Simulation-based verification of lean improvement for emergency room process
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
One of the key challenges to health care access in Canadian hospitals is growing overcrowding of the Emergency Departments (EDs), leading to the medical personnel overload, and the excessive waiting times to receive proper care. These adverse effects directly impact the patient satisfaction levels, the ability of the medical professionals to attend promptly to patients' health issues, and generate unnecessary costs. Addressing the sources of waste and improving the process provides better care and higher patient satisfaction, as well as increases operational efficiency and the ability of the medical professionals to intervene on time. This paper describes an effort aimed at improvement of patients' experience over their ED stay. A combination of lean tools were used to analyze, assess and improve the current situation. Simulation models based on current and future (desired) states were developed. Comparative analysis of both enabled verification of feasibility of proposed solutions, and provided quantifiable results.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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