Getting the message: a quality improvement initiative to reduce pages sent to the wrong physician
Bibliographic record
Abstract
BACKGROUND: One in seven pages are sent to the wrong physician and may result in unnecessary delays that potentially threaten patient safety. The authors aimed to implement a new team-based paging process to reduce pages sent to the wrong physician. METHODS: The authors redesigned the paging process on general internal medicine (GIM) wards at a Canadian academic medical centre by implementing a standardised team-based paging process (pages directed to one physician responsible for receiving pages on behalf of the entire physician team) using rapid-cycle change methods. The authors evaluated the intervention using a controlled before-after study design by measuring pages sent to the wrong physician before and after implementation of the redesigned paging process. RESULTS: Pages sent to the wrong physician from the GIM (intervention) wards decreased from 14% to 3% (11% reduction), while pages sent to the wrong physician from control wards fell from 13% to 7% (6% reduction). The difference between the intervention wards and the control wards was significant (5% greater reduction in the intervention group compared with the control group, p=0.008). Nurses were more satisfied with team-based paging than the existing paging process. Team-based paging may, however, introduce changes in communication workflow that lead to increased paging interruptions for certain members of the physician team. CONCLUSIONS: The authors successfully redesigned the hospital's paging process to decrease pages sent to the wrong physician. They recommend that the frequency of pages sent to the wrong physician is measured and changes be implemented to paging processes to reduce this error.
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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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".