Improving Depression Management in Primary Care

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Background: VA’s Primary Care–Mental Health Integration (PC-MHI) is rooted in evidence-based collaborative care models, where care managers, mental health specialists, and primary care providers jointly treat depression in primary care. While PC-MHI enabled specialists to support medication treatment in primary care, timely and sufficient access to psychotherapy is unattainable. Alternative therapy modalities are needed. Significance/Impact: Depression is disabling and affects one in five Veterans. Psychotherapy is preferred by Veterans, but fraught with multilevel barriers (e.g., staff availability, patient travel to clinic, limited clinic hours). Without enhancing existing PC-MHI models to enable better primary care patient access to effective psychotherapies, Veteran engagement in depression treatment is unlikely to improve. Innovation: This CDA aims to close the gap in psychotherapy access for VA primary care patients with depression by adapting PC-MHI collaborative care models to improve uptake of computerized cognitive behavioral therapy (cCBT). cCBT is accessible 24/7 via the internet and has effectively treated depression in more than 30 trials. With modest specialist support, it is non-inferior to face-to-face psychotherapy. PC-MHI can facilitate Veteran uptake of cCBT, using an evidence-based collaborative care model to provide the follow- up care management and mental health specialist back-up that characterizes the most effective cCBT trials. Specific Aims: This CDA will enable me to be a VA implementation scientist who designs, tests, implements, and disseminates effective collaborative care model improvements to treat depression in primary care. My Specific Aims are: (1) to adapt PC-MHI collaborative care to improve uptake of cCBT among VA primary care patients with depression, based on input from multilevel stakeholders; (2) to pilot test the feasibility, acceptability, and potential effects of cCBT-enhanced collaborative care on Veterans’ depression symptoms and related outcomes in one primary care clinic, in preparation for a larger, multi-site hybrid effectiveness- implementation trial; and (3) to establish expert consensus on the translation of pilot findings into a design for cCBT-enhanced collaborative care that is feasible locally, regionally and nationally in VA. Methodology: In Aim 1, I will use qualitative methods and elicit feedback from Veterans, VA providers, and other key stakeholders of national experts and operations leaders (CDA advisory group) to adapt the PC-MHI collaborative care model to improve cCBT uptake. In Aim 2, I will conduct a pilot randomized controlled trial (RCT) to examine feasibility, acceptability, and potential effects on depression, patient activation, and health- related quality of life in VA primary care patients with depression receiving either (1) cCBT-enhanced collaborative care (n=32) or (2) usual care (n=32) in West Los Angeles VA, from baseline to 2-months (post- intervention). This pilot will position me to conduct a multi-site hybrid type I effectiveness-implementation RCT. In Aim 3, I will conduct a virtual expert panel using modified Delphi methods to examine critical barriers and facilitators in the cCBT-enhanced collaborative care model for closing the gap in psychotherapy access for Veterans with depression and other illnesses in routine VA primary care, which will be informed by existing literature and VA-based pilot data. The CDA training and mentorship will facilitate my transition into an independent VA HSR&D investigator by filling explicit training gaps in implementation science (and qualitative methods), clinical trial design (for depression care), and health informatics. Next Steps/Implementation: Adapting PC-MHI’s collaborative care model to incorporate cCBT can improve access to psychotherapy and engage the ~400,000 untreated Veterans with depression who prefer psychotherapy, especially OIF/OEF/OND Veterans seeking care that is convenient. The CDA will provide mentorship and training to begin my career as an implementation scientist who leads collaborative care model improvements using novel technology to address unmet needs and preferences of Veterans in primary care.