صورة الغلاف

Exploring the impact of artificial intelligence integration on medication error reduction: A nursing perspective

محفوظ في:
الحاوية / القاعدة:Nurse Education in Practice vol. 86 (Jul 2025), p. 104438
المؤلف الرئيسي: Alqaraleh, Muhyeeddin
مؤلفون آخرون: Wesam Taher Almagharbeh, Ahmad, Muhammad Waleed
منشور في:
Elsevier Limited
الموضوعات:
Appreciation
Transparency
Safeguards
Infusion devices
Operating rooms
Prescribing
Human error
Efficacy
Automation
Health care industry
Medical errors
Artificial intelligence
Algorithms
Professional practice
Patient safety
Safety
Systematic review
Drugs
Clinical decision making
Critical incidents
Clinical nursing
Drug administration
Decision support systems
Predictive analytics
Fatigue
Ethics
Errors
Nurses
Resistance
Support networks
Validity
Adoption of innovations
Health services
Nursing
Medical decision making
Patients
Hospitals
Literature Reviews
Influence of Technology
Records (Forms)
Mixed Methods Research
Meta Analysis
Reference Materials
Qualitative Research
Search Strategies
Information Seeking
Database Management Systems
Individual Characteristics
الوصول للمادة أونلاين:Citation/Abstract
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مستخلص:Aim To systematically evaluate the impact of artificial intelligence (AI) technologies on reducing medication errors in nursing practice, focusing on tools such as clinical decision support systems (CDSS), smart infusion pumps, barcode scanning and automated prescription validation. Background Medication errors are a persistent threat to patient safety and a major burden on healthcare systems. Nurses, who are central to the medication administration process, remain vulnerable to human error. AI offers new opportunities to enhance safety through real-time decision support and predictive analytics. Design A systematic review following PRISMA 2020 guidelines and using a mixed-methods approach to integrate quantitative outcomes with qualitative insights from nursing practice. Methods Studies published in English between January 2013 and March 2024 were retrieved from PubMed, ScienceDirect and CINAHL. Eligibility was guided by the PICO framework. Quality appraisal tools appropriate to study designs were applied. Results Twelve studies were included. CDSS reduced operating room errors by up to 95 %, while smart infusion pumps reduced IV medication errors by approximately 80 %. Prescription validation tools led to a 55 % reduction in prescribing errors. AI-driven alert filtering decreased non-actionable alerts by 45 %. Qualitative data revealed both appreciation of AI’s utility and concerns about algorithmic bias, system usability and trust. Conclusions AI technologies significantly improve medication safety in nursing. However, successful implementation depends on nurse training, system integration, ethical safeguards and workflow alignment. Further experimental studies are needed to validate efficacy and address barriers such as alert fatigue, algorithm transparency and adoption resistance.
تدمد:1471-5953
1873-5223
DOI:10.1016/j.nepr.2025.104438
المصدر:Sociology Database