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Updated: Jun 12, 2026

An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
A competing risks prescription refill model of compliance and persistence
T Ian Barron1, Kathleen Bennett, John Feely
1Department of Pharmacology & Therapeutics, Trinity College, University of Dublin, Dublin, Ireland. barront@tcd.ie
Objectives:
There is evidence to suggest that noncompliant and nonpersistent behaviors have differing risk factors, clinical consequences, and responses to intervention. This has led to calls for these behaviors to be defined and measured separately to characterize medication-taking behavior comprehensively. Current prescription refill models of compliance are, however, unable to appropriately distinguish between noncompliant and nonpersistent behaviors. To address this limitation, a prescription refill model of medication-taking behavior in which noncompliance and nonpersistence are treated as competing risks is presented.
Methods:
The proposed competing risks model of compliance and persistence is compared with a selection of widely applied prescription refill models of compliance and persistence using a common cohort of patients prescribed statin therapy.
Results:
The competing risks model allows the simultaneous measurement of noncompliance and nonpersistence, the partitioning of their individual contributions to medication-taking behavior, and the estimation of noncompliance risk for patients with varying treatment persistence. The results from this model provide information about the relative and overall contributions of noncompliant and nonpersistent behaviors to medication-taking behavior. The methodology also allows an assessment of the differential influence of various risk factors on these behaviors.
Conclusions:
The proposed competing risks model differentiates between noncompliant and nonpersistent behaviors using prescription refill data. Results from the model provide insights into the dynamics of noncompliant and nonpersistent behaviors that have not been possible with current prescription refill methodologies.
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