Converting Health Level 7 Clinical Document Architecture (CDA) documents to Observational Medical Outcomes...

Area of Science:

• Health Informatics
• Data Standardization
• Clinical Data Transformation

Background:

• Health Level 7 (HL7) Clinical Document Architecture (CDA) is a widely used standard for clinical documents.
• The Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) is crucial for harmonizing observational health data.
• Transforming HL7 CDA documents to OMOP CDM presents significant Extract, Transform, Load (ETL) challenges.

Purpose of the Study:

• To develop a novel methodology for transforming HL7 CDA documents into the OMOP CDM.
• To improve the efficiency and accuracy of the ETL design process using HL7 CDA Template definitions and the CDA Refined Message Information Model (CDA R-MIM).

Main Methods:

• Utilized HL7 CDA Templates for defining structural and semantic mappings.
• Employed the CDA Refined Message Information Model (CDA R-MIM) for semantic alignment with OMOP CDM.
• Developed a tool, CDA Rabbit, to generate project files from HL7 CDA Template definitions for integration into the OMOP toolchain.

Main Results:

• Successfully mapped 430 anonymized CDA documents from 13 Austrian national EHR System (ELGA) CDA Templates to 10 OMOP CDM tables.
• Achieved a 99% pass rate in data quality assessment using OMOP's DataQualityDashboard.
• Demonstrated a robust and accurate data transformation process.

Conclusions:

• Presented a novel framework for HL7 CDA to OMOP CDM transformation using template definitions and CDA R-MIM.
• The methodology enhances semantic interoperability, mapping reusability, and ETL design efficiency.
• The approach supports the secondary use of health data for research by adhering to standardized data models.