Staff perceptions of how changes occur in an emergency department: a qualitative study
Bibliographic record
Abstract
Introduction Changes in healthcare organisations often incur significant financial costs and disrupt of normal operations. The objective of this research was to explore staff perceptions of changes at a university teaching hospital in the UK. Methods Grounded theory methodology was used to perform a secondary analysis of 41 interview transcripts from participants consisting of 20 physicians, 13 nurses, 2 support workers and 6 managers involved in paediatric emergency care at the hospital. Results Four major themes identified from the analysis were types of changes, change readiness, change triggers and challenges to implementing changes. Both planned and emergent changes can occur simultaneously, and emergency department staff are ready to manage them although external pressures seem to be the main trigger for changes, emergent changes appear to occur as initiatives to improve performance or improve services. Emergent changes at a systemic level have an inclusive planning, implementation and evaluation process. They have to be implemented at minimal cost and show the value of changes. Discussion and conclusion These results suggest that emergent changes that were to be implemented at a system level had higher scrutiny of their value and to occur with zero or minimum financial cost. Planned changes implemented by senior management as top–down process should have similar procedures and scrutiny to emergent changes arising from staff, to ensure value for cost. Policy makers and senior managers should encourage and evaluate group or system level changes that arise as a bottom–up process and assess associated financial cost.
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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 | 0.016 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| 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".