Diagnoses, Intervention Strategies, and Rates of Functional Improvement in Integrated Behavioral Health Care Patients

Objective: Compared with more traditional mental health care, integrated behavioral health care (IBHC) offers greater access to services and earlier identification and intervention of behavioral and mental health difficulties. The current study examined demographic, diagnostic, and intervention factors that predict positive changes for IBHC patients. Method: Participants were 1,150 consecutive patients (mean age = 30.10 years, 66.6% female, 60.1% Hispanic, 47.9% uninsured) seen for IBHC services at 2 primary care clinics over a 34-month period. Patients presented with depressive (23.2%), anxiety (18.6%), adjustment (11.3%), and childhood externalizing (7.6%) disorders, with 25.7% of patients receiving no diagnosis. Results: The most commonly delivered interventions included behavioral activation (26.1%), behavioral medicine-specific consultation (14.6%), relaxation training (10.3%), and parent-management training (8.5%). There was high concordance between diagnoses and evidence-based intervention selection. We used latent growth curve modeling to explore predictors of baseline global assessment of functioning (GAF) and improvements in GAF across sessions, utilizing data from a subset of 117 patients who attended at least 3 behavioral health visits. Hispanic ethnicity and being insured predicted higher baseline GAF, while patients with an anxiety disorder had lower baseline GAF than patients with other diagnoses. Controlling for primary diagnosis, patients receiving behavioral activation or exposure therapy improved at faster rates than patients receiving other interventions. Demographic variables did not relate to rates of improvement. Conclusion: Results suggest even brief IBHC interventions can be focused, targeting specific patient concerns with evidence-based treatment components.