Public Health Commons^™

Data-Driven Decision Support Tool Co-Development With A Primary Health Care Practice Based Learning Network, Jacqueline K. Kueper, Jennifer Rayner, Sara Bhatti, Kelly Angevaare, Sandra Fitzpatrick, Paulino Lucamba, Eric Sutherland, Daniel J. Lizotte

Epidemiology and Biostatistics Publications

Background: The Alliance for Healthier Communities is a learning health system that supports Community Health Centres (CHCs) across Ontario, Canada to provide team-based primary health care to people who otherwise experience barriers to care. This case study describes the ongoing process and lessons learned from the first Alliance for Healthier Communities’ Practice Based Learning Network (PBLN) data-driven decision support tool co-development project.

Methods: We employ an iterative approach to problem identification and methods development for the decision support tool, moving between discussion sessions and case studies with CHC electronic health record (EHR) data. We summarize our work to date in …

Inaugural Artificial Intelligence For Public Health Practice (Ai4php) Retreat: Ontario, Canada, Jacqueline K. Kueper, Laura C. Rosella, Richard G. Booth, Brent D. Davis, Sarah Nayani, Maxwell J. Smith, Dan Lizotte

Computer Science Publications

The Artificial Intelligence (AI) for Public Health Practice Retreat was a hybrid event held in October 2022 in London, Ontario to achieve three main goals: 1) Identify both the goals of public health practitioners and the tasks that they undertake as part of their practice to achieve those goals that could be supported by AI, 2) Learn from existing examples and the experience of others about facilitators and barriers to AI for public health, and 3) Support new and strengthen existing connections between public health practitioners and AI researchers. The retreat included a keynote presentation, group brainstorming exercises, breakout group …

Developing Artificial Intelligence And Machine Learning To Support Primary Care Research And Practice, Jacqueline K. Kueper

Electronic Thesis and Dissertation Repository

This thesis was motivated by the potential to use "everyday data", especially that collected in electronic health records (EHRs) as part of healthcare delivery, to improve primary care for clients facing complex clinical and/or social situations. Artificial intelligence (AI) techniques can identify patterns or make predictions with these data, producing information to learn about and inform care delivery. Our first objective was to understand and critique the body of literature on AI and primary care. This was achieved through a scoping review wherein we found the field was at an early stage of maturity, primarily focused on clinical decision support …