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Table 2 Logistic Regression Models Predicting Opioid Prescription During Emergency Department Visit

From: Provider Bias in prescribing opioid analgesics: a study of electronic medical Records at a Hospital Emergency Department

  Model 1a Model 2b Model 3c
AME 95% CI AME 95% CI AME 95% CI
Contextual Variables
 ED crowdingd −0.002 *** [− 0.002,− 0.001] -0.001 *** [− 0.002,-0.001] − 0.002 *** [− 0.005,-0.002]
 ED crowding x black 0.000   [− 0.001,0.001] 0.000   [−0.001,0.001] 0.000   [−0.003,0.002]
Timee
6 am-11:59 am 0.008 * [0.001,0.015] −0.005   [−0.01,0.001] 0.018   [0.004,0.030]
12 pm-5:59 pm −0.009 * [−0.016,-0.001] − 0.014 * [− 0.019,-0.010] − 0.006   [− 0.027,0.017]
6 pm-11:59 pm − 0.021 *** [− 0.028,-0.013] − 0.020 *** [− 0.023,-0.017] − 0.026 *** [− 0.033,-0.019]
Weekend 0.022 *** [0.017,0.026] 0.014 *** [0.011,0.016] 0.029 *** [0.025,0.032]
Year −0.022 *** [− 0.023,-0.021] − 0.025 *** [− 0.025,-0.024] − 0.028 *** [− 0.032,-0.026]
Prev. prescribed (#) 0.081 *** [0.080,0.083] 0.063 *** [0.061,0.064] 0.114 *** [0.109,0.118]
Demographic Variables
 Age 20–30 −0.012   [− 0.055,0.031] − 0.006   [− 0.031,0.018]    
 Age 30–40 0.007   [−0.036,0.050] 0.011   [−0.013,0.035]    
 Age 40–50 0.019   [−0.024,0.062] 0.019   [−0.005,0.044]    
 Age 50–60 0.004   [−0.039,0.048] 0.004   [−0.022,0.031]    
 Age 60–70 −0.009   [−0.053,0.035] −0.017   [−0.044,0.010]    
 Age 70–80 −0.055 ** [−0.100,-0.010] −0.063 ** [−0.093,-0.033]    
 Age 80–90 −0.094 *** [−0.140,-0.049] −0.119 *** [−0.140,-0.099]    
 Age 90+ −0.128 *** [−0.179,-0.077] −0.152 *** [−0.182,-0.123]    
Racef
Black −0.033 *** [−0.045,-0.02] −0.018 ** [−0.029,-0.007]    
Latino 0.024 *** [0.010,0.039] 0.000   [−0.008,0.008]    
Asian −0.049 ** [−0.083,-0.014] −0.040 * [−0.058,-0.022]    
Other 0.007   [−0.014,0.027] −0.004   [−0.017,0.008]    
Marital Statusg
Married 0.021 *** [0.015,0.027] 0.014 *** [0.012,0.017]    
Divorced 0.002   [−0.008,0.011] 0.006   [−0.002,0.014]    
Widowed 0.016 * [0.004,0.028] 0.012 * [0.004,0.019]    
Separated −0.002   [−0.015,0.011] 0.001   [−0.006,0.009]    
Sex
Female 0.001   [−0.008,0.009] 0.003   [−0.004,0.010]    
Female x Black −0.011 * [−0.022,-0.001] −0.007   [−0.013,0.001]    
Female x Latino −0.021 * [−0.040,-0.002] −0.004   [−0.018,0.009]    
Female x Asian −0.022   [−0.068,0.024] −0.005   [−0.009,0.001]    
Female x Other −0.023   [−0.050,0.005] −0.020   [−0.044,0.003]    
  1. Notes: * p < 0.05; ** p < 0.01; *** p < 0.001. Parameter estimates reported in average marginal effects. Full models include polynomial terms and interaction effects between prev. Prescribed (#) and year. Sample includes all EMR from hospital ED (n = 180,829 events; 63,513 unique individuals). Years of analysis = 2008–2014. a Includes within-person random effects. b Includes within-person random effects and ICD9 diagnosis. c Includes within-person fixed effects and ICD9 diagnosis. d Number of ED patients in last 4 h. e Reference time = 12 am −5:59 am. f Reference race = White. g Reference marital status = Unmarried. ED emergency department, AME average marginal effects, CI confidence interval