CDE-Mapper: Using retrieval-augmented language models for linking clinical data elements to controlled vocabularies

Computers in Biology and Medicine, vol. 196, pp. 110745

Abstract

The standardization of clinical data elements (CDEs) aims to ensure consistent and comprehensive patient information across various healthcare systems. Existing methods often falter when standardizing CDEs of varying representation and complex structure, impeding data integration and interoperability in clinical research. This paper presents CDE-Mapper, a framework that combines a retrieval-augmented generation strategy with large language models to automate the alignment of CDEs with controlled vocabularies. Our modular approach features query decomposition to manage varying levels of CDEs complexity, integrates expert-defined rules within prompt engineering, and employs in-context learning alongside multiple retriever components to resolve terminological ambiguities. In addition, we propose a knowledge reservoir validated by a human-in-loop approach, achieving accurate concept linking for future applications while minimizing computational costs. For four diverse datasets, CDE-Mapper achieved an average of 7.2% higher accuracy improvement compared to baseline methods. This work highlights the potential of advanced language models in improving data harmonization and significantly advancing capabilities in clinical decision support systems and research.

Authors 5

1. Komal Gilani corresponding

   Maastricht University

   Affiliation as printed

   Institute of Data Science, Maastricht University, Maastricht, Netherlands. Electronic address: komal.gilani@maastrichtuniversity.nl

2. Marlo Verket Aachen Department of Internal Medicine I (Cardiology)

   Universitätsklinikum Aachen · RWTH Aachen University

   Affiliation as printed

   Department of Internal Medicine I, University Hospital RWTH Aachen, Aachen, Germany. Electronic address: mverket@ukaachen.de

3. Michel J. Dumontier

   Maastricht University

   Affiliation as printed

   Institute of Data Science, Maastricht University, Maastricht, Netherlands. Electronic address: michel.dumontier@maastrichtuniversity.nl

4. Hans‐Peter Brunner‐La Rocca

   Maastricht University

   Affiliation as printed

   Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Maastricht, Netherlands. Electronic address: hp.brunnerlarocca@mumc.nl

5. Visara Urovi

   Maastricht University

   Affiliation as printed

   Institute of Data Science, Maastricht University, Maastricht, Netherlands. Electronic address: v.urovi@maastrichtuniversity.nl