title: Relationship between generic and preferred-brand prescription copayment differentials and generic fill rate.
abstract: OBJECTIVE
  To evaluate the relationship between generic and brand copayment differentials and generic fill rate (GFR).
  
  
  METHODS
  Cross-sectional.
  
  
  METHODS
  Aggregate-level retail prescription utilization and demographic data from 2005 were used. Plan sponsors were included if they were continuously eligible with Express Scripts Inc during 2005, had no benefit change, were commercially insured, offered a subsidized benefit, adopted 1 of 2 standard formularies, and had at least 100 members. The relationship between GFR and model independent variables was examined by generalized linear modeling using a logistic function for GFR.
  
  
  RESULTS
  A total of 3979 plan sponsors met the inclusion criteria. Controlling for plan demographics, factors that significantly and positively impacted generic usage were step therapy, 3-tier plan design, and increased generic and brand copayment differentials. Relative to plans without step therapy, plans with this feature had estimated GFRs that were 2.6 percentage points higher on average (P < .001). Relative to plan sponsors with flat 3-tier designs, those with flat 2-tier designs, coinsurance, or tiered coinsurance had GFRs that were 2.0 (P < .001), 1.5 (P < .001), and 1.2 (P < .01) percentage points lower, respectively. Compared with plan sponsors that had a $0 to $5 differential between generic and brand copayments, plans with $11 to $15, $16 to $20, and $21+ differentials had GFRs that were 1.9, 2.9, and 5.2 percentage points higher on average, respectively (all P < .001).
  
  
  CONCLUSIONS
  Factors to consider when designing a plan are benefit structure and the financial incentives used to differentiate between generics and brands.
authors.affiliation: Express Scripts, Inc, , Maryland Heights, MO 63043, USA. doug.mager@expressscripts. com
authors.forename: Douglas E
authors.initials: DE
authors.lastname: Mager
authors.forename: Emily R
authors.initials: ER
authors.lastname: Cox
mesh_terms: D000328:Adult; D017677:Age Distribution; D003430:Cross-Sectional Studies; D003669:Deductibles and Coinsurance / Q000191:economics* / Q000706:statistics & numerical data; D017723:Drug Utilization Review; D016568:Drugs, Generic / Q000191:economics*; D005260:Female; D019538:Health Care Surveys; D006801:Humans; D007356:Insurance, Pharmaceutical Services / Q000191:economics* / Q000706:statistics & numerical data; D016014:Linear Models; D008297:Male; D016017:Odds Ratio; D011306:Prescription Fees; D017678:Sex Distribution; D014481:United States
chemical_list: D016568:Drugs, Generic