HAD4000H-F

Prerequisite

Objectives

At the end of this course students will be able to:
1. Explain the concepts of design and innovation.
2. Describe the role of design in the context of health innovation.
3. Articulate what design-led innovation is intended to achieve.
4. Build a design-led innovation lab.
5. Evaluate machine learning (ML)-based solutions for clinical applications.
6. Analyse the critical issues to be considered in the clinical deployment of ML solutions.

Description

Healthcare systems are making concerted efforts to enhance quality, manage population health, and reduce costs using quality improvement tools to enhance their services. However, the scale and complexity of challenges necessitate innovative approaches to change that enable organizations to develop, adopt, and scale successful innovations rapidly in the face of an unpredictable future.
In this course we will explore future oriented human-centered design capabilities that will equip students with design led approaches to healthcare improvement. We will start with an in-depth exploration of the expectations, best practices, and impact of the innovation lab within the context of Ontario’s health system and local challenges. Students will gain insights from the experiences of global leaders in quality, innovation, and AI. Students will apply these insights in class, participate in an innovation lab case and explore the foundational elements of Machine Learning (ML) in healthcare including how to critically appraise its clinical applications.

Instructors

Evaluation Breakdown

Competencies