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Updated: May 29, 2025

Using Visual and Narrative Methods to Achieve Fair Process in Clinical Care
Published on: February 16, 2011
An institutional framework to support ethical fair and equitable artificial intelligence augmented care
Steven Dykstra1,2, Matthew MacDonald1,2, Rhys Beaudry1,2
1Department of Cardiac Sciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.
Abstract:
Coordinated access to multi-domain health data can facilitate the development and implementation of artificial intelligence-augmented clinical decision support (AI-CDS). However, scalable institutional frameworks supporting these activities are lacking. We present the PULSE framework, aimed to establish an integrative and ethically governed ecosystem for the patient-guided, patient-contextualized use of multi-domain health data for AI-augmented care. We describe deliverables related to stakeholder engagement and infrastructure development to support routine engagement of patients for consent-guided data abstraction, pre-processing, and cloud migration to support AI-CDS model development and surveillance. Central focus is placed on the routine collection of social determinants of health and patient self-reported health status to contextualize and evaluate models for fair and equitable use. Inaugural feasibility is reported for over 30,000 consecutively engaged patients. The described framework, conceptually developed to support a multi-site cardiovascular institute, is translatable to other disease domains, offering a validated architecture for use by large-scale tertiary care institutions.
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