AIMC Topic: Patient Safety
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A machine learning-based clinical predictive tool to identify patients at high risk of medication errors.
Scientific reports
Dec 30, 2024
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...
Ethical Application of Generative Artificial Intelligence in Medicine.
Arthroscopy : the journal of arthroscopic & related surgery : official publication of the Arthroscopy Association of North America and the International Arthroscopy Association
Dec 15, 2024
Generative artificial intelligence (AI) may revolutionize health care, providing solutions that range from enhancing diagnostic accuracy to personalizing treatment plans. However, its rapid and largely unregulated integration into medicine raises eth...
Leveraging artificial intelligence to reduce diagnostic errors in emergency medicine: Challenges, opportunities, and future directions.
Academic emergency medicine : official journal of the Society for Academic Emergency Medicine
Dec 15, 2024
Diagnostic errors in health care pose significant risks to patient safety and are disturbingly common. In the emergency department (ED), the chaotic and high-pressure environment increases the likelihood of these errors, as emergency clinicians must ...
AI: Promise or Peril for Patient Safety.
Journal of patient safety
Nov 25, 2024
Patient safety advocates identify concerns for the impact of AI on patient safety. Patients identified the following 4 main areas that AI developers, regulatory bodies, and clinical users of AI are asked to consider: data integrity and bias, efficacy...
Health technology assessment framework for artificial intelligence-based technologies.
International journal of technology assessment in health care
Nov 21, 2024
OBJECTIVES: Artificial intelligence (AI)-based health technologies (AIHTs) have already been applied in clinical practice. However, there is currently no standardized framework for evaluating them based on the principles of health technology assessme...
I-SIRch: AI-powered concept annotation tool for equitable extraction and analysis of safety insights from maternity investigations.
International journal of population data science
Nov 20, 2024
BACKGROUND: Maternity care is a complex system involving treatments and interactions between patients, healthcare providers, and the care environment. To enhance patient safety and outcomes, it is crucial to understand the human factors (e.g. individ...
Safeguarding Patients in the AI Era: Ethics at the Forefront of Pharmacovigilance.
Drug safety
Sep 27, 2024
Artificial intelligence is increasingly being used in pharmacovigilance. However, the use of artificial intelligence in pharmacovigilance raises ethical concerns related to fairness, non-discrimination, compliance, and responsibility as the central e...
Evaluation of a Natural Language Processing Approach to Identify Diagnostic Errors and Analysis of Safety Learning System Case Review Data: Retrospective Cohort Study.
Journal of medical Internet research
Aug 26, 2024
BACKGROUND: Diagnostic errors are an underappreciated cause of preventable mortality in hospitals and pose a risk for severe patient harm and increase hospital length of stay.
Development of Automated Triggers in Ambulatory Settings in Brazil: Protocol for a Machine Learning-Based Design Thinking Study.
JMIR research protocols
Aug 12, 2024
BACKGROUND: The use of technologies has had a significant impact on patient safety and the quality of care and has increased globally. In the literature, it has been reported that people die annually due to adverse events (AEs), and various methods e...
Safety improvement requires data: the case for automation and artificial intelligence during incident reporting.
British journal of anaesthesia
Jul 29, 2024
The reporting of incidents has a long association with safety in healthcare and anaesthesia, yet many incident reporting systems substantially under-report critical events. Better understanding the underlying reasons for low levels of critical incide...
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