Exploring Inpatient Unit Nurses’ Experience with Emergency Department Crowding, Access and Flow, and Associated Patient Outcomes
Bibliographic record
Abstract
Background: Emergency department crowding and hospital access and flow are complex and long standing issues that negatively impact healthcare delivery. This study aims to address these issues through the perspectives of inpatient unit nurses. Strategies to alleviate ED crowding are supported by research exploring ED staff perspectives; however, a paucity of research exists addressing the perceptions of inpatient unit nurses and other key stakeholders. Methods: The research aims were addressed using qualitative method. Semi-structured virtual interviews were completed with eleven inpatient unit registered nurses from two hospital sites. A 17-question interview tool facilitated the collection of data. Results: Three main themes emerged from the data analysis. Inpatient unit nurses identified ED crowding, hospital access and flow, and site congestion as key areas of concern. In addition, the influence of understaffing was viewed as a contributor to ED crowding, resulting in negative outcomes for patient care. Conclusion: This study is the initial step to understanding different experiences, perceptions and knowledge on emergency department crowding and access and flow processes. Further research exploring diverse viewpoints on this topic is necessary given the interconnected organizational structure of healthcare today and how key stakeholders, outside of the emergency department, strongly influence access block and ED outflow.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".