Outcomes indicators and processes in transitional care in adolescents with haemophilia: A Delphi survey of Canadian haemophilia care providers
Bibliographic record
Abstract
INTRODUCTION: It is unclear which outcome indicators should be used to measure the success of haemophilia transition programs, and what are key elements of a haemophilia transition program to ensure success. AIM: To establish by expert consensus a list of important and feasible outcome indicators of successful haemophilia transition, and a list of key elements of transition planning. METHODS: A modified two-stage Delphi survey was developed and disseminated among a panel of Canadian interdisciplinary haemophilia care providers. Participants were asked to rate the importance and feasibility of outcome indicators of effective haemophilia transition and elements of haemophilia transition program. In the second round, participants were asked to choose the top five outcomes suitable for inclusion in a core outcome set of transition effectiveness, and the top five elements that are important and feasible for implementation within the next 5 years. RESULTS: In total, 34/73 (47%) of participants completed the first round and 33 completed the second round, representing a variety of disciplines. Top outcome indicators recommended for a core outcome set include measurement of adherence, change in bleeding rate, self-efficacy skills, haemophilia knowledge, patient and caregiver satisfaction, time gap between last paediatric and first adult clinic, and number of emergency room or hospital admissions. Fourteen elements of transition achieved consensus in importance ratings, while eight were felt to be feasible for implementation within next 5 years. CONCLUSIONS: Results will contribute towards the development of a haemophilia transition outcome instrument and provide guidance for future studies of the effectiveness of transition programs.
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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 | 0.029 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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 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".