My research program, Program in Health System and Technology Evaluation, focuses on the innovative technologies related to chronic disease management (i.e., devices, services, complex interventions and programs). We work closely with all relevant stakeholders including patient partners and their family members, innovators, researchers within and outside UHN, policy decision-makers, and the public. This program is affiliated with the Ted Rogers Centre for Heart Research, Peter Munk Cardiac Centre and Toronto General Hospital Research Institute.

Using a variety of evaluative approaches to assess our health care system, we provide rapid real-time feedback to all involved stakeholders that contribute to the establishment of a learning health care system. We generate rigorous evidence and provide decision support to implement the innovative, system-disruptive technologies that empower patients, deliver best outcomes, and create high-performing, cost-effective health care systems.

Study Status: active

Institute: Toronto General Hospital Research Institute

Study Purpose: People from underserved communities in Canada, including Indigenous Peoples, those living in rural or remote areas, and people with lower incomes, are more likely to experience serious health issues from diabetes. New artificial intelligence (AI) tools, like eye screening cameras and smart foot sensors, are being developed to detect these problems early. This study aims to understand how well these AI tools work for these communities, and how they can be designed and used in ways that are fair, trustworthy, and useful.

Background: Using AI tools may improve the early detection of diabetes health complications. However, concerns exist about whether these tools are equally useful for everyone. Many technologies are not designed with underserved communities in mind, which may limit their usefulness or the ability of patients to access them. It is important to understand how and why these tools succeed or fail in the real world, especially for those most affected by diabetes.

Study Methods: We are conducting a “realist review,” which looks at existing research to understand what works, for whom, and under what circumstances. A key part of this study is partnering with people with lived experience to help shape the research questions, interpret the results, and ensure that the results reflect community needs and priorities. This study will help identify how AI tools can be improved and used more fairly in diabetes care. The findings will support future research, guide the development of better technologies, and shape policies aimed at making healthcare more equitable. By working with community members, we will ensure that the results are practical, relevant, and grounded in real-life experiences.

Health Conditions: Diabetes

For a list of Dr. Rac's publications, please visit PubMed, Scopus or Publons.

• Associate Program Director and Director, Clinical Research Division, Toronto Health Economics and Technology Assessment Collaborative
• Assistant Professor, Institute of Health Policy, Management and Evaluation, University of Toronto