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Participatory governance over research in an academic research network: the case of Diabetes Action Canada
  1. Donald J Willison1,
  2. Joslyn Trowbridge2,
  3. Michelle Greiver3,4,
  4. Karim Keshavjee5,
  5. Doug Mumford6,
  6. Frank Sullivan4,7
  1. 1 Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
  2. 2 Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
  3. 3 Family and Community Medicine, University of Toronto, Toronto, Ontario, Canada
  4. 4 Family and Community Medicine, North York General Hospital, Toronto, Ontario, Canada
  5. 5 Infoclin, Toronto, Canada
  6. 6 Patent Representative, Toronto, Ontario, Canada
  7. 7 School of Medicine, University of St. Andrews, St Andrews, UK
  1. Correspondence to Dr Donald J Willison; don.willison{at}


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.

  • information governance
  • research governance
  • participatory governance

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  • Contributors DJW and JT conducted the literature review and developed the initial and successive conceptual and operational governance models. MG, KK and FS reviewed and suggested revisions to the models. DJW developed the training workshop syllabus and content. MG and DM reviewed and suggested revisions to the workshop material. DJW wrote the initial draft of the manuscript and made subsequent revisions, in response to feedback from JT, MG, KK, DM and FS.

  • Funding This work was supported by Diabetes Action Canada, which is funded, in part, through a Canadian Institutes of Health Research chronic disease network grant under the Strategy for Patient-Oriented Research (Funding Reference number: SCA 145101).

  • Competing interests The Institute of Health Policy, Management and Evaluation received funds from Diabetes Action Canada SPOR Network towards a partial secondment of DJW time for the development of the governance process for the diabetes data repository. The Department of Family and Community Medicine, University of Toronto, received funds from Diabetes Action Canada SPOR Network towards a partial secondment of MG time for the development of the Diabetes data repository. KK received personal fees from InfoClin during the conduct of the study towards designing the architecture of the Diabetes data repository. In addition, KK has a patent ‘Prediction of Diabetes Mellitus Type 2 Using Biomarkers in Electronic Health Records and Differential Calculus’, pending.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Patient consent for publication Not required.

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