Development of Entrustable Professional Activities for Advanced Inflammatory Bowel Disease Fellowship Training in the United States
Bibliographic record
Abstract
BACKGROUND: The level of inflammatory bowel disease (IBD) training in general gastroenterology fellowship is often insufficient to prepare trainees to deliver advanced IBD care in practice. Advanced IBD fellowships have been developed to fill this training gap, but there is no established curriculum, and significant variability exists across programs. Entrustable professional activities (EPAs) are practical and realistic objectives that define essential tasks of a specialty that physicians should master to be competent during independent practice. The American College of Gastroenterology (ACG) and Crohn's & Colitis Foundation (Foundation) established a task force to develop and appraise EPAs for advanced IBD fellowship. METHODS: Entrustable professional activities were developed using a multistep approach in a similar manner to other specialties. Initial EPAs identified via focus groups were evaluated, critiqued, and changed using an iterative model of feedback. The final EPAs were selected after the task force conducted a 3-phase modified Delphi method consisting of 2 sequential rounds of web-based voting and an in-person consensus meeting. RESULTS: Ten EPAs for advanced IBD fellowship were established including detailed descriptions with the associated knowledge, skills, and attitudes for each that can serve as curricular milestones. CONCLUSION: Ten EPAs describing the core work of an advanced IBD fellowship-trained physician have been established by a multisociety task force. Creating EPAs for an advanced curriculum comes with unique challenges, particularly the need to prevent duplication of prior training competencies while demonstrating the potential for unique milestones.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.063 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".