Abstract

Opioids are commonly used to manage pain, despite an increased risk of adverse events and complications when used against recommendations. This register study uses data of osteoarthritis (OA) patients with joint replacement surgery to identify and characterize problematic opioid use (POU) prescription patterns. The study population included adult patients diagnosed with OA in specialty care undergoing joint replacement surgery in Denmark, Finland, Norway, and Sweden during 1 January 2011 to 31 December 2014. Those with cancer or OA within three years before the first eligible OA diagnosis were excluded. Patients were allocated into six POU cohorts based on dose escalation, frequency, and dosing of prescription opioids post-surgery (definitions were based on guidelines, previous literature, and clinical experience), and matched on age and sex to patients with opioid use, but not in any of the six cohorts. Data on demographics, non-OA pain diagnoses, cardiovascular diseases, psychiatric disorders, and clinical characteristics were used to study patient characteristics and predictors of POU. 13.7% of patients with OA and a hip/knee joint replacement were classified as problematic users and they had more comorbidities and higher pre-surgery doses of opioids than matches. Patients dispensing high doses of opioids pre-surgery dispensed increased doses post-surgery, a pattern not seen among patients prescribed lower doses pre-surgery. Being dispensed 1-4,500 oral morphine equivalents in the year pre-surgery or having a non-OA pain diagnosis was associated with post-surgery POU (OR: 1.44-1.50, and 1.11-1.20, respectively). Based on the discovered POU predictors, the study suggests that prescribers should carefully assess pain management strategies for patients with a history of comorbidities and pre-operative, long-term opioid use. Healthcare units should adopt risk assessment tools and ensure that these patients are followed up closely. The data also demonstrate potential areas for further exploration in improving patient outcomes and trajectories.

Full Text
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