The rules of the game: interprofessional collaboration on the intensive care unit team
Bibliographic record
Abstract
BACKGROUND: The intensive care unit (ICU) is a nexus for interspecialty and interdisciplinary tensions because of its pivotal role in the care of the hospital's most critically ill patients and in the management of critical care resources. In an environment charged with temporal, financial and professional tensions, learning how to get results collaboratively is a critical aspect of professional competence. This study explored how team members in the ICU interact to achieve daily clinical goals, delineate professional boundaries and negotiate complex systems issues. METHODS: Seven 1-hour focus groups were conducted with ICU team members in two hospitals. Participants consisted of four nursing groups (n = 27), two resident groups (n = 6) and one intensivist group (n = 4). Interviews were audio-recorded, anonymized and transcribed. With the use of a standard qualitative approach, transcripts were analyzed iteratively for recurrent themes by four researchers. RESULTS: Team members articulated their perceptions of the mechanisms by which team collaboration was achieved or undermined in a complex and high-pressure context. Two mechanisms were recurrently described: the perception of 'ownership' and the process of 'trade'. Analysis of these mechanisms reveals how power is commodified, possessed and exchanged as team members negotiate their daily needs and goals with one another. CONCLUSION: Our data provide a non-idealized depiction of how health care professionals function on a team so as to meet both individual and collective goals. We contend that the concept of 'team' must move beyond the rhetoric of 'cooperation' and towards a more authentic depiction of the skills and strategies required to function in the competitive setting of the interprofessional health care team.
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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 | 0.010 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.018 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".