Primary Care Severe Asthma Registry and Education Project (PCSAR-EDU): Phase 1 – an e-Delphi for registry definitions and indices of clinician behaviour
Bibliographic record
Abstract
INTRODUCTION: Although most asthma is mild to moderate, severe asthma accounts for disproportionate personal and societal costs. Poor co-ordination of care between primary care and specialist settings is recognised as a barrier to achieving optimal outcomes. The Primary Care Severe Asthma Registry and Education (PCSAR-EDU) project aims to address these gaps through the interdisciplinary development and evaluation of both a 'real-world' severe asthma registry and an educational programme for primary care providers. This manuscript describes phase 1 of PCSAR-EDU which involves establishing interdisciplinary consensus on criteria for the: (1) definition of severe asthma; (2) generation of a severe asthma registry and (3) definition of an electronic-medical record data-based Clinician Behaviour Index (CBI). METHODS AND ANALYSIS: In phase 1, a modified e-Delphi activity will be conducted. Delphi panellists (n≥13) will be invited to complete a 30 min online survey on three separate occasions (i.e., three separate e-Delphi 'rounds') over a 3-month period. Expert opinion will be collected via an open-ended survey ('Open' round 1) and 5-point Likert scale and ranking surveys ('Closed' round 2 and 3). A fourth and final Delphi round will occur via synchronous meeting, whereby panellists approve a finalised ideal 'core criteria list', CBI and corresponding item weighting. ETHICS AND DISSEMINATION: Ethical approval has been obtained for the activities involved in phase 1 from the University of Toronto's Human Research Ethics Programme (approval number 39695). Future ethics approvals will depend on information gathered in the proceeding phase; thus, ethical approval for phase 2 and 3 of this study will be sought sequentially. Findings will be disseminated through conference presentations, peer-reviewed publications and knowledge translation tools.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".