Abstract
BACKGROUND: Prescribing habits during admission have largely contributed to the opioid epidemic. Orthopedic surgeons represent the third-highest opioid-prescribing specialty. Since more than half of body fractures in Saudi Arabia have been lower extremity fractures, it is imperative to understand opioid administration patterns and correlates among opioid-naive inpatients. OBJECTIVES: Assess opioid administration patterns and correlates among opioid-naive inpatients with lower extremity fractures. DESIGN AND SETTINGS: Retrospective cohort PATIENTS AND METHODS: Opioid naive individuals aged 18 to 64 years, admitted due to lower extremity fracture from 2016 to 2020 were included. Data was collected from health records of the Ministry of National Guard Health Affairs (MNG-HA) at five different medical centers. The high-dose (>= 50 MME) patients were compared with low dose (<50 MME) patients. Any association between inpatient factors and high-dose opioid use was analyzed by multiple logistic regression. MAIN OUTCOME MEASURES: Opioids taken during inpatient admission as measured by milligram morphine equivalents (MME)/per day. SAMPLE SIZE: 1520 patients RESULTS: Most of the 1520 patients (88.5%) received an opioid medication, while (20.3%) received high-dose opioids at a median daily dose of 33.7 MME/per day. The proportion of patients received naloxone (20.7%) was double among high-dose opioid inpatients. High -dose opioid patients during admission were two times more likely to receive an opioid prescription after discharge (odds ratio, 2.32; 95% confidence interval, 1.53, 3.51), and three more times likely to receive ketamine during admission (odds ratio, 3.02; 95% confidence interval, 1.64, 5.54). CONCLUSION: Notable variabilities exist in opioid administration patterns that were not explained by patient factors. Evidence-based opioid prescribing practices should be developed for orthopedic patients to prevent opioid overprescribing and potential opioid overdose among orthopedic patients. LIMITATIONS: Retrospective, unmeasurable confounders might have biased our results. Since based on National Guard employees, results not be