Seattle, WA, USA – Clinical trial patients often exhibit high medication adherence. But what happens in the real world? Medication adherence in routine practice is often lower and the effectiveness may differ. Models used to evaluate the cost- and comparative effectiveness of drugs typically assume constant medication adherence and trial-based efficacy. Such models are “naïve” to potential transitions in adherence over time and related changes in drug effectiveness.
Researchers from the University of Washington School of Pharmacy, Regis University School of Pharmacy, and University of Colorado presented a practical approach to adherence modeling. They described a novel method to convert an “adherence-naïve” base-case Markov model of statin therapy into a dynamic adherence model by incorporating real-world adherence and effectiveness rather than assuming static adherence and trial-based efficacy. The dynamic adherence model resulted in fewer cardiovascular events avoided versus the adherence-naïve model, highlighting the difference between trial-based and real-world effectiveness. Such a model may be used to understand the value of improving patients’ adherence.
Julia F. Slejko, PhD, postdoctoral Fellow at the Pharmaceutical Outcomes Research and Policy Program at the University of Washington School of Pharmacy and corresponding author, states, “Our approach illustrated value differences overall, and by adherence subgroup. This is an advantage over methods that use average patient cohorts and model findings may be used to inform and evaluate patient-centered interventions to improve adherence.”
The full study, “Dynamic Medication Adherence Modeling in Primary Prevention of Cardiovascular Disease: A Markov Microsimulation Methods Application,” is published in Value in Health.