Using ontologies to integrate and share resuscitation data from diverse medical devices

Area of Science:

• Biomedical Informatics
• Health Services Research
• Emergency Medicine

Background:

• Outcome statistics in emergency medical systems (EMS) for resuscitation vary significantly, hindering comparative analysis and identification of improvement factors.
• Comparable data is essential for robust analysis and advancing resuscitation science.
• Current data formats are device-dependent, limiting interoperability and data aggregation.

Purpose of the Study:

• To propose a standardized method for data representation in resuscitation research.
• To demonstrate a technology capable of translating device-dependent data into this standard format.
• To facilitate the comparison and combination of data from diverse sources.

Main Methods:

• Development of a standardized ontology for defining and describing resuscitation therapy information (e.g., shock delivery, chest compressions, ventilation).
• Implementation of a technology to transform data from proprietary device formats into the standardized ontology.
• Utilizing rules and logic for data merging and combination to generate new insights.

Main Results:

• The proposed technology enables structured and standardized data capture and storage from various devices.
• Data transformation into the standardized format is feasible and efficient.
• The standardized format allows for data comparison and combination, irrespective of the original data source or structure.

Conclusions:

• The developed technology successfully captures and stores diverse device data in a standardized format.
• Data transformation, comparison, and combination are facilitated, overcoming original structural limitations.
• This approach supports improved analysis of resuscitation outcomes by ensuring data comparability across different EMS.