The goal of this proposal is to test whether an electronic shared decision making (eSDM) tool can increase the uptake of collaborative care (CC) for depression in primary care. Depression is projected to be the second largest contributor to chronic disease burden in the world by 2030, and contributes to disparities in quality of life and mortality. CC integrates primary and behavioral health through depression care managers who provide antidepressant adherence counseling and/or psychotherapy. CC doubles the rate of depression remission in comparison to primary care provider-led depression treatment alone, particularly in racial and ethnic minorities, and results in a 24% reduction in mortality and nearly $1300 in net annual savings per patient. Despite this model's potential to improve access to mental health, implementation efforts reveal low provider CC referral rates and low patient engagement rates of 9-50%, particularly in minority patients. To identify factors contributing to poor patient engagement in CC, we conducted focus groups in 8 healthcare systems implementing CC, representing 33 clinics and 1 million predominantly Medicaid, minority patients. We learned that key physician-level barriers included limited time/resources to discuss treatment options and conduct “warm handoffs” to care managers; patient-level barriers included poor knowledge of treatment options, miscommunication, stigma, language barriers, and low motivation. We applied a theory- informed process of engaging stakeholders to select an acceptable, feasible intervention and determined that SDM would target the greatest number of barriers to CC engagement. SDM involves a collaborative process whereby providers and patients make health decision together, and is a proven approach for improving depression treatment initiation and guideline concordant care, particularly in minorities, but widespread use has been limited by time and resources. Accordingly, we developed and alpha tested an iPad delivered, video-assisted, interactive eSDM tool that would reduce barriers to SDM uptake and target CC engagement. We hypothesize that a state-of-the-art eSDM tool that automates the SDM process, activates providers, staff, and patients and interfaces with the electronic health record will improve efficient CC enrollment (primary outcome). We propose to refine and adapt the eSDM prototype (Aim 1) and conduct a stepped wedge trial across 4 primary care medical homes to assess the effectiveness of implementing our eSDM tool on provider behavior (Aim 2), patient enrollment in CC (Aim 3), patient adherence to depression treatment (therapy or antidepressants) and depressive symptoms (Exploratory Aims) amongst 1440 primary care patients in our healthcare system. Our study has the potential to produce a theory-informed, scalable eSDM tool that improves the reach of CC programs and potentially other team-based approaches.