Navigating ethical considerations in the use of artificial intelligence for patient care: a systematic review
Abstract
Aim To explore the ethical considerations and challenges faced by nursing professionals in integrating artificial intelligence (AI) into patient care. Background AI's integration into nursing practice enhances clinical decision-making and operational efficiency but raises ethical concerns regarding privacy, accountability, informed consent, and the preservation of human-centered care. Methods A systematic review was conducted, following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Thirteen studies were selected from databases including PubMed, Embase, IEEE Xplore, PsycINFO, and CINAHL. Thematic analysis identified key ethical themes related to AI use in nursing. Results The review highlighted critical ethical challenges, such as data privacy and security, accountability for AI-driven decisions, transparency in AI decision-making, and maintaining the human touch in care. The findings underscore the importance of stakeholder engagement, continuous education for nurses, and robust governance frameworks to guide ethical AI implementation in nursing. Discussion The results align with existing literature on AI's ethical complexities in healthcare. Addressing these challenges requires strengthening nursing competencies in AI, advocating for patient-centered AI design, and ensuring that AI integration upholds ethical standards. Conclusion Although AI offers significant benefits for nursing practice, it also introduces ethical challenges that…
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AI in cancer care navigation has crucial limitations and serious ethical risks.
“However, there remain crucial limitations and serious ethical risks that must be acknowledged and proactively managed.20”
Empathic and agentic AI capabilities promise to enhance coordination, communication, and continuity of care.
“Empathic and agentic AI capabilities promise to enhance coordination, communication, and continuity of care.20”
Integrating social data into AI care delivery support systems offers an opportunity to personalize care, anticipate barriers, and identify patients at highest risk for treatment interruption or poor outcomes.
“Integrating social data into AI care delivery support systems offers a powerful opportunity to personalize care, anticipate barriers, and identify patients at highest risk for treatment interruption or poor outcomes.20”
There remain regulatory, legal, and ethical governance challenges for the safe application of AI.
“There also remain regulatory, legal, and ethical governance challenges for the safe application of AI.20”
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- Authors
- Badawy, W., Zinhom, H., & Shaban, M.
- Affiliations
- King Khalid University (SA)
- Zayed University (AE)
- Jouf University (SA)
- Corresponding author
- Shaban, Mostafa
- Venue
- International Nursing Review
- Publisher
- Wiley
- Published
- 2024-11-15
- Volume
- 72
- Issue
- 3
- Pages
- e13059-e13059
- ISSN
- 0020-8132 (ISSN-L)
- 1466-7657
- OpenAlex
- W4404416639
- Cited by
- 80
- References
- 15
- Citations by year
- 2026: 52 · 2025: 27 · 2024: 1
- FWCI
- 1.80
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- International Nursing Review (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Ethics and bioethics in healthcare
- Keywords
- artificial intelligence in nursing, AI ethics, patient care, data privacy, transparency in AI decision-making, human-centered care, informed consent, AI governance, nursing education, stakeholder engagement, clinical decision-making, health policy
- MeSH terms
- Artificial Intelligence, Ethics, Nursing, Humans, Nursing Care, Patient-Centered Care
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