Emergency boarding: An integrative framework for analyzing causes and seeking solutions
Bibliographic record
Abstract
Background: One of the root causes of crowding at the Emergency Department (ED) is boarding, i.e. the practice of holding admitted patients in the ED until an inpatient (IP) bed becomes available. Although ED boarding has been approached by various authors, few of them have aimed to see how different hospitals perform in regard to this issue.Objective: This study will approach ED boarding from different angles, analyzing both quantitative and qualitative data, and following both deductive and inductive reasoning. The purpose is to develop a validated integrative conceptual framework which can be used to analyze ED boarding, and to look for solutions.Methods: The development of the framework is based on an extensive literature review and a multiple case study research with both qualitative and quantitative data collection.Results: ED boarding was found to be prominent in the studied hospitals. Four root causes of ED boarding were elucidated, which are: (1) uncoordinated admissions and discharges, (2) late discharges, (3) the inability to discharge patients, and (4) a lack of communication, collaboration, and information between the different actors of the patient care process. Many solutions are proposed to improve these issues.Conclusions: Through the analysis of various types of data, an integrative conceptual framework for ED boarding was elaborated for analyzing causes and seeking solutions. The quantative data cannot only be used in the analysis stage, but can also help in designing a solution as there are clear recognizable trends in arrival, discharge and ED boarding time. “Communication, collaboration and information”, although not explicitly discussed in the literature, was found to be the most prominent cause and solution to ED boarding in the field study. Practice implications: Management practitioners now have a framework demonstrating probable causes for ED boarding, which provides a starting point for analysis within their establishments. Pathways to improvement are suggested as well, which will help managers to reduce ED boarding. Communication, collaboration and information are important in these improvement efforts.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".