Dr. Melanie Powis is the Scientific Director for the Cancer Quality Lab at Princess Margaret Cancer Centre, an Assistant Professor in the Institute for Health Policy, Management and Evaluation at the University of Toronto, and Adjunct Scientist at the Institute for Clinical Evaluative Sciences. As a Health Services Researcher and Implementation Scientist, her work focuses on leveraging quality improvement (QI) and implementation research methodologies to implement and pragmatically evaluate interventions to improve the quality of cancer care delivered to underserved patients. To maximize uptake and policy impacts of her work, she has ongoing collaborations with community partner organizations, and knowledge users from across Canada and internationally. She holds leadership roles in International Collaborative for Digital Health Translation (Canadian Hub Lead for Digital Health Translation) and the Consortium for Cancer Implementation Science of the National Cancer Institute (Vice-Chair, Implementation of Technology Action Group).
Some of her current areas of research include:
- Embedding digital health technologies into routine cancer care: We are working with patients, health equity experts, clinicians and policy makers/ knowledge users from across the country to develop a comprehensive virtual cancer care evaluation framework, which will inform policy and funding decisions. We are helping to translate innovations, such as remote monitoring and AI-driven clinical risk prediction models, to routine care while furthering the science/ theory of how to effectively embed these technologies in practice. Additionally, we are working to understand and optimize the role of patients and community partners in digital health technology implementation and evaluation.
- Improving the quality of cancer care for under-served patients: we are leveraging AI to evaluate the unmet supportive care needs of patients, to identify high-needs sub-populations, and high-needs supports. In addition, we are utilizing community-based participatory research approaches to co-create, implement and evaluate interventions to address disparities in cancer care for underserved patient populations, including those who self-identify Black, and those patients who use drugs.
- Predicting and addressing cancer care workforce challenges: we are utilizing population-level data to develop a cancer care workforce requirements simulation model and evaluating the impact of different potential solutions (ie: task shifting, utilization of AI, new models of care) on system capacity. We are also implementing and pragmatically evaluating a CIHR-funded pan-Canadian cancer care workforce optimization education and coaching program.