The Value of Patient-Generated Health Data from Self-Management mHealth Solutions for Healthcare Professionals in Chronic Care

The rapid advancement of mobile technologies has opened new opportunities for patients to take a more active role in managing their health. Self-management mobile health solutions, such as smartphone applications and wearable devices, enable patient-generated health data, which can support the care of noncommunicable diseases. Despite their increasing availability, these solutions remain underutilised in clinical workflows.

This dissertation investigates how patient-generated health data from self-management mobile health solutions can be effectively leveraged by healthcare professionals to enhance the care process for noncommunicable diseases, with a focus on multiple sclerosis as a case study. Using a multi-method research approach, which included a systematic literature review, interviews, surveys, and focus groups, it examines how healthcare professionals perceive the value of patient-generated health data and how such data can best be presented to support clinical decision-making.

The results show that healthcare professionals selectively engage with patient-generated health data, prioritising information that provides actionable insights and improves decision-making. The visual representation of patient-generated health data emerged as a critical factor, highlighting the importance of clear, intuitive, and context-sensitive visualisations. The dissertation contributes to theory and practice by offering evidence-based recommendations for developers, healthcare organisations, and policymakers to improve the integration of mobile health solutions into clinical care.

By addressing barriers to adoption and emphasising collaboration between patients and healthcare professionals, this work demonstrates the potential of patient-generated health data-driven mobile health solutions to enhance the efficiency and effectiveness of chronic disease management.