Table 3.

 Logistic regression model for arrival vs non-adherence with initial appointment (OR refer to odds of arriving to clinic; N = 3002)

Variable	Odds ratio	95% CI	P values
Language
English language (reference)	1	N/A	N/A
Spanish language	1.32	1.06–1.64	0.014
Other language	0.86	0.55–1.34	0.51
Age	1.01	1.00–1.01	0.011
Female	1.16	1.00–1.41	0.061
Married	1.18	0.99–1.41	0.061
Race
Other race (reference)	1	N/A	N/A
White	1.27	1.01–1.61	0.043
Black	1.06	0.89–1.27	0.51
Decline	1.39	1.10–1.75	0.005
Employment status
Unknown employment status (reference)	1	N/A	N/A
Employed	0.88	0.72–1.08	0.21
Unemployed	0.72	0.56–0.92	0.009
Disability	0.72	0.33–1.59	0.42
Retired	1.09	0.67–1.80	0.72
Insurance status
Managed care (reference)	1	N/A	N/A
Medicare	0.78	0.63–0.97	0.028
Medicaid	0.94	0.66–1.34	0.72
Commercial insurance	1.43	1.13–1.81	0.003
Self pay	0.63	0.19–2.10	0.45
Procedure performed	0.46	0.17–1.20	0.11

OR, CI, and P values for association between patient characteristics and arrival at the pain clinic in a logistic regression model including variables with bivariate baseline testing results of P ≤ 0.25; or variables, such as age, race, and gender, that were selected a priori. For nominal variables like language spoken, race, and employment status, the reference group in the logistic regression models was assigned based on sample size with largest serving as reference (e.g., English language for language, Other race for race, Unknown employment status for employment, Managed care for insurance type). CI = confidence interval; N/A = not applicable.