Patient Safety Training Simulations Based on Competency Criteria of the Accreditation Council for Graduate Medical Education
Bibliographic record
Abstract
This report reviews and critically evaluates the development of 3 movements in healthcare that have had a profound impact on changes occurring at all levels of medical education: patient safety, healthcare simulation, and competency-based education (exemplified by the Accreditation Council for Graduate Medical Education). The authors performed a critical and selective review of the literature from 1999 to 2011 to identify uses of simulation to address patient-safety issues aligned according to the Accreditation Council for Graduate Medical Education 6 core competencies: (1) patient care; (2) medical knowledge; (3) interpersonal and communication skills; (4) professionalism; (5) practice-based learning; and (6) systems-based practice. The research synthesis is reported to inform and provide evidence about how simulation is used to train and evaluate learners on a range of patient-safety issues for each of the core competencies: There is emerging evidence that simulation can be used in training efforts to reduce medical errors related to medical knowledge and patient care (particular invasive procedures as well as improved communication and teamwork skills). There remains limited evidence on its impact to improve patient safety related to more complex competencies of practice-based learning and systems-based practice. Simulation-based learning can lead to positive patient outcomes and reduction of medical errors particularly when used for individual skills. However, particular attention needs to be placed on the organizational context in which it is implemented if improvements in practice-based learning and systems-based practice are to be realized.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".