Bridging the Gap: Designing User-Centred AI Implementations for Healthcare
Artificial Intelligence (AI) holds immense potential for optimizing treatment decisions in clinical practice. AI's ability to predict patient outcomes and tailor interventions based on unique patient or disease characteristics can facilitate significant progress toward personalized healthcare. However, the adoption and use of AI in clinical settings remains low due to several challenges: lack of trust in and understanding of AI models, misalignment of AI model outputs with clinical workflow and decision points, and uncertainty about the accuracy and impact of AI on outcomes that clinicians and patients value.
Research question: How can we apply human-centred design principles to improve the adoption and impact of AI in clinical settings?
Research design: Mixed methods qualitative and quantitative research
Methods for data collection: Literature review, interviews (structured, semi-structured, think aloud), qualitative coding, quantitative data analysis, user interface and interaction design
Potential supervisor: Yemu Katanda, PhD Student at Maastricht University (yemu.katanda@maastrichtuniversity.nl)
Required skills:
- English language written and verbal proficiency
- Qualitative and/or quantitative research skills
- User research or human-centred design experience or strong interest
- Analytical and critical thinking
- Basic understanding of healthcare contexts and/or AI applications (or willingness to learn)
Time period: 3-6 months
Location: Maastricht or Remote