HECON: Health Condition Evolution Ontology

Morales Tirado, Alba; Daga, Enrico and Motta, Enrico (2022). HECON: Health Condition Evolution Ontology. In: Proceedings of 5th Workshop on Semantic Web solutions for large-scale biomedical data analytics co-event with The ESWC 2022: Extended Semantic Web Conference.

Abstract

Health records contain extensive information, including conditions, test results, procedures, and appointments. These data reveal past medical observations that could allow drawing a picture of the current health state of a patient. Widely adopted clinical terminology taxonomies, such as SNOMED CT and the FHIR standard, facilitate the processing and exchange of electronic health records. However, despite these efforts, the task of estimating whether a particular condition is affecting a patient's health at a certain point in time is not supported yet.This paper introduces HECON, the Health Condition Evolution Ontology that represents the evolution of health conditions over time. This representation enables reasoning on possible ongoing health issues derivable from patients' health records for the benefit of intelligent systems in the emergency domain. We describe the process for building the ontology and the application of HECON in a fire emergency scenario. We design the ontology following established ontology engineering practices, including Competency Questions and ontology reuse. Furthermore, we construct a Knowledge Graph from a database of extracted Health Evolution Statements and use it to validate the consistency and requirements of the HECON Ontology.

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