PhD Defence Iva Halilaj

"Leveraging Patient Decision Aids and Decision Support Systems: Towards More Personalised Medical Treatments"
 

This thesis explores the advancement of patient-centered care, focusing on Shared Decision Making (SDM) and the development of Patient Decision Aids (PDAs) for non-small cell lung cancer (NSCLC) patients. The work is structured around two primary objectives: developing individualized PDAs to enhance patient involvement in treatment decisions and reviewing machine learning-based Decision Support Systems (DSS) in oncology. Key research questions address the design, clarity, and personalization of PDAs and the clinical relevance of predictive models in real-world settings.

Chapters highlight the rise of medical apps and predictive models in healthcare, emphasizing the need for validation and patient safety. The thesis successfully develops multimedia PDAs, tailored to individual patient needs, and shows their positive reception among patients and clinicians. However, challenges remain, such as incorporating predictive models, overcoming clinician skepticism, and ensuring accessibility across patient demographics.

Additionally, the work discusses the creation of trial-specific PDAs, like one for the ImmunoSABR trial, and introduces AI4Cancer, an open-source repository for predictive models. Throughout, the thesis stresses the importance of collaboration, usability, and inclusivity in implementing SDM and DSS tools in clinical practice.

In conclusion, the research contributes valuable insights for enhancing clinical decision-making and patient engagement, underscoring the future potential of personalized tools in healthcare.

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