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

Keister, Lisa A.; Stecher, Chad; Aronson, Brian; McConnell, William; Hustedt, Joshua; Moody, James W.

doi:10.1186/s12889-021-11551-9

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 1^a			Model 2^b			Model 3^c
	AME		95% CI	AME		95% CI	AME		95% CI
Contextual Variables
ED crowding^d	−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]
Time^e
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]
Race^f
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 Status^g
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]

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

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