Notice bibliographique
Résumé
Graduate medical education (GME) worldwide is undergoing a fundamental transition from a knowledge-based to a competency-based medical education (CBME) system.1 In the United States, the Next Accreditation System (NAS) of the Accreditation Council for Graduate Medical Education (ACGME) is using defined competency endpoints with intermediate milestones as the framework for CBME.2 Four articles in this month's issue of Academic Emergency Medicine illustrate the historical context of emergency medicine (EM) milestone development,3 describe the validation study used to refine the EM milestones,4 give us an example of how a multiorganizational group of stakeholders provides a roadmap for one milestone (PC-12),5 and remind us that GME milestones are on a continuum of development from undergraduate medical education, to GME, to continuing medical education.6 Milestones are descriptors of the expected abilities of physicians at defined stages of expertise development. Milestones are essential to a competency-based approach and are under development in many countries at this time. Beeson et al.3 describe the historical context of the EM milestone development. Representatives of eight stakeholder organizations comprised the EM milestone-working group (EM MWG). In a relatively short time, the EM MWG developed the first draft of milestones, and through collaboration with the ACGME Review Committee in Emergency Medicine, was able to incorporate EM milestones in the EM core program requirements. As an early adopter of NAS, EM has set the standard for the design, alignment, and integration of milestones into the educational framework of the future and can serve as a model for other specialties. Korte et al.4 describe the survey used as a validation study of the EM draft milestones. Despite a short 16-day survey period, the study received responses from over 60% of residencies on 24 EM subcompetencies and 255 milestones. Based on the results, the EM MWG eliminated one subcompetency and changed the number of subcompetency milestones to 227. Lewiss et al.5 describe the efforts of a multiorganizational committee composed of representatives from four stakeholder organizations to address EM milestone PC-12 (goal-directed focused ultrasound). This comprehensive article describes the historical perspective of emergency ultrasound (EUS) training, a description of core EUS skills needed by graduating EM residents, suggested blueprints for residency training, and a description of assessment tools. Santen et al.6 remind us that the NAS is on a continuum of professional development from medical student, to resident, to practicing physician. In their provocative article, the authors indicate that graduating medical students have not been fully taught or assessed on the Level 1 EM milestones requisite for entering EM residencies. The authors propose that responsibilities for Level 1 milestones be shared between medical schools and residencies. This, however, creates other challenges: how will medical school and residency obligations be determined for Level 1 milestone assessment? Will all medical schools coordinate among themselves with minimum Level 1 milestone requirements? How can program directors assure that incoming interns have met the Level 1 milestones at medical school graduation, unless standardized assessment tools exist for graduating medical students? Is there a need to develop entry-to-residency “bootcamps,” as other specialties have done?7 The Postgraduate Orientation Assessment (POA) is one potential approach.8 The POA is a tool to assess incoming residents in general competencies common to all specialties. In our opinion, pairing the general POA with specialty-specific assessment tools can ensure that all residents are at Level 1 milestones when starting residencies. Until medical schools develop reliable assessment tools for graduating medical students for Level 1 milestones for all specialties, we propose the adoption of a general POA tool plus specialty-specific Level 1 milestone assessments at the local residency institution as a key component of residency orientation. Where are we going? The future of CBME will require significant changes in the learning environment, resident assessment frequency, and faculty development. The learning environment will need to evolve to be based on outcomes and focused on the learner and be nonhierarchical.9 Assessment of professional competence will need to be based on multiple assessment methods, each with a minimum of 8 to 10 observations to ensure reliable inferences.10 Faculty will have to take on new roles to coach residents progressing through the milestones and assess their achievements.11 Effective faculty performance will be measured on the assessment skill set they demonstrate as much as the knowledge or procedural skills they may have.12 These changes will result in the transformation of education from a hierarchy focused on the teacher to a network focused on the learner. The resulting energy released by this transformation will serve as fuel for innovative networks of educators involved in CBME. EM has the room with a view on the changing health care system.13 It can also serve as the canary in the coal mine for the NAS's journey into CBME.
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 | 0,020 | 0,062 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,003 | 0,003 |
| Études des sciences et des technologies | 0,006 | 0,023 |
| Communication savante | 0,014 | 0,031 |
| Science ouverte | 0,004 | 0,011 |
| Intégrité de la recherche | 0,007 | 0,017 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,019 | 0,007 |
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 ».