title: Transition probabilities and predictors of adherence in a California Medicaid population using antihypertensive and lipid-lowering medications.
abstract: OBJECTIVE
  To determine adherence rates, transition probabilities, and factors associated with transition from higher to lower adherence in antihypertensive (AH) and lipid-lowering (LL) medications.
  
  
  METHODS
  California Medicaid data (1995-2003) were used to identify hypertensive patients with prescriptions for both AH and LL medications. Proportion of days covered (PDC) was used to define three adherence classifications: fully adherent (FA, PDC >or= 0.8), partially adherent (PA, 0.2 <or= PDC < 0.8), and nonadherent (NA, PDC < 0.2). Annual transition matrices documented the probability of adherence status changes.
  
  
  RESULTS
  Only 13% of the 5943 patients were FA to both drugs at baseline. Patients who were FA (60%) or NA (84%) to both drugs had high probability of maintaining status at year two (Y2). Significant variables associated with a transition from adherent to NA at Y2 included African American race (odds ratio [OR] 1.5), other race groups (OR 1.2), lack of Medicare eligibility (OR 1.3), and initiating LL therapy of fibric acid derivatives (OR 1.3) or niacin (OR 1.8).
  
  
  CONCLUSIONS
  Patients FA or NA with both drugs at baseline were more likely to maintain their adherence status. Race, insurance coverage, and type of LL medication were significantly associated with transitioning from any adherence status to nonadherence. These findings may be useful in guiding cost-effectiveness analyses incorporating adherence estimates.
authors.affiliation: Department of Clinical Pharmacy and Pharmaceutical Economics and Policy, School of Pharmacy, University of Southern California, Los Angeles, CA 90033, USA. mnichol@usc.edu
authors.forename: Michael B
authors.initials: MB
authors.lastname: Nichol
authors.forename: Tara K
authors.initials: TK
authors.lastname: Knight
authors.forename: Joanne
authors.initials: J
authors.lastname: Wu
authors.forename: Simon S K
authors.initials: SS
authors.lastname: Tang
authors.forename: Spencer B
authors.initials: SB
authors.lastname: Cherry
authors.forename: Joshua S
authors.initials: JS
authors.lastname: Benner
authors.forename: Mohamed
authors.initials: M
authors.lastname: Hussein
mesh_terms: D000368:Aged; D000959:Antihypertensive Agents / Q000627:therapeutic use*; D002140:California; D003625:Data Collection; D016208:Databases, Factual; D005260:Female; D006801:Humans; D006949:Hyperlipidemias / Q000188:drug therapy*; D006973:Hypertension / Q000188:drug therapy*; D000960:Hypolipidemic Agents / Q000627:therapeutic use*; D016015:Logistic Models; D008297:Male; D008484:Medicaid / Q000706:statistics & numerical data; D008875:Middle Aged; D016017:Odds Ratio; D055553:Prescription Drugs; D011336:Probability; D018570:Risk Assessment; D013997:Time Factors; D014481:United States; D016903:Drug Monitoring
chemical_list: D000959:Antihypertensive Agents; D000960:Hypolipidemic Agents; D055553:Prescription Drugs