Procurement-network contributions to healthcare supply chain resilience: a case study from Canada
Why this work is in the frame
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Bibliographic record
Abstract
Purpose This article investigates how the healthcare sector can reorganize its procurement network to better balance its resilience and cost-minimization objectives. Design/methodology/approach A single case study was conducted on the procurement of personal protective equipment (PPE) during the first COVID-19 pandemic wave in the Quebec public healthcare network. Interviews were conducted with stakeholders from the supply chain management (SCM) departments at eight public healthcare institutions. Findings Two major challenges in the early months of the pandemic impacted the development of resilience in the healthcare network. First, peripheral actors’ decisions, which orient procurement objectives, limited the deployment of resilience measures in the supply chain (SC). Second, SC resilience included hundreds of products other than PPE that are critical to the delivery of care. The article illustrates the challenges of SCR, which will inevitably be accompanied by additional costs when purchasing in the public healthcare sector is often focused on the lowest price. Originality/value Drawing from the network perspective model, this article examines the actions of Quebec supply network stakeholders through the three phases of SCR: anticipation, response to disruption, and recovery. Finally, the article suggests that decision-makers remove the cost of resilience measures from the purchase price of products, in order to maintain these measures over the long term.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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