Dee Lin, Dominic Pilon, Laura Morrison, Aditi Shah, Marie-Hélène Lafeuille, Patrick Lefebvre, Carmela Benson
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引用次数: 0
Abstract
Background: Patient affordability is an important nonclinical consideration for treatment access among patients with schizophrenia.
Objective: This study evaluated and measured out-of-pocket (OOP) costs for antipsychotics (APs) among Medicaid beneficiaries with schizophrenia.
Methods: Adults with a schizophrenia diagnosis, ≥ 1 AP claim, and continuous Medicaid eligibility were identified in the MarketScan® Medicaid Database (1 January 2018-31 December 2018). OOP AP pharmacy costs ($US 2019) were normalized for a 30-day supply. Results were descriptively reported by route of administration [ROA; orals (OAPs), long-acting injectables (LAIs)], generic/branded status within ROAs, and dosing schedule within LAIs. The proportion of total (pharmacy and medical) OOP costs AP-attributable was described.
Results: In 2018, 48,656 Medicaid beneficiaries with schizophrenia were identified (mean age 46.7 years, 41.1% female, 43.4% Black). Mean annual total OOP costs were $59.97, $6.65 of which was AP attributable. Overall, 39.2%, 38.3%, and 42.3% of beneficiaries with a corresponding claim had OOP costs > $0 for any AP, OAP, and LAI, respectively. Mean OOP costs per patient per 30-day claim (PPPC) were $0.64 for OAPs and $0.86 for LAIs. By LAI dosing schedule, mean OOP costs PPPC were $0.95, $0.90, $0.57, and $0.39 for twice-monthly, monthly, once-every-2-months, and once-every-3-months LAIs, respectively. Across ROAs and generic/branded status, projected OOP AP costs per-patient-per-year for beneficiaries assumed fully adherent ranged from $4.52 to $13.70, representing < 25% of total OOP costs.
Conclusion: OOP AP costs for Medicaid beneficiaries represented a small fraction of total OOP costs. LAIs with longer dosing schedules had numerically lower mean OOP costs, which were lowest for once-every-3-months LAIs among all APs.
期刊介绍:
Drugs - Real World Outcomes targets original research and definitive reviews regarding the use of real-world data to evaluate health outcomes and inform healthcare decision-making on drugs, devices and other interventions in clinical practice. The journal includes, but is not limited to, the following research areas: Using registries/databases/health records and other non-selected observational datasets to investigate: drug use and treatment outcomes prescription patterns drug safety signals adherence to treatment guidelines benefit : risk profiles comparative effectiveness economic analyses including cost-of-illness Data-driven research methodologies, including the capture, curation, search, sharing, analysis and interpretation of ‘big data’ Techniques and approaches to optimise real-world modelling.