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Increasing Access to Hepatitis C Virus Medications: A Program Model Using Patient Navigators and Specialty Pharmacy to Obtain Prior Authorization Approval

BACKGROUND: Obtaining prior authorization (PA) approval for the new direct-acting antiviral (DAA) hepatitis C medications is time consuming and requires specific expertise. Our primary care-based program treats hepatitis C virus (HCV)-infected patients at an urban academic medical center and employs...

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Detalles Bibliográficos
Autores principales: Vu, Trang M., Toribio, Wilma, Riazi, Farah, Ciprian, Genesis, Gibbs, Nathalia, Giardina, Martha, Camacho, Jocelyn A., Parrella, Korin, Cambe, Joy, Amory, Catherine, Chasan, Rachel, Sigel, Keith M., Weiss, Jeffrey J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Academy of Managed Care Pharmacy 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6862767/
https://www.ncbi.nlm.nih.gov/pubmed/29578854
http://dx.doi.org/10.18553/jmcp.2018.24.4.329
Descripción
Sumario:BACKGROUND: Obtaining prior authorization (PA) approval for the new direct-acting antiviral (DAA) hepatitis C medications is time consuming and requires specific expertise. Our primary care-based program treats hepatitis C virus (HCV)-infected patients at an urban academic medical center and employs patient navigators trained in the PA process who collaborate with a nurse and specialty pharmacy to manage the PA process. OBJECTIVE: To demonstrate the rate of PA approvals for our programmatic model and determine potential predictors of PA approval. METHODS: We conducted a review of program databases and medical records of patients for whom DAA hepatitis C medications were ordered between November 1, 2014, and October 31, 2015 (n = 197). We first evaluated patient characteristics associated with the number of steps to approval. Then we used a multivariable ordinal regression to determine independent predictors of fewer steps to approval. Using Kaplan-Meier methods, we assessed patient characteristics associated with approval time and then fit a multivariable Cox regression model to determine independent predictors of time to approval. RESULTS: Of the 197 patients, 69% (n = 136) had Medicaid; 12% (n = 24) had Medicare; 10% (n = 19) had both Medicaid and Medicare; 5% (n = 10) had private insurance; and 4% (n = 8) were uninsured. Ninety-three percent of the patients were eventually approved for HCV treatment. The steps in the PA cascade were approval on first submission (37%; mean days = 30.7; SD = 29.9); approval after internal appeal (45%; mean days = 66.8; SD = 70.5); approval after external appeal (11%; mean days = 124.7; SD = 60.2); and no approval obtained (7%). Unadjusted factors found to have a P value < 0.200 in relation to fewer steps in the PA cascade were older age, female gender, non-Medicaid insurance, comorbid hypertension, comorbid diabetes, being domiciled, and being nongenotype 2. After adjustment, non-Medicaid insurance and nongenotype 2 remained significant. In survival analysis, non-Medicaid insurance and mid-range fibrosis were associated with fewer days to PA approval. CONCLUSIONS: Our program obtained 93% of PA approvals for hepatitis C medications. Patient navigators collaborating with a nurse and specialty pharmacy as a program may improve the PA approval process, although further research with a control group is necessary.