The PATH project in eight European countries: an evaluation
Bibliographic record
Abstract
PURPOSE: This paper's aim is to evaluate the perceived impact and the enabling factors and barriers experienced by hospital staff participating in an international hospital performance measurement project focused on internal quality improvement. DESIGN/METHODOLOGY/APPROACH: Semi-structured interviews involving international hospital performance measurement project coordinators, including 140 hospitals from eight European countries (Belgium, Estonia, France, Germany, Hungary, Poland, Slovakia and Slovenia). Inductively analyzing the interview transcripts was carried out using the grounded theory approach. FINDINGS: Even when public reporting is absent, the project was perceived as having stimulated performance measurement and quality improvement initiatives in participating hospitals. Attention should be paid to leadership/ownership, context, content (project intrinsic features) and processes supporting elements. RESEARCH LIMITATIONS/IMPLICATIONS: Generalizing the findings is limited by the study's small sample size. Possible implications for the WHO European Regional Office and for participating hospitals would be to assess hospital preparedness to participate in the PATH project, depending on context, process and structural elements; and enhance performance and practice benchmarking through suggested approaches. ORIGINALITY/VALUE: This research gathered rich and unique material related to an international performance measurement project. It derived actionable findings.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.050 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".