Integrating a conceptual consent permission model from the informed consent ontology for software application...

Area of Science:

• Health Informatics
• Ontology Engineering
• Computational Law

Background:

• Informed consent documents often contain implicit information.
• Existing methods struggle to computationally represent and deduce permission details from consent forms.
• Integrating ontologies can bridge this gap in health information technology.

Purpose of the Study:

• To develop and demonstrate a software implementation for integrating the Informed Consent Ontology (ICO).
• To express implicit descriptions and conceptual permissions within the informed consent lifecycle.
• To elucidate incomplete information in consent documents using a computational model.

Main Methods:

• Developed a simulated process for software implementation.
• Utilized the Semantic Web Rule Language (SWRL) to describe permissions.
• Applied the Informed Consent Ontology (ICO) to "All of Us" informed consent documents.

Main Results:

• Successfully demonstrated a computational model for deducing information from ICO.
• Showcased how the model can elucidate incomplete information in consent documents.
• Validated the approach using real-world informed consent data.

Conclusions:

• The developed computational approach facilitates the integration of ICO for better data interpretation.
• This method enhances health information technology by providing a clearer understanding of permissions.
• Future work includes applying this approach to specific domains like vaccine informed consent.