Engaging the Canadian public on reimbursement decision-making for drugs for rare diseases: a national online survey
Notice bibliographique
Résumé
BACKGROUND: Funding of drugs for rare diseases (DRDs) requires decisions that balance fairness for all individuals within the healthcare system with compassion for affected individuals. Our study objective was to conduct a national online survey to determine the Canadian public's perspective, including regional variations, associated with DRD decision-making. METHODS: The survey collected responses from 1631 Canadians. Respondents were asked to rank at least three and up to five DRD decision-making priorities, out of a total of eight priorities presented. They were also asked to compare and rate their agreement level on a 5-point Likert scale with four funding scenarios described. The frequency of each priority, independent of where it was ranked in relation to the other priorities, was calculated. Regression analyses were conducted to measure the association between respondents' demographics and selected priorities with their agreement level for each funding scenario. RESULTS: Among the survey respondents, Improved Quality of Life and Effective Health Care were most frequently selected as top priorities. Also, 79.2% of respondents agreed with equal access to DRDs across Canada, and 73.0% agreed with DRD funding if additional expenses are justified in the DRD's cost-effectiveness. Approximately half agreed to pay for DRDs independent of their effectiveness. There were no geographic differences in priorities. Selecting Effective Health Care in the top priorities was positively associated with both prioritizing other programs over programs for rare diseases and DRD funding only if deemed as cost-effective. Respondents, who selected National Access as one of the top priorities, were less likely to agree to fund DRDs only if deemed as cost-effective and were more likely to agree with the scenario to provide national access to DRDs. CONCLUSIONS: The survey results suggest the level of public support for funding decisions and programs that incorporate assessment of the effectiveness of drugs for improving quality of life, and to promote similar access across Canada. The responses anticipate public responses to different policy scenarios and the priorities that underlie them. Decision-makers may find it useful to consider whether and how to incorporate these results into policy decisions and their justification to citizens and patients.
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 | 0,005 | 0,012 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,003 | 0,005 |
| Études des sciences et des technologies | 0,005 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».