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Stud Health Technol Inform. 2019 Aug 21;264:724-728. doi: 10.3233/SHTI190318.

Implementation of Clinical Decision Support Services to Detect Potential Drug-Drug Interaction Using Clinical Quality Language.

Author information

1
Informatik 5, RWTH Aachen University, Aachen, Germany.
2
Department of Biomedical Informatics, University of Utah, Salt Lake City, Utah, USA.
3
Fraunhofer FIT, Sankt Augustin, Germany.
4
College of Pharmacy, University of Arizona, Tucson, Arizona, USA.
5
Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.

Abstract

Potential drug-drug interactions (PDDI) rules are currently represented without any common standard making them difficult to update, maintain, and exchange. The PDDI minimum information model developed by the Semantic Web in the Healthcare and Life Sciences Community Group describes PDDI knowledge in an actionable format. In this paper, we report implementation and evaluation of CDS Services which represent PDDI knowledge with Clinical Quality Language (CQL). The suggested solution is based on emerging standards including CDS Hooks, FHIR, and CQL. Two use cases are selected, implemented with CQL rules and tested at the Connectathon held at the 32nd Annual Plenary & Working Group Meeting of HL7.

KEYWORDS:

Clinical decision support systems; Electronic health records; Potential Drug-Drug Interaction

PMID:
31438019
DOI:
10.3233/SHTI190318
[Indexed for MEDLINE]

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