Content area

Abstract

Introduction

Adverse events in hospitals significantly compromise patient safety and trust in healthcare systems, with medical errors being a leading cause of death globally. Despite efforts to reduce these errors, reporting remains low, and effective system changes are rare. This systematic review explores the potential of artificial intelligence (AI) in clinical risk management.

Methods

The systematic review was conducted using the PRISMA Statement 2020 guidelines to ensure a comprehensive and transparent approach. We utilized the online tool Rayyan for efficient screening and selection of relevant studies from three different online bibliographic.

Results

AI systems, including machine learning and natural language processing, show promise in detecting adverse events, predicting medication errors, assessing fall risks, and preventing pressure injuries. Studies reveal that AI can improve incident reporting accuracy, identify high-risk incidents, and automate classification processes. However, challenges such as socio-technical issues, implementation barriers, and the need for standardization persist.

Discussion

The review highlights the effectiveness of AI in various applications but underscores the necessity for further research to ensure safe and consistent integration into clinical practices. Future directions involve refining AI tools through continuous feedback and addressing regulatory standards to enhance patient safety and care quality.

Details

1009240
Title
Artificial intelligence in healthcare: transforming patient safety with intelligent systems—A systematic review
Author
De Micco, Francesco 1 ; Gianmarco Di Palma 2 ; Ferorelli, Davide 3 ; De Benedictis, Anna 4 ; Tomassini, Luca 5 ; Tambone, Vittoradolfo 6 ; Cingolani, Mariano 7 ; Scendoni, Roberto 8 

 Research Unit of Bioethics and Humanities, Department of Medicine and Surgery, Università Campus Bio-Medico di Roma, Rome, Italy, Department of Clinical Affair, Fondazione Policlinico Universitario Campus Bio-Medico, Rome, Italy 
 Research Unit of Bioethics and Humanities, Department of Medicine and Surgery, Università Campus Bio-Medico di Roma, Rome, Italy, Department of Public Health, Experimental and Forensic Sciences, University of Pavia, Pavia, Italy 
 Interdisciplinary Department of Medicine (DIM), Section of Legal Medicine, University of Bari “Aldo Moro”, Bari, Italy 
 Research Unit of Bioethics and Humanities, Department of Medicine and Surgery, Università Campus Bio-Medico di Roma, Rome, Italy, Research Unit of Nursing Science, Department of Medicine and Surgery, Università Campus Bio-Medico di Roma, Rome, Italy 
 International School of Advanced Studies, University of Camerino, Camerino, Italy 
 Research Unit of Bioethics and Humanities, Department of Medicine and Surgery, Università Campus Bio-Medico di Roma, Rome, Italy 
 Department of Law, Institute of Legal Medicine, University of Macerata, Macerata, Italy 
 Department of Law, Institute of Legal Medicine, University of Macerata, Macerata, Italy, Italian Network for Safety in Healthcare (INSH), Coordination of Marche Region, Macerata, Italy 
Publication title
Volume
11
First page
1522554
Number of pages
13
Publication year
2025
Publication date
Jan 2025
Section
Regulatory Science
Publisher
Frontiers Media SA
Place of publication
Lausanne
Country of publication
Switzerland
Publication subject
e-ISSN
2296858X
Source type
Scholarly Journal
Language of publication
English
Document type
Journal Article
Publication history
 
 
Online publication date
2025-01-08
Milestone dates
2024-11-04 (Recieved); 2024-12-13 (Accepted)
Publication history
 
 
   First posting date
08 Jan 2025
ProQuest document ID
3270815814
Document URL
https://www.proquest.com/scholarly-journals/artificial-intelligence-healthcare-transforming/docview/3270815814/se-2?accountid=208611
Copyright
© 2025. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Last updated
2025-12-18
Database
ProQuest One Academic