Trusting our trainees: competency-based training of cardiologists using Entrustable Professional Activities (EPA)
Notice bibliographique
Résumé
Abstract Assessment of trainees is a core activity of educators, ensuring that trainees can be trusted to provide high quality care with no supervision. Training and the demands on trainees have changed with specialization, need for more technical skills, digitization, needs for teamwork and greater communication skills. Competency-based medical education was introduced to capture these changing needs for trainees. The 7th ESC Education Conference – “From competence to good clinical care” – brought together national directors of training (39), young cardiology representatives (7), patients (7), ESC partners in education (10), and the ESC Education Committee (22) to discuss contemporary challenges in cardiology training and Entrustable Professional Activities (EPAs)-based solutions. Methods Pre- and post-conference surveys were conducted. The different issues were discussed in 4 workshops: core knowledge and evidence, skills and competence, performing into context, and training the trainers. Results Pre-conference, 90% of respondents believed that trainees should be certified only when they can be entrusted to perform in an unsupervised fashion, and 84% thought that specific training for educators should be required. From the workshops 4 themes emerged: 1) Core knowledge and evidence: rotations to different centres are needed to enable trainees to meet EPA requirements. 2) Skills and competence: a learning agreement between trainers and trainees should be established with protected time to achieve EPAs, and patient feedback on trainee performance should be obtained. 3) Performing into context (when is a trainee ready to practice): clinicians do informal assessment on a daily basis; EPAs formalize this with regular observation linked with progression in responsibility. 4) Train the trainer: good doctors are not automatically good trainers and should be required to undergo specific training themselves. We reviewed complex training frameworks such as the Canadian Medical Education Directives for Specialists (CanMEDS) that contains too many components to be useful for clinical teachers. EPAs were identified as a practical way to implement competency-based cardiology training across the ESC. The 2020 ESC Core Curriculum contains EPAs that a cardiologist should be able to perform independently by the end of training. Post-conference there was unanimous agreement (100%) that EPAs are a valuable concept in training. A majority of participants (69%) agreed that EPA's are applicable in practice today. Conclusion Trainee assessment is a daily challenge for educators. The ESC Education Conference identified distinct goals to be achieved before, during and at the completion of a training programs. The EPA concept was widely accepted as an efficient method to monitor trainees progress, while trusting them to perform activities in which they are proficient. Trusting our trainees should be a major educational goals for cardiologists in Europe. Funding Acknowledgement Type of funding source: None
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,016 | 0,039 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,001 | 0,008 |
| Intégrité de la recherche | 0,001 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».