Teaching M&M rounds skills: enhancing and assessing patient safety competencies using the Ottawa M&M model
Bibliographic record
Abstract
BACKGROUND: Postgraduate medical education bodies and national patient safety institutes recommend that trainees develop patient safety competencies such as those for Morbidity and Mortality (M&M) rounds, yet there exists no model for their educational delivery. OBJECTIVE: We studied the effect of a single educational intervention on emergency medicine residents' aptitudes in selecting and analysing M&M rounds cases. METHODS: In this before-and-after study, participants attended an 1 h educational session based on the previously described Ottawa Morbidity and Mortality Model (OM3). Residents were asked to submit a case suitable for M&M rounds both preintervention and postintervention. A novel M&M rounds case critique tool was developed based on OM3 and used to assign a numerical score to each submitted case. Our primary outcome was an increase in mean scores between phases using the case critique tool. An a priori score increase of 1 was defined as educationally significant. Data were analysed using a paired Student's t test. RESULTS: A total of 19 residents were recruited for our pre-intervention and 15 residents for the post-intervention analysis. Mean M&M rounds case critique scores increased from 5.53 to 8.67 (p<0.01) between phases. Residents reported higher comfort with structured case selection and analysis, with an increase in five-point Likert scale means of 2.32 and 3.69 (p<0.01). CONCLUSIONS: We found that residents were more effective at M&M rounds case selection and analysis after our focused 1 h educational intervention. Training programmes should consider an M&M rounds training model to ensure future physicians have these skills for 21st-century practice.
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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 | 0.005 | 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 | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".