An institutional framework to support ethical fair and equitable artificial intelligence augmented care

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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Publication Details

Journal
npj Digital Medicine
Published
2025-02-05
DOI
https://doi.org/10.1038/s41746-025-01490-9
Citations
7
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
4.58

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article

An institutional framework to support ethical fair and equitable artificial intelligence augmented care

Jeffrey A. Bakal, Steven Dykstra, Paul W.M. Fedak, Matthew MacDonald et al.
7 citations
npj Digital Medicine
Artificial Intelligence in Healthcare and Education
4.58
article

An institutional framework to support ethical fair and equitable artificial intelligence augmented care

Jeffrey A. Bakal, Steven Dykstra, Paul W.M. Fedak, Matthew MacDonald, Rhys I. Beaudry, James A. White, Marina L. Gavrilova, B.-H. Lee, Yuanchao Feng, Jacqueline Flewitt, Dina Labib, Melanie King, Stafford Dean
article en
7 citations

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.

npj Digital MedicineVol. 8(1)
Alberta Health Services (CA), University of Calgary (CA), Libin Cardiovascular Institute of Alberta (CA)
Alberta Innovates
Openalex Percentile: Top 6%
Artificial Intelligence in Healthcare and Education
4.58
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