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A Software Tool for Exploring the Relation between Diagnostic Accuracy and Measurement Uncertainty
Theodora Chatzimichail1, Aristides T Hatjimihail1
1Hellenic Complex Systems Laboratory, Kostis Palamas 21, 66131 Drama, Greece.
Diagnostics (Basel, Switzerland)
|August 23, 2020
Summary
This study introduces a tool to explore the relationship between diagnostic accuracy and measurement uncertainty in medical tests. It helps assess test performance, crucial for clinical decisions and lab quality management.
Area of Science:
- Medical Diagnostics
- Laboratory Medicine
- Biostatistics
Background:
- Diagnostic accuracy measures evaluate classification correctness in clinical research.
- Measurement uncertainty is critical for quality and risk management in laboratory medicine.
- The relationship between diagnostic accuracy and measurement uncertainty requires further investigation.
Purpose of the Study:
- To develop an exploratory tool for analyzing the link between diagnostic accuracy measures and measurement uncertainty.
- To provide a resource for understanding how measurement uncertainty impacts diagnostic test performance.
- To support informed clinical decision-making and laboratory quality management.
Main Methods:
- Developed a freely available interactive program for calculating, optimizing, plotting, and comparing diagnostic accuracy measures.
- Integrated the concept of measurement uncertainty into the analysis of diagnostic and screening tests.
- Applied the tool to a case study involving glucose measurements in diabetic and non-diabetic populations.
Main Results:
- The program allows for the assessment of diagnostic accuracy considering various factors like disease prevalence, measurand properties, and measurement uncertainty.
- Demonstrated the tool's utility in evaluating the risk associated with diagnostic tests.
- The case study illustrated the practical application of the tool in a real-world scenario.
Conclusions:
- The developed interactive program serves as a user-friendly educational and research tool.
- It facilitates a better understanding of the interplay between diagnostic accuracy and measurement uncertainty.
- The tool aids in improving medical decision-making and laboratory risk management.
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