• Juliana de Oliveira Costa, Claudia Bruno, Navya Baranwal, Natasa Gisev, Timothy A Dobbins, Louisa Degenhardt, and Sallie-Anne Pearson.
• Centre for Big Data Research in Health, Faculty of Medicine, UNSW Sydney, Sydney, NSW, Australia.
• Br J Clin Pharmacol. 2021 Oct 1; 87 (10): 3706-3720.

AbstractRoutinely collected data have been increasingly used to assess long-term opioid therapy (LTOT) patterns, with very little guidance on how to measure LTOT from these data sources. We conducted a systematic review of studies published between January 2000 and July 2019 to catalogue LTOT definitions, the rationale for definitions and LTOT rates in observational research using routinely collected data in nonsurgical settings. We screened 4056 abstracts, 210 full-text manuscripts and included 128 studies, mostly from the United States (81%) and published between 2015 and 2019 (69%). We identified 78 definitions of LTOT, commonly operationalised as 90 days of use within a year (23%). Studies often used multiple criteria to derive definitions (60%), mostly based on measures of duration, such as supply days/days of use (66%), episode length (21%) or prescription fills within specified time periods (12%). Definitions were based on previous publications (63%), clinical judgment (16%) or empirical data (3%); 10% of studies applied more than one definition. LTOT definition was not provided with enough details for replication in 14 studies and 38 studies did not specify the opioids evaluated. Rates of LTOT within study populations ranged from 0.2% to 57% according to study design and definition used. We observed a substantial rise in the last 5 years in studies evaluating LTOT with large variability in the definitions used and poor reporting of the rationale and implementation of definitions. This variation impacts on research reproducibility, comparability of findings and the development of strategies aiming to curb therapy that is not guideline-recommended.© 2021 British Pharmacological Society.

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