Lessons learned from the pandemic: expanding the collaboration between clinical and logistics activities in a hospital
Bibliographic record
Abstract
PURPOSE: The Covid-19 pandemic generated significant changes in the operating methods of hospital logistics departments. The objective of this research is to understand how these changes took place, what collaboration mechanisms were developed with clinical authorities and, to what extent, logistics and clinical care activities should be decoupled to maximize each area's contribution? DESIGN/METHODOLOGY/APPROACH: The case study is selected to investigate practices implemented during the COVID-19 pandemic in hospitals in Canada. The pandemic presented an opportunity to contrast practices implemented in response to this crisis with those historically used in this environment. FINDINGS: The strategy of decoupling logistical tasks of an operational nature from clinical activities is well-founded and helps free clinical staff from tasks for which they are not trained. However, the decoupling of operational tasks should be combined with an integration of the clinical information flow to the logistics hub players. With this clinical information, the logistics hub can generate its full potential enabling better inventory management decisions to be made. ORIGINALITY/VALUE: The concept of decoupling is studied to identify configurations that offer the best benefits for clinical staff.
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.
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 | 0.003 | 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 | 0.001 | 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) | 0.000 | 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".