Is It Time to Be More Explicit About the Purpose of a Hospital Admission?
Bibliographic record
Abstract
PURPOSE: Patient care suffers when teaching teams fail to achieve a shared understanding of problems to be addressed during a hospital admission. In academic contexts where attending physicians take turns supervising, practice variability may contribute to undermining this shared understanding. Exploring variability around what constitutes the purpose of the hospital admission was the focus of this study. METHOD: Constructivist grounded theory was used to inform data collection and analysis of this two-phase study, conducted in London and Hamilton, Ontario, Canada, in 2012. In phase 1, interviews with 24 attending physicians from 2 academic health centers were conducted. Phase 2 involved analyzing 18 audio-recorded admission case review discussions in relation to the emergent theory from phase 1. Participants for phase 2 were 7 different attendings, 7 medical students, and 5 junior residents. RESULTS: Three dominant perspectives around the purpose of an admission were identified. The most focused perspective characterized the purpose as making patients ready for discharge. By contrast, the most comprehensive perspective characterized admission as an opportunity to identify ways to improve overall patient health status. The third perspective was in-between-treating acute issues while monitoring pertinent chronic conditions. All attendings expressed a sense of discharge pressure but responded with different strategies. Attendings rarely explicitly discussed their perspectives as part of case review. CONCLUSIONS: These extremes of practice and lack of overt dialogue are concerning. Potential effects include mixed messages to trainees and missed opportunities for dialogue and debate around what can and should be achieved during a hospital admission.
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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 | 0.047 | 0.197 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.017 |
| Scholarly communication | 0.013 | 0.010 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.003 | 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".