Harmonizing Electronic Health Records to the OMOP Common Data Model: A Case Study on Surgical Complications

Area of Science:

• Health Informatics
• Clinical Data Management
• Biomedical Research Data Standards

Background:

• Electronic Health Records (EHR) contain valuable clinical information but often exist in disparate formats.
• Standardization is crucial for enabling interoperability and large-scale analysis of healthcare data.
• The Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) provides a standardized structure for observational health data.

Purpose of the Study:

• To detail the process of transforming Asunción Klinika's EHR data into the OMOP CDM version 5.4.
• To harmonize diverse clinical data, including surgical records, into a standardized format.
• To facilitate large-scale research, comparative analysis, and the development of predictive models.

Main Methods:

• Extraction of Asunción Klinika's EHR data, encompassing patient demographics, diagnoses, procedures, prescribed medications, and laboratory tests.
• Structural and conceptual mapping of the source data to the OMOP CDM 5.4 standard.
• Application of standardized vocabularies to ensure data consistency and compatibility with global research networks.

Main Results:

• A harmonized dataset conforming to the OMOP CDM 5.4 standard was successfully created.
• The transformed data demonstrated high compatibility with key OMOP tables.
• The standardized dataset is suitable for integration into global research networks and for developing predictive models.

Conclusions:

• The transformation of EHR data to the OMOP CDM 5.4 standard is feasible and beneficial for healthcare research.
• Standardized data facilitates comparative effectiveness research and the development of data-driven decision support systems.
• This work lays the groundwork for advancing predictive analytics in surgical complications and clinical outcomes.