From Fragmentation to Integration: Challenges and Solutions for Record Linkage in OMOP CDM

Secondary use of data for research purposes is becoming increasingly important to improve medical research and thus patient care. In this context, linking different data sources provides a unique opportunity to gain a comprehensive overview of a patient's medical history. The interoperability of different data sets can be ensured by using the standardized data model OMOP. However, the record linkage of separate OMOP databases is an open problem. In this paper, we present an approach to link disparate datasets in OMOP using German clinical data and claims data as an example. We highlight three challenges and propose solutions for them to ensure accurate and efficient data integration.

Authors

Institutions

Publication Details

Journal
Studies in health technology and informatics
Published
2025-05-15
DOI
https://doi.org/10.3233/shti250619
Primary Topic
Data Quality and Management
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

From Fragmentation to Integration: Challenges and Solutions for Record Linkage in OMOP CDM

Mirko Gruhl, Michéle Zoch, Yuan Peng, Elisa Henke et al.
Studies in health technology and informatics
Data Quality and Management
article

From Fragmentation to Integration: Challenges and Solutions for Record Linkage in OMOP CDM

Mirko Gruhl, Michéle Zoch, Yuan Peng, Elisa Henke, Martin Sedlmayr
article en

Abstract

Secondary use of data for research purposes is becoming increasingly important to improve medical research and thus patient care. In this context, linking different data sources provides a unique opportunity to gain a comprehensive overview of a patient's medical history. The interoperability of different data sets can be ensured by using the standardized data model OMOP. However, the record linkage of separate OMOP databases is an open problem. In this paper, we present an approach to link disparate datasets in OMOP using German clinical data and claims data as an example. We highlight three challenges and propose solutions for them to ensure accurate and efficient data integration.

Studies in health technology and informaticsVol. 327
University Hospital Carl Gustav Carus (DE)
Gemeinsame Bundesausschuss
Openalex Percentile: Top 72%
Data Quality and Management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.