Enhancing the Quality of Morbidity and Mortality Rounds: The Ottawa M&M Model
Bibliographic record
Abstract
OBJECTIVES: The objective of this study was to determine the feasibility and acceptability of a structured morbidity and mortality (M&M) rounds model through an innovative educational intervention. METHODS: The authors engaged the Departments of Emergency Medicine (EM) and Trauma Services at a tertiary care teaching hospital. A needs assessment was performed; the Ottawa M&M rounds model was developed, implemented, and then evaluated as a four-part intervention. This consisted of: 1) physician training on case selection and analysis, 2) engaging interprofessional members, 3) disseminating lessons learned, and 4) creating an administrative pathway for acting on issues identified through the M&M rounds. The measures of intervention feasibility included the proportion of sessions adherent to the new model and M&M rounds attendance. Pre- and postintervention surveys of presenters and attendees were used to determine intervention acceptability. M&M presentation content was reviewed to determine the most frequently adopted components of the model. RESULTS: Nine of 14 (64.3%) sessions were adherent to three of four components of the Ottawa M&M Model. Of those M&M attendees who responded to the survey (796 of 912, 87.2%), improvements were found in M&M rounds attendance as well as perceived effect on clinical practice at both individual and departmental levels. Thirty-seven case presentations were analyzed and improvements postintervention were found in appropriate case selection and recognition of cognitive and system issues. CONCLUSIONS: The Ottawa M&M Model was a feasible intervention that was perceived to be effective by both presenters and attendees. The authors believe that this could be readily applied to any hospital department seeking to enhance quality of care and patient safety.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".