AI & Patient Engagement

Data to Enable a Learning Health System
In Progress
Artificial Intelligence, Patient Engagement
March 2020 - December 2021 | Funders: SPOR Evidence Alliance


Patients are often identified as key stakeholders in the design of artificial intelligence (AI) healthcare applications. However, the extent and method of patient engagement in AI development in healthcare has not been previously studied, and currently no guidelines exist. We conducted a systematic review to explore if patients have been engaged in AI health research, and if so, how it has happened. Following these insights, we are now conducting an exploratory qualitative study to understand, from multiple perspectives (patients, care providers, AI developers, health policy makers, data managers) the most effective, feasible, and preferred method to engage patients in the development guidelines for patient engagement in AI healthcare application development.


This work highlights the importance of patients engaging in every step of AI development. It will create a multi-disciplinary and committed network of folks in the AI health space.

Team Members

Advisory Members

  • Jane Cooney (Patient partner)
  • Joanna McFadzean (Patient partner)

Contact Information