Developing a Patient-Directed Policy Framework for Managing Orphan and Ultra-Orphan Drugs Throughout Their Lifecycle
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Notice bibliographique
Résumé
INTRODUCTION: Policy decisions related to orphan and ultra-orphan drugs challenge traditional decision-making processes and often frustrate those affected by them. In general, these drugs are associated with significant uncertainties around clinical benefit, 'value for money', affordability, and 'adoption/diffusion', all of which arise from a lack of available high-quality evidence. Increasingly, patients with rare diseases and their families are looking for opportunities to contribute to initiatives aimed at reducing these uncertainties. Therefore, a policy framework for guiding their involvement is needed to optimize the impact of any evidence generated. OBJECTIVES: The aims of this study were (1) to explore opportunities for patient involvement in reducing decision uncertainties throughout the lifecycle of orphan and ultra-orphan drugs from the perspectives of patients within the Canadian rare disease community; and (2) to develop a policy framework for patient input that maximizes the impact of their involvement on decision uncertainties around orphan and ultra-orphan drugs. METHODS: Two one-day conferences and four workshops involving patients and/or families from rare disease communities in Canada were held to discuss issues around orphan and ultra-orphan drug development, access, and coverage, and identify opportunities for patient input to reduce related decision uncertainties. Their feedback and the findings from a recent literature review on patient involvement in rare diseases were combined into a draft policy framework based upon Kingdon's multiple streams model of decision making. The framework was presented to a group of patients and other stakeholders, including providers, pharmaceutical drug plan managers, and industry representatives, and then revised accordingly. RESULTS: Patients and family members/caregivers identified tangible ways of contributing to the generation of information at all stages of the drug lifecycle. However, the proximity of that information to the reduction of a specific decision uncertainty varied. While the scope of possible ways mentioned was less broad when compared with the findings of the literature review, the focus was similar-capturing the clinical benefit of an orphan or ultra-orphan drug. A policy framework comprising three stages, each with a key question and corresponding set of sub-questions to be asked by patients, was developed. The three main sequential questions were as follows. (1) What uncertainties need to be addressed? (2) What roles should patients play? (3) Is each role feasible? CONCLUSIONS: Reducing decision uncertainties around orphan and ultra-orphan drugs requires a policy framework that explicates when and what type of information needs to be generated, and recognizes the role of patients as important sources of such information throughout the lifecycle of these drugs.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 découle