Artificial intelligence (AI) applications in healthcare and considerations for nursing education
Abstract
Aim/objective To review the current AI applications in healthcare and explore the implications for nurse educators in innovative integration of this technology in nursing education and training programs.Background There are a variety of Artificial Intelligence (AI) applications currently supporting patient care in many healthcare settings. A nursing workforce that leverages healthcare technology to enhance efficiency and accuracy of patient health outcomes is necessary. Nurse educators must understand the various uses of AI applications in healthcare to equip themselves to effectively prepare students to use the applications.Design Qualitative synthesis and analysis of existing literature.Methods Generative AI (ChatGPT) was used to support the development of a list of the current AI applications in healthcare. Each application was evaluated for relevance and accuracy. A literature review to define and understand the use of each application in clinical practice was completed. The search terms "AI" and "Health Education" were used to review the literature for evidence on educational programs used for training learners.Results Ten current applications of AI in healthcare were identified and explored. There is little evidence that outlines how to integrate AI education into educational training for nurses.Conclusion A comprehensive multimodal educational approach that uses innovative learning strategies has potential to support the integration of AI concepts into nursing curriculum. The use of simulation and clinical practicum experiences to support experiential learning and to offer opportunities for practical application and training. Considerations for ethical use and appropriate critical evaluation of AI applications are necessary.
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The 18 included studies collectively explored diverse applications of AI in nursing across research, practice, and education.
“The 18 included studies in this umbrella review collectively explored the diverse applications of AI in nursing across research, practice, and education [32-49].”
From The Role of AI in Nursing Education and Practice: Umbrella Review (2025) · cites this paper as [36]
By simulating realistic scenarios, these technologies bridge the gap between theoretical knowledge and practical application, allowing students to refine their skills in controlled, feedback-rich settings.
“By simulating realistic scenarios, these technologies bridge the gap between theoretical knowledge and practical application, allowing students to refine their skills in controlled, feedback-rich settings [36,47].”
From The Role of AI in Nursing Education and Practice: Umbrella Review (2025) · cites this paper as [36]
Tools such as LLMs, augmented reality, and VR offer immersive learning environments that enhance clinical judgment, critical thinking, and decision-making capabilities.
“Tools such as LLMs, augmented reality, and VR offer immersive learning environments that enhance clinical judgment, critical thinking, and decision-making capabilities [32,36].”
From The Role of AI in Nursing Education and Practice: Umbrella Review (2025) · cites this paper as [36]
Reviews like Montejo et al. (2024) and El Arab et al. (2025) discuss AI broadly without focusing on GenAI's interactive, generative functions, overlooking implementation questions specific to nursing education.
“However, reviews like Montejo et al. (2024) and El Arab et al. (2025) discuss AI broadly without focusing on GenAI's interactive, generative functions, over looking implementation questions specific to nursing education.”
From Patterns, advances, and gaps in using ChatGPT and similar technologies in nursing education: A PAGER scoping review (2025) · cites this paper as Montejo et al., 2024
Existing reviews have highlighted limited real-world implementation evidence.
“limited real-world implementation evidence (Montejo et al., 2024).”
From Patterns, advances, and gaps in using ChatGPT and similar technologies in nursing education: A PAGER scoping review (2025) · cites this paper as Montejo et al., 2024
Many scoping reviews do not differentiate GenAI from broader AI technologies.
“Despite their distinct educational implications, many scoping re views do not differentiate GenAI from broader AI technologies.”
From Patterns, advances, and gaps in using ChatGPT and similar technologies in nursing education: A PAGER scoping review (2025) · cites this paper as Montejo et al., 2024
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- Authors
- Montejo, L., Fenton, A., & Davis, G.
- Affiliations
- Johns Hopkins University (US)
- Corresponding author
- Montejo, Leigh
- Venue
- Nurse Education in Practice
- Publisher
- Elsevier BV
- Published
- 2024-10
- Volume
- 80
- Pages
- 104158
- ISSN
- 1471-5953 (ISSN-L)
- OpenAlex
- W4403258942
- Cited by
- 100
- References
- 31
- Citations by year
- 2026: 65 · 2025: 34 · 2024: 1
- FWCI
- 2.28
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Nurse Education in Practice (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Innovations in Medical Education
- Keywords
- artificial intelligence in healthcare, nursing education, nursing faculty, generative AI, ChatGPT, nursing curriculum, simulation-based training, clinical practicum, experiential learning, ethical use of AI, critical evaluation of AI
- MeSH terms
- Artificial Intelligence, Curriculum, Delivery of Health Care, Education, Nursing, Humans, Students, Nursing
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