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Reducing the Toxicity Risk in Antibiotic Prescriptions by Combining Ontologies with a Multiple Criteria Decision Model.
- Source :
-
AMIA ... Annual Symposium proceedings. AMIA Symposium [AMIA Annu Symp Proc] 2018 Apr 16; Vol. 2017, pp. 1625-1634. Date of Electronic Publication: 2018 Apr 16 (Print Publication: 2017). - Publication Year :
- 2018
-
Abstract
- We consider the risk of adverse drug events caused by antibiotic prescriptions. Antibiotics are the second most common cause of drug related adverse events and one of the most common classes of drugs associated with medical malpractice claims. To cope with this serious issue, physicians rely on guidelines, especially in the context of hospital prescriptions. Unfortunately such guidelines do not offer sufficient support to solve the problem of adverse events. To cope with these issues our work proposes a clinical decision support system based on expert medical knowledge, which combines semantic technologies with multiple criteria decision models. Our model links and assesses the adequacy of each treatment through the toxicity risk of side effects, in order to provide and explain to physicians a sorted list of possible antibiotics. We illustrate our approach through carefully selected case studies in collaboration with the EpiCURA Hospital Center in Belgium.
- Subjects :
- Anti-Bacterial Agents therapeutic use
Belgium
Biological Ontologies
Drug Prescriptions
Humans
Practice Guidelines as Topic
Anti-Bacterial Agents adverse effects
Decision Support Systems, Clinical
Decision Support Techniques
Drug Therapy, Computer-Assisted
Drug-Related Side Effects and Adverse Reactions prevention & control
Subjects
Details
- Language :
- English
- ISSN :
- 1942-597X
- Volume :
- 2017
- Database :
- MEDLINE
- Journal :
- AMIA ... Annual Symposium proceedings. AMIA Symposium
- Publication Type :
- Academic Journal
- Accession number :
- 29854233