The Economic Impact of Originator-to-Biosimilar Non-medical Switching in the Real-World Setting: A Systematic Literature Review
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Notice bibliographique
Résumé
INTRODUCTION: To save costs to the healthcare system, forced non-medical switch (NMS) policies that cut drug coverage for originator biologics and fund only less expensive biosimilars are being implemented. However, costs related to the impact of NMS on healthcare resource utilization (HCRU) must also be considered. This study aims to summarize the evidence on the economic impact of an originator-to-biosimilar NMS. METHODS: A systematic literature review (SLR) was conducted. Publications reporting on HCRU or costs associated with originator-to-biosimilar NMS in the real-world setting were searched in MEDLINE and EMBASE from January 2008 to February 2020. In addition to hand searching the reference lists of relevant publications and SLRs, key conference websites, PubMed, and various government sites were also searched for the 2 years preceding the search (2018-2020). RESULTS: A total of 1845 citations were identified, of which 49 were retained for data extraction. Most studies reporting on the HCRU associated with NMS reported on post-NMS HCRU alone without a comparison pre-NMS. However, four studies described a difference in HCRU (i.e., investigations pre- vs post-switch or between non-switchers vs switchers), all of which reported a relative increase in HCRU, including laboratory testing, imaging, medical visits, and hospitalizations, amongst patients who underwent an originator-to-biosimilar NMS. Most studies reporting on the costs associated with NMS reported significant savings following NMS on the basis of drug costs alone. However, four studies specifically reporting on the difference of costs following originator-to-biosimilar NMS all demonstrated an increase in HCRU-related costs associated with NMS (increase in HCRU-related costs of 4-37% or 148-2234 2020 Canadian dollars). CONCLUSION: Amongst the studies that reported on the difference in HCRU pre- vs post-switch or between non-switchers and switchers, all showed an increase in HCRU and related costs associated with NMS, suggesting that the expected overall savings due to less costly drug prices may be reduced as a result of an increase in HCRU and its associated costs post-switch. Nevertheless, more real-world studies that include NMS-related healthcare costs in addition to drug costs are needed.
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Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,005 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,003 | 0,001 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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