The PrescIT Knowledge Graph: Supporting ePrescription to Prevent Adverse Drug Reactions

Stud Health Technol Inform. 2023 May 18:302:551-555. doi: 10.3233/SHTI230203.

Abstract

Adverse Drug Reactions (ADRs) are an important public health issue as they can impose significant health and monetary burdens. This paper presents the engineering and use case of a Knowledge Graph, supporting the prevention of ADRs as part of a Clinical Decision Support System (CDSS) developed in the context of the PrescIT project. The presented PrescIT Knowledge Graph is built upon Semantic Web technologies namely the Resource Description Framework (RDF), and integrates widely relevant data sources and ontologies, i.e., DrugBank, SemMedDB, OpenPVSignal Knowledge Graph and DINTO, resulting in a lightweight and self-contained data source for evidence-based ADRs identification.

Keywords: Adverse Drug Reactions; Clinical Decision Support Systems; Drug Safety; ePrescription.

MeSH terms

  • Adverse Drug Reaction Reporting Systems
  • Decision Support Systems, Clinical*
  • Drug-Related Side Effects and Adverse Reactions* / prevention & control
  • Humans
  • Pattern Recognition, Automated
  • Semantics