The Member States in the eHealth Network have adopted these supplementary clauses to the general guidelines for the electronic exchange of health data under Cross-Border Directive 2011/24/EU to support the exchange of Hospital Discharge Report for continuity of care in a cross-border setting. The Hospital Discharge Guideline builds on the foundations laid out by the Patient Summary and the ePrescription Guidelines (including datasets and code systems). The eHealth Network guidelines build a set of guidelines that should be seen as complementing each other in different use cases and are operating under the umbrella of the General Guidelines.

This document is the first version of the Strategic Research and Innovation Roadmap of the TAILOR project, focussed on Trustworthy Artificial Intelligence (AI) through Learning, Optimization and Reasoning. The project objectives are extremely ambitious, and address topics that are currently very actively investigated. Therefore, defining a roadmap is itself an ambitious goal. We have started analysing many documents containing Roadmaps and Research and Innovation agendas of AI related initiatives (in particular we have analysed the AI4EU Strategic Research and Innovation Agenda and the AI, Data and Robotics PPP Strategic Research Innovation and Deployment Agenda and the AI Watch Index 2021).

The healthcare industry faces challenges due to constantly changing conditions, including demographic transitions and the advancements we have achieved until now in health science and the healthcare industry. Life expectancy has increased, and we live longer with chronic diseases (Anderson & Hussey, 2000; Bongaart et al., 2015). This requires the healthcare industry to focus on an increasingly older population with a more complex disease burden than healthcare previously dealt with. As a direct consequence of the demographic shift, non-communicable and chronic diseases are becoming more prevalent, straining all health systems (Harris, 2019).

On 24 March 2021, Regulation (EU) 2021/522 of the European Parliament and of the Council1 was adopted as part of the Multiannual Financial Framework for the 2021-2027 period. That Regulation established a Programme for the Union's action in the field of health ('the EU4Health Programme').

The COVID-19 pandemic has caused an unprecedented health crisis in the Union and beyond, with severe socio-economic consequences and human suffering. The EU4Health Programme represents an unparalleled Union level financial commitment for health actions in comparison with previous health programmes.

This study presents an overview of the development, adoption and use of Artificial Intelligence (AI) technologies and applications in the healthcare sector across all Member States. The main aim of this study was to support the European Commission in identifying and addressing any issues that might be hindering the wider adoption of AI technologies in the healthcare sector. The study will help the Commission to take action to achieve its long-term goal on the effective implementation of AI in the healthcare sector, based around common legislation and policy framework.

Artificial Intelligence (AI) refers to the ability of algorithms encoded in technology to learn from data so that they can perform automated tasks without every step in the process having to be programmed explicitly by a human. WHO recognizes that AI holds great promise for the practice of public health and medicine. WHO also recognizes that, to fully reap the benefits of AI, ethical challenges for health care systems, practitioners and beneficiaries of medical and public health services must be addressed. Many of the ethical concerns described in this report predate the advent of AI, although AI itself presents a number of novel concerns.

The Programme should be a means of promoting actions in areas where there is a Union added value that can be demonstrated. Such actions should include, inter alia, strengthening the exchange of best practices between Member States, supporting networks for the sharing of knowledge or for mutual learning, addressing cross-border threats to health so as to reduce the risks of such threats and to mitigate their consequences, addressing certain issues relating to the internal market in relation to which the Union can achieve Union-wide high-quality solutions, thereby unlocking the potential of innovation in health, and improving efficiency by avoiding the duplication of activities and optimising the use of financial resources.