Predictors of Opioid Prescription Among a Sample of Patients with Acute Musculoskeletal Pain at a Tertiary Care Hospital in Saudi Arabia

Abstract

Background: Musculoskeletal pain is one of the most complex and debilitating types of pain. Although different pharmacologic treatments are available, very few studies have explored the predictors for opioid analgesics prescription to manage this type of pain. Objective: The aim of this study was to explore the predictors for opioid prescription in patients with acute musculoskeletal pain in Saudi Arabia. Methods: This was a single-center, retrospective chart review of adult patients (≥ 18 yrs.) with an acute nociceptive musculoskeletal pain at a university-affiliated medical center in Riyadh, Saudi Arabia. Cancer patients and those with chronic neuropathic pain were excluded. Patients’ age, gender, number of comorbidities, duration of pain management, number of clinic visits for pain, and Numeric Pain Rating Scale (NPRS) scores at rest and with normal activities were collected. Multiple logistic regression was conducted to examine the relationship between the type of musculoskeletal pain and the prescription of opioid analgesics controlling for NPRS score on activity, age, gender, number of comorbidities, duration of pain treatment, and number of clinic visits for pain. Results: The mean age of the 227 patients, who met the inclusion criteria, was 39 years and 68% of them were male. Sixty-three percent of the patients were prescribed opioid analgesics, and 61% of them had shoulder pain, 29% had back pain, and 10% had lower extremity pain (eg, hip, thigh, lower leg, knee, ankle, and foot pain). Tramadol was the most commonly prescribed opioid analgesic (82%), followed by codeine (13%). Ninety-seven percent of patients who were prescribed non-opioid analgesics had shoulder pain. Patients with shoulder pain had lower odds of receiving opioid analgesics (OR=0.019, P< 0.0001, 95% CI=0.004– 0.081) in comparison to their counterparts who had lower extremity or back pains. Moreover, the higher the pain score on activity was, the higher odds of receiving opioid analgesics (OR=1.317, P< 0.0001, 95% CI=1.029– 1.685). Conclusion: Future studies should explore the impact of different opioid prescribing policies to improve the quality of patient care and reduce the unnecessary prescribing of opioids for patients with non-cancer musculoskeletal pain.