Effects of restrictions on reimbursement for pharmaceutical drugs
Notice bibliographique
Résumé
Our review on restrictions to reimbursement by drug benefit plans (1) is part of an emerging series on pharmaceutical policies from the Cochrane Effective Practice and Organization of Care group (2–5). As expected, we found strong evidence that these restrictions do lead to lower spending on drugs but the more important question for us to answer was whether the savings associated with the restrictions can be obtained without unintended health consequences or shifting costs to other parts of the health care system. The answer is yes, but not always. The Cochrane Collaboration has taken up the challenge of Archie Cochrane's vision of systematically reviewing the best available evidence in all areas of health care, to support clinical practice. We have a similar vision for a collection of reviews to support informed decision making on pharmaceutical policies. Many people are not aware of how much the science of pharmaceutical policy has advanced, with the availability of large administrative datasets and the ability of researchers to process anonymous data from millions of routine transactions. Our review is the fourth to be completed in the planned series of 13 Cochrane reviews of pharmaceutical policy. The other three completed reviews looked at reference pricing, copayments and caps, and physician incentives; and have all yielded insights that can be used to formulate better pharmaceutical policies. As we brought together the data for our review, we were surprised to find how much the results varied by drug class. In the 29 included studies, nine drug classes had been targeted for restriction. Most looked at policies restricting gastric acid suppressants and non steroidal anti inflammatory drugs, or NSAIDS. For these, there is good evidence that restrictive policies lead to savings without increasing the use of other health services. We also found evidence supporting restrictions for wet nebulizer respiratory drugs and fluroquinolone antimicrobials. However, second generation antipsychotic medications provided an exception to the generally positive findings. There was good evidence that restrictions for these were associated with treatment discontinuity and increased out-patient visits. This makes them poor targets for restrictive policies. We also found that the available evidence does not support restrictions for anti-platelets and angiotensin receptor blocker medications. The global nature of our review made us aware of European strategies to encourage the use of cost effective medications to prevent secondary complications of high blood pressure and blood cholesterol. We found a small but high quality body of evidence supporting the lifting or exemption of restrictions, when these drugs are used for secondary prevention. The evidence available for our review applies mostly to older or low income populations, because the research was conducted using data from publicly funded drug benefit plans. However, the policies are also used by employer or private insurance plans and our findings might be relevant in those settings. Spending on prescription medications has increased dramatically in recent years, while public funding has contracted, so the use of policies to control costs may be essential to ensure that drug benefit plans can be sustained. We are excited about our early steps in realizing the vision of providing policy makers with systematic reviews of pharmaceutical policy across all 13 major areas. These policies can have enormous ramifications for the health of populations and the sustainability of health systems. We will be moving on to investigate policies that determine which drugs are reimbursed but the body of research in this area is growing so quickly that we also need to develop strategies to ensure the regular updating of the existing reviews.
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
Étiquettes directes de modèles (non validées)
Étiquettes de catégorie et de devis d'étude par modèle, issues des rondes d'étiquetage. C'est une sortie machine, non validée, et le désaccord entre modèles est livré comme donnée. Aucun devis ici n'est encore validé contre MEDLINE.
| Bras | Catégories | Devis d'étude | Confiance |
|---|---|---|---|
| gemma | aucune catégorie Domaine: non disponible · Genre: Empirique Porte sur le système de recherche canadien: non · Porte sur un sujet canadien: non | Observationnel | high |
| gpt | aucune catégorie Domaine: non disponible · Genre: Empirique Porte sur le système de recherche canadien: non · Porte sur un sujet canadien: non | Observationnel | low |
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 | 0,002 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 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 découleClassification
machine, non validéeÉtiqueté directement par 2 modèles lisant le dossier complet.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».