Performance indicators for organ donation and transplantation programmes in Europe: modified Delphi consensus study
Bibliographic record
Abstract
BACKGROUND: Health system performance assessment helps identify areas for improvement and guides policy initiatives. Although well-validated indicators exist for measuring organ donation and transplantation performance at the facility level, consensus on indicators for assessing national programmes is lacking. The aim of this study was to develop a comprehensive scorecard for evaluating national organ donation and transplantation programmes. METHODS: A three-step approach was used. First, a targeted literature review identified potential indicators from regulatory documents, national transplant organization reports, and databases. Second, indicators were mapped to an established transplant system framework and refined through preliminary expert consultations. Third, a modified Delphi consensus process validated the indicators. The Delphi panel comprised international experts in health policy, organ donation, transplantation, and patient representation. Participants rated 168 indicators using a five-point Likert scale across two rounds (24 experts completed round 1 and 22 experts completed round 2). Consensus for inclusion required 80% agreement. RESULTS: Of 168 indicators evaluated, 103 achieved consensus for inclusion. After consolidation of organ-specific indicators, the final set contained 84 indicators across seven domains: monitoring and reporting (8 indicators), prevention and need (9 indicators), waiting lists (11 indicators), consent (4 indicators), donation (28 indicators), transplantation (14 indicators), and follow-up (10 indicators). The indicator set incorporates established metrics such as waiting list statistics, donation rates, and complication rates alongside novel system-level indicators addressing structural factors, patient-centredness, and equity in care delivery. CONCLUSION: This validated indicator set provides a standardized tool for assessing and comparing transplant system performance across European countries, supporting performance benchmarking and evidence-informed policy development.
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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 | 0.001 | 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 | 0.000 | 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".