In-House, Overnight Physician Staffing: A Cross-Sectional Survey of Canadian Adult ICUs
Bibliographic record
Abstract
OBJECTIVES: Overnight physician staffing in the ICU has been recommended by the Society of Critical Care Medicine and the Leapfrog Consortium. We conducted a survey to review practice in the current era and to compare this with results from a 2006 survey. DESIGN: Cross-sectional survey. SETTING: Canadian adult ICUs. PARTICIPANTS: ICU directors. INTERVENTIONS: None. MEASUREMENT AND MAIN RESULTS: A 29-question survey was sent to ICU directors describing overnight staffing by residents, fellows, nurse practitioners, and staff physicians, as well as duty duration, clinical responsibilities, and unit characteristics. We established contact with 122 ICU directors, of whom 107 (88%) responded. Of the 107 units, 60 (56%) had overnight in-house physicians. Compared with ICUs without overnight in-house physician coverage, ICUs with in-house physicians were in larger hospitals (p < 0.0001), had more beds (p < 0.0001), had more ventilated patients (p < 0.0001), and had more admissions (p < 0.0001). Overnight in-house physicians were first year residents (R1) in 20 of 60 (33%), second to fifth year residents (R2-R5) in 46 of 60 (77%), and Critical Care Medicine trainees in 19 of 60 (32%). Advanced practice nurses provided overnight coverage in four of 107 ICUs (4%). The most senior in-house physician was a staff physician in 12 of 60 ICUs (20%), a Critical Care Medicine trainee in 14 of 60 (23%), and a resident (R2-R5) in 20 of 60 (33%). The duration of overnight duty was on average 20-24 hours in 22 of 46 units (48%) with R2-R5 residents and 14 of 19 units (74%) covered by Critical Care Medicine trainees. CONCLUSIONS: Variability of in-house overnight physician presence in Canadian adult ICUs is linked to therapeutic complexity and unit characteristics and has not changed significantly over the decade since our 2006 survey. Additional evidence about patient and resident outcomes would better inform decisions to revise physician scheduling in Canadian ICUs.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".