Utilization of Artificial Intelligence in Reducing the Incidence of Medication Error: A Bibliometric Analysis

Abstract

Background and Aims: Medication errors (MEs) represent a significant challenge in healthcare, compromising patient safety and contributing to adverse outcomes. Artificial intelligence (AI) has emerged as a promising tool to address this issue by enhancing medication management processes and decision support systems. This study aims to visualize and examine the dissemination of published work on AI-related research in reducing MEs. Methods: = 184) relevant articles were identified and analyzed using VOS Viewer software, which examined citations, keyword relations, and network analysis to identify key contributors, influential publications, and emerging themes. Results: (6R's) to AI's potential roles in mitigating MEs. Conclusion: Empirical research is crucial for understanding AI utilization in reducing MEs. The medical community is increasingly interested in using AI to mitigate MEs and address critical issues related to patient safety in medication administration. The identified prominent keywords and themes illustrate AI's potential in enhancing healthcare delivery and reducing mistakes, paving the way for further exploration and practical application in clinical settings. Additional studies on AI use in reducing MEs should be conducted in less developed countries.

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