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Record W3024407389 · doi:10.22374/cjgim.v14i3.317

EPAs for the Ambulatory Internist in Translation: Findings from a Canadian Multi-Center Survey

2019· article· en· W3024407389 on OpenAlex
Rupal Shah, Lindsay Melvin, Rodrigo B. Cavalcanti

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCanadian Journal of General Internal Medicine · 2019
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineAccreditationContext (archaeology)AmbulatoryScope (computer science)Medical educationFamily medicineMEDLINEAmbulatory careHealth careSurgery

Abstract

fetched live from OpenAlex

Background Increased demand for outpatient care has made defining the role of ambulatory general internists an educational priority. Canadian residency programs are transitioning towards competency-based education, where learning goals are articulated as entrustable professional activities (EPAs). Engaging frontline internists in the validation of context-specific EPAs is important for implementation. Objective This study describes a consensus approach for developing EPAs for ambulatory general internal medicine (GIM) training and results of a Canada-wide survey seeking feedback from academic internists. Methods In 2016, we reviewed Royal College of Physicians and Surgeons of Canada GIM accreditation documents, and systematic literature search results for internal medicine ambulatory training objectives, to draft EPAs. EPAs were revised via expert consensus at the University of Toronto. A survey was distributed to Canadian academic internists to determine level of agreement on proposed EPAs. Consensus was defined as greater than 80% inter-rater agreement. Open-ended questions explored reasons for disagreements, which were reviewed independently by authors and iteratively organized into categories. Results Eight EPAs were generated. The survey response rate was 24.9% (63/253). Consensus was achieved on all EPAs except obstetrical medicine (49/63, 77.8%). Reasons for disagreements reflected a variable understanding of EPA concepts by respondents. Where understood well, disagreements fell into 3 main categories: (1) further training required, (2) not within internal medicine scope, and (3) implementation barriers. Conclusions Frontline academic physicians are pivotal in validating proposed EPAs. Disagreements were either content or concept related and recognizing these diverse perspectives can help clinician-educators predict and prepare for challenges with EPA implementation.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.227
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.053
GPT teacher head0.334
Teacher spread0.281 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it