Dr. Melanie Powis is a Toxicologist and Health Services Researcher, and the Scientific Director for the Cancer Quality Lab (CQuaL) at Princess Margaret Cancer Centre- a pan-disciplinary research group aimed at improving the quality of cancer care across the continuum by leveraging quality improvement and implementation science methods. Dr. Powis’ research interests include implementing and evaluating interventions to address disparities in cancer care with a focus on systemic therapy-related toxicities, exploring new models for cancer care delivery that improve patient and provider experiences while addressing clinical capacity issues, and examining how to embed new technologies in clinical practice to improve care delivery.
Some of her current areas of research include:
- Improving systemic therapy-related toxicity management: There remains racial disparities in breast cancer treatment, whereby Black women are less likely to receive appropriate genetic testing, timely systemic therapy, treatment with newer targeted drugs or access to interventional trials, and there is growing evidence of higher incidence of serious treatment-related toxicity, such as anthracyclin-induced cardiotoxicity. To address these disparities, participatory co-design methods will be utilized to design, implement and pragmatically evaluate a Black Patient Navigator role for women initiating systemic therapy for breast cancer.
- Developing a practical implementation framework for embedding AI-driven models into routine care: There is a growing number of AI-driven models aimed at improving cancer care, though enabling factors for effective translation to clinical practice remains to be explored. As such, work is being undertaken to develop a consolidated framework for AI deployment and implementation in healthcare settings, informed by behavioural change models, and social and behaviour change theory.
- Characterizing Cancer Care Human Resource Needs and Developing New Models of Care: Most work undertaken to date to quantify oncology workloads and project future staffing needs to date has focused on quantifying the number of new patient consultations, or on resources associated with delivery of a single modality of treatment, most often radiotherapy. Most of these models are older and do not capture the complexities of delivering modern treatment regimens, and increased patient volumes associated with improved survival leading to more lines of treatment and longer follow-ups. As such, administrative billing data at the Institute for Clinical Evaluative Sciences (ICES) will be utilized to construct data-driven models to predict future cancer care resource needs across clinical disciplines, and understand drivers of high resource utilization. These findings will inform the development and evaluation of new models of care aimed at improving clinical workflows and system capacity.