Projet de création conjointe d’un outil d’aide à la décision reposant sur des données | Phase 1 : Détermination du problème

La croissance rapide du volume de données générées et recueillies en matière de soins de santé, conjuguée aux avancées dans les méthodes et technologies d’analyse de données, transforme le domaine de la santé. L’intelligence artificielle (IA) et les outils connexes d’aide à la décision ont un potentiel exceptionnel pour exploiter les données en vue d’améliorer la qualité et d’adapter les programmes et services pour répondre aux besoins des communautés.

Data-Driven Decision Support Tool Co-Development Project | Phase 1: Problem Scoping

A rapid increase in the amount of health care data being generated and collected, coupled with advancements in data-analysis methods and technologies, is transforming healthcare. Artificial intelligence (AI) and related decision-support tools show remarkable potential for using data to empower quality improvement and tailoring of programs and services to meet client and community needs.

Virtual care in Ontario community health centres: a cross-sectional study to understand changes in care delivery



There has been a large-scale adoption of virtual delivery of primary care as a result of the COVID-19 pandemic.


In this descriptive study, an equity lens is used to explore the impact of transitioning to greater use of virtual care in community health centres (CHCs) across Ontario, Canada.

Design & setting

A cross-sectional survey was administered and electronic medical record (EMR) data were extracted from 36 CHCs.

Using the quadruple aim to understand the impact of virtual delivery of care within Ontario community health centres: a qualitative study


The onset of the COVID-19 pandemic and introduction of various restrictions resulted in drastic changes to 'traditional' primary healthcare service delivery modalities.


To understand the impact of virtual care on healthcare system performance within the context of Ontario community health centres (CHCs).

Design & setting

Thematic analysis of qualitative interviews with 36 providers and 31 patients.

Using Learning Collaborative Teams to Address the COVID-19 Cancer-Screening Backlog

This research poster was presented at the North American Primary Care Research Group (NAPCRG) Practice-Based Research Network Conference in June 2022. It presents the results of the Alliance's first learning collaborative, which supported member centres in equitably clearing their cancer screening backlogs built up through the COVID-19 pandemic.

Access and Analysis of Provincial Administrative Data for Cohort Disclosure to Guide Community-Based Diabetic Retinopathy Screening


It is recommended that individuals living with diabetes have their eyes examined for signs of retinopathy annually. Even with access to eye care resources across Canada, including tele-ophthalmology, many individuals with diabetes remain unscreened with screening rates lowest in vulnerable populations. A population-based approach to identify, engage, and provide screening is needed. 

Increasing Diabetic Retinopathy Screening Rates Utilizing Provincial Healthcare Administrative Data


Diabetic retinopathy (DR) is the leading cause of blindness in working age Canadians. Despite all eye care resources, including tele-ophthalmology, DR screening rates remain low; 35% of individuals with diabetes are unscreened for DR. New strategies are required to identify, engage and provide ongoing monitoring to those requiring DR screening.