Towards Excellence in Asthma Management (TEAM): A Populational Disease-Management Model
Bibliographic record
Abstract
Asthma management is not always optimal, and deficiencies such as inadequate treatment and insufficient patient education are often reported. Towards Excellence in Asthma Management (TEAM) is a four-phase disease management program of the Quebec Asthma Education Network (QAEN), to be carried out over a 5-year period. The program aims to achieve a continuous improvement of asthma management by caregivers and patients. The first phase, completed in January 2000, consisted of determining the actual level of asthma-associated morbidity and mortality in various Quebec regions. The second phase, which began in September 1999, included three parts: 1. Definition of the burden of asthma, taking into account the socioeconomic consequences of the disease and the quality of life of the patients, 2. Comparison of current medical practices with the Canadian Asthma Consensus Guidelines for adult and pediatric populations, 3. Evaluation of the level of compliance with medical treatment and with the environmental changes recommended to asthmatic patients. This phase is carried out via a cohort study of physicians, mainly general practitioners and pediatricians, generating a patient cohort study, in addition to substudies evaluating specific aspects of asthma care. Once the care gap is identified, it will be possible to define, apply, and evaluate a series of interventions for physicians, other health professionals, and patients. The interventions will be particularly targeted at regions where asthma incidence and morbidity are higher. We hope that this model of disease management will progressively reduce the burden associated with asthma, and potentially other chronic diseases, and will result in the more effective use of health services.
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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 | 0.009 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.011 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".