The work of patient flow management: A grounded theory study of emergency nurses
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
INTRODUCTION: The current crisis of emergency department overcrowding demands novel approaches. Despite a growing body of patient flow literature, there is little understanding of the work of emergency nurses. This study explored how emergency nurses perform patient flow management. METHODS: Constructivist grounded theory and situational analysis methodologies were used to examine the work of emergency nurses. Twenty-nine focus groups and interviews of 27 participants and 64 hours of participant observation across four emergency departments were conducted between August 2022 and February 2023. Data were analyzed using coding, constant comparative analysis, and memo-writing to identify emergent themes and develop a substantive theory. FINDINGS: Patient flow management is the work of balancing department resources and patient care to promote collective patient safety. Patient safety arises when care is ethical, efficient, and appropriately weighs care timeliness and comprehensiveness. Emergency nurses use numerous patient flow management strategies that can be organized into five tasks: information gathering, continuous triage, resource management, throughput management, and care oversight. CONCLUSION: Patient flow management is complex, cognitively demanding work. The central contribution of this paper is a theoretical model that reflects emergency nurses'conceptualizations, discourse, and priorities. This model lays the foundation for knowledge sharing, training, and practice improvement.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it