AI applications in primary health care: opportunities and challenges for Latin America
DOI:
https://doi.org/10.71112/kbqj4x03Keywords:
artificial intelligence, primary health care, machine learning, digital health, Latin AmericaAbstract
Artificial intelligence (AI) has progressively been incorporated into medical practice, particularly in Primary Health Care (PHC), where structural limitations highlight the need to optimize processes. This study analyzes literature published between 2015 and 2024 to identify its main applications and the factors influencing its implementation in Latin America. A narrative review with a systematized approach inspired by PRISMA 2020 was conducted. Four main areas were identified: clinical decision support, automated triage, predictive models, and telemonitoring. Findings suggest improvements in service organization and early disease detection. However, limitations persist regarding data quality, fragmentation, and the need for local adaptation. AI should be understood as a complementary tool whose impact depends on its contextual implementation.
Downloads
References
Álvarez Guachichulca, J. S., Jaramillo Aguilar, D., & López Becerra, A. X. (2024). Aplicaciones, oportunidades y desafíos de implementar la inteligencia artificial en medicina: una revisión narrativa. Anales de la Facultad de Ciencias Médicas. https://doi.org/10.18004/anales/2024.057.02.90
Amann, J., Blasimme, A., Vayena, E., Frey, D., & Madai, V. I. (2020). Explainability for artificial intelligence in healthcare: A multidisciplinary perspective. BMC Medical Informatics and Decision Making, 20(1), 310. https://doi.org/10.1186/s12911-020-01332-6
Beam, A. L., & Kohane, I. S. (2018). Big data and machine learning in health care. JAMA, 319(13), 1317–1318. https://doi.org/10.1001/jama.2017.18391
Blease, C., Kaptchuk, T. J., Bernstein, M. H., Mandl, K. D., Halamka, J. D., & DesRoches, C. M. (2019). Artificial intelligence and the future of primary care: Exploratory qualitative study of UK general practitioners’ views. Journal of Medical Internet Research, 21(3), e12802. https://doi.org/10.2196/12802
Bonis Sanz, J., & Bravo Toledo, R. (2025). La inteligencia artificial en atención primaria: ¿solución o problema? Atención Primaria, 57(4), 103223. https://doi.org/10.1016/j.aprim.2025.103223
Char, D. S., Shah, N. H., & Magnus, D. (2018). Implementing machine learning in health care. New England Journal of Medicine, 378(11), 981–983. https://doi.org/10.1056/NEJMp1714229
Davenport, T., & Kalakota, R. (2019). The potential for artificial intelligence in healthcare. Future Healthcare Journal, 6(2), 94–98. https://doi.org/10.7861/futurehosp.6-2-94
Esteva, A., et al. (2017). Dermatologist-level classification of skin cancer with deep neural networks. Nature, 542(7639), 115–118. https://doi.org/10.1038/nature21056
Floridi, L., et al. (2018). AI4People—An ethical framework. Minds and Machines, 28(4), 689–707. https://doi.org/10.1007/s11023-018-9482-5
Goodman, K. W., & Flaxman, S. (2017). European Union regulations on AI. AI Magazine, 38(3), 50–57. https://doi.org/10.1609/aimag.v38i3.2741
Gulshan, V., et al. (2016). Development of a deep learning algorithm for diabetic retinopathy. JAMA, 316(22), 2402–2410. https://doi.org/10.1001/jama.2016.17216
Jiang, F., et al. (2017). Artificial intelligence in healthcare: Past, present and future. Stroke and Vascular Neurology, 2(4), 230–243. https://doi.org/10.1136/svn-2017-000101
Kelly, C. J., et al. (2019). Key challenges for delivering clinical impact with AI. BMC Medicine, 17, 195. https://doi.org/10.1186/s12916-019-1426-2
Lopes Júnior, L. C., et al. (2025). Entre algoritmos y territorios: una revisión de alcance sobre salud digital e inteligencia artificial en atención primaria de salud. Revista Panamericana de Salud Pública. https://doi.org/10.26633/RPSP.2025.126
Lozada Pazmiño, J. V. (2025). Inteligencia artificial en la práctica médica: aplicaciones y consideraciones. Revista Ecuatoriana de Pediatría. https://doi.org/10.52011/RevSepEc/e346
Mayer, M. A. (2023). Inteligencia artificial en atención primaria: un escenario de oportunidades y desafíos. Atención Primaria. https://doi.org/10.1016/j.aprim.2023.102744
Miotto, R., et al. (2018). Deep learning for healthcare. Briefings in Bioinformatics, 19(6), 1236–1246. https://doi.org/10.1093/bib/bbx044
Obermeyer, Z., & Emanuel, E. (2016). Predicting the future — big data and machine learning in health care. Science, 353(6301), 760–761. https://doi.org/10.1126/science.aaf2608
Reddy, S., et al. (2019). Artificial intelligence-enabled healthcare delivery. Journal of the Royal Society of Medicine, 112(1), 22–28. https://doi.org/10.1177/0141076818815510
Ruiz de Larramendi, D., et al. (2025). Inteligencia artificial en atención primaria: promesas, límites y realidades. Revista Pediatría de Atención Primaria, 27. https://doi.org/10.60147/4776da54
Singh, M. P., & Keche, Y. N. (2025). Ethical integration of artificial intelligence in healthcare. Cureus, 17(5), e84804. https://doi.org/10.7759/cureus.84804
Ting, D. S. W., et al. (2017). AI for diabetic retinopathy screening. JAMA, 318(22), 2211–2223. https://doi.org/10.1001/jama.2017.18152
Topol, E. (2019). High-performance medicine: The convergence of human and artificial intelligence. The Lancet Digital Health, 1(1), e44–e56. https://doi.org/10.1038/s41591-018-0300-7
Wahl, B., et al. (2018). Artificial intelligence (AI) and global health. NPJ Digital Medicine, 1, 1–3. https://doi.org/10.1136/bmjgh-2018-000798
Whicher, D., et al. (2023). Artificial intelligence in health care: The hope, the hype, the promise, the peril. National Academies Press. https://doi.org/10.17226/27111
Yu, K.-H., et al. (2018). Artificial intelligence in healthcare. Nature Biomedical Engineering, 2(10), 719–731. https://doi.org/10.1038/s41551-018-0305-z
Fernández-Luque, L., & Imran, M. (2020). Artificial intelligence in global health: Applications, challenges, and future directions. Global Health Journal, 4(2), 45–52. https://doi.org/10.1016/j.glohj.2020.06.003
Shah, P., et al. (2019). Artificial intelligence and machine learning in clinical development: A translational perspective. npj Digital Medicine, 2, 69. https://doi.org/10.1038/s41746-019-0148-3
González, D., & Valdez, A. (2021). Digital health interventions and artificial intelligence in primary care in Latin America: A scoping review. Revista Panamericana de Salud Pública, 45, e15. https://doi.org/10.26633/RPSP.2021.15
Martínez-Pérez, B., de la Torre-Díez, I., & López-Coronado, M. (2018). Mobile health applications for healthcare management: Review of opportunities and challenges. Journal of Medical Systems, 42(7), 128. https://doi.org/10.1007/s10916-018-0992-2.1038/s41591-018-0307-0
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Carlos Enrique Muñoz Cofre, Darla Lizeth Yánez Zúñiga (Autor/a)
This work is licensed under a Creative Commons Attribution 4.0 International License.
