This course offers a comprehensive exploration of multi-modal healthcare data: its types, sources, and secure storage across platforms. Students will examine key compliance areas with international data standards and global privacy regulations. The curriculum also addresses the integration of social care with healthcare data to support equitable access across diverse populations, including rural communities. Learners will assess the technical and regulatory challenges of linking heterogeneous data and apply this knowledge to the design of AI and MedTech solutions. Through a blend of theory and hands-on exercises, students will be equipped to navigate the complexities of data governance and digital innovation in healthcare.

This course runs in Semester 2 and will in-person.

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1. Group work output (25%, 10 mins with 5 mins Q&A) [ILOs 1-2]

2. Project output (75%, ~3500 words) [ILOs 1-4]

This course enables students to develop proficiency in integrating multi-modal data across MedTech applications, while equipping students to assess robust data security and management within healthcare systems. Students cultivate capabilities to devise innovative, scalable solutions that address healthcare accessibility challenges, while critically evaluating privacy and security considerations essential for sustainable data-driven innovation.

By the end of this course students will be able to:

1. Critically assess the challenges and opportunities of multi-modal healthcare and social care data integration. 

2. Evaluate the suitability of various digital solution housing options in healthcare considering their compliance with cyber security and data governance standards.

3. Critically appraise frameworks that ensure ethical and compliant use of health and social care information.

4. Design integrated MedTech solutions that uses multi-modal data and addresses healthcare access and equity challenges.