The accountability of clinical education: its definition and assessment
Bibliographic record
Abstract
BACKGROUND: Medical education is not exempt from increasing societal expectations of accountability. Competition for financial resources requires medical educators to demonstrate cost-effective educational practice; health care practitioners, the products of medical education programmes, must meet increasing standards of professionalism; the culture of evidence-based medicine demands an evaluation of the effect educational programmes have on health care and service delivery. Educators cannot demonstrate that graduates possess the required attributes, or that their programmes have the desired impact on health care without appropriate assessment tools and measures of outcome. OBJECTIVE: To determine to what extent currently available assessment approaches can measure potentially relevant medical education outcomes addressing practitioner performance, health care delivery and population health, in order to highlight areas in need of research and development. METHODS: Illustrative publications about desirable professional behaviour were synthesized to obtain examples of required competencies and health outcomes. A MEDLINE search for available assessment tools and measures of health outcome was performed. RESULTS: There are extensive tools for assessing clinical skills and knowledge. Some work has been done on the use of professional judgement for assessing professional behaviours; scholarship; and multiprofessional team working; but much more is needed. Very little literature exists on assessing group attributes of professionals, such as clinical governance, evidence-based practice and workforce allocation, and even less on examining individual patient or population health indices. CONCLUSIONS: The challenge facing medical educators is to develop new tools, many of which will rely on professional judgement, for assessing these broader competencies and outcomes.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.003 | 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 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".