Modelling system level health information exchange: an ontological approach.

Area of Science:

• Health Informatics
• Information Science
• Systems Engineering

Background:

• Improving health information flow between providers is crucial but hindered by a lack of data on digital information exchange.
• Current systems lack inventories of system-level digital information flows and measures of inter-organizational electronic information exchange (HIE).

Purpose of the Study:

• To formalize a model for decomposing inter-organizational electronic health information flow.
• To develop a method for measuring health information exchange (HIE) using a regional health system dataset.
• To identify providers with low and high HIE for planning and data quality monitoring.

Main Methods:

• Utilized Protégé 4, an open-source OWL Web ontology editor, to create a formal model.
• Decomposed inter-organizational electronic health information flow into concepts like diversity, breadth, volume, structure, standardization, and connectivity.
• Employed self-reported data from a regional health system to measure HIE.

Main Results:

• Developed an ontology that models inter-organizational electronic health information flow.
• Successfully measured HIE using self-reported data.
• Identified providers with varying levels of HIE, providing actionable insights for planners.
• Established a related database for monitoring data quality.

Conclusions:

• The formalized ontology provides a robust framework for understanding and measuring health information exchange.
• The developed model and measurement approach are valuable tools for health system planners and data quality assessment.
• This work addresses a critical gap in understanding digital information flow within health systems.