Application of Artificial Intelligence as an Aid for the Correction of the Objective Structured Clinical Examination (OSCE)

• Published in: Applied sciences Vol. 15; no. 3; p. 1153
• Main Authors: Luordo, Davide, Torres Arrese, Marta, Tristán Calvo, Cristina, Shani Shani, Kirti Dayal, Rodríguez Cruz, Luis Miguel, García Sánchez, Francisco Javier, Lagares Gómez-Abascal, Alfonso, Rubio García, Rafael, Delgado Jiménez, Juan, Pérez Carreras, Mercedes, Diez Lobato, Ramiro, Granizo Martínez, Juan José, Tung-Chen, Yale, Villena Garrido, Mª Victoria
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.02.2025
• Subjects: AI in healthcare; AI-assisted grading; Artificial intelligence; Chatbots; clinical competency assessment; Computational linguistics; Decision making; Hospitals; Language processing; Medical education; Medical students; Natural language interfaces; Natural language processing; objective structured clinical examination (OSCE); Patients; Skills; Subjectivity; Spain
• ISSN: 2076-3417; 2076-3417
• DOI: 10.3390/app15031153

The assessment of clinical competencies is essential in medical training, and the Objective Structured Clinical Examination (OSCE) is an essential tool in this process. There are multiple studies exploring the usefulness of artificial intelligence (AI) in medical education. This study explored the use of the GPT-4 AI model to grade clinical reports written by students during the OSCE at the Teaching Unit of the 12 de Octubre and Infanta Cristina University Hospitals, part of the Faculty of Medicine at the Complutense University of Madrid, comparing its results with those of human graders. Ninety-six (96) students participated, and their reports were evaluated by two experts, an inexperienced grader, and the AI using a checklist designed during the OSCE planning by the teaching team. The results show a significant correlation between the AI and human graders (ICC = 0.77 for single measures and 0.91 for average measures). AI was more stringent, assigning scores on an average of 3.51 points lower (t = −15.358, p < 0.001); its correction was considerably faster, completing the analysis in only 24 min compared to the 2–4 h required by human graders. These results suggest that AI could be a promising tool to enhance efficiency and objectivity in OSCE grading.