title: Predicting adherence trajectory using initial patterns of medication filling.
abstract: OBJECTIVE
  To evaluate the ability of initial medication dispensings to predict long-term patterns of adherence.
  
  
  METHODS
  A retrospective cohort study of statin initiators enrolled in a Medicare Part D drug plan from CVS Caremark from 2005 to 2008.
  
  
  METHODS
  We used group-based trajectory models to classify patients into 6 adherence trajectories based on patterns of statin filling over the year following therapy initiation. Baseline clinical characteristics and indicators of statin filling during the first 2 to 4 months following initiation were used to predict adherence trajectory in logistic regression models, separately within strata of the days' supply of the initial statin dispensing. Cross-validation was used to measure predictive accuracy of models in data not used for model estimation.
  
  
  RESULTS
  Among 77,703 statin initiators, prediction using baseline variables only was poor (cross-validated C statistic ≤ 0.61). When using 3 months of initial adherence to predict trajectory, prediction was greatly improved among patients with an index supply ≤30 days (0.62 ≤ C ≤ 0.91). With 4 months of initial adherence in the model, prediction was strong for all patients (C ≥ 0.72), especially for the best and worst trajectories (C = 0.90 and 0.94, respectively, in patients with an index supply ≤ 30 days; and C = 0.83 and 0.90, respectively, in patients with an index supply > 30 days).
  
  
  CONCLUSIONS
  Initial filling behavior strongly predicted future adherence trajectory. Predicting adherence trajectories may facilitate better targeting of interventions to patients most likely to benefit.
authors.affiliation: 1620 Tremont St, Ste 3030, Boston, MA 02120. E-mail: JMFranklin@partners.org.
authors.forename: Jessica M
authors.initials: JM
authors.lastname: Franklin
authors.forename: Alexis A
authors.initials: AA
authors.lastname: Krumme
authors.forename: William H
authors.initials: WH
authors.lastname: Shrank
authors.forename: Olga S
authors.initials: OS
authors.lastname: Matlin
authors.forename: Troyen A
authors.initials: TA
authors.lastname: Brennan
authors.forename: Niteesh K
authors.initials: NK
authors.lastname: Choudhry
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D005260:Female; D006801:Humans; D019161:Hydroxymethylglutaryl-CoA Reductase Inhibitors / Q000008:administration & dosage / Q000627:therapeutic use*; D007345:Insurance Claim Review; D016015:Logistic Models; D008297:Male; D054524:Medicare Part D / Q000706:statistics & numerical data; D015203:Reproducibility of Results; D012189:Retrospective Studies; D013997:Time Factors; D014481:United States; D016903:Drug Monitoring
chemical_list: D019161:Hydroxymethylglutaryl-CoA Reductase Inhibitors