AIMC Topic: Medication Errors
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Subgroup Discovery to Identify Determinants of Influence on CDSS Medication Alert Handling: A Feasibility Study.
Studies in health technology and informatics
May 15, 2025
Clinical decision support systems (CDSSs) are designed to enhance patient safety by providing alerts to prescribers about potential medication issues. However, a significant proportion of these alerts are ignored, which can compromise patient safety....
A semi-supervised learning approach to classify drug attributes in a pharmacy management database: A STROBE-compliant study.
Medicine
Mar 7, 2025
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...
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
Dec 16, 2024
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 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
May 20, 2024
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...
Pharmaceutical Decision Support System Using Machine Learning to Analyze and Limit Drug-Related Problems in Hospitals.
Studies in health technology and informatics
Mar 1, 2024
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 ...
Rule-Based Natural Language Processing Pipeline to Detect Medication-Related Named Entities: Insights for Transfer Learning.
Studies in health technology and informatics
Jan 25, 2024
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 ...
Clinical decision support system, using expert consensus-derived logic and natural language processing, decreased sedation-type order errors for patients undergoing endoscopy.
Journal of the American Medical Informatics Association : JAMIA
Jan 15, 2021
OBJECTIVE: Determination of appropriate endoscopy sedation strategy is an important preprocedural consideration. To address manual workflow gaps that lead to sedation-type order errors at our institution, we designed and implemented a clinical decisi...
A machine learning-based clinical decision support system to identify prescriptions with a high risk of medication error.
Journal of the American Medical Informatics Association : JAMIA
Nov 1, 2020
OBJECTIVE: To improve patient safety and clinical outcomes by reducing the risk of prescribing errors, we tested the accuracy of a hybrid clinical decision support system in prioritizing prescription checks.
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