O18 National variation and factors associated with long-term opioid use for non-cancer pain in the first year of use

Abstract

Abstract Background Physician prescribing behaviour has been described as a key driver of rising opioid prescriptions and long-term opioid use. However, the effect of prescribers requires interpretation within context. No studies have investigated the extent to which regions, practices, prescribers, vary in opioid prescribing by considering this hierarchy together, whilst accounting for case-mix. Objectives: (i)quantify and identify risk factors for the transition from new-users to long-term opioid users (ii) quantify variation of long-term use attributed to region, practice, prescriber, accounting for patient mix and chance variation. Methods We conducted a retrospective observational study between 2006-2017 using Clinical Practice Research Datalink. New users of opioids, ≥18 years, without cancer were identified. Long-term opioid use was defined as ≥ 3 opioid prescriptions within a 90-day period from index date, or ≥ 1 opioid prescription lasting at least 90-days in the first year. A multi-level random-effects logistic regression model was used to examine the association of patient characteristics with the odds of becoming a long-term opioid-user. To examine variation in opioid use among prescribers, GP-practices and region after adjusting for case-mix, we used a nested random-effect structure. A ‘high-risk’ region, prescriber or practice was defined as those where the entire adjusted 95% CI lay above population average. Results 1,968,742 new opioid users were included; 14.6% transitioned to long-term use. In the fully-adjusted model, factors associated with higher-odds of long-term use included high morphine-milligram equivalents (MME)/day at first prescription, older-age, deprivation, fibromyalgia, rheumatological conditions and prior surgery (Table 1). After adjustment for case-mix, the North-West, Yorkshire and South-West were found to be high-risk regions for long-term use. 103 practices (25.6%) and 540 prescribers (3.5%) were associated with a significantly higher risk of long-term use. The odds of becoming a long-term user for patients belonging to these prescribers reached up to > 3.5 times than the population average. Conclusion Prescribing factors, age, deprivation and conditions including fibromyalgia and rheumatological conditions were associated with higher odds of long-term opioid use. In the first UK study evaluating long-term opioid prescribing with patient-level characteristics adjustment, variation in regions, especially practices and prescribers were observed. Our findings support greater calls for action to reduce practice/prescriber variation by promoting safe practice in opioid-prescribing. Disclosures M. Jani: None. B. Birlie-Yimer: None. T. Sheppard: None. M. Lunt: None. W.G. Dixon: None.