El método Delphi como herramienta de consenso en el diseño de un marco de aplicación de la Inteligencia Artificial en Educación Médica en España

Introduction. The rapid integration of artificial intelligence (AI) into biomedical education hascreated an urgent need for a framework that can guide both learners and academic staff. In Spain,where institutions are adopting AI at speed but without homogeneous regulatory or pedagogicalguidance, str...

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Detalles Bibliográficos
Autores: García-Pardina, Alejandro, Bellido-Esteban, alberto, Ryan Murúa, Pablo, Teresa de Jesús, María, Giménez Maroto, Ana, García García, Esther, González Soltero, Rocío, Ramírez Moreno, Carlos, Biscaia, José Miguel, Mohedano, Rosa B., Gal Iglesias, Beatriz, Sánchez-Vera, Isabel, Castelao, Olga, Arcis, Álvaro, López Castro, José, Balaguer Santamaría, Albert, Parés, David, Zarmora, Alberto, Muñoz, María José, Sanz Sanz, Emilio J., Torres Belma, Alberto, Pérez Frías, Javier
Tipo de recurso: artículo
Fecha de publicación:2026
País:España
Institución:Universidad de Murcia
Repositorio:DIGITUM. Depósito Digital Institucional de la Universidad de Murcia
OAI Identifier:oai:dnet:digitum_____::73b19e37f3ae61920edb5b32cd9ade22
Acceso en línea:https://doi.org/10.6018/edumed.702541
http://hdl.handle.net/10201/225021
Access Level:acceso abierto
Palabra clave:Delphi
Medical Education
Inteligencia Artificial,
Educación Médica
España
Artificial Intelligence
No relacionado con ningún objetivo de desarrollo sostenible
Descripción
Sumario:Introduction. The rapid integration of artificial intelligence (AI) into biomedical education hascreated an urgent need for a framework that can guide both learners and academic staff. In Spain,where institutions are adopting AI at speed but without homogeneous regulatory or pedagogicalguidance, structured approaches are required to prioritize competencies and address ethical, legaland educational challenges. Methods. A Delphi study was coordinated by the Universidad Europeade Madrid, using the REDCap platform to manage iterative rounds. The project received financialsupport from the Spanish Society for Medical Education (SEDEM). Experts in medical education,including some with specific AI expertise, participated in a sequence of online questionnaires.Through anonymized feedback, participants evaluated, refined and prioritized a core of areas wherethe impact of AI seems essential. Results. Experts agreed on the need for skills extending beyondtechnical literacy, emphasizing critical thinking, interpretation of AI-generated outputs, biasawareness and professional responsibility. Ethical and legal considerations, particularly concerningprivacy, transparency and decision-making, were strongly prioritized. Participants also highlightedthe transversal nature of AI, suggesting that competencies should be embedded across curricularather than treated as isolated content. Discussion. Despite institutional heterogeneity, consensusconverged on areas that balance innovation with ethical safeguards. The results support thedevelopment of a competency-based framework capable of guiding curriculum design, informingfaculty development and promoting responsible, evidence-informed use of AI while safeguardingprofessional autonomy

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