Table 2.

Odds of Receipt of Opioid Risk Reduction Strategies for Black vs White Patientsa

Additive Adjustment for Sets of Variables
StrategyUnadjustedClusteringbDemographicscSubstance AbusedComorbiditieseHealth Care FactorsfPractice Site
Note: Values are odds ratios (95% confidence intervals) and P values.
a Nonlinear mixed effect regression models adjusting additively for sets of patient, clinical, and health care variables.
b Clustering of patients within physician.
c Includes sex, age, median household income of neighborhood.
d Includes problem substance use (alcohol, nonopiates, and opioids), tobacco use.
e Mental health and medical comorbidities.
f Includes duration of long-term opioid treatment, appointment attendance rate, and primary care use category. Primary care use category was not included in the regular office visits models.
g Urine drug testing analysis excludes 2 practices that performed only 1 test or no tests in patients (n = 274 patients).
Urine drug testingg1.63 (1.03–2.59) P=.041.53 (0.92–2.53) P=.101.44 (0.82–2.54) P=.211.45 (0.82–2.58) P=.201.54 (0.86–2.73) P=.151.56 (0.87–2.78) P=.141.41 (0.78–2.54) P=.26
Regular office visits2.03 (1.65–2.49) P <.0012.22 (1.71–2.87) P <.0011.74 (1.28–2.38) P <.0011.74 (1.28–2.38) P <.0011.66 (1.21–2.28) P <.011.55 (1.10–2.19) P=.011.51 (1.06–2.14) P=.02
Restricted early refills1.48 (1.17–1.87) P <.011.60 (1.22–2.10) P <.011.48 (1.06–2.08) P=.021.50 (1.07–2.10) P=.021.50 (1.01–2.11) P=.021.56 (1.06–2.31) P=.031.55 (1.03–2.32) P=.04