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In times of steadily increasing numbers of administered drugs, the detection of adverse drug events (ADEs) is an important aspect of improving patient safety. At present only about 1–13% of detected ADEs are reported. Raising the number of reported ADEs will result in greater and more efficient support of pharmacovigilance. Potential ADE's must be identified early. In the iMedication system, which is a rule-based application, triggers are used for computerized detection of possible ADEs. Creating a pilot system, we defined the relevant use cases hyperkalemia, hyponatremia, renal failure, and over-anticoagulation; knowledge bases were implemented in Arden Syntax for each use case. The objective of these knowledge bases is to interpret patient-specific clinical data and generate notifications based on a calculated ADE risk score, which may indicate possible ADEs. This will permit appropriate monitoring of potential ADE situations over time in the interest of patient care, quality assurance, and pharmacovigilance.
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