Biomedical Informatics Group, Universidad Politécnica de Madrid, Madrid, Spain.
Biomedical Informatics Group, Universidad Politécnica de Madrid, Madrid, Spain; TriNetX, LLC, Cambridge, MA, USA.
Int J Med Inform. 2025 Jan;193:105665. doi: 10.1016/j.ijmedinf.2024.105665. Epub 2024 Oct 28.
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.
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.
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.
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.
本研究的主要目的是解决临床实验室数据中单位不标准化的关键问题，这对数据互操作性和二次使用带来了重大挑战。尽管 UCUM（统一度量单位代码）为实验室测试单位提供了独特的表示方法，但近 60%的医疗机构实验室代码使用非标准单位。我们旨在设计、实施和测试一种在大型研究网络中使单位与 UCUM 标准协调一致的方法。
使用量纲分析和精心制作的等价表，提出的方法将不同的单位协调到 UCUM 标准。该过程侧重于识别和转换不符合 UCUM 的单位，目标是增强不同系统之间的数据可比性和互操作性。
该方法成功地实现了 TriNetX 研究网络中超过 90%的实验室数据单位符合 UCUM 标准，与基线测量相比有了显著提高。这种单位标准化的增强直接促进了实验室数据的互操作性，使得在各种医疗机构中进行更可靠和可比的数据分析成为可能。
成功地将实验室数据单位协调到 UCUM 标准代表了生物医学信息学领域的重大进展。通过展示一种实用且有效的方法来克服非标准化单位的挑战，我们的研究为提高数据互操作性和可用于二次目的（如研究和观察性研究）的可用性做出了贡献。未来的工作将集中解决单位标准化的剩余差距，并探讨该方法对临床结果和研究能力的影响。
