Overview of Health Technology Assessment Processes for Time-Limited Recommendations
Notice bibliographique
Résumé
Several regulatory agencies have implemented processes to facilitate timely access to innovative therapies for patients with rare or life-threatening diseases with high unmet medical needs, typically with additional data-generation requirements to address important uncertainties in the existing evidence base at the time of regulatory approval. Many health technology assessment (HTA) agencies have adapted their processes to include time-limited recommendations (TLRs) for such therapies, which allows patients access to these medications while additional data are collected to verify the clinical efficacy, real-world effectiveness, or economic value of the new therapeutic. The objective of this Environmental Scan is to identify what HTA agencies have processes in place for TLRs and to describe these processes, if applicable. HTA agencies in North America, Europe, Australia, and New Zealand were considered for this report based on commonalities to the Canadian context in terms of geography and relevant regulatory or HTA and reimbursement processes. Seven HTA agencies (the National Institute for Health and Care Excellence, the Scottish Medicines Consortium, France’s Haute Autorité de Santé, the Dutch National Health Care Institute, the Italian Medicines Agency, the Belgium National Institute for Health and Disability Insurance, and the Australian Pharmaceutical Benefits Advisory Committee) that have implemented formal TLR processes, through managed entry agreements, special access funds, or other related programs were identified. Most TLR programs are referred to as managed access or entry agreements, but other types include interim acceptance, conditional inclusion, assessment contingent on additional evidence development, and additional specialized programs or pathways. TLRs are primarily used for promising (and sometimes high-cost) medicines intended to treat a condition with an important unmet medical need; some specify that the disease must be serious and life threatening (regardless of prevalence), others indicate that the process is used for orphan drugs intended to treat rare conditions, and others consider multiple criteria or do not have prerequisite criteria for eligible indications. Evidence generation requirements for TLRs vary across HTA agencies and are often dependent on the nature of the clinical and economic uncertainties identified in the initial assessment; sources include later follow-up from ongoing clinical trials, new clinical trials, real-world data, or a combination of both clinical and real-world studies. Additionally, most TLR processes have explicit maximum durations for the time-limited period, which range from 2 to 7 years across the included HTA agencies (although some allow for time adjustments or renewals); however, the French and Scottish HTA agencies determine the duration of the time-limited period on a case-by-case basis. Overall, this report provides an overview of HTA processes for TLRs across HTA agencies in Europe and Australia, many of which may be useful to inform the implementation of future TLR processes in Canada, as well as to refine existing ones.
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 | 0,331 | 0,497 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,003 |
| Méta-épidémiologie (sens large) | 0,004 | 0,012 |
| Bibliométrie | 0,029 | 0,036 |
| Études des sciences et des technologies | 0,003 | 0,003 |
| Communication savante | 0,022 | 0,014 |
| Science ouverte | 0,009 | 0,013 |
| Intégrité de la recherche | 0,007 | 0,011 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,030 | 0,012 |
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 ».