This work will test a set of strategies for helping community health centers(CHCs) routinely identify and take action on the SDH-related needs of patients with / at risk for DM. The work will specifically study: (a) EHR-based SDH data collection / action in CHCs, and (b) the impact of a set of scalable implementation strategies known to support clinical practice changes (the 'SDH Action Plan'), on CHCs' adoption of SDH data collection and action. Focusing on DM risk management and obesity prevention outcomes in adult patients, the investigators will conduct a mixed methods formative evaluation of SDH data collection uptake among CHCs that had SDH data tools activated in their EHR in June 2016. (Quantitative data will come from all 440 CHCs' shared EHR, qualitative data from 10-12 CHCs purposively recruited from this pool). Identify patterns of SDH data collection in these diverse CHCs, and clinic-level factors associated with variation in SDH data collection rates. Use results to fine-tune the SDH Action Plan intervention's strategies for helping CHCs systematically: (i) collect SDH data in standard workflows, and (ii) integrate SDH data into care plans (e.g., making referrals to social services; adapting treatment plans) for adults with / at risk for DM.~Through a pragmatic, stepped-wedge, cluster-randomized trial in 30 CHCs, the CHCs will be randomized to one of five 6-month wedges, with staggered timing. CHCs in each wedge will receive intensive implementation support (the SDH Action Plan). This scalable intervention includes both comprehensive technical assistance and training materials designed to help CHCs plan for and implement SDH data collection / action, and six months of remote access to an 'SDH Implementation Team' that will tailor implementation support to each CHC's needs, with an emphasis on the Building Blocks of Primary Care.45 To test this approach, the investigators will conduct a realist evaluation of whether and how the SDH Action Plan intervention improves: (i) SDH data collection in CHC workflows; (ii) integration of SDH data into DM risk management care; and (iii) clinical measures associated with effective DM risk management (controlled blood pressure, HbA1c, BMI, lipids, etc.; up-to-date preventive care). H3a: Intervention CHCs will have significantly greater increases in (i) SDH data collection, and (ii) actions taken to address SDH needs, compared to control CHCs. H3b: Patients at intervention CHCs for whom SDH data are collected will have significant improvements in DM / obesity risk management / receipt of related preventive care, compared to those at control CHCs.
This work will test a set of strategies for helping community health centers (CHCs) routinely identify and take action on the SDH-related needs of patients with / at risk for DM using a stakeholder-driven process to develop EHR-based SDH data collection / summary tools for CHCs.