title: Unintended consequences of a Medicaid prescription copayment policy.
abstract: OBJECTIVE
  Medication copayments can influence patient choices. We evaluated 2 copayment policies implemented by Massachusetts Medicaid incentivizing the use of selected generic medications.
  In 2009, Massachusetts Medicaid copayments were $1 for generics and $3 for brands. On February 1, 2009, copayments for generic antihypertensives, antihyperlipidemics, and hypoglycemics (target medications) remained at $1, whereas copayments for all nontarget generics increased to $2 (policy #1) and $3 on July 1, 2010 (policy #2). Using state-level, aggregate prescription data, we developed interrupted time-series models with controls to evaluate the impact of these policies on use of target generics, target brands, and nontarget essential medications (defined as medications required for ongoing treatment of serious medical conditions).
  
  
  RESULTS
  After policy #1, target generic use increased by 0.93% (P<0.001) with a subsequent quarterly slope decrease of -0.16% (P<0.01); policy #2 led to a slope increase of 0.20% (P<0.01) for target generics; increase in target generics attributable to policy changes was 28,000 prescriptions per year. Neither policy affected target brand use. For nontarget essential generics, there was a -0.27% (P<0.001) quarterly slope decrease after policy #1 and a 0.32% (P<0.01) slope increase after policy #2 with total decrease attributable to policy changes of 127,300 prescriptions per year. For nontarget essential brands, there was a level increase of 0.91% (P<0.001) after policy #1 with increased use attributable to policy changes of 98,300 prescriptions per year.
  
  
  CONCLUSIONS
  Two copayment policies designed to encourage use of selected generic medications modestly increased their use; however, there was a shift in other essential medications from generics to brands, which could increase Medicaid costs. When adjusting copayments, careful consideration must be given to unintended consequences of specific policy structures.
authors.affiliation: *Division of Emergency Medicine, Harborview Medical Center, University of Washington, Seattle, WA †Division of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women's Hospital and Harvard Medical School, Boston, MA.
authors.forename: Daniel A
authors.initials: DA
authors.lastname: Lieberman
authors.forename: Jennifer M
authors.initials: JM
authors.lastname: Polinski
authors.forename: Niteesh K
authors.initials: NK
authors.lastname: Choudhry
authors.forename: Jerry
authors.initials: J
authors.lastname: Avorn
authors.forename: Michael A
authors.initials: MA
authors.lastname: Fischer
mesh_terms: D003669:Deductibles and Coinsurance / Q000191:economics / Q000706:statistics & numerical data*; D004363:Drug Utilization / Q000706:statistics & numerical data*; D016568:Drugs, Generic / Q000191:economics*; D006801:Humans; D008404:Massachusetts; D008484:Medicaid / Q000706:statistics & numerical data*; D055553:Prescription Drugs / Q000191:economics*; D014481:United States
chemical_list: D016568:Drugs, Generic; D055553:Prescription Drugs