Advancing health data justice: Integrating compassion and artificial wisdom in AI
What if healthcare AI could be grounded in the wisdom of the communities it hopes to serve? Marisol’s project explores how Indigenous knowledges and their unique perspectives on compassion can reshape how we design AI tools in healthcare. Grounded in the perspectives of Indigenous patients and caregivers, Marisol is working alongside Indigenous mentors and community…
Read MoreExploring the role of immersive virtual reality simulation to enhance compassionate interprofessional collaboration
Effective interprofessional collaboration (IPC) enhances patient care outcomes (safety) and experiences (quality of care), optimizes participation in clinical decision making, and fosters respect of disciplinary contributions. During COVID-19, interprofessional learnings across health and social care disciplines point to the importance of enhancing interprofessional education opportunities to build effective IPC. Despite provincial and national recommendations to…
Read MoreAutomating the evaluation of clinical large language models to support compassionate care
With their incredible conversational and reasoning capabilities, Large Language Models (LLMs) can alter the patient-provider relationship and the very nature of compassionate care. However, inaccurate LLM-generated answers and pseudo-empathy displays can affect patient safety and trust, leading to severe negative outcomes. Pedro’s research project focuses on co-designing LLMs-as-a-Judge (LLM-J), which evaluates answers from other LLMs…
Read MoreEngaging people in compassionate care through patient portals and artificial intelligence
Patient portals provide access to critical health information such as test results, but sometimes it is presented in complex medical language. Artificial Intelligence (AI) holds potential to deliver this information more compassionately and in patient-friendly language. In Shelley’s study, patients and doctors will be interviewed to explore patient portal experiences and participate in focus groups…
Read MoreReimagining health apps for inclusive and equitable access through artificial intelligence
Health apps have crossed over to the mainstream for self-care and clinical care, with one-third of Canadians having used one in 2023. Unfortunately, large groups of underserved consumers and patients who may benefit the most from health apps, are unable to use them due to barriers related to language-spoken, and digital, health and/or language literacy.…
Read MoreFostering compassionate engagement in AI research for major trauma patients: A Delphi study and best practice guidelines
Severely injured patients often cannot give consent to participate in research due to the urgency of their care. While emergency consent waivers exist, there is no national guidance on how to engage, inform, or follow up with patients in a compassionate, patient-centered way—especially in studies involving artificial intelligence (AI). Brodie’s fellowship will use public consultation,…
Read MoreBeing resilient together: Compassionate virtual peer support for aging HIV communities
Kristina’s project looks at how digital tools and artificial intelligence (AI) can help make peer support for older adults living with HIV more compassionate. We understand compassion as taking meaningful actions that help people feel connected and supported. Instead of assuming that using technology automatically makes support more caring, Kristina’s team want to explore how…
Read MoreUsing large language models to support resident-centered decision-making about transfers from long-term care to hospital
When a person living in long-term care (LTC) becomes unwell, transfer to a hospital can provide rapid access to effective treatments. However, if the person has a short time to live transfer to hospital may result in a medicalized death instead of the peaceful, comfort-focused end-of-life experience that most people desire. Daniel’s project will utilize…
Read MoreExamining virtual cancer care in Ontario: Integrating big data, machine learning, and patient perspectives to explore compassionate care delivery and access
Patients receiving treatment for cancer may experience symptoms related to their disease and therapies. Traditionally, doctors see patients in-person to manage these symptoms, but these visits can be costly and time-consuming for patients and caregivers. Virtual care delivery via telephone and videoconferencing increased during the COVID-19 pandemic, but the ideal balance with in-person care remains…
Read MoreCo-designing an educational framework to foster meaningful patient and caregiver engagement in AI research and development to enable compassionate healthcare technology
Meaningful patient engagement in artificial intelligence (AI) research and development is crucial to ensure technologies support compassionate, inclusive healthcare—but it remains rare. Many patients and caregivers describe feeling unprepared and unsupported to contribute effectively. Meghan’s project collaborates with patients, caregivers and AI experts to identify knowledge gaps, review existing resources, and determine what’s missing. The…
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