AI Article Synopsis
- Adverse drug event (ADE) detection and prevention is crucial for patient safety in healthcare organizations.
- While lab and medication-based ADEs are well-studied with rule-based systems, identifying descriptive ADEs, like somnolence, poses significant challenges.
- The research focuses on automating the detection of these descriptive ADEs from free-text clinician notes, which typically contain valuable signals.
Article Abstract
Detection and prevention of adverse drug events (ADEs) forms a large part of the patient safety efforts in any healthcare organization. Detection of laboratory and medication based ADEs is well-studied through the use of rule-based systems, however identifying descriptive ADEs, such as somnolence, is a challenging problem. Signals for the detection of these ADEs can often only be found in free-text clinical notes. We describe the automated detection of descriptive ADEs in free-text clinician notes.
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