xShare envisions everyone sharing their health data in EEHRxF with a click-of-a-button. The xShare button to be featured across health portals and patient apps and allow people to exercise their data portability rights under GDPR. Hence, the European EHRxF will be the driver for research and innovation in EHDS. xShare will establish the European EHRxF Standards and Policy Hub, the “Hub” partnership of six standards developing organizations (CEN/TC251, HL7 Europe, IHE Europe, SNOMED, CDISC, IEEE) market actors (DIGITAL Europe, MedTech-Europe and EUCROF), supported by competence centers, nationals and regional authorities and European SMEs. xShare will develop: 1) Harmonized common specifications, create and maintain xBundles i.e., collection of common data specifications including FHIR implementation guides, tools and data sets, and educational support for key EHRxF health information domains as noted in the EHDS draft regulation Annex 1. 2) A set of common elements across EHRxF health information domains applicable across EHDS-1 (JA-9), public/population health (EHDS-2), and clinical research. 3) Extended harmonized IPS specification to include care plans and making it fit for the purpose of clinical research use cases i.e. clinical trial eligibility, real world data, patient reported outcomes, and returning clinical research data to patients. 4) xShare feature the xShare Button in 8 adoption settings in Hospital network (Italy), National portal (Greece, Ireland, Cyprus), regional network with emphasis in medical tourism and the connection of the public to the private sector (Catalunya and Madeira), entry of digital health applications to the myHealthSpace ecosystem in France. Care plans will be demonstrated in Denmark. xShare investigate the feasibility and value of the EU xShare Industry label as a vehicle towards implementing the draft EHDS regulation. Lastly open calls at the last year of the project aim to onboard with EHRxF almost 100 settings across Europe.

The European health services have well responded to the COVID-19 emerging crisis, especially if and where the intensive care unit (ICU) capacities were sufficient, were prepared and collectively cooperating, sharing knowledge and were able to protect from further spreading of the disease among the healthcare workforce and the patients. Today, only 47% of hospitals have the recommended coverage of intensive care specialists and they are unevenly distributed between centres and periphery. The Cyber-Physical System for Telemedicine and Intensive Care (CPS4TIC) enables existing or new ICU structures to transform and operate as one ICU Hub with one central ICU and connected ICUs in peripheral hospitals. CPS4TIC was used successfully in the first wave of COVID-19 to ensure efficient and effective diagnosis and treatment of COVID-19 patients, while reducing the risk of infection drastically. The CPS4TIC consists of a telemedicine cockpit, telemedicine consoles at each peripheral hospital, a connector platform and smart bedside hubs including robotic arm at the bedsides of both, the central telemonitoring clinics and the peripheral telemonitored hospitals. The ICU Hub operates telemedicine, continuous real-time telemonitoring and bedside smart care environment. The bedside smart care environment reduces the risk of infection for the health workforce significantly both for the central and the peripheral hospitals. ICU4Covid will deploy and test the CPS4TIC at large-scale, in 10 ICU Hubs in Europe, involving more than 30000 patients/year with a coverage of approximately 60 Million citizens.

TeleRehaB DSS targets the promotion of AI adoption in everyday clinical practice for balance rehabilitation training. An AI-based decision support system (DSS) will be developed expanding upon the existing Augmented Reality (AR) rehabilitation training platform, with its balance exercises, exergames, cognitive training and remote patient monitoring with wearables and IoT devices from HOLOBALANCE project (TL6), to provide suggestive feedback for experts through the entire clinical rehabilitation pathway. The first component of AI models of TeleRehaB DSS will assess prognostic factors for risk of falls, treatment effectiveness, outcomes and side effects at baseline level, using a high volume of retrospective data for initial training. The other AI pillar of TeleRehaB DSS will introduce automated balance intervention planning and management functionality. The DSS will provide for each patient an optimal set of personalised rehabilitation activities, considering the best clinically effective treatment in conjunction with socio-economic effectiveness, and eHealth literacy. The later will be evaluated with a quick and easy to use tool with simple tasks to assess patient's level of technological awareness (i.e. use of smart devices, AR and IoT equipment), in order to predict if this is going to affect compliance and adherence with interventions that rely on the use of such novel technologies. Finally, the most beneficial use of AI in TeleRehaB DSS will consist of automated remote patient monitoring with wearables and IoT sensing devices, allowing rehabilitation training programs to be performed at home. The DSS will evaluate in real-time patient performance, symptoms occurrence with virtual AR physio's providing corrective and motivational feedback as activities are performed. These performance evaluation measures will be fed back to the DSS to support experts with their most time and effort-consuming activities of day-to-day patient management.

QualiChain targets the creation, piloting and evaluation of a decentralised platform for storing, sharing and verifying education and employment qualifications and focuses on the assessment of the potential of blockchain technology, algorithmic techniques and computational intelligence for disrupting the domain of public education, as well as its interfaces with private education, the labour market, public sector administrative procedures and the wider socio-economic developments. The project focuses more specifically on the assessment of the implications (technical, political, socio-economic, legal and cultural) as well as the impact - in terms of benefits and risks - of the prescribed solution’s utilisation, whose disruptive potential lies both in the exploitation of the innovative features of the aforementioned individual technologies, as well as in their unique combination in a new territory for the provision of a set of baseline services (Awards’/ Qualifications’ Archiving; Awards’/ Qualifications’ Verification; Qualifications’ Portfolio Management) and a number of value-adding services (Career Counselling and Intelligent Profiling and Competency Management including Recruitment; Competencies’ Evaluation and Development; Consulting and Decision Support). The proposed solution will be piloted through four representative scenarios, including: (i) cross-university degree equivalence verification; (ii) smart curriculum design; (iii) staffing the public sector; (iv) providing HR consultancy and competency management services.

It is a fact that the European population growth is slowing down, while the population ageing accelerates. Rapid increases in the elderly population are predicted for the coming decades due to the ageing of post-war baby births. Within Europe’s ageing population, Hearing Loss, Cardio Vascular Diseases, Cognitive Impairments, Mental Health Issues and Balance Disorders, as well as Frailty, are prevalent conditions, with tremendous social and financial impact. Preventing, slowing the development of or dealing effectively with the effects of the above impairments can have a significant impact on the quality of life and lead to significant savings in the cost of healthcare services. Digital tools hold the promise for many health benefits that can enhance the independent living and well-being of the elderly. Motivated by the above, the aim of the SMART BEAR platform is to integrate heterogeneous sensors, assistive medical and mobile devices to enable the continuous data collection from the everyday life of the elderly, which will be analysed to obtain the evidence needed in order to offer personalised interventions promoting their healthy and independent living. The platform can also be connected to hospitals and other health care service systems to obtain data of the end-users (e.g., medical history) to be considered in making decisions for interventions. SMART BEAR will leverage big data analytics and learning capabilities, allowing for large scale analysis of the above mentioned collected data, to generate the evidence required for making decisions about personalised interventions. Privacy-preserving and secure by design data handling capabilities, covering data at rest, in processing, and in transit, will cover comprehensively all the components and connections utilized by the SMART BEAR platform. The SMART BEAR solution will be validated through five large-scale pilots involving up to 4.100 elderly living at home in Greece, Italy, France, Portugal and Romania.