Healthcare is complex. Systems such as electronic health records, diagnostic tools, and administrative platforms must all work together in clinical practices that consist of various groups of healthcare professionals and workflows. At the same time, healthcare professionals such as doctors and nurses, hospital managers, authorities, and patients may have different expectations about what AI should do. Regulations (such as GDPR and the EU AI Act) also shape what is possible.
This proposed theme for master projects concerns the adoption and scaling of AI in healthcare, the challenges that arise during adoption and scaling, and what AI implementations means for everyday work and service delivery. In this context, “scaling” refers to moving from small-scale pilots or implementations to sustained, everyday use across multiple sites (e.g., across clinical practices, hospitals and/or health regions). A simple way to think about scaling is in terms of size (more users and locations) and scope (more tasks and contexts).
Potential topics to explore include, but are not limited to:
- How healthcare organisations prepare for AI implementations, adoption and/or scaling
- How AI changes the work of healthcare professionals
- How healthcare services can realise benefits from AI implementations
- How experiences and lessons learned from AI implementation in one clinical practice or hospital can benefit other healthcare organisations
- The challenges of scaling AI in the Norwegian healthcare services
- Case studies of specific AI projects
Preferred methods
The student(s) will identify and establish access to an empirical research setting for a qualitative study.
Who is this project for?
The project is well suited for students in the Master’s Programme in Digitalization of the Healthcare Sector (DIGHEL). It is relevant to both students with a healthcare background and those with a background in informatics or information systems. As some of the proposed topics requires a good understanding of both the empirical domain and the technology, it may also be particularly suitable for DIGHEL students with combined backgrounds in healthcare and informatics who are working in pairs.