Competency Framework for AI Integration in Healthcare
Why develop a competency framework?
AI is revolutionizing how we work. Even if it is promising, its implementation does not happen automatically. Our analyses show that technical skills are essential, but that they are insufficient. It takes an inherently human skillset to integrate AI for the benefit of patients and the population.
The CHUM’s School of Artificial Intelligence in Healthcare (SAIH) has developed a unique competency framework allowing better integration of AI into healthcare practice.
Healthcare AI Competency Framework © 2020 by The CHUM School of Artificial Intelligence in Healthcare (SAIH) is licensed under CC BY-NC-ND 4.0
General Structure of the Model
The Competency Framework for AI Integration in Healthcare is built around 2 axes, namely :
4 levels of competencies :
LAYERS
Illustrated by different colours
- Enabling mindsets
- Human competencies
- Technical know-how
- Competencies for human-machine collaboration
4 categories of competencies :
QUADRANTS
Divided by 2 perpendicular axes
- Relational competencies
- Reflective competencies
- Self-based competencies
- Action-oriented competencies
The intersection of these two axes makes it possible to locate each of the 16 competencies.
How the SAIH uses the competency framework in its projects
All learning activities offered by the SAIH builds on those competencies from its Competency Framework for AI Integration in Healthcare. Everyone can refer to them to choose learning activities and personalize their training program.
A rigorous design approach
The Competency Framework for AI Integration in Healthcare is the result of 18 months of research, analysis and design. It was developed with the collaboration of experts from the fields of education, AI and healthcare.
To find out more
To know more about the SAIH Competency Framework for AI Integration in Healthcare, please contact us through the following form.
