Healthcare
Information Systems are the backbone of modern health(care) ecosystems. They are critical for clinical research, for clinical operations, and for the optimization of the multi-stakeholder care chain. The IS group investigates and develops methods, techniques and tools for data-driven workflow and decision support systems that streamline (inter-organizational) patient journeys. Furthermore, the group investigates how more robust AI can support more Personalized, Predictive, Preventive and Participatory (P4) medicine. In support of aforementioned research, the group develops healthcare data platforms that are more patient-centric and that enable the responsible sharing of data between care providers and with research institutes, while supporting privacy by design instead of by committee.
Specific topics that we focus include the following:
- Clinical guideline refinement
- Design of business models and health ecosystems
- Explainable/Transparent Clinical Decision Support (CDS)
- Prediction and Personalization of Care Pathways
- Process discovery and modeling
- (Interactive) Process compliance analysis
- Structured improvement of care pathways across organizations
- Business process redesign
- Digital Twins and Personalized Avatars
- Participatory and Responsible Design to boost Adoption
- Merging model- and data-driven health AI
- Personal health data platforms
- Privacy-preserving health data sharing for research