Research Groups
Patient-Generated Data
Incorporating the patient perspective into healthcare and research is essential for an efficient, sustainable health system. To optimally collect and analyse data from patients and other stakeholders, our group applies a broad range of quantitative and qualitative methods. We conduct preference research (e.g., discrete choice experiments and other stated-preference approaches) to understand what outcomes, trade-offs, and care attributes matter most to people. To explore needs, preferences, and lived experiences in everyday life, we use interviews, focus groups, surveys, and observations across diverse settings and patient populations.
We also systematically analyse data from qualitative studies, combining established qualitative approaches (e.g., thematic analysis and framework methods) with scalable techniques for larger datasets. When appropriate, we use text-analytic and machine-learning methods (including natural language processing) to process and interpret large volumes of unstructured data, enabling robust insight generation while preserving the richness of patient narratives.
Health Outcomes Observatory und Value-Based Care
We develop and implement patient-centred outcome measurement to advance Value-Based Care. Within the Innovative Health Initiative (IHI) project Health Outcomes Observatory (H2O), we convene public and private stakeholders to establish Europe-wide standards for the collection, governance, and use of health outcomes data. A central focus is on patients’ experiences and preferences, as well as meaningful patient control over personal health data.
Our work spans the development and implementation of core outcome sets, ensuring that outcomes are relevant, comparable, and feasible across settings and countries. We also advance participatory research, co-designing outcome frameworks, data collection approaches, and reporting formats with patients, clinicians, and other end users to strengthen relevance, trust, and uptake.
Methodologically, we contribute to outcomes research by developing and applying innovative approaches, including machine learning for prediction and risk stratification using patient-reported data, and quantitative methods to structure and analyse patient interviews (e.g., NLP-based coding, topic modelling, and mixed-methods integration). By generating robust, comparable real-world outcomes data, we support evidence-based decision-making in clinical practice, health policy, and resource allocation, shifting healthcare towards patient-reported outcomes, transparency, and sustainable resource use.
Stamm T.A., Partheymüller J., Mosor E., Ritschl V., Kritzinger S., Alunno A., Eberl J.-M. (2023) Determinants of COVID-19 Vaccine Fatigue. Nature Medicine 29(5), 1164–1171.
Arthritis and Rehabilitation
We aim to improve care for people with inflammatory and degenerative joint diseases, and other conditions requiring rehabilitation by generating evidence that directly informs clinical practice. To this end, we conduct clinical and outcomes studies, integrate sensor-based assessments and e-health applications, and analyse real-world data to evaluate effectiveness and support quality improvement. In addition, we carry out basic and translational arthritis research in close collaboration with rheumatology, orthopaedics, and physiology centres, linking mechanistic insights with patient-relevant outcomes.
A specific focus of our work is osteoarthritis. We host and coordinate a dedicated osteoarthritis registry study, enabling longitudinal monitoring of symptoms, function, and treatment pathways, and providing a strong foundation for outcome research and the development of targeted rehabilitation strategies. In this context, we also host the Ludwig Boltzmann Institute for Arthritis and Rehabilitation.