Failure to Cope
Bibliographic record
Abstract
PURPOSE: The study explored optimal intraprofessional collaboration between physicians in the emergency department (ED) and those from general internal medicine (GIM). Prior to the study, a policy was initiated that mandated reductions in ED wait times. The researchers examined the impact of these changes on clinical practice and trainee education. METHOD: In 2010-2011, an ethnographic study was undertaken to observe consults between GIM and ED at an urban teaching hospital in Ontario, Canada. Additional ad hoc interviews were conducted with residents, nurses, and faculty from both departments as well as formal one-on-one interviews with 12 physicians. Data were coded and analyzed using concepts of institutional ethnography. RESULTS: Participants perceived that efficiency was more important than education and was in fact the new definition of "good" patient care. The informal label "failure to cope" to describe high-needs patients suggested that in many instances, patients were experienced as a barrier to optimal efficiency. This resulted in tension during consults as well as reduced opportunities for education. CONCLUSIONS: The authors suggest that the emphasis on wait times resulted in more importance being placed on "getting the patient out" of the ED than on providing safe, compassionate, person-centered medical care. Resource constraints were hidden within a discourse that shifted the problem of overcrowding in the ED to patients with complex chronic conditions. The term "failure to cope" became activated when overworked physicians tried to avoid assuming care for high-needs patients, masking institutionally produced stress and possibly altering the way patients are perceived.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".