“It’s Parallel Universes”
Bibliographic record
Abstract
OBJECTIVES: The intensivist-led model of ICU care requires surgical consultants and the ICU team to collaborate in the care of ICU patients and to communicate effectively across teams. We sought to characterize communication between intensivists and surgeons and to assess enablers and barriers of effective communication. DESIGN: Qualitative interview study. An inductive data analysis approach was taken. SETTING: Seven intensivist-led ICUs in four academic hospitals. SUBJECTS: Surgeons (attendings and residents), intensivists (attendings and residents), and ICU nurses participating in the care of surgical patients in the ICU. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Communication enablers and barriers existed at two distinct levels: 1) organizational and 2) cultural. At an organizational level, participants identified that formally sanctioned communication structures and processes often acted as barriers to communication. Participants had developed informal strategies to improve communication. At a cultural level, surgical and ICU participants often expressed conflicting perspectives regarding patient ownership, scope of practice, and clinical expertise. CONCLUSIONS: Major barriers to optimal communication between surgical and ICU teams exist in the intensivist-led ICU environment. Many are related to the structures and processes meant to facilitate communication across teams and others to how some aspects of care in the ICU are conceptualized. Multiple actionable opportunities exist to improve communication in the intensivist-led ICU.
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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 | 0.011 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.070 |
| Scholarly communication | 0.009 | 0.028 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".