North American cost analysis of brand name versus generic drugs for the treatment of glaucoma.

Abstract

BackgroundAccording to the World Health Organization, glaucoma is a leading cause of irreversible blindness worldwide. By 2020, 80 million people will be affected by glaucoma in the world, which represents a significant financial burden to society. Glaucoma medications alone make up 38–52% of the total direct cost. The purpose of this research is to conduct a cost-minimization analysis to evaluate brand-name medications versus generic medications for treating glaucoma patients.MethodsThe per-bottle cost (in Canadian dollars) of brand-name drugs for glaucoma was obtained from the wholesaler, McKesson Canada, and, for generic drugs, from the Ontario Drug Benefit (ODB) Formulary. Further, a wastage adjustment fee, a pharmacy mark-up, and an ODB dispensing fee ($CAD) was added to the cost of both brand and generic. Previously published frequencies of medication prescription were utilized to calculate the average annual cost for each class of brand and generic. For each medication class and for mono-, bi-, and tri-drug therapy, the cost differential between brands and generics over a six-year period was computed and analyzed from third-party payer perspective.ResultsIn descending order, the average annual government-funded health care system costs were: combination drugs such as Cosopt® ($748.23) were the most expensive, followed by prostaglandin analogs ($246.36), carbonic anhydrase inhibitors (CAIs) ($45.04), α-agonist ($30.34), β-blockers ($29.29), and cholinergic agonists ($16.51). Brand-name mono-drugs are 34% more expensive compared to generics. Brand-generic percentage cost differential for various medication classes over a six-year period was the highest for prostaglandin analogous (44%), followed by β-blockers (35%), α-agonist (31%), cholinergic agonists (22%), combination drugs (10%), and CAIs (1%).ConclusionBrand-name drugs are relatively more expensive than their generic counterparts, with variable cost differentials depending on drug class.