AI implementation in Healthcare
Artificial intelligence (AI) is rapidly reshaping healthcare delivery, yet its successful integration into clinical and organisational practice remains limited. Implementation science provides a structured lens to understand how contextual factors, stakeholder dynamics, and workflow adaptation influence the adoption, scale-up, and sustainability of AI applications. Using implementation-focused evaluation frameworks and process models to identify barriers and shape targeted strategies, this research situates AI not only as a technological innovation but as a complex intervention requiring coordinated behavioural, organisational, and system-level change.
Research question: How do healthcare organisations integrate AI sustainably into routine practice, and which factors, identified through implementation science, support or hinder its effective adoption and long-term integration?
Research design: Mixed methods grounded in implementation science theory.
Methods for data collection: Literature research, Semi-structured interviews with key stakeholders, Stakeholder-Analyses, document and policy analysis, and quantitative indicators such as adoption rates, usability metrics, and process outcomes.
Potential supervisor: Rianne Fijten (rianne.fijten@maastro.nl)
Rachelle Swart (rachelle.swart@maastro.nl)
Required skills:
- Qualitative Research
- Conducting semi-structured interviews
- Deductive and inductive thematic analysis
- Coding using qualitative data analysis software
Time period: 2024-2028
Location: Maastricht