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Enhancing real world data interoperability in healthcare: A methodological approach to laboratory unit harmonization
Aída Muñoz Monjas1, David Rubio Ruiz2, David Pérez Del Rey1
1Biomedical Informatics Group, Universidad Politécnica de Madrid, Madrid, Spain.
Objective:
The primary aim of this study is to address the critical issue of non-standardized units in clinical laboratory data, which poses significant challenges to data interoperability and secondary usage. Despite UCUM (Unified Code for Units of Measure) offering a unique representation for laboratory test units, nearly 60% of laboratory codes in healthcare organizations use non-standard units. We sought to design, implement and test a methodology for the harmonization of units to the UCUM standards across a large research network.
Methods:
Using dimensional analysis and a curated equivalence table, the proposed methodology harmonizes disparate units to UCUM standards. The process focused on identifying and converting non-UCUM conforming units, with the goal of enhancing data comparability and interoperability across different systems.
Results:
The methodology successfully achieved over 90% coverage of laboratory data with units in UCUM standards across the TriNetX research network, a significant improvement from baseline measurements. This enhancement in unit standardization directly contributed to increased interoperability of laboratory data, facilitating more reliable and comparable data analysis across various healthcare organizations.
Conclusion:
The successful harmonization of laboratory data units to UCUM standards represents a significant advancement in the field of biomedical informatics. By demonstrating a practical and effective approach to overcoming the challenges of non-standardized units, our study contributes to the broader efforts to improve data interoperability and usability for secondary purposes such as research and observational studies. Future work will focus on addressing the remaining gaps in unit standardization and exploring the implications of this methodology on clinical outcomes and research capabilities.
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