Effects of efforts to optimise morbidity and mortality rounds to serve contemporary quality improvement and educational goals: a systematic review
Bibliographic record
Abstract
BACKGROUND: The quality and safety movement has reinvigorated interest in optimising morbidity and mortality (M&M) rounds. We performed a systematic review to identify effective means of updating M&M rounds to (1) identify and address quality and safety issues, and (2) address contemporary educational goals. METHODS: Relevant databases (Medline, Embase, PubMed, Education Resource Information Centre, Cumulative Index to Nursing and Allied Health Literature, Healthstar, and Global Health) were searched to identify primary sources. Studies were included if they (1) investigated an intervention applied to M&M rounds, (2) reported outcomes relevant to the identification of quality and safety issues, or educational outcomes relevant to quality improvement (QI), patient safety or general medical education and (3) included a control group. Study quality was assessed using the Medical Education Research Study Quality Instrument and Newcastle-Ottawa Scale-Education instruments. Given the heterogeneity of interventions and outcome measures, results were analysed thematically. RESULTS: The final analysis included 19 studies. We identified multiple effective strategies (updating objectives, standardising elements of rounds and attaching rounds to a formal quality committee) to optimise M&M rounds for a QI/safety purpose. These efforts were associated with successful integration of quality and safety content into rounds, and increased implementation of QI interventions. Consistent effects on educational outcomes were difficult to identify, likely due to the use of methodologies ill-fitted for educational research. CONCLUSIONS: These results are encouraging for those seeking to optimise the quality and safety mission of M&M rounds. However, the inability to identify consistent educational effects suggests the investigation of M&M rounds could benefit from additional methodologies (qualitative, mixed methods) in order to understand the complex mechanisms driving learning at M&M rounds.
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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 | 0.021 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".