Establishing standards: harmonising coding principles for a minimal cancer dataset in the OMOP Common Data Model

Area of Science:

• Oncology
• Health Informatics
• Data Standardization

Background:

• Clinical data analysis across networks faces challenges due to data heterogeneity.
• The Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) offers a standardized framework for clinical data.
• Standardization enhances analytical power and research robustness in multi-center studies.

Purpose of the Study:

• To develop a framework for capturing specific oncology information within the OMOP CDM.
• To facilitate network-level comparisons and data combination for the Digital Oncology Network for Europe (DigiONE).
• To address the challenges of data heterogeneity in European oncology research.

Main Methods:

• The Minimal Essential Description of Cancer (MEDOC) framework was developed through iterative, community-driven processes.
• Deep-dive sessions were conducted to align source data with the MEDOC structure.
• MEDOC was utilized in pilot studies within the DigiONE network.

Main Results:

• The initial MEDOC version has been applied to two DigiONE observational cancer studies, with two more in progress.
• Training resources and an implementation guide for MEDOC have been developed.
• Challenges were identified in aligning data granularity for diagnosis date, metastasis location, and tumor classification.

Conclusions:

• The MEDOC framework demonstrates utility in research applications and will be continuously developed.
• Alignment with the OMOP CDM is timely, supporting European initiatives for health data harmonization.
• Further development will incorporate learnings from participating centers and advancements in oncology.