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Race and Gender Are Associated with Opioid Dose Reduction Among Patients on Chronic Opioid Therapy
Michele Buonora1, Hector R Perez2, Moonseong Heo3
1Albert Einstein College of Medicine, Bronx, New York.
Objective:
Among patients with chronic pain, risk of opioid use is elevated with high opioid dose or concurrent benzodiazepine use. This study examined whether these clinical factors, or sociodemographic factors of race and gender, are associated with opioid dose reduction.
Design And Setting:
A retrospective cohort study of outpatients prescribed chronic opioid therapy between 2007 and 2012 within a large, academic health care system in Bronx, New York, using electronic medical record data. Included patients were prescribed a stable dose of chronic opioid therapy over a one-year "baseline period" and did not have cancer.
Methods:
The primary outcome was opioid dose reduction (≥30% reduction from baseline) within two years. Multivariable logistic regression tested the associations of two clinical variables (baseline daily opioid dose and concurrent benzodiazepine prescription) and two sociodemographic variables (race/ethnicity and gender) with opioid dose reduction.
Results:
Of 1,097 patients, 463 (42.2%) had opioid dose reduction. High opioid dose (≥100 morphine-milligram equivalents [MME]) was associated with lower odds of opioid dose reduction compared with an opioid dose <100 MME (adjusted odds ratio [AOR] = 0.69, 95% confidence interval [CI] = 0.54-0.89). Concurrent benzodiazepine prescription was not associated with opioid dose reduction. Black (vs white) race and female (vs male) gender were associated with greater odds of opioid dose reduction (AOR = 1.82, 95% CI = 1.22-2.70; and AOR = 1.43, 95% CI = 1.11-1.83, respectively).
Conclusions:
Black race and female gender were associated with greater odds of opioid dose reduction, whereas clinical factors of high opioid dose and concurrent benzodiazepine prescription were not. Efforts to reduce opioid dose should target patients based on clinical factors and address potential biases in clinical decision-making.
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