Can A Community Evidence-based Asthma Care Program Improve Clinical Outcomes?
Bibliographic record
Abstract
RATIONALE: Asthma is associated with significant morbidity. Previous studies highlight significant variations in asthma management approaches within primary care settings where the adoption of published asthma guidelines is typically suboptimal. OBJECTIVE: To determine whether the implementation of an evidence-based asthma care program in community primary care settings leads to improved clinical outcomes in asthma patients. METHODS, MEASUREMENTS, AND MAIN RESULTS: A community-based participatory research project was implemented at 8 primary care practices across Ontario, Canada, consisting of elements based on the Canadian Asthma Consensus Guidelines (asthma care map, program standards, management flow chart and action plan). A total of 1408 patients aged 2-55 years participated. Conditional logistic regression analyses were used to calculate the odds ratios (OR) comparing baseline to follow-up while adjusting for age, gender, socioeconomic status and other covariates. At 12-month follow-up, there were statistically significant reductions in self-reported asthma exacerbations from 77.8% to 54.5% [OR = 0.35; 95% confidence interval (CI): 0.28-0.43]; emergency room visits due to asthma from 9.9% to 5.5% (OR = 0.47; 95% CI: 0.32-0.62); school absenteeism in children from 19.9% to 10.2% (OR = 0.37; 95% CI: 0.25-0.54); productivity loss in adults from 12.0% to 10.3% (OR = 0.49; 95% CI: 0.34-0.71); uncontrolled daytime asthma symptoms from 62.4% to 41.4% (OR = 0.34; 95% CI: 0.27-0.42); and uncontrolled nighttime asthma symptoms from 46.4% to 25.4% (OR = 0.29; 95% CI: 0.23-0.37). CONCLUSIONS: Development and implementation of a community-based primary care asthma care program led to risk reductions in exacerbations, symptoms, urgent health service use and productivity loss related to asthma.
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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 | 0.046 | 0.176 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".