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DIALOGUE: Un estudio de simulación previo basado en IA generativa para mejorar la comunicación diagnóstica en
Ricardo Xopan Suárez-García1,2, Quetzal Chavez-Castañeda2, Rodrigo Orrico-Pérez2
1Unidad de Remisión de Diabetes Mellitus (URDM), Facultad de Estudios Superiores-Iztacala, Universidad Nacional Autónoma de México, Tlalnepantla 54090, Mexico.
Resumen
La capacitación en inteligencia artificial generativa (GenAI) mejoró significativamente las habilidades de comunicación de diagnóstico de los estudiantes de medicina, particularmente en la explicación de los diagnósticos de diabetes mellitus tipo 2. El programa DIALOGUE mejoró la claridad, la estructura y la empatía en los encuentros con los pacientes.
Área de la Ciencia:
- Educación médica
- Inteligencia artificial en el cuidado de la salud
- Comunicación para el diagnóstico
Sus antecedentes:
- La comunicación diagnóstica efectiva es crucial para los resultados de los pacientes.
- La formación médica tradicional puede no equipar plenamente a los estudiantes con las habilidades de comunicación necesarias.
- La inteligencia artificial generativa (GenAI) ofrece nuevas modalidades de capacitación.
Objetivo del estudio:
- Evaluar la eficacia del programa DIALOGUE (aprendizaje de IA diagnóstica a través de una experiencia de usuario orientada por objetivos) en la mejora de las habilidades de comunicación diagnóstica de los estudiantes de medicina.
- Evaluar el impacto de la formación mediada por GenAI en la capacidad de los estudiantes para revelar un diagnóstico de diabetes mellitus tipo 2.
- Identificar los factores que influyen en la mejora de la comunicación diagnóstica.
Principales métodos:
- Un diseño de estudio previo y posterior de un solo brazo en el que participaron 30 estudiantes de medicina en fase clínica.
- Evaluaciones previas y posteriores a la prueba mediante encuentros simulados con pacientes con puntuación obtenida por evaluadores a ciegas.
- Diez escenarios de entrenamiento asíncrono de GenAI con retroalimentación automatizada utilizando el programa DIALOGUE.
- Análisis de las mejoras de rendimiento en ocho dominios de comunicación y factores de influencia.
Principales resultados:
- Mejora significativa en el rendimiento general de la comunicación diagnóstica (aumento medio de 36,7 puntos, p < 0,001).
- La proporción de estudiantes de alto rendimiento aumentó del 0% al 70%.
- Se observaron ganancias en todos los dominios, con mejoras notables en la apertura, el cierre y las explicaciones específicas de la diabetes.
Conclusiones:
- La formación mediada por GenAI, ejemplificada por el programa DIALOGUE, puede mejorar sustancialmente las habilidades de comunicación diagnóstica de los estudiantes de medicina.
- El programa muestra potencial como un complemento escalable e individualizado a la educación médica tradicional.
- Las características del alumno, como la empatía inicial y la autoeficacia digital, influyeron en los resultados del entrenamiento.
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