Journal of opioid management · 2023
Predictors of opioid prescription among outpatients with osteoarthritis in the United States.
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Gohil Shrey, Deyhim Niaz, Mgbere Osaro, Essien Ekere James
Аннотация
BACKGROUND: Osteoarthritis (OA) management targets pain reduction through multimodal strategies to improve functional status. Among pharmaceutical options, opioids have been selected as a treatment option for pain management, without endorsement by evidence-based guidelines.
OBJECTIVE: To examine the predictors of opioid prescriptions for OA during outpatient visits in the United States (US).
DESIGN: This study was based on the National Ambulatory Medical Care Survey (NAMCS) database (2012-2016), with a retrospective, cross-sectional study design of US adult outpatient visits with OA. The primary outcome was opioid prescription, and socio-demographic and clinical characteristics were independent variables. Weighted descriptive, bivariate, and multivariable logistic regression analyses were utilized to study patient characteristics and to assess the predictors of opioid prescription.
RESULTS: Approximately, 51.68 million (95 percent CI = 44.41-58.95 million) OA-related outpatient visits were made between 2012 and 2016. Most patients were established patients (82.32 percent), and 20.58 percent of the visits resulted in opioid prescriptions. Key prescriptions within the opioid analgesic and combination categories were tramadol-based (5.16 percent) and hydrocodone-based (9.10 percent). Patients who paid through Medicaid were three times more likely (aOR = 3.25, 95 percent CI = 1.60-6.61, p = 0.0012) than those who paid through private insurance to receive an opioid prescrip-tion, new patients were 59 percent less likely (aOR = 0.41, 95 percent CI = 0.24-0.68, p = 0.0007) to receive an opioid prescription as compared to established patients, and obese patients were twice as likely (aOR = 1.88, 95 percent CI = 1.11-3.20, p = 0.0199) than nonobese patients to receive an opioid prescription.
CONCLUSIONS: Payment source, obesity, and patient visit status were associated with the receipt of an opioid prescription among OA outpatients. Further research is needed to establish intrinsic factors that drive opioid prescription in this population.
OBJECTIVE: To examine the predictors of opioid prescriptions for OA during outpatient visits in the United States (US).
DESIGN: This study was based on the National Ambulatory Medical Care Survey (NAMCS) database (2012-2016), with a retrospective, cross-sectional study design of US adult outpatient visits with OA. The primary outcome was opioid prescription, and socio-demographic and clinical characteristics were independent variables. Weighted descriptive, bivariate, and multivariable logistic regression analyses were utilized to study patient characteristics and to assess the predictors of opioid prescription.
RESULTS: Approximately, 51.68 million (95 percent CI = 44.41-58.95 million) OA-related outpatient visits were made between 2012 and 2016. Most patients were established patients (82.32 percent), and 20.58 percent of the visits resulted in opioid prescriptions. Key prescriptions within the opioid analgesic and combination categories were tramadol-based (5.16 percent) and hydrocodone-based (9.10 percent). Patients who paid through Medicaid were three times more likely (aOR = 3.25, 95 percent CI = 1.60-6.61, p = 0.0012) than those who paid through private insurance to receive an opioid prescrip-tion, new patients were 59 percent less likely (aOR = 0.41, 95 percent CI = 0.24-0.68, p = 0.0007) to receive an opioid prescription as compared to established patients, and obese patients were twice as likely (aOR = 1.88, 95 percent CI = 1.11-3.20, p = 0.0199) than nonobese patients to receive an opioid prescription.
CONCLUSIONS: Payment source, obesity, and patient visit status were associated with the receipt of an opioid prescription among OA outpatients. Further research is needed to establish intrinsic factors that drive opioid prescription in this population.