1. Anxiety/Depression Diagnoses and Antidepressant Prescribing Patterns by Primary Care and Psychiatric Specialties, NAMCS 1995- 2003 Coauthors: Isabel Lagomasino, M.D., Jeanne Miranda, Ph.D. Supported by a grant from the MacArthur Foundation

2. Background Rates of diagnosis and treatment for depression/anxiety low among ethnic minorities (Skaer et al. 2000; Olfson et al. 2002). Improvements in depression care for minorities may be due to national efforts in primary care settings. Kessler et al. 2005 - 2.6 fold increase in MH treatment in the general medical sector, 2.2 fold in psychiatric settings. Pincus et al. 1998; Olfson et al 2002 - much of the increase in antidepressant prescriptions has been among psychiatrists.

3. Research Questions and Hypotheses No previous studies have simultaneously examined the roles of physician specialty and patient race/ethnicity in diagnoses and treatment. Examine trends in diagnoses and treatment for depressive and anxiety, by psychiatrists and primary care physicians, for white, Hispanic, and African-American patients. Hypotheses: 1) depression/anxiety diagnoses and treatment will increase over time and 2) ethnic differences in diagnoses and treatment will persist but be reduced over time, especially in the primary care sector.

4. NAMCS 1995-2003 Office-based outpatient visits for psychiatric specialties (n=10747) and primary care (n=61516). Outcomes: depression/anxiety diagnoses, antidepressant prescriptions Predictors: race/ethnicity (white, black, Hispanic), gender, age, source of payment (private insurance, Medicare, Medicaid/workers’ compensation, self- pay/charity care), time period (1995-1997, 1998-2000, 2001-2003), depression/anxiety reason for visit. Analysis: Multivariate logistic regression, main effects and interactions, standardized predictions.

5. ORs for predictors of depression/anxiety diagnosis OR (95% CI)PsychiatryPrimary care Race/ethnicity (vs white) Black0.62 (0.45, 0.86)**0.55 (0.43, 0.70)*** Hispanic0.81 (0.59, 1.11)0.57 (0.44, 0.75)*** Age1.01 (1.01, 1.02)***1.00 (1.00, 1.01) Female1.36 (1.16, 1.59)***1.19 (1.08, 1.31)*** Expected payment (vs priv. ins.) Medicare0.48 (0.39, 0.60)***0.96 (0.80, 1.16) Medicaid/Worker’s comp.0.45 (0.34, 0.58)***1.20 (0.94, 1.54) Self pay/charity care0.66 (0.51,.84)***1.34 (1.09, 1.64)** Time period (vs 1995-97) 1998-20001.20 (0.87, 1.65)0.99 (0.84, 1.17) 2001-20031.36 (0.98, 1.88)~1.29 (1.10, 1.52)** Depression/anxiety visit4.31 (3.48, 5.34)***24.6 (21.9,27.7)***

6. ORs for predictors of antidepressant prescriptions OR (95% CI)PsychiatryPrimary care Race/ethnicity (vs white) Black0.78 (0.57, 1.07)0.57 (0.47, 0.68)*** Hispanic0.98 (0.71, 1.34)0.57 (0.41, 0.80)** Age1.00 (1.00, 1.01)*1.01 (1.00, 1.01)** Female1.15 (0.95, 1.39)1.30 (1.18, 1.43)*** Expected payment (vs priv. ins.) Medicare0.73 (0.62, 0.87)***1.08 (0.94, 1.23) Medicaid/Worker’s comp.0.73 (0.58, 0.94)*1.19 (0.97, 1.46)~ Self pay/charity care0.47 (0.38, 0.59)***0.85 (0.68, 1.05) Time period (vs 1995-97) 1998-20001.59 (1.18, 2.15)**1.30 (1.09, 1.54)** 2001-20031.49 (1.12, 1.98)**1.59 (1.38, 1.84)*** Depression/anxiety visit1.90 (1.55, 2.32)***9.30 (8.25,10.5)***

9. Primary care visits involving black and Hispanic patients, and psychiatric visits involving black patients, are significantly less likely to result in a diagnosis of depression or anxiety. Psychiatric specialists are equally likely to prescribe antidepressants to black or Hispanic patients (as compared with whites), but primary care office visits involving black or Hispanic patients are less likely to result in a prescription for antidepressants. These differences remain remarkably consistent over time. Conclusions

10. Significance/Implications for Policy Differences in rates of diagnoses and treatment may be a consequence of physician knowledge and ability to identify the disorder, differences in the pathways to care for psychiatric specialties versus primary care, and/or differences in patient preferences. Although interventions aimed at improving depression identification and care in primary care may help to reduce disparities, other factors outside the medical care setting may also need to be targeted.