Translating Strategies into Tactical Actions: The Role of Sourcing Levers in Healthcare Procurement
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
Expensive medical devices, especially in the areas of orthopedics, and cardiology, have a significant impact on hospital costs and the delivery of high-quality services. These medical supplies are known as physician preference items (PPIs), as they act as “surrogate buyers”—impacting the selection and sourcing of products. There is a gap between the purchasing strategy and the adoption of tactical activities for these complex medical supplies. In the context of the healthcare exceptionalism thesis, this research investigates how healthcare organizations can successfully adopt suitable sourcing levers aiming to achieve different purchasing results. This research conducts a multi-case study in 15 healthcare organizations in nine countries. Three new sourcing levers specific to the healthcare sector emerged, based on the healthcare exceptionalism thesis. It was possible to identify five main sourcing levers clusters. The fit between strategy and tactical level can be allowed by the implementation of suitable sourcing levers—facilitating the achievement of the desired objectives. Healthcare procurement practitioners should assess the fit between strategy and the tactical level by employing suitable sourcing levers. Organizations wishing to move towards a value-based procurement approach should adopt a set of supporting sourcing levers to enable this transition.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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 it