title: Patterns and predictors of generic narrow therapeutic index drug use among older adults.
abstract: OBJECTIVE
  To ascertain predictors of initiation of brand-name versus generic narrow therapeutic index (NTI) drugs.
  
  
  METHODS
  Retrospective cohort study.
  
  
  METHODS
  Data from CVS Caremark were linked to Medicare claims and to U.S. census data.
  
  
  METHODS
  Individuals aged 65 and older who initiated an NTI drug in 2006 and 2007 (N = 36,832).
  
  
  METHODS
  Demographic, health service utilization, and geographic predictors of whether participants initiated a generic or brand-name version of their NTI drug were identified using logistic regression.
  
  
  RESULTS
  Overall, 30,014 (81.5%) participants started on a generic version of their NTI drug. The most commonly initiated NTI drugs were warfarin (n = 17,790; 48%), levothyroxine (n = 10,779; 29%), and digoxin (n = 6,414; 17%). Older age (odds ratio (OR) = 1.12, 95% confidence interval (CI) = 1.02-1.22 comparing aged ≥ 85 with 65-74), higher burden of comorbidity (OR = 1.05, 95% CI = 1.04-1.07 for each 1-point increase in comorbidity score), and prior use of any generic drug (OR = 1.55, 95% CI = 1.29-1.87) were positively associated with generic drug initiation. Independent of other predictors, residing in the census block group with the highest generic use was positively associated with greater odds of generic NTI drug initiation (OR = 1.24, 95% CI = 1.14-1.35 compared with the lowest quintile).
  
  
  CONCLUSIONS
  Demographic, health service utilization, and geographic characteristics are important determinants of whether individuals initiate treatment with a brand-name or generic NTI drug. These factors may contribute to disparities in care and highlight potential targets for educational campaigns.
authors.affiliation: Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts.
authors.forename: Joshua J
authors.initials: JJ
authors.lastname: Gagne
authors.forename: Jennifer M
authors.initials: JM
authors.lastname: Polinski
authors.forename: Aaron S
authors.initials: AS
authors.lastname: Kesselheim
authors.forename: Niteesh K
authors.initials: NK
authors.lastname: Choudhry
authors.forename: David
authors.initials: D
authors.lastname: Hutchins
authors.forename: Olga S
authors.initials: OS
authors.lastname: Matlin
authors.forename: Angela
authors.initials: A
authors.lastname: Tong
authors.forename: William H
authors.initials: WH
authors.lastname: Shrank
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D016001:Confidence Intervals; D004363:Drug Utilization / Q000706:statistics & numerical data*; D016568:Drugs, Generic / Q000627:therapeutic use*; D005260:Female; D005500:Follow-Up Studies; D006296:Health Services / Q000706:statistics & numerical data*; D006801:Humans; D007356:Insurance, Pharmaceutical Services / Q000706:statistics & numerical data*; D008297:Male; D006278:Medicare / Q000191:economics*; D016017:Odds Ratio; D012189:Retrospective Studies; D014481:United States / Q000453:epidemiology
chemical_list: D016568:Drugs, Generic
keywords: Medicare; drugs; health services research; pharmacoepidemiology; utilization