Harmonisation of German Health Care Data Using the OMOP Common Data Model - A Practice Report

Area of Science:

• Health Informatics
• Clinical Data Management
• Real-World Data Analysis

Background:

• Data harmonization is crucial for large-scale healthcare data analysis and real-world evidence generation.
• The Observational Medical Outcomes Partnership (OMOP) common data model provides a standardized framework for data harmonization.
• Hannover Medical School (MHH) established an Enterprise Clinical Research Data Warehouse (ECRDW) to consolidate clinical data.

Purpose of the Study:

• To implement the OMOP common data model on the MHH's ECRDW data source.
• To identify and address challenges in mapping German healthcare terminologies to the OMOP standard.
• To facilitate standardized real-world data analysis at MHH.

Main Methods:

• Implementation of the OMOP common data model within the MHH ECRDW infrastructure.
• Analysis of German healthcare terminologies and their mapping to OMOP standard concepts.
• Development of strategies to overcome terminology mapping challenges.

Main Results:

• Successful initial implementation of the OMOP common data model at MHH.
• Identification of specific challenges related to German healthcare terminologies (e.g., ICD-10-GM, OPS).
• Demonstration of the feasibility and complexities of harmonizing local data to a global standard.

Conclusions:

• The OMOP common data model can be implemented on existing clinical data warehouses.
• Mapping local terminologies to OMOP is a significant but manageable challenge.
• Standardized data through OMOP facilitates robust real-world data research and evidence generation.