Longitudinal dose patterns among patients newly initiated on long-term opioid therapy in the United States, 2018 to 2019: an observational cohort study and time-series cluster analysis

Abstract

Abstract Opioid prescribing varies widely, and prescribed opioid dosages for an individual can fluctuate over time. Patterns in daily opioid dosage among patients prescribed long-term opioid therapy have not been previously examined. This study uses a novel application of time-series cluster analysis to characterize and visualize daily opioid dosage trajectories and associated demographic characteristics of patients newly initiated on long-term opioid therapy. We used 2018 to 2019 data from the IQVIA Longitudinal Prescription (LRx) all-payer pharmacy database, which covers 92% of retail pharmacy prescriptions dispensed in the United States. We identified a cohort of 277,967 patients newly initiated on long-term opioid therapy during 2018. Patients were stratified into 4 categories based on their mean daily dosage during a 90-day baseline period (<50, 50-89, 90-149, and ≥150 morphine milligram equivalent [MME]) and followed for a 270-day follow-up period. Time-series cluster analysis identified 2 clusters for each of the 3 baseline dosage categories <150 MME and 3 clusters for the baseline dosage category ≥150 MME. One cluster in each baseline dosage category comprised opioid dosage trajectories with decreases in dosage at the end of the follow-up period (80.7%, 98.7%, 98.7%, and 99.0%, respectively), discontinuation (58.5%, 80.0%, 79.3%, and 81.7%, respectively), and rapid tapering (50.8%, 85.8%, 87.5%, and 92.9%, respectively). These findings indicate multiple clusters of patients newly initiated on long-term opioid therapy who experience discontinuation and rapid tapering and highlight potential areas for clinician training to advance evidence-based guideline-concordant opioid prescribing, including strategies to minimize sudden dosage changes, discontinuation, or rapid tapering, and the importance of shared decision-making.