Morning Handover of On-Call Issues
Bibliographic record
Abstract
IMPORTANCE: Handover is the process of transferring pertinent patient information and clinical responsibility between health care practitioners. Few studies have examined morning handover from the overnight trainee to the daytime team. OBJECTIVE: To characterize current morning handover practices in 2 academic medical centers by assessing the frequency of omissions of clinically important overnight issues during morning handover and identifying factors that influence the occurrence of such omissions. DESIGN, SETTING, AND PARTICIPANTS: A prospective, point-prevalence study was conducted in the general internal medicine wards of 2 tertiary care academic medical centers in Toronto, Ontario, Canada, in 2012 and 2013. Participants included on-call third-year medical students and first- and second-year residents. MAIN OUTCOMES AND MEASURES: Completeness of morning handover of clinically important overnight issues identified using a targeted medical records review and processes of morning handover characterized by direct observation. RESULTS: We identified 141 clinically important overnight issues during 26 days of observation. The on-call trainee omitted 40.4% (95% CI, 32.3%-48.5%) of clinically important issues during morning handover and did not document any information in the patient's medical record for 85.8% (95% CI 80.1%-91.6%) of these issues. By univariate analysis, running the list patient-by-patient (ie, the entire team discusses each patient) (OR, 4.32; 95% CI, 1.94-9.60; P < .001) and using a dedicated handover location (OR, 2.61; 95% CI, 1.30-5.22; P = .007) positively correlated with handover of an issue taking place, whereas distractions in the meeting area inversely correlated with the likelihood of handover of an issue taking place (OR, 0.96 for every increase in 1 distraction; 95% CI, 0.93-0.98; P = .002). Using a multivariate mixed-effects model, only running the list remained as an independent predictor of the handover of an issue (OR, 3.80; 95% CI, 1.25-11.49; P = .02). CONCLUSIONS AND RELEVANCE: On-call trainees omit numerous clinically important issues when handing over to the daytime team. Training programs should introduce educational activities and workflow changes, and provide dedicated time and a distraction-free environment, to improve handover of on-call issues.
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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 | 0.003 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".