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Medication Errors

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Large language models for preventing medication direction errors in online pharmacies.

Nature medicine
Errors in pharmacy medication directions, such as incorrect instructions for dosage or frequency, can increase patient safety risk substantially by raising the chances of adverse drug events. This study explores how integrating domain knowledge with ...

Rule-Based Natural Language Processing Pipeline to Detect Medication-Related Named Entities: Insights for Transfer Learning.

Studies in health technology and informatics
We document the procedure and performance of a rule-based NLP system that, using transfer learning, automatically extracts essential named entities related to drug errors from Japanese free-text incident reports. Subsequently, we used the rule-based ...

Pharmaceutical Decision Support System Using Machine Learning to Analyze and Limit Drug-Related Problems in Hospitals.

Studies in health technology and informatics
The health product circuit corresponds to the chain of steps that a medicine goes through in hospital, from prescription to administration. The safety and regulation of all the stages of this circuit are major issues to ensure the safety and protect ...

Validation of a natural language processing algorithm using national reporting data to improve identification of anesthesia-related ADVerse evENTs: The "ADVENTURE" study.

Anaesthesia, critical care & pain medicine
BACKGROUND: Reporting and analysis of adverse events (AE) is associated with improved health system learning, quality outcomes, and patient safety. Manual text analysis is time-consuming, costly, and prone to human errors. We aimed to demonstrate the...

The use of artificial intelligence to optimize medication alerts generated by clinical decision support systems: a scoping review.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Current Clinical Decision Support Systems (CDSSs) generate medication alerts that are of limited clinical value, causing alert fatigue. Artificial Intelligence (AI)-based methods may help in optimizing medication alerts. Therefore, we cond...

A machine learning-based clinical predictive tool to identify patients at high risk of medication errors.

Scientific reports
A medication error is an inadvertent failure in the drug therapy process that can cause serious harm to patients by increasing morbidity and mortality and are associated with significant economic costs to the healthcare system. Medication reconciliat...

Evaluating the impact of an automated drug retrieval cabinet and robotic dispensing system in a large hospital central pharmacy.

American journal of health-system pharmacy : AJHP : official journal of the American Society of Health-System Pharmacists
PURPOSE: To determine the impact of implementing 2 technologies in succession, the Carousel system and XR2 robot, in a hospital central pharmacy. The study examined the technologies' impact on workload shifted from fully human-involved, labor-intensi...

The Effects of Presenting AI Uncertainty Information on Pharmacists' Trust in Automated Pill Recognition Technology: Exploratory Mixed Subjects Study.

JMIR human factors
BACKGROUND: Dispensing errors significantly contribute to adverse drug events, resulting in substantial health care costs and patient harm. Automated pill verification technologies have been developed to aid pharmacists with medication dispensing. Ho...

A semi-supervised learning approach to classify drug attributes in a pharmacy management database: A STROBE-compliant study.

Medicine
With the development of information and communication technology, it has become possible to improve pharmacy management system (PMS) using these technologies. Our study aims to enhance the accuracy of drug attribute classification and recommend appro...