Clinicians’ perspectives on quality: do they match accreditation standards?
Bibliographic record
Abstract
BACKGROUND: Quality of training is determined through programs' compliance with accreditation standards, often set for a number of years. However, perspectives on quality of training within these standards may differ from the clinicians' perspectives on quality of training. Knowledge on how standards relate to clinicians' perspectives on quality of training is currently lacking yet is expected to lead to improved accreditation design. METHODS: This qualitative study design was based on a case-study research approach. We analyzed accreditation standards and conducted 29 interviews with accreditors, clinical supervisors and trainees across Australia and the Netherlands about the quality and accreditation of specialist medical training programs. The perspectives were coded and either if applicable compared to national accreditation standards of both jurisdictions, or thematized to the way stakeholders encounter accreditation standards in practice. RESULTS: There were two evident matches and four mismatches between the perspectives of clinicians and the accreditation standards. The matches are: (1) accreditation is necessary (2) trainees are the best source for quality measures. The mismatches are: (3) fundamental training aspects that accreditation standards do not capture: the balance between training and service provision, and trainee empowerment (4) using standards lack dynamism and (5) quality improvement; driven by standards or intrinsic motivation of healthcare professionals. CONCLUSION: In our Australian and Dutch health education cases accreditation is an accepted phenomenon which may be improved by trainee empowerment, a dynamic updating process of standards and by flexibility in its use.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".