Abstract Objective To determine if ChatGPT can generate useful suggestions for improving
clinical decision support (CDS) logic and to assess noninferiority compared to human …

ABSTRACT Objective To determine if ChatGPT can generate useful suggestions for
improving clinical decision support (CDS) logic and to assess noninferiority compared to …

Ineffective computerized alerts for potential Drug-Drug Interactions (DDI) is a longstanding
informatics issue. Prescribing clinicians often ignore or override such alerts due to lack of …

Objective Considerable international investment in hospital electronic prescribing
(ePrescribing) systems has been made, but despite this, it is proving difficult for most …

Objective The study sought to determine frequency and appropriateness of overrides of high-
priority drug-drug interaction (DDI) alerts and whether adverse drug events (ADEs) were …

Objective To evaluate the potential for machine learning to predict medication alerts that
might be ignored by a user, and intelligently filter out those alerts from the user's view …

Thoughtful integration of interruptive clinical decision support (CDS) alerts within the
electronic health record is essential to guide clinicians on the application of …

Objective To develop and evaluate a data-driven process to generate suggestions for
improving alert criteria using explainable artificial intelligence (XAI) approaches. Methods …

Objective Alert fatigue is a common issue with off-the-shelf clinical decision support. Most
warnings for drug–drug interactions (DDIs) are overridden or ignored, likely because they …

Drug–drug interactions (DDIs) frequently trigger adverse drug events or reduced efficacy.
Most DDI alerts, however, are overridden because of irrelevance for the specific patient …