title: Prior Authorization for Medications in a Breast Oncology Practice: Navigation of a Complex Process.
abstract: The cost and burden associated with prior authorization (PA) for specialty medications are concerns for oncologists, but the impact of the PA process on care delivery has not been well described. We examined PA processes and approval patterns within a high-volume breast oncology clinic at a major academic cancer center.
  
  
  
  We met with institutional staff to create a PA workflow and process map. We then abstracted pharmacy and medical records for all patients with breast cancer (N = 279) treated at our institution who required a PA between May and November 2015 (324 prescriptions). We examined PA approval rates, time to approval, and associations of these outcomes with the type of medication being prescribed, patient demographics, and method of PA.
  
  
  
  Seventeen possible process steps and 10 decision points were required for patients to obtain medications requiring a PA. Of the 324 PAs tracked, 316 (97.5%) were approved on the first PA request after an average time of 0.82 days (range, 0 to 14 days). Approximately half of PAs were for either palbociclib (26.5%) or pegfilgrastim (22.2%), and 13.6% of PAs were for generic hormonal therapy. Requirements to fax PA requests were associated with greater delay in approval time (1.31 v 0.17 days for online requests; P < .001). The use of specialty pharmacies increased staff burden and delays in medication receipt.
  
  
  
  The PA process is complicated and labor intensive. Given the high PA approval rate, it is unlikely that PA requirements reduce medication utilization in practice, and these requirements may impose unnecessary burdens on patient care. The goals and requirements for PAs should be readdressed.
authors.affiliation: Dana-Farber Cancer Institute; and Boston University School of Medicine, Boston, MA.
authors.forename: Ankit
authors.initials: A
authors.lastname: Agarwal
authors.affiliation: Dana-Farber Cancer Institute; and Boston University School of Medicine, Boston, MA.
authors.forename: Rachel A
authors.initials: RA
authors.lastname: Freedman
authors.affiliation: Dana-Farber Cancer Institute; and Boston University School of Medicine, Boston, MA.
authors.forename: Felicia
authors.initials: F
authors.lastname: Goicuria
authors.affiliation: Dana-Farber Cancer Institute; and Boston University School of Medicine, Boston, MA.
authors.forename: Catherine
authors.initials: C
authors.lastname: Rhinehart
authors.affiliation: Dana-Farber Cancer Institute; and Boston University School of Medicine, Boston, MA.
authors.forename: Kathleen
authors.initials: K
authors.lastname: Murphy
authors.affiliation: Dana-Farber Cancer Institute; and Boston University School of Medicine, Boston, MA.
authors.forename: Eileen
authors.initials: E
authors.lastname: Kelly
authors.affiliation: Dana-Farber Cancer Institute; and Boston University School of Medicine, Boston, MA.
authors.forename: Erin
authors.initials: E
authors.lastname: Mullaney
authors.affiliation: Dana-Farber Cancer Institute; and Boston University School of Medicine, Boston, MA.
authors.forename: Myra
authors.initials: M
authors.lastname: St Amand
authors.affiliation: Dana-Farber Cancer Institute; and Boston University School of Medicine, Boston, MA.
authors.forename: Phuong
authors.initials: P
authors.lastname: Nguyen
authors.affiliation: Dana-Farber Cancer Institute; and Boston University School of Medicine, Boston, MA.
authors.forename: Nancy U
authors.initials: NU
authors.lastname: Lin
mesh_terms: D001943:Breast Neoplasms / Q000628:therapy*; D000066491:Clinical Decision-Making; D011307:Drug Prescriptions; D005260:Female; D006801:Humans; D008510:Medication Systems, Hospital; D010818:Practice Patterns, Physicians'; D013997:Time Factors; D057188:Workflow