El cuidado en la encrucijada: de Florence Nightingale a la inteligencia artificial
Palabras clave:
cuidado; enfermería; inteligencia artificial.Resumen
RESUMEN
Introducción: La inteligencia artificial se consolida en enfermería como apoyo esencial, al integrar la tecnología y los valores éticos para optimizar el cuidado seguro y personalizado del paciente.
Objetivo: Exponer la transición del cuidado de enfermería desde la época de Florence Nightingale hasta el surgimiento de la inteligencia artificial.
Métodos: Se realizó una revisión sistemática de estudios publicados, entre 2015 y 2025, en PubMed, SciELO, CINAHL, IEEE Xplore y Google Scholar. Se aplicaron criterios PICOS y se evaluó la calidad metodológica con herramientas estandarizadas.
Resultados: La inteligencia artificial mejora la precisión diagnóstica (60-70 %), la monitorización clínica (50-65 %) y la gestión operativa (45-60 %), especialmente, en los cuidados intensivos; requiere competencias digitales y formación ética, y enfrenta barreras tecnológicas, infraestructura y desigualdad en el acceso.
Conclusiones: La integración de la inteligencia artificial con la enfermería exige formación continua en los modos de actuación de estos profesionales, donde se precisa de la existencia de regulaciones con un enfoque ético, lo cual contribuye al fortalecimiento de la práctica humanista y profesional de la enfermería.
Descargas
Citas
1. Bjerring P. The challenge of artificial intelligence for professional autonomy in nursing. J Adv Nurs. 2024;80(5):2523–32. Disponible en: https://doi.org/10.1111/jan.16035
2. Coiera E, Miller A, Pedell L. Artificial intelligence in healthcare: the paradigm shift from technology adoption to clinical transformation. J Am Med Inform Assoc. 2024;31(1):151–8. Disponible en: https://doi.org/10.1093/jamia/ocad199
3. Al-Hafidh AS, Alghanim H, Al-Siyabi T, et al. Artificial intelligence in nursing education and practice: a scoping review on the impact on professional autonomy. J Nurs Educ. 2023;62(10):585–92. Disponible en: https://doi.org/10.3928/01484834-20230919-01
4. Lee H, Kang M, Yoo M, et al. Nursing students’ readiness for artificial intelligence and its determinants. Nurse Educ Today. 2023;126:105828. Disponible en: https://doi.org/10.1016/j.nedt.2023.105828
5. O’Connor R, O’Shea M, Butler M, et al. The application of artificial intelligence in clinical decision support for nurses: a systematic review. J Nurs Manag. 2023;31(5):1378–93. Disponible en: https://doi.org/10.1111/jonm.13786
6. Wang S, Lin X, Kang X. The philosophical foundations and ethical implications of artificial intelligence in nursing. Nurs Ethics. 2023;30(3):421–30. Disponible en: https://doi.org/10.1177/09697330221102943
7. Kyriacos U, Jordan J, Taylor M, et al. AI and the human touch: balancing technology and humanistic care in nursing. J Clin Nurs. 2024;33(10):7346–55. Disponible en: https://doi.org/10.1111/jocn.16912
8. Dossey BM, DePalma JA. Florence Nightingale’s legacy: the humanistic basis for professional nursing practice. Nurs Sci Q. 2021;34(1):21–6. Disponible en: https://doi.org/10.1177/0894318420967590
9. Attwood M, Atkin J, Hughes B. Nightingale’s vision in the digital age: data-driven practice and clinical safety. J Nurs Scholarsh. 2023;55(1):15–24. Disponible en: https://doi.org/10.1111/jnu.12818
10. Park S, Park JW, Kim H, et al. Ethical considerations of artificial intelligence applications in critical care nursing: a systematic review. Int J Nurs Stud. 2024;151:104671. Disponible en: https://doi.org/10.1016/j.ijnurstu.2023.104671
11. Chen J, Zhang S, Li J, et al. AI-powered patient monitoring systems in intensive care: improving accuracy and reducing nurse workload. Int J Med Inform. 2023;177:105151. Disponible en: https://doi.org/10.1016/j.ijmedinf.2023.105151
12. Smith D, Johnson T. Ethical challenges of algorithmic bias in healthcare artificial intelligence: implications for nursing. Nurs Inq. 2024;31(1):e12595. Disponible en: https://doi.org/10.1111/nin.12595
13. Echevarría J, Ramos F. Digital literacy and competency frameworks for nurses in the age of artificial intelligence. Nurse Educ Today. 2024;133:106037. Disponible en: https://doi.org/10.1016/j.nedt.2023.106037
14. Vayena E, Blasimme A. Governing clinical artificial intelligence: ethical, legal, and regulatory considerations. NPJ Digit Med. 2024;7(1):49. Disponible en: https://doi.org/10.1038/s41746-024-00994-x
15. Miller D, Green A. Policy and governance models for responsible AI deployment in healthcare institutions. Health Policy Technol. 2023;12(3):100778. Disponible en: https://doi.org/10.1016/j.hlpt.2023.100778
16. Borja M, Galarza J, Jaramillo M. Artificial intelligence for early detection of sepsis and respiratory failure in Intensive Care Units: a systematic review. J Crit Care. 2023;78:154316. Disponible en: https://doi.org/10.1016/j.jcrc.2023.154316
17. Roppelt JS, Kanbach DK, Kraus S. Artificial intelligence in healthcare institutions: a systematic literature review on influencing factors. Technol Soc. 2024;76:102443. Disponible en: https://doi.org/10.1016/j.techsoc.2023.102443
18. Jones M, Williams L. Data privacy and security in AI-driven healthcare: nurses' critical role in stewardship. Comput Inform Nurs. 2024;42(4):257–63. Disponible en: https://doi.org/10.1097/CIN.0000000000001041
19. Laksmi S, Sutomo S, Bachtiar M. The role of artificial intelligence in continuous education and professional development for nurses. J Nurs Educ Pract. 2023;13(4):34–42. Disponible en: https://doi.org/10.5430/jnep.v13n4p34
20. Toapanta J, Galarza L, Jaramillo R, et al. AI in nursing education, clinical practice, and management: a comprehensive overview. Front Public Health. 2024;12:1370903. Disponible en: https://doi.org/10.3389/fpubh.2024.1370903
21. Pérez-Mejías C, García-Bernal E, Mielgo-Ayuso J. Impact of artificial intelligence on clinical decision making and professional training in nursing: a scoping review. Int J Environ Res Public Health. 2024;21(5):543. Disponible en: https://doi.org/10.3390/ijerph21050543
22. Brown A, Davis R. Longitudinal studies on the impact of artificial intelligence on nursing workload and patient outcomes. J Adv Nurs. 2024;80(6):3001–10. Disponible en: https://doi.org/10.1111/jan.16091
23. Medeiros-de-Souza L. The epistemic complexity of nursing care: from practice to science. Rev Bras Enferm. 2024;77(1):e20230232. Disponible en: https://doi.org/10.1590/0034-7167-2023-0232
24. Hunter R, Stoddart R, Arcus V. Systematic review as a scientific method: ensuring rigor in methodology. J Adv Nurs. 2024;80(1):475–83. Disponible en: https://doi.org/10.1111/jan.15934
25. Page MJ, McKenzie JE, Bossuyt PM, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021;372:n71. Disponible en: https://doi.org/10.1136/bmj.n71
26. Kim S, Kim H. Ethical governance for artificial intelligence in the health sector. Health Policy. 2023;135:104845. Disponible en: https://doi.org/10.1016/j.healthpol.2023.104845
27. Maddox RR, Shakal E, Hultman T, et al. Intelligent systems and adaptive learning in nursing education: a systematic review. Nurs Outlook. 2023;71(4):101980. Disponible en: https://doi.org/10.1016/j.outlook.2023.101980
28. Mina Curay MA, Toapanta VJ, Recimundo J. Application of artificial intelligence in the practice of nursing opportunities and challenges, a systematic review. RECIMUNDO. 2025;9(2):220–9. Disponible en: https://recimundo.com/index.php/es/article/view/2951
29. García-Sánchez A, López-Rodríguez P. Integration of artificial intelligence in nursing workflows: benefits and challenges. Int J Nurs Pract. 2024;30(2):e13245. Disponible en: https://doi.org/10.1111/ijn.13245
30. Martínez-Carrillo R, Fernández-García M. Ethical and legal considerations of AI in clinical nursing practice: a scoping review. Nurs Ethics. 2024;31(2):987–1002. Disponible en: https://doi.org/10.1177/09697330231100234
Descargas
Publicado
Cómo citar
Número
Sección
Licencia
Derechos de autor 2026 ydalsys naranjo hernández

Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial 4.0.

