertainty methods will enhance collaboration between metrology and diagnostic laboratories.
- Both error and uncertainty quantification methods should be considered legitimate for determining diagnostic uncertainty.
- Adoption of advanced statistical methods like Bayesian approaches could improve diagnostic accuracy in laboratory medicine.
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