Effects of Unit Census and Patient Acuity Levels on Discussions During Patient Rounds
Bibliographic record
Abstract
OBJECTIVES: PICU teams adapt the duration of patient rounding discussions to accommodate varying contextual factors, such as unit census and patient acuity. Although studies establish that shorter discussions can lead to the omission of critical patient information, little is known about how teams adapt their rounding discussions about essential patient topics (i.e., introduction/history, acute clinical status, care plans) in response to changing contexts. To fill this gap, we examined how census and patient acuity impact time spent discussing essential topics during individual patient encounters. DESIGN: Observational study. SETTING: PICU at a university-affiliated children's hospital, Toronto, ON, Canada. SUBJECTS: Interprofessional morning rounding teams. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We observed 165 individual patient encounters during morning rounds over 10 weeks. Regardless of census or patient acuity, the duration of patient introductions/history did not change. When census was high versus low, acute clinical status discussions significantly decreased for both low acuity patients (00 min:50 s high census; 01 min:39 s low census; -49.5% change) and high acuity patients (01 min:10 s high census; 02 min:02 s low census; -42.6% change). Durations of care plan discussions significantly reduced as a function of census (01 min:19 s high census; 02 min:52 s low census; -54.7% change) for low but not high acuity patients. CONCLUSIONS: Under high census and patient acuity levels, rounding teams disproportionately shorten time spent discussing essential patient topics. Of note, while teams preserved time to plan the care for acute patients, they cut care plan discussions of low acuity patients. This study provides needed detail regarding how rounding teams adapt their discussions of essential topics and establishes a foundation for consideration of varying contextual factors in the design of rounding guidelines. As ICUs are challenged with increasing census and patient acuity levels, it is critical that we turn our attention to these contextual aspects and understand how these adaptations impact clinical outcomes to address them.
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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 | 0.004 | 0.039 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".