EMERGENCY DEPARTMENT PROCESS FLOW IMPROVEMENT BASED ON EFFICIENT ARCHITECTURAL LAYOUT, LEAN CONCEPT AND POST-LEAN SIMULATION
Bibliographic record
Abstract
Long waiting times in Emergency Departments (ED) have been an issue in Canadian hospitals for years. Many factors have contributed to the excessive waiting time, including the current design scheme which is known architecturally as the “Funnel Design Scheme.” Current architectural and engineering practice lacks standards to quantify the effect of ED design and ancillary departments on waiting time and Length of Stay (LOS). This research focuses on assessing the architectural standards of ED on the basis of a patient-focused environment. The objective is to optimize the space requirement to reduce waiting time following what is called “universal zero delay treatment.” The proposed methodology uses two techniques: a) a statistical analysis of forty two ED architectural designs, and b) the application of Lean Healthcare combined with Post Lean Simulation which offers an opportunity to evaluate the potential impact of different interventions on patient flow and throughput. The proposed methodology is tested through a case study and interviews with healthcare professionals.
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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 | 0.000 |
| 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) | 0.000 | 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".