Primary Care Pathway for Childhood Asthma: Protocol for a Randomized Cluster-Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Asthma is the most common chronic condition in children. For many, the disease is inadequately controlled, which can burden the lives of children and their families as well as the health care system. Improved use of the best available scientific evidence by primary care practitioners could reduce the need for hospital care and improve quality of life and asthma control, thereby reducing overall costs to society and families. OBJECTIVE: The Primary Care Pathway for Childhood Asthma aims to improve the management of children with asthma by (1) providing primary care practitioners with an electronic guide (a clinical pathway) incorporated into the patient's electronic medical record, and (2) providing train-the-trainer education to chronic disease management health professionals to promote the provision of asthma education in primary care. METHODS: The research will utilize a pragmatic cluster-controlled design, quantitative and qualitative research methodologies, and economic evaluation to assess the implementation of a pathway and education intervention in primary care. The intervention will be analyzed for effectiveness, and if the results are positive, a strategy will be developed to implement delivery to all primary care practices in Alberta. RESULTS: The research has been successfully funded and ethics approvals have been obtained. Practice recruitment began fall 2015, and we expect all study-related activities to be concluded by March 2018. CONCLUSIONS: The proposed pathway and education intervention has the potential to improve pediatric asthma management in Alberta. The intervention is anticipated to result in better quality of care for equal or lesser cost. CLINICALTRIAL: ClinicalTrials.gov NCT02481037; https://clinicaltrials.gov/ct2/show/NCT02481037 (Archived by WebCite at http://www.webcitation.org/6fPIQ02Ma).
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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 | 0.015 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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".