title: Adverse drug event prevention in neonatal care: a rule-based approach.
abstract: Adverse drug events (ADE) in a neonatal unit can be of great importance due to the underlying nature and the special characteristics of the patients. This paper presents our work on the development of a knowledge base (KB) for supporting the identification and prevention of ADEs. First, a literature review was conducted to identify ADEs observed through the use of the most commonly-used drugs in a specific neonatal unit. Then, the acquired knowledge was encoded according to an ontological data model developed for the representation of the specific facts for the neonatal unit. Finally, a rule-based prototype consisting of 164 rules was implemented in order to represent and simulate the inference procedure about preventing ADEs.
authors.affiliation: Aristotle University, Thessaloniki, Greece. klazou@med.auth.gr
authors.forename: Katerina
authors.initials: K
authors.lastname: Lazou
authors.forename: Maria
authors.initials: M
authors.lastname: Farini
authors.forename: Vassilis
authors.initials: V
authors.lastname: Koutkias
authors.forename: Vassiliki
authors.initials: V
authors.lastname: Drossou
authors.forename: Nicos
authors.initials: N
authors.lastname: Maglaveras
authors.forename: Nick
authors.initials: N
authors.lastname: Bassiliades
mesh_terms: D000465:Algorithms; D003628:Database Management Systems; D062313:Databases, Pharmaceutical; D020000:Decision Support Systems, Clinical; D064420:Drug-Related Side Effects and Adverse Reactions / Q000517:prevention & control*; D006801:Humans; D007231:Infant, Newborn; D015931:Intensive Care, Neonatal / Q000379:methods*; D014584:User-Computer Interface