Integrating evidence generation in eHealth development

Abstract

eHealth solutions promise more efficient and patient-centred healthcare, yet their development is challenged by differing approaches to evidence generation. In practice, designers tend to favour dynamic, context-sensitive evidence generated through iterative engagement with users, while healthcare professionals often incline towards static, predefined evidence to ensure clinical safety and regulatory compliance. Although these preferences are not absolute, insufficient integration between them can hinder the development of clinically robust and meaningful eHealth solutions. This thesis investigates how static and dynamic approaches to evidence generation can be integrated to support user-centred, standard-compliant eHealth development. Through systematic literature review, qualitative interviews, case study research, and theory adaptation, the thesis identifies shared evidence practices across design and healthcare, clarifies how patient-centred outcomes can guide dynamic evidence generation, and examines how integration can be structured within existing eHealth standards. Based on these findings, the thesis develops the Clinical Data-Enabled Design (C-DED) framework, which structures evidence generation through iterative development phases and evidence reflections. The thesis concludes that tensions in eHealth evidence generation stem from insufficient integration rather than incompatible practices.