Secondary use of external quality assessment data - estimating inter-assay variation in LOINC-coded datasets

Area of Science:

• Laboratory Medicine
• Health Informatics
• Metrology

Background:

• The secondary scientific use of routine laboratory data relies on semantic standards like LOINC, especially for the European Health Data Space (EHDS).
• Current semantic standardization using LOINC overlooks metrological aspects, particularly analytical limitations and result variability across assays, leading to statistical uncertainty in research data.
• Incomplete harmonization of laboratory data hinders accurate quantitative conclusions, such as establishing diagnostic thresholds.

Purpose of the Study:

• To propose a novel approach for enhancing the metrological quality of semantic standards for laboratory data.
• To introduce the use of external quality assessment (EQA) data for annotating LOINC codes with uncertainty metrics.
• To support the secondary scientific use of routine diagnostic data by improving data harmonization and reliability.

Main Methods:

• Leveraging the global data pool from external quality assessment (EQA) programs.
• Developing and demonstrating a proof-of-concept analysis for annotating LOINC codes with uncertainty metrics derived from EQA data.
• Exploring various design options for implementing the proposed annotation strategy.

Main Results:

• Demonstrated the feasibility of using EQA data to assign uncertainty metrics to LOINC codes.
• Showcased a method for improving the harmonization of laboratory data used in research.
• Highlighted the potential for advancing precision research through enhanced data quality.

Conclusions:

• Annotating LOINC codes with uncertainty metrics derived from EQA data is feasible and beneficial for secondary scientific data use.
• This approach addresses critical metrological gaps in current semantic standardization, reducing statistical uncertainty in research.
• Collaboration between EQA providers, coding institutions, scientific societies, and the IVD industry can advance precision research by implementing this concept.