Development and Validation of an Asthma Policy Model for Canada: Lifetime Exposures and Asthma outcomes Projection (LEAP)
Notice bibliographique
Résumé
Abstract Purpose To develop Lifetime Exposures and Asthma outcomes Projection (LEAP), a reference policy model for evaluating health outcomes and costs of asthma interventions and policies for the Canadian population. Methods Following the best practice guidelines for development, we first created a conceptual map with a steering committee of clinician experts and economic modelers through a modified Delphi-process. Following the committee’s recommendations and given the multidimensionality of risk factors and the need for modeling realistic aspects (e.g., gradual market penetration) of adopting health technologies, we opted for an open-population microsimulation design. For the first version of the model, we concentrated on several key risk factors (age, sex, family history of asthma at birth, and exposure to antibiotics in the first year of life) from the concept map. The model consists of five intertwined modules: 1) demographic, 2) risk factors, 3) asthma occurrence, 4) asthma outcomes, and 5) payoffs. The demographic module, including birth, mortality, immigration, and emigration, was based on sex– and age-specific estimates and projections from Statistics Canada. The distributions of risk factors, including family history of asthma and exposure to antibiotics, were estimated from population-based administrative databases and a population-based longitudinal birth cohort. To estimate parameters in the asthma occurrence (prevalence, incidence, reassessment) and asthma outcomes (severity, symptom control, exacerbations) modules, we performed quantitative evidence synthesis. Costs and utility weights were obtained from the literature. We conducted multiple face and internal validation assessments. Results LEAP is capable of modeling asthma-related health outcomes at the individual and aggregate levels from 2001 onwards. Face validity was confirmed by checking the structure, equations, codes, and results. We calibrated and internally validated the age-sex stratified demographic projections to the estimates and projections from Statistics Canada, the age-sex stratified asthma prevalence to the administrative data, and the asthma control levels and exacerbation rates to the estimates from the literature. Conclusions LEAP is the first reference Canadian asthma policy model that emerged from identified needs for health policy planning for early interventions in asthma. As an open-source and open-access platform, LEAP can provide a unified framework under which different interventions and policies can be consistently compared to identify those with the highest value proposition. Funding This study was funded by a research grant from the Canadian Institutes of Health Research and Genome Canada (274CHI). The funders had no role in any aspect of this study and were not aware of the results. Ethics This study was approved by the institutional review board of the University of British Columbia, Vancouver (H22-00571).
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,019 | 0,041 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,003 | 0,004 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,004 | 0,001 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».