Recognizing warnings in adults at risk of life-threatening diagnoses using AI

Clinical Scientist, Unity Health Toronto Delays, and often omissions, of life-threatening diagnoses are common, especially with hospitalized patients. To render the correct diagnosis, healthcare providers need sufficient uninterrupted time to review a patient’s medical record and speak with the patient directly, but the chaotic inpatient environment presents many challenges: interruptions, task-switching, limited time, lack of…

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Evaluating a person-centred digital intervention to promote physical activity behaviour change following dysvascular lower limb amputation

Scientist, West Park Healthcare Centre Physical activity is the “medicine” of the century with evidence demonstrating reduced risk of chronic disease and mortality and improved quality of life. However, people with lower limb amputations often have reduced balance and walking ability resulting in sedentary behaviour. Crystal’s project will evaluate a digital intervention consisting of virtual…

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Using patient stories to explore how big data can be deployed to support compassionate care

Physician/Clinician Scientist, Trillium Health Partners Understanding the “whole person”, including each person’s unique life circumstances (including the social determinants of health), may help healthcare workers provide compassionate care. Healthcare workers now use technology to record this information or predict how these circumstances influence people’s health. But we do not yet know how best to design…

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Self-compassion training for specialist inpatient rehabilitation providers

Physiatrist, Sunnybrook Research Institute This project will assess an online self-compassion course for rehabilitation providers. Rehabilitation is founded in a bio-psycho-social model and depends on effective relational care between healthcare providers and those receiving rehabilitative treatments. Compassionate care in rehabilitation is linked to better health outcomes for patients but caring for people with disabling long-term…

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Coping with grief in the digital era: exploring the role of compassion

Post-Doctoral Fellow, Centre for Addiction and Mental Health Given the ongoing COVID-19 pandemic and opioid crisis, individuals across Canada have been impacted by the loss of someone they know. This loss effects many domains of one’s life, including emotional and behavioral. Grief following bereavement is an extremely painful, but unfortunately common experience. Strategies to cope…

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Identifying patient‐validated compassion and equity concepts in community care clinical notes through natural language processing

Assistant Professor, The University of British Columbia – Okanagan In Charlene’s project, she aims to develop and test compassion and equity-grounded natural language processing (NLP) application to leverage otherwise unused community nursing clinical notes. She will develop a dictionary that merges understandings of equity and compassionate care from the perspectives of community nurses and patients…

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Re-imagining digital health compassion through the lens of Canadian newcomers

Scientist at the Institute for Health System Solutions and Virtual Care at Women’s College Hospital Virtual care can be beneficial, but it can also result in Canadian newcomers (landed immigrants and refugees) being excluded within the health care system. This can add to the stress they experience from adjusting to a new country and system.…

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Using digital models and visualization to help patients better understand prognosis and uncertainty

Radiation Oncologist, London Health Sciences Centre Understanding prognosis is important for treatment decisions, life planning, and psychological well-being in patients with metastatic disease. Physicians are increasingly using statistical and AI-based models for prognosis estimates, but these are inaccessible to patients. No models are designed specifically for patient use. How are patient interactions with prognosis models…

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Using machine learning to predict cognitive decline among long-term care residents in Ontario

Post-Doctoral Fellow, Ottawa Hospital Research Institute Being able to anticipate cognitive decline can help long-term care residents and their family caregivers plan for care options and address modifiable factors in a compassionate and timely manner. Wenshan’s project will describe cognitive trajectories of long-term care residents in Ontario, highlighting the impact of social isolation before and during…

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Exploring how older adults and carers perceive and experience a real-time location system in a long-term care home

Assistant Professor of Gerontology, Department of Recreation and Leisure Studies and Master of Applied Gerontology, Brock University Real-time location systems are technologies that continuously track the location of individuals and assets. These are being implemented in long-term care homes with an interest in improving the quality of care through automation of care tasks and prediction…

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