Explicit Dialogue About the Purpose of Hospital Admission Is Essential: How Different Perspectives Affect Teamwork, Trust, and Patient Care
Bibliographic record
Abstract
PURPOSE: The authors previously found that attending physicians conceptualize hospital admission purpose according to 3 perspectives: one focused dominantly on discharge, one on monitoring and managing chronic conditions, and one on optimizing overall patient health. Given implications of varying perspectives for patient care and team collaboration, this study explored how purpose of admission is negotiated and enacted within clinical teaching teams. METHOD: Direct observations and field interviews took place in 2 internal medicine teaching units at 2 teaching hospitals in Ontario, Canada, in summer 2017. A constructivist grounded theory approach was used to inform data collection and analysis. RESULTS: The 54 participants included attendings, residents, and medical students. Management decisions were identified across 185 patients. Attendings and senior medical residents (second- and third-year residents) were each observed to enact one dominant perspective, while junior trainees (first-year residents and students) appeared less fixed in their perspectives. Teams were not observed discussing purpose of admission explicitly; however, differing perspectives were present and enacted. These differences became most noticeable when at the extremes (discharge focused vs optimization focused) or between senior medical residents and attendings. Attendings implicitly signaled and enforced their perspectives, using authority to shut down and redirect discussion. Trainees' maneuvers for enacting their perspectives ranged from direct advocacy to covert manipulation (passive avoidance/forgetting and delaying until attending changeover). CONCLUSIONS: Failing to negotiate and explicitly label perspectives on purpose of admission may lead to attendings and senior medical residents working at cross-purposes and to trainees participating in covert maneuvers, potentially affecting trust and professional identify development.
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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 | 0.021 | 0.049 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.017 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.004 |
| 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 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".