Digital data generated in the course of clinical care are increasingly being leveraged for a wide range of secondary purposes. Researchers need to develop governance policies that can assure the public that their information is being used responsibly. Our aim was to develop a generalisable model for governance of research emanating from health data repositories that will invoke the trust of the patients and the healthcare professionals whose data are being accessed for health research. We developed our governance principles and processes through literature review and iterative consultation with key actors in the research network including: a data governance working group, the lead investigators and patient advisors. We then recruited persons to participate in the governing and advisory bodies. Our governance process is informed by eight principles: (1) transparency; (2) accountability; (3) follow rule of law; (4) integrity; (5) participation and inclusiveness; (6) impartiality and independence; (7) effectiveness, efficiency and responsiveness and (8) reflexivity and continuous quality improvement. We describe the rationale for these principles, as well as their connections to the subsequent policies and procedures we developed. We then describe the function of the Research Governing Committee, the majority of whom are either persons living with diabetes or physicians whose data are being used, and the patient and data provider advisory groups with whom they consult and communicate. In conclusion, we have developed a values-based information governance framework and process for Diabetes Action Canada that adds value over-and-above existing scientific and ethics review processes by adding a strong patient perspective and contextual integrity. This model is adaptable to other secure data repositories.

Objectives: The Sustainable Development Goals (SDGs) re-orient action towards improving the social and ecological determinants of health and equity. SDG 17 calls for enhanced policy and institutional coherence and strong multi-stakeholder partnerships. Intersectoral action (IA) has a promising history in public health, including health promotion and global health. Some experts see IA as crucial to the SDGs. Yet less is known about how IA is conceptualized and what promising models exist with relevance to the SDGs. We sought to investigate how IA is understood conceptually and empirically.Methods: We conducted a narrative review of global public health and political science literatures and grey literature on the SDGs to identify theoretical models, case studies and reviews of IA research.Results: Multiple competing conceptualizations of IA exist. Research has focused on case studies in high-income countries. More conceptual clarity, analyses of applications in LMICs, and explorations of political and institutional factors affecting IA are needed, as is attention to power dynamics between sectors.Conclusion: IA is required to collaborate on the SDGs and address equity. New models for successful implementation merit exploration.

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