AIMC Topic: Medical Order Entry Systems

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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...
Humans Artificial Intelligence Decision Support Systems, Clinical Medication Errors Medical Order Entry Systems
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Why do users override alerts? Utilizing large language model to summarize comments and optimize clinical decision support.

Journal of the American Medical Informatics Association : JAMIA May 20, 2024
OBJECTIVES: To evaluate the capability of using generative artificial intelligence (AI) in summarizing alert comments and to determine if the AI-generated summary could be used to improve clinical decision support (CDS) alerts.
Humans Artificial Intelligence Electronic Health Records Decision Support Systems, Clinical Natural Language Processing Medical Order Entry Systems
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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.
Humans Machine Learning Patient Safety ROC Curve Decision Support Systems, Clinical Expert Systems Medication Errors Pharmacists Prescriptions Medical Order Entry Systems Paris Hospitals, Voluntary
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Reducing drug prescription errors and adverse drug events by application of a probabilistic, machine-learning based clinical decision support system in an inpatient setting.

Journal of the American Medical Informatics Association : JAMIA Dec 1, 2019
BACKGROUND: Drug prescription errors are made, worldwide, on a daily basis, resulting in a high burden of morbidity and mortality. Existing rule-based systems for prevention of such errors are unsuccessful and associated with substantial burden of fa...
Humans Machine Learning Algorithms Patient Safety Prospective Studies Decision Support Systems, Clinical Drug-Related Side Effects and Adverse Reactions Israel Academic Medical Centers Medication Errors Drug Therapy, Computer-Assisted Medication Systems, Hospital Medical Order Entry Systems
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Developing and maintaining clinical decision support using clinical knowledge and machine learning: the case of order sets.

Journal of the American Medical Informatics Association : JAMIA Nov 1, 2018
Development and maintenance of order sets is a knowledge-intensive task for off-the-shelf machine-learning algorithms alone. We hypothesize that integrating clinical knowledge with machine learning can facilitate effective development and maintenance...
Humans Machine Learning Decision Support Systems, Clinical Workload Medical Order Entry Systems
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Comparison of three commercial knowledge bases for detection of drug-drug interactions in clinical decision support.

Journal of the American Medical Informatics Association : JAMIA Jul 1, 2017
OBJECTIVE: To compare 3 commercial knowledge bases (KBs) used for detection and avoidance of potential drug-drug interactions (DDIs) in clinical practice.
Humans Clinical Decision-Making Decision Support Systems, Clinical Drug Interactions Knowledge Bases Drug Therapy, Computer-Assisted Medical Order Entry Systems
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