A Mixture Distribution Approach to Assessing Medication Refill Compliance with Administrative Pharmacy Refill Records

Abstract

The assessment of a patient’s medication compliance using pharmacy refill data is often challenging due to the complex distribution of the measures used to assess compliance. To address this problem, we propose a mixture distribution approach, with which methods based on the likelihood function, such as the likelihood ratio test, can be applied for testing intervention effects in randomized clinical trials. The advantage of a mixture distribution approach is that it allows for a flexible adaptation of censored data analysis to modeling refill data. It also supports visualization of the risk curve of noncompliance, conditional on given levels of refill compliance. Our approach is illustrated using pharmacy refill data from a prospective clinical trial.