@inproceedings{Kra2014,
Author = {Krahn, Tobias; Eichelberg, Marco; Müller, Frerk; Gönül, Suat; Laleci Erturkmen, Gokce B.; Sinaci, A. Anil; Appelrath, Hans-Jürgen},
Title = {Adverse Drug Event Notification on a Semantic Interoperability Framework},

Year = {2014},
Pages = {111-115},
Publisher = {IOS Press},
Edition = {205},
Booktitle = {Stud Health Technol Inform},
type = {inproceedings},
note = {Adverse drug events (ADEs) are common, costly and one of the most important issues in contemporary pharmacotherapy. Current drug safety surveillance methods are largely based on spontaneous reports. However, this is known to be rather ineffective. There i},
Abstract = {Adverse drug events (ADEs) are common, costly and one of the most important issues in contemporary pharmacotherapy. Current drug safety surveillance methods are largely based on spontaneous reports. However, this is known to be rather ineffective. There is a lack of automated systems checking potential ADEs on routine data captured in electronic health records (EHRs); present systems are usually built directly on top of specific clinical information systems through proprietary interfaces. In the context of the European project \"SALUS\", we aim to provide an infrastructure as well as a tool-set for accessing and analyzing clinical patient data of heterogeneous clinical information systems utilizing standard methods. This paper focuses on two components of the SALUS architecture: The \"Semantic Interoperability Layer\" (SIL) enables an access to disparate EHR sources in order to provide the patient data in a common data model for ADE detection within the \"ADE Detection and Notification Tool\" (ANT). The SIL in combination with the ANT can be used in different clinical environments to increase ADE detection and reporting rates. Thus, our approach promises a profound impact in the domain of pharmacovigilance. }
}
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