Abstract Purpose The current study aimed to identify patients presenting with acute pain who may be at risk for a complicated trajectory, via identifying clusters of early opioid prescribing patterns. Methods National Veterans Affairs administrative data were utilized to build a cohort of outpatients with acute pain presentations and no more than minimal opioid use in the prior year. Latent Class Analyses (LCAs) identified clusters of early opioid prescribing patterns. The risk of progression to long‐term opioid use was contrasted between LCA clusters using log‐binomial regression, adjusting for confounding variables. Results The 2018 cohort included N?=?191,283. Among the 27,890 who received an initial opioid prescription, LCA classes were identified using: first supply day, total days dispensed across 30?days, opioid type, dose and number of prescriptions across the first 30?days. In the three‐class model: class 1 indicated an immediate, low‐dose and brief supply; class 2 included delayed, low‐dose and longer duration prescriptions and class 3 included delayed, high‐dose and moderate duration prescriptions. Adjusted relative risk ratios for progression to long‐term opioid use in the following year were 3.33 (95 CI: 2.71–4.10) for class 1 (absolute risk 1.1); 7.76 (95 CI: 6.69–8.99) for class 2 (3.1) and 6.81 (95 CI: 5.72–8.12) for class 3 (2.4) compared to patients who did not receive an acute opioid prescription (0.3). Conclusions These clusters of acute opioid prescribing could facilitate the identification of patients who may benefit from enhanced pain care earlier in the pain trajectory and decrease future reliance on long‐term opioid therapy.
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