Turning a new “page”: ways to decrease the number of pages after hours without compromising patient care
Bibliographic record
Abstract
Background: Pages to house staff after hours, especially overnight, lead to interrupted sleep and fatigue the next day. Although some pages are urgent, others may not need an immediate response. In this study we aimed to identify unwarranted pages and to establish ways to reduce them. Methods: Over 2 months, all pages to the Department of Pediatric Urology at the Hospital for Sick Children in Toronto, Canada, during call hours were documented, including the assessment of the responding physicians of their medical necessity. After analyzing the reasons for inappropriate pages, we took several steps to try to reduce them without impairing patient care. One year later, pages were tracked again to evaluate the efficacy of our interventions. Results: In the initial measurement period, no calls from parents and approximately 50% of the in-hospital pages (15 of 36 pages from the wards, 27 of 49 pages from the emergency department, 17 of 31 pages requesting consultations, and 8 of 8 pages from the inhouse pharmacy and outside pharmacies) were considered medically urgent. The reasons for unwarranted pages were inconsistent parent teaching, lack of adequate triaging and prioritizing on the ward and lack of awareness of the structure of the on-call provisions among different services in the hospital. Several steps were taken to streamline the teaching of parents and nurses, standardize information, provide alternative means of communication within the hospital and restrict parents’ access by phone to the urologist on call. One year later, the number of pages had decreased by 70%. Conclusion: Although physician coverage throughout the day and night is necessary for high-quality and safe patient care, communication with on-call physicians should be only for appropriate reasons. The provision of consistent teaching and alternative communication channels can improve patient care as well as decrease the number of after-hour pages.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 0.004 |
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 source (direct Gemma or distilled Codex), 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".