Utilization of emergency and hospital services among individuals in substance abuse treatment

Table 2 Random effect negative binomial regression on ER visits

	IRR	SE	p	95% CI
Race/ethnicity
Non-Latino White^a
Black	0.852	0.031	< .001	0.793, 0.915
Latino	0.826	0.025	< .001	0.778, 0.876
Age	1.000	0.001	.836	0.997, 1.002
Male	0.777	0.021	< .001	0.737, 0.819
Education	1.017	0.005	.001	1.007, 1.028
Homeless	1.212	0.035	< .001	1.145, 1.283
History of mental health issues	0.661	0.018	< .001	0.627, 0.698
Days of mental health counseling	1.021	0.003	< .001	1.015, 1.028
Days of psychiatric care	1.032	0.003	< .001	1.025, 1.039
Days of physical problems	1.067	0.001	< .001	1.065, 1.069
Age at first drug use	0.998	0.002	.210	0.995, 1.001
Days of primary drug use	0.996	0.001	.001	0.994, 0.998
Primary drug problem
Alcohol^a
Cocaine	1.790	0.075	< .001	1.649, 1.942
Heroin	1.113	0.051	.020	1.017, 1.218
Marijuana	1.194	0.059	< .001	1.083, 1.316
Methamphetamine	1.113	0.072	.096	0.981, 1.264
Other	1.620	0.090	< .001	1.454, 1.806
Children younger than 18	1.008	0.004	.036	1.001, 1.016
Program modality
Outpatient^a
Methadone	0.964	0.116	.763	0.761, 1.221
Residential	1.606	0.068	< .001	1.479, 1.744

Note: ER, emergency room; IRR, incidence rate ratio. IRRs can be interpreted as the estimated rate ratio for a 1-unit increase in the independent variable, given the other variables are held constant in the model. For example, if days of physical problems increased by 1 point, the ratio for number of ER visits would be expected to increase by a factor of IRR = 1.067, while holding all other variables in the model constant.
Wald chi-square tests with degrees of freedom (20) = 6693.30. The corresponding p-value is less than 0.0001.
^aReference category.

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