VALUE How People Value Health: An Introduction to Patient Preferences

The course is delivered entirely online over a two-month period and is organised into five learning activities, for a total of 5 ECTS credits. The programme combines online lectures, methodological insights, case studies, and interactive sessions with academic and professional experts. Content covers the theoretical foundations of Patient Preference Studies (PPS), quantitative methodologies for preference elicitation, and their use in regulatory and Health Technology Assessment (HTA) contexts. Particular attention is devoted to Discrete Choice Experiments (DCE), evidence synthesis through systematic reviews and meta-analyses, and applications of artificial intelligence in patient preference research. The programme includes case studies and applications using the Repertor.IO platform, as well as opportunities for discussion with patient advisors. The final assessment consists of a written examination.

The course is intended for graduates and professionals interested in health research, epidemiology, biostatistics, Health Technology Assessment (HTA), regulatory science, and evidence-based decision-making. It is suitable for candidates with backgrounds in biomedical sciences, healthcare, statistics, computer science, economics, mathematics, or engineering, as well as professionals working in the healthcare, pharmaceutical, medical device, and health policy sectors. The programme is particularly relevant for researchers, data scientists, CRO professionals, HTA experts, staff of pharmaceutical and biomedical companies, healthcare professionals, and individuals involved in regulatory and clinical decision-making processes. Upon completion, participants will be able to interpret the results of patient preference studies, assess their methodological quality, integrate evidence into decision-making processes, and communicate their implications to different stakeholders.

Module 1: Introduction to PPS
Contents: definition of Patient Preference Studies, main methods for collecting preferences, differences from traditional clinical and economic approaches, applications in healthcare settings, and the role of regulatory agencies.

Module 2: Discrete Choice Experiments
Contents: introduction to DCEs, study design and implementation, utility theory, analysis and interpretation of results, replicability, and preference heterogeneity.

Module 3: Evidence Synthesis
Contents: systematic reviews and meta-analyses applied to DCEs, objectives of evidence synthesis, use in regulatory and HTA contexts, and presentation of case studies.

Module 4: AI-Assisted Preference Research
Contents: case studies, use of artificial intelligence in evidence synthesis, and functionalities and applications of the Repertor.IO platform.

Module 5: The Patient Voice and Future Perspectives
Contents: direct patient involvement, discussion with patient advisors, final synthesis of key concepts, future research perspectives, and Q&A session.

The course draws on a faculty composed of university professors, researchers, and experts in biostatistics, epidemiology, artificial intelligence applied to healthcare, and clinical research. The collaboration between the University of Padua, the University of Turin, and Repertor.IO ensures a multidisciplinary approach, combining methodological rigour with practical applications. Participants will have the opportunity to engage with professionals involved in national and international projects on patient preferences, evidence synthesis, HTA, and digital innovation in healthcare.

A distinctive feature of the course is the integration of established patient preference research methodologies with innovative artificial intelligence tools. Through case studies and practical demonstrations, participants will explore the use of AI-based solutions for evidence synthesis and analysis. The Repertor.IO platform will be presented as an applied example to illustrate how technological innovation can support more efficient, transparent, and patient preference-oriented decision-making processes.

The programme places particular emphasis on direct patient involvement and on enhancing the role of the patient voice in healthcare decision-making processes. Discussions with patient advisors help connect methodological tools with patients’ real-life experiences and healthcare needs. This perspective enables participants to understand how preferences can contribute to the development, evaluation, and access to healthcare technologies, strengthening a patient-centred approach to research and health policy.

The general ranking of merit for the academic year 2025/26 will be published on the Italian page of this Course according to the timing provided in the Call.