Handovers Among Staff Intensivists: A Study of Information Loss and Clinical Accuracy to Anticipate Events*
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVES: Handovers are associated with medical errors, and our primary objective is to identify missed diagnosis and goals immediately after a shift handover. Our secondary objective is to assess clinicians' diagnostic accuracy in anticipating clinical events during the night shift. DESIGN: Single-center prospective observational cohort study. SETTING: Thirty-bed tertiary ICU in Sao Paulo, Brazil. PATIENTS: Three-hundred fifty-two patient encounters over 44 day-to-night handovers. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We used a multimethods approach to measure transmission of information among staff physicians on diagnoses and goals for the night shift. We surveyed clinicians immediately after a handover and identified clinical events through chart abstractions and interviews with clinicians the next morning. Nighttime clinicians correctly identified 454 of 857 diagnoses (53%; 95% CI 50-56) and 123 of 304 goals (40%; 95% CI, 35-46). Daytime clinicians were more sensitive (65% vs 46%; p < 0.01) but less specific (82% vs 91%; p < 0.01) than nighttime clinicians in anticipating clinical events at night, resulting in similar accuracy (area under the receiver operating characteristic curve, 0.74 [95% CI, 0.68-0.79] vs 0.68 [95% CI 0.63-0.74]; p = 0.09). The positive predictive value of both daytime and nighttime clinicians was low (13% vs 17%; p = 0.2). Gaps in diagnosis and anticipation of events were more pronounced in neurologic diagnoses. CONCLUSIONS: Among staff intensivists, diagnoses and goals of treatment are either not conveyed or retained 50-60% of the cases immediately after a handover. Clinicians have limited ability to anticipate events, and the expectation that anticipatory guidance can inform handovers needs to be balanced against information overload. Handovers among staff intensivists showed more gaps in the identification of diagnostic uncertainty and for neurologic diagnoses, which could benefit from communication strategies such as cognitive checklists, prioritizing discussion of neurologic patients, and brief combined clinical examination at handover.
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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 | 0.000 | 0.016 |
| 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 | 0.001 |
| 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 it