title: Is there a relationship between patient beliefs or communication about generic drugs and medication utilization?
abstract: BACKGROUND
  Insurers and policymakers strive to stimulate more cost-effective prescribing and, increasingly, are educating beneficiaries about generics.
  
  
  OBJECTIVE
  To evaluate the relationship between patient beliefs and communication about generic drugs and actual drug use.
  
  
  METHODS
  We performed a national mailed survey of a random sample of 2500 commercially-insured adults. Patient responses were linked to pharmacy claims data to assess actual generic medication use.
  
  
  METHODS
  We used factor analysis to develop 5 multi-item scales from patient survey responses that measured: (1) general preferences for generics, (2) generic safety/effectiveness, (3) generic cost/value, (4) comfort with generic substitution, and (5) communication with providers about generics. The relationship between each scale and the proportion of prescriptions filled for generics was assessed using linear regression, controlling for demographic, health, and insurance characteristics. Separate models were created for each scale and then all 5 scales were included simultaneously in a fully-adjusted model.
  
  
  RESULTS
  The usable response rate was 48%. When evaluated independently, a 1 SD increase in each of the 5 scales was associated with a 3.1% to 6.3% increase in generic drug use (P < 0.05 for each). In the fully adjusted model, only 2 scales were significantly associated with generic drug use: comfort with generic substitution (P = 0.021) and communication with providers about generic drugs (P = 0.012).
  
  
  CONCLUSIONS
  Generic drug use is most closely associated with the 2 actionable items we evaluated: communication with providers about generics and comfort with generic substitution. Educational campaigns that focus on these 2 domains may be most effective at influencing generic drug use.
authors.affiliation: Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 02120, USA. wshrank@partners.org
authors.forename: William H
authors.initials: WH
authors.lastname: Shrank
authors.forename: Suzanne M
authors.initials: SM
authors.lastname: Cadarette
authors.forename: Emily
authors.initials: E
authors.lastname: Cox
authors.forename: Michael A
authors.initials: MA
authors.lastname: Fischer
authors.forename: Jyotsna
authors.initials: J
authors.lastname: Mehta
authors.forename: Alan M
authors.initials: AM
authors.lastname: Brookhart
authors.forename: Jerry
authors.initials: J
authors.lastname: Avorn
authors.forename: Niteesh K
authors.initials: NK
authors.lastname: Choudhry
mesh_terms: D000328:Adult; D000368:Aged; D003142:Communication; D016527:Drug Costs; D016568:Drugs, Generic / Q000627:therapeutic use*; D005163:Factor Analysis, Statistical; D005260:Female; D019538:Health Care Surveys; D006801:Humans; D007356:Insurance, Pharmaceutical Services; D008297:Male; D055118:Medication Adherence / Q000523:psychology*; D008875:Middle Aged; D017060:Patient Satisfaction / Q000706:statistics & numerical data*; D010465:Perception; D010817:Physician-Patient Relations; D012449:Safety; D011795:Surveys and Questionnaires; D016896:Treatment Outcome; D014481:United States; D055815:Young Adult; D016903:Drug Monitoring
chemical_list: D016568:Drugs, Generic