Staff Perceptions of Improving Emergency Care for Children
Bibliographic record
Abstract
The objective of this study was to identify staff perceptions of a service improvement for pediatric emergency care at a university teaching hospital. Semistructured qualitative interviews of stakeholders were conducted, and grounded theory approach was used for analysis. Forty-one interviews were conducted with physicians, nurses, managers, and health care workers. Major themes emerging from the analysis included the physical space of and flow within the pediatric emergency department (ED), impact of technology, staffing in the ED, the effects of frontline pediatricians and emergency physicians managing children in the ED, and the need for and expectations of a pediatric emergency medicine (PEM) consultant. Human interactions among health care providers, leadership, and teaching are considered as equally important as providing the appropriate environment and qualified professionals for improving care for children in the ED. Appointment of a PEM consultant was suggested to provide leadership and education to manage relationships and implement changes. Subsequent to the study, the model of care for PEM was changed, the pediatric care delivery became more integrated with the main ED, and two PEM consultants were appointed to the institution.
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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 | 0.006 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".