The role of accreditation in 21st century health professions education: report of an International Consensus Group
Bibliographic record
Abstract
BACKGROUND: Accreditation is considered an essential ingredient for an effective system of health professions education (HPE) globally. While accreditation systems exist in various forms worldwide, there has been little written about the contemporary enterprise of accreditation and even less about its role in improving health care outcomes. We set out to 1) identify a global, contemporary definition of accreditation in the health professions, 2) describe the relationship of educational accreditation to health care outcomes, 3) identify important questions and recurring issues in twenty-first century HPE accreditation, and 4) propose a framework of essential ingredients in present-day HPE accreditation. METHODS: We identified health professions accreditation leaders via a literature search and a Google search of HPE institutions, as well as by accessing the networks of other leaders. These leaders were invited to join an international consensus consortium to advance the scholarship and thinking about HPE accreditation. We describe the consensus findings from the International Health Professions Accreditation Outcomes Consortium (IHPAOC). RESULTS: We define accreditation as the process of formal evaluation of an educational program, institution, or system against defined standards by an external body for the purposes of quality assurance and enhancement. In the context of HPE, accreditation is distinct from other forms of program evaluation or research. Accreditation can enhance health care outcomes because of its ability to influence and standardize the quality of training programs, continuously enhance curriculum to align with population needs, and improve learning environments. We describe ten fundamental and recurring elements of accreditation systems commonly found in HPE and provide an overview of five emerging developments in accreditation in the health professions based on the consensus findings. CONCLUSIONS: Accreditation has taken on greater importance in contemporary HPE. These consensus findings provide frameworks of core elements of accreditation systems and both recurring and emerging design issues. HPE scholars, educators, and leaders can build on these frameworks to advance research, development, and operation of high-quality accreditation systems worldwide.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.282 | 0.183 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.016 | 0.015 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.010 | 0.018 |
| Research integrity | 0.012 | 0.018 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".