Midi de la recherche SIO avec Ciara Heavin

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Le Département de systèmes d’information organisationnels vous invite à une présentation de la professeure Ciara Heavin sur sa recherche CommPAL-Driving Resilience and Innovation in Community Palliative Care through AI. Une boîte à lunch sera offerte gratuitement aux personnes présentes.

Inscription obligatoire avant le 14 novembre

Résumé

CommPAL-Driving Resilience and Innovation in Community Palliative Care through AI

There is a growing need to deliver palliative care to patients with acute, advanced care needs in the community, yet often those most in need of care do not receive it. With advances in healthcare, the complexity of patient care needs continues to increase, creating additional tasks for already overstretched healthcare professionals who are committed to delivering gold standard care. Data and systems remain dated and siloed resulting in significant additional work for healthcare professionals required to build “a complete picture” of patient stability to deliver consistent, standard, and safe care. This presents challenges globally in terms of accurate, real-time patient care coordination, caseload management, and the allocation of “the right care to the right patient (and their families/carers) at the right time.” Cognitive burden is a real issue, healthcare providers are under pressure from burnout and as such are struggling to retain experienced staff. Our research project, CommPAL, aims to use the advanced capabilities of AI to address the needs for practical, fair decision-making required in palliative care, setting a precedent for future research and application in the domain. The integration of AI in healthcare has the potential to significantly enhance patient care, particularly in palliative care where accurate and timely care delivery is of paramount importance. The complexity of healthcare data and the need for nuanced decision-making in palliative care present unique challenges. These challenges demand not only a high degree of predictive accuracy from AI but also a level of ethics, data security, transparency, and interpretability that engenders trust among healthcare providers.