Use of a multi-state model in a claims database: illustration with methadone

Abstract

Purpose: In pharmacoepidemiology, one of the main concerns is analysis of drug exposure time. However, in real-life settings, patient's behavior is complex and characterized by drug exposure dynamics. Multi-state models allow assessing the probabilities of various patterns, instead of just continuous use and/or discontinuation. The aim of this study was to illustrate with methadone, the use of multi-state model (MSM) in a large claims database.

Methods: This study is based on the French health insurance reimbursement database. Methadone exposure is defined using four states for each period of follow-up: syrup only, capsule only, syrup-capsule and no dispensing. The model considered 12 possible transitions (including reverse transitions) from one state to another. To describe these transitions a time-homogeneous Markov model was used.

Results: A total of 1265 methadone users were included. When patients belonged to the syrup-capsule state, they had a 61.8% chance of moving to capsules the following month and 20.9% of moving to syrup. The probability of moving from the syrup to the non-user state was 13.6% (11.7% from capsule state to non-user state). The average length of stay was 5.9 months (CI95%: [5.5-6.4]) in capsule state, 4.9 (CI95%: [4.6-5.2]) in syrup state and 5.9 (CI95%: [5.5-6.3]) in non user state.

Conclusion: MSM provided a good description of methadone patterns of use. It outlined behaviors which have led to a rapid spread of capsule formulation among methadone users. Therefore, it illustrates the utility of MSM for modeling multiple sequences of drug use in a large claims database.

Keywords: Markov; formulation; methadone; multi-state model; pharmacoepidemiology.