Determinants of Readiness for Primary Care-Mental Health Integration (PC-MHI) in the VA Health Care System

Abstract

Depression management can be challenging for primary care (PC) settings. While several evidence-based models exist for depression care, little is known about the relationships between PC practice characteristics, model characteristics, and the practice's choices regarding model adoption. We examined three Veterans Affairs (VA)-endorsed depression care models and tested the relationships between theoretically-anchored measures of organizational readiness and implementation of the models in VA PC clinics. 1) Qualitative assessment of the three VA-endorsed depression care models, 2) Cross-sectional survey of leaders from 225 VA medium-to-large PC practices, both in 2007. We assessed PC readiness factors related to resource adequacy, motivation for change, staff attributes, and organizational climate. As outcomes, we measured implementation of one of the VA-endorsed models: collocation, Translating Initiatives in Depression into Effective Solutions (TIDES), and Behavioral Health Lab (BHL). We performed bivariate and, when possible, multivariate analyses of readiness factors for each model. Collocation is a relatively simple arrangement with a mental health specialist physically located in PC. TIDES and BHL are more complex; they use standardized assessments and care management based on evidence-based collaborative care principles, but with different organizational requirements. By 2007, 107 (47.5%) clinics had implemented collocation, 39 (17.3%) TIDES, and 17 (7.6%) BHL. Having established quality improvement processes (OR 2.30, [1.36, 3.87], p = 0.002) or a depression clinician champion (OR 2.36, [1.14, 4.88], p = 0.02) was associated with collocation. Being located in a VA regional network that endorsed TIDES (OR 8.42, [3.69, 19.26], p < 0.001) was associated with TIDES implementation. The presence of psychologists or psychiatrists on PC staff, greater financial sufficiency, or greater spatial sufficiency was associated with BHL implementation. Both readiness factors and characteristics of depression care models influence model adoption. Greater model simplicity may make collocation attractive within local quality improvement efforts. Dissemination through regional networks may be effective for more complex models such as TIDES.