Predicting adherence trajectory using initial patterns of medication filling

Abstract

Objectives: To evaluate the ability of initial medication dispensings to predict long-term patterns of adherence.

Study design: 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.