Educational Resources

The DaTSHealth program, through its educational content development and dissemination activities, produces a range of videos and podcasts addressing the major challenges of digital health. Drawing on the expertise of its academic, hospital, clinical, and industry partners in France and internationally, these resources explore the technical, clinical, ethical, and societal dimensions of the digital transformation of healthcare, with the aim of supporting a broad audience in understanding these ongoing changes.

Topics include:

Understanding digital health
Accessing healthcare through digital tools
Managing health data
Artificial intelligence in care
Training in digital health
Ensuring digital security in healthcare
Digital health and equitable access
Innovating and transforming practices
Digital tools in healthcare

Understanding Digital Health

This section brings together multimedia content designed to help users become familiar with the key concepts of digital health: its evolution, applications, and main challenges. These resources, produced by Institut Polytechnique de Paris or sourced from public organizations, health agencies, and international institutions (such as the World Health Organization), help provide a better understanding of current dynamics and the perspectives associated with the increasing integration of digital technologies into healthcare systems.

Managing Health Data

Health data is a central element of the digital health ecosystem. It is collected, structured, stored, and used across a variety of technical environments: information systems, monitoring platforms, analytical tools, and even artificial intelligence models. This section addresses the challenges related to the collection, sharing, protection, and reuse of these data. The content highlights issues such as data flow architecture, access security, medical information processing, and the governance frameworks associated with digital health.

Artificial Intelligence in Care

What Are the Current Uses of Artificial Intelligence in Healthcare? This section examines the contributions of AI to clinical practice, including diagnostic support, prediction, image analysis, and automated sorting. It also addresses the associated limitations and challenges, such as explainability, algorithmic bias, and acceptance by healthcare professionals and patients.

Digital Health Education

The digital transformation of healthcare is accompanied by evolving skill requirements for engineers, healthcare professionals, and all stakeholders, whether in the public or private sector. This section presents testimonials, case studies, and training initiatives, illustrating the diversity of profiles involved in digital health careers. It highlights the interdisciplinary connections at play and the opportunities offered by a constantly evolving sector.

Digital Health and Equity of Access

The development of new healthcare technologies—whether decision-support tools, remote monitoring devices, or digital interfaces in care pathways—raises important equity issues affecting both patients and healthcare professionals. Questions around the acceptability of these tools, inequalities in access depending on context, and the economic challenges related to their deployment are the focus of much current research. This section brings together multimedia content that sheds light on these issues and explores potential solutions.

Prévention du risque et impact sur la couverture assurantielle en santé

Innovating and Transforming Practices

This section brings together content that traces the development of innovative digital health projects, from the initial idea to real-world implementation. It features initiatives originating from research, entrepreneurial efforts, or collaborations between public and private actors. These stories allow readers to follow the different stages of a project: design, prototyping, testing, adjustments, and challenges encountered. Special attention is given to the journey of the project leaders: the decisions they made, the steps they took, the adjustments implemented, and the lessons their experiences can offer to those aspiring to innovate in digital health.