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Record W4391582025 · doi:10.5334/pme.963

Enabling Implementation of Competency Based Medical Education through an Outcomes-Focused Accreditation System

2024· article· en· W4391582025 on OpenAlexafffundabout
Timothy R. Dalseg, Brent Thoma, Keith Wycliffe-Jones, Jason R. Frank, Sarah Taber

Bibliographic record

VenuePerspectives on Medical Education · 2024
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsCanadian Network for Innovation in EducationUniversity of OttawaRoyal College of Physicians and Surgeons of CanadaUniversity of CalgaryUniversity of SaskatchewanToronto General HospitalUniversity of Toronto
FundersQueen's UniversityCanadian Internet Registration AuthorityRoyal College of Physicians and Surgeons of CanadaUniversity of Ottawa
KeywordsAccreditationMedical educationCertification and AccreditationQuality assuranceProcess (computing)MedicineEngineering managementComputer scienceEngineering

Abstract

fetched live from OpenAlex

Competency based medical education is being adopted around the world. Accreditation plays a vital role as an enabler in the adoption and implementation of competency based medical education, but little has been published about how the design of an accreditation system facilitates this transformation. The Canadian postgraduate medical education environment has recently transitioned to an outcomes-based accreditation system in parallel with the adoption of competency based medical education. Using the Canadian example, we characterize four features of an accreditation system that can facilitate the implementation of competency based medical education: theoretical underpinning, quality focus, accreditation standards, and accreditation processes. Alignment of the underlying educational theories within the accreditation system and educational paradigm drives change in a consistent and desired direction. An accreditation system that prioritizes quality improvement over quality assurance promotes educational system development and progressive change. Accreditation standards that achieve the difficult balance of being sufficiently detailed yet flexible foster a high fidelity of implementation without stifling innovation. Finally, accreditation processes that recognize the change process, encourage program development, and are not overly punitive all enable the implementation of competency based medical education. We also discuss the ways in which accreditation can simultaneously hinder the implementation of this approach. As education bodies adopt competency based medical education, particular attention should be paid to the role that accreditation plays in successful 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.

How this classification was reachedexpand

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)0.002
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.742
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.022
GPT teacher head0.419
Teacher spread0.397 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations14
Published2024
Admission routes3
Has abstractyes

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