An evolutionary approach to realism-based adverse event representations.
BACKGROUND
Part of the ReMINE project involved the creation of an ontology enabling computer-assisted decision support for optimal adverse event management.


OBJECTIVE
The ontology was required to satisfy the following requirements: 1) to be able to account for the distinct and context-dependent ways in which authoritative sources define the term 'adverse event', 2) to allow the identification of relevant risks against patient safety (RAPS) on the basis of the disease history of a patient as documented in electronic health records, and 3) to be compatible with present and future ontologies developed under the Open Biomedical Ontology (OBO) Foundry framework.


METHODS
We used as feeder ontologies the Basic Formal Ontology, the Foundational Model of Anatomy, the Ontology for General Medical Science, the Information Artifact Ontology and the Ontology of Mental Health. We further used relations defined according to the pattern set forth in the OBO Relation Ontology. In light of the intended use of the ontology for the representation of adverse events that have actually occurred and therefore are registered in a database, we also applied the principles of referent tracking.


RESULTS
We merged the upper portions of the mentioned feeder ontologies and introduced 22 additional representational units of which 13 are generally applicable in biomedicine and nine in the adverse event context. We provided for each representational unit a textual definition that can be translated into equivalent formal definitions.


CONCLUSIONS
The resulting ontology satisfies all of the requirements set forth. Merging the feeder ontologies, although all designed under the OBO Foundry principles, brought new insight into what the representational units of such ontologies actually denote.
New York State Center of Excellence in Bioinformatics & Life Sciences, 701 Ellicott Street, Buffalo, NY 14203, USA. ceusters@buffalo.edu
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W
Ceusters
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Capolupo
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G
de Moor
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Devlies
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B
Smith
D003658:Decision Making, Computer-Assisted; D005062:European Union; D019300:Medical Errors / Q000517:prevention & control*; D012308:Risk Management / Q000458:organization & administration*; D017751:Safety Management / Q000458:organization & administration*