PROJECT SUMMARY/ABSTRACT: Health risks, outcomes, and care quality for people with / at risk for diabetes mellitus (DM) are profoundly affected by non-clinical factors called ‘social determinants of health’ (SDH). Diverse public health leaders and initiatives – including the Institute of Medicine, the Office of the National Coordinator for Health Information Technology, the Medicare Access & CHIP Reauthorization Act of 2015, and the Centers for Medicare & Medicaid Services 2016 Quality Strategy – emphasize the importance of documenting patients’ SDH data in electronic health records (EHRs), and using this data to inform care. However, little is known about how to help primary care teams routinely collect and act on SDH data using EHR-based tools. This knowledge gap is particularly problematic for the community health centers (CHCs) serving our nation’s most vulnerable patients, whose DM prevalence and risk (notably, obesity rates) are higher than the general population’s, and whose health is particularly impacted by SDH. The proposed trial builds on an NIDDK-funded pilot study in which we developed a suite of EHR-based SDH data management tools for primary care CHCs. In June 2016, these tools went live in 440 CHCs that are located in 19 states, but share a centrally-managed EHR. Having demonstrated that ‘SDH data tools’ can be built for CHCs, we now propose to assess: whether and how pragmatic implementation strategies that support other types of practice change will also help CHC teams systematically identify and take action on the SDH-related needs of adult patients with / at risk for DM; and, the impact of doing so on DM risk management. We will do this as follows. Step 1: Evaluate current EHR-based SDH data collection in 440 CHCs; use those formative results to hone a set of approaches for helping CHCs routinely collect SDH data and integrate it into care plans. Step 2: Conduct a pragmatic, stepped-wedge, cluster-randomized trial. Thirty CHCs will be randomized to one of five 6-month wedges, with staggered timing for receiving the intervention: a scalable implementation support package including technical assistance, training, and six months of access to an ‘SDH Implementation Team’ that will tailor support to meet each CHC’s needs. Step 3: Conduct a realist evaluation of how the impact on: (i) integration of SDH data collection into workflows; (ii) integration of SDH data into care; and (iii) DM risk management (controlled BP, HbA1c, BMI, lipids, etc.; up- to-date recommended care). Per PAR-15-157, we will test implementation strategies that are pragmatic, replicable, delivered under routine conditions, use existing resources, and target standard care processes. Our multidisciplinary team includes experts in SDH, implementation science, informatics, and primary care transformation. Study deliverables will include scalable strategies; results will inform SDH data collection and action implementation guidelines and materials for use by CHCs an...