Focus: To generate and manage quality and reliable data.

Real World Data Science focuses on harnessing real-world data’s vast potential to drive healthcare innovation. This axis emphasizes the importance of collecting, analyzing, and managing data that reflects patient experiences and healthcare processes.

Focus: To create, validate and foster data modeling and adoption of trusted algorithms, including AI.

This axis is dedicated to advancing the field of modelling and numerical methods, focusing on developing and applying sophisticated algorithms and computational techniques that can improve healthcare decision-making and outcomes.

Focus: To facilitate implementation, organizational change and proof of concepts.

Axis 3 focuses on synthesizing evidence from various sources to guide the design, development, and deployment of effective digital health interventions. This involves a systematic approach to gathering, analyzing, and translating data into practical solutions that can be sustainably integrated into healthcare systems.

Focus: To disseminate best practices for sustainable design and deployment of digital tools.

Axis 4 is centered around the practical application of digital health research. It focuses on implementing innovative solutions in real-world settings, evaluating their impact, and using living labs as testbeds for new ideas. This axis aims to turn theoretical research into tangible health improvements.