MétaCan
Menu
Back to cohort
Record W4405413200 · doi:10.1080/10401334.2024.2439850

Supporting Patient Involvement in U.S. Medical Education Through Changes in Accreditation

2024· article· en· W4405413200 on OpenAlexaff
Sean Tackett, Yvonne Steinert, Jeffrey L. Jackson, Gayle Johnson Adams, Darcy A. Reed, Cynthia Whitehead, Scott M. Wright

Bibliographic record

VenueTeaching and Learning in Medicine · 2024
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsUniversity of TorontoMcGill University Health Centre
Fundersnot available
KeywordsAccreditationCurriculumGraduate medical educationMedical educationCorporate governanceMedicinePolitical sciencePublic relationsPsychologyBusinessPedagogy

Abstract

fetched live from OpenAlex

For over half of a century, there have been calls for greater patient and community involvement in U.S. medical education. Accrediting agencies, as the regulatory authorities for medical education, develop policies that impact every program in the U.S.; they have the ability to support patient involvement across the medical education system. In this article, we first review the requirements of U.S. accrediting agencies for undergraduate and graduate medical education to involve patients in educational programs. While agencies have patient members on their committees, they do little to encourage patient involvement through their standards or procedures. We then describe opportunities for accreditation to support patient involvement across teaching and learning activities, curriculum design and evaluation, policymaking and governance, and scholarly endeavors. We link these opportunities to specific standards that could be revised or have their data reporting requirements adjusted. U.S. agencies could also follow the examples of their counterparts outside the U.S., which have created new standards to encourage patient involvement. Ensuring patient representation on educational programs' governing and policymaking bodies is one among many immediate actions that could be taken by accrediting authorities to encourage system-level reforms. As medical school and residency training represent the beginnings of decades of practice for physicians, properly involving patients would maximize benefits for learners, educators, and society.

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)0.005
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.823
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0000.000

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 head0.023
GPT teacher head0.392
Teacher spread0.369 · 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 designOther design
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

Citations2
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueTeaching and Learning in MedicineSame topicInnovations in Medical EducationFrench-language works237,207