AIMC Topic: Inappropriate Prescribing

Clear Filters Showing 1 to 9 of 9 articles

MAPRS: An intelligent approach for post-prescription review based on multi-label learning.

Artificial intelligence in medicine Aug 30, 2024
Antimicrobial resistance (AMR) is a major threat to public health worldwide. It is a promising way to improve appropriate prescription by the review and stewardship of antimicrobials, and Post-Prescription Review (PPR) is currently the main tool used...
Humans Machine Learning Algorithms Antimicrobial Stewardship Drug Prescriptions Inappropriate Prescribing Anti-Bacterial Agents Anti-Infective Agents China
View on PubMed DOI

Mobile applications on app stores for deprescribing: A scoping review.

British journal of clinical pharmacology Aug 4, 2024
Deprescribing is an evidence-based intervention to reduce potentially inappropriate medication use. Yet its implementation faces barriers including inadequate resources, training and time. Mobile applications (apps) on app stores could address some b...
Polypharmacy Humans Inappropriate Prescribing Artificial Intelligence Deprescriptions Mobile Applications
View on PubMed DOI

A model for identifying potentially inappropriate medication used in older people with dementia: a machine learning study.

International journal of clinical pharmacy Jul 9, 2024
BACKGROUND: Older adults with dementia often face the risk of potentially inappropriate medication (PIM) use. The quality of PIM evaluation is hindered by researchers' unfamiliarity with evaluation criteria for inappropriate drug use. While tradition...
Dementia Inappropriate Prescribing Potentially Inappropriate Medication List Machine Learning Humans Aged Algorithms Aged, 80 and over Female Male
View on PubMed DOI

Traditional Methods Hold Their Ground Against Machine Learning in Predicting Potentially Inappropriate Medication Use in Older Adults.

Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research Jul 6, 2024
OBJECTIVES: Machine learning methods have gained much attention in health sciences for predicting various health outcomes but are scarcely used in pharmacoepidemiology. The ability to identify predictors of suboptimal medication use is essential for ...
Pharmacoepidemiology Inappropriate Prescribing Potentially Inappropriate Medication List Aged Aged, 80 and over Male Humans Logistic Models Machine Learning Bayes Theorem Female Quebec
View on PubMed DOI

Using machine learning or deep learning models in a hospital setting to detect inappropriate prescriptions: a systematic review.

European journal of hospital pharmacy : science and practice Jun 21, 2024
OBJECTIVES: The emergence of artificial intelligence (AI) is catching the interest of hospital pharmacists. A massive collection of health data is now available to train AI models and hold the promise of disrupting codes and practices. The objective ...
Humans Pharmacy Service, Hospital Inappropriate Prescribing Machine Learning Deep Learning Pharmacists
View on PubMed DOI

Development and validation of a machine learning model to improve precision prediction for irrational prescriptions in orthopedic perioperative patients.

Expert opinion on drug safety May 2, 2024
OBJECTIVE: Our objective was to develop a machine learning model capable of predicting irrational medical prescriptions precisely within orthopedic perioperative patients.
Practice Patterns, Physicians' Perioperative Care Orthopedic Procedures Pharmacists Inappropriate Prescribing Adult Male Middle Aged Humans Machine Learning Female Aged
View on PubMed DOI

A Machine Learning Approach to Identify Predictors of Potentially Inappropriate Non-Steroidal Anti-Inflammatory Drugs (NSAIDs) Use in Older Adults with Osteoarthritis.

International journal of environmental research and public health Dec 28, 2020
Evidence from some studies suggest that osteoarthritis (OA) patients are often prescribed non-steroidal anti-inflammatory drugs (NSAIDs) that are not in accordance with their cardiovascular (CV) or gastrointestinal (GI) risk profiles. However, no suc...
Male Cardiovascular Diseases Gastrointestinal Diseases Anti-Inflammatory Agents, Non-Steroidal Female Humans Medicare United States Inappropriate Prescribing Aged Machine Learning Osteoarthritis Aged, 80 and over Retrospective Studies
View on PubMed DOI

PARS, a system combining semantic technologies with multiple criteria decision aiding for supporting antibiotic prescriptions.

Journal of biomedical informatics Oct 14, 2019
OBJECTIVE: Motivated by the well documented worldwide spread of adverse drug events, as well as the increased danger of antibiotic resistance (caused mainly by inappropriate prescribing and overuse), we propose a novel recommendation system for antib...
Biological Ontologies Drug Prescriptions Inappropriate Prescribing Decision Support Systems, Clinical Humans Medical Informatics Machine Learning Semantics Anti-Bacterial Agents
View on PubMed DOI

Potentially inappropriate polypharmacy is an important predictor of 30-day emergency hospitalisation in older adults: a machine learning feature validation study.

Age and ageing May 31, 2025
BACKGROUND: Machine learning (ML) models in healthcare are crucial for predicting clinical outcomes, and their effectiveness can be significantly enhanced through improvements in accuracy, generalisability, and interpretability. To achieve widespread...
Risk Assessment Time Factors Age Factors Humans Aged Machine Learning Aged, 80 and over Female Reproducibility of Results Male Polypharmacy Risk Factors Inappropriate Prescribing Hospitalization Emergency Service, Hospital Potentially Inappropriate Medication List Geriatric Assessment United Kingdom
View on PubMed DOI
Popular Topics
Recent Journals