PARS, a system combining semantic technologies with multiple criteria decision aiding for supporting antibiotic prescriptions

Publication date: Available online 14 October 2019Source: Journal of Biomedical InformaticsAuthor(s): Souhir Ben Souissi, Mourad Abed, Lahcen El Hiki, Philippe Fortemps, Marc PirlotAbstractObjectiveMotivated by the well documented worldwide spread of adverse drug events, as well as the increased danger of antibiotic resistance (caused mainly by inappropriate prescribing and overuse), we propose a novel recommendation system for antibiotic prescription (PARS).MethodOur approach is based on the combination of semantic technologies with MCDA (Multiple Criteria Decision Aiding) that allowed us to build a two level decision support model. Given a specific domain, the approach assesses the adequacy of an alternative/action (prescription of antibiotic) for a specific subject (patient) with an issue (bacterial infection) in a given context (medical). The goal of the first level of the decision support model is to select the set of alternatives which have the potential to be suitable. Then the second level sorts the alternatives into categories according to their adequacy using an MCDA sorting method (MR–Sort with Veto) and a structured set of description logic queries.ResultsWe applied this approach in the domain of antibiotic prescriptions, working closely with the EpiCura Hospital Center (BE). Its performance was compared to the EpiCura recommendation guidelines which are currently in use. The results showed that the proposed system is more consistent in its recommendations when ...
Source: Journal of Biomedical Informatics - Category: Information Technology Source Type: research