Expanding the OMOP common data model to support extracorporeal life support research

Area of Science:

• Biomedical Informatics
• Critical Care Medicine
• Data Standards

Background:

• Standardized data collection for extracorporeal life support (ECLS) is lacking despite electronic health record availability.
• Existing data models may not adequately capture high-resolution ECLS data.
• Interoperability is crucial for multi-center research and quality improvement initiatives in ECLS.

Purpose of the Study:

• To assess the Observational Medical Outcomes Partnership Common Data Model (OMOP CDM) for ECLS data interoperability.
• To develop a custom data model expansion if the OMOP CDM proved insufficient for ECLS data.
• To create an open-source, standardized data collection method for ECLS.

Main Methods:

• Qualitative analysis of the OMOP CDM by expert consensus for ECLS data capture capabilities.
• Comparison of database entries required by OMOP CDM versus a custom data model expansion for ECLS.
• Development and implementation of a custom ECLS Common Data Model (ECLS CDM) with novel concepts.

Main Results:

• The OMOP CDM exhibited limitations in capturing ECLS circuit-derived data due to a paucity of suitable concepts.
• A custom ECLS CDM was developed, incorporating ECLS-specific tables and novel concepts.
• The ECLS CDM reduced the number of database entries for ECLS use cases by up to 90%.
• The ECLS CDM was released as an open-source project.

Conclusions:

• The ECLS CDM offers an improved, interoperable data model for ECLS data.
• This model enhances data quality, facilitating multi-center research and quality initiatives.
• The open-source nature promotes wider adoption and collaborative improvement.