Bibliographic record
Abstract
An effective interprofessional medical team can efficiently coordinate health care providers to achieve the collective outcome of improving each patient's health. To determine how current teams function, four groups of business students independently observed interprofessional work rounds on four different internal medicine services in a typical academic hospital and also interviewed the participants. In all instances, caregivers had formed working groups rather than working teams. Participants consistently exhibited parallel interdependence (individuals working alone and assuming their work would be coordinated with other caregivers) rather than reciprocal interdependence (individuals working together to actively coordinate patient care), the hallmark of effective teams. With one exception, the organization was hierarchical, with the senior attending physician possessing the authority. The interns exclusively communicated with the attending physician in one-on-one conversations that excluded all other members of the team. Although nurses and pharmacists were often present, they never contributed their ideas and rarely spoke.The authors draw on these observations to form recommendations for enhancing interprofessional rounding teams. These are to include the bedside nurse, pharmacist, and case manager as team members, begin with a formal team launch that encourages active participation by all team members, use succinct communication protocols, conduct work rounds in a quiet, distraction-free environment, have teams remain together for longer durations, and receive teamwork training and periodic coaching. High-performing businesses have effectively used teams for decades to achieve their goals, and health care professionals should follow this example.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".