Within only six months, over 7.4 million people have been diagnosed with SARS-CoV-2. In the most severely hit countries, more than 10% of infected patients have received treatment in Intensive Care Units (ICUs). Insufficient data and limited knowledge on the disease as well as the lack of tools to support the intensivist in making accurate, timely and informed decisions has led to high mortality rates. Continuous surveillance, the collection and intelligent analysis of data from many sources, including ventilators and electrical impedance tomography, would allow intensivists to decide on the best suitable treatment to accelerate the recovery of the often comorbid COVID-19 patients, while reducing the burden on clinical staff and healthcare costs. This information would also increase our understanding of the yet unknown course of disease, supporting other stakeholders in the quest for new therapies. In ENVISION, our multidsciplinary public-private consortium will advance an innovative digital tool, Sandman.MD, a real-time and plug-and-play monitoring app, to an intelligent decision-support system for monitoring, prediction and treatment of COVID-19 patients in ICUs – the Sandman.ICU – reaching Technology Readiness Level 9 and ready for CE marking by the end of the project. The app has been developed by our SME partner app@work and successfully introduced by several hospitals in Germany for use during the perioperative period. Sandman.ICU will be integrated into an AI-driven data analytics suite with predictive modelling tools and enhanced with a smart alert functionality. The digital tool will be validated and demonstrated in 14 hospitals across Europe. Our Health Technology Assessment expert partner will demonstrate the economic and societal value of Sandman.ICU, while an experienced SME will manage the innovation process in view of an immediate market uptake. The rollout will be supported by the European Society of Anaesthesiology and Intensive Care.

Project Goal: The project responded to the current situation in nursing staff training, specifically the situation in the field of Moving & Handling. Although there are many VET programs in this area, their impact on the incidence of musculoskeletal injuries / disorders in nursing staff is relatively low. There is a gap in the educational and training approaches, which would bring a shift in the training and change the moving and handling stereotypes brought by the old training methodologies. The aim of the project was therefore to transfer the innovative M&H training program developed by Birmingham City University from Great Britain to 4 European countries (to the Czech Republic, Poland, Estonia and Lithuania).Partnership: The main coordinator of the project was LINET, the leading European manufacturer of hospital and nursing beds, which is also very active in the VET of nurses worldwide. Other partners were Birmingham City University as a university that developed an innovative M&H programme, two nursing associations (Czech Association of Nurses, Polskie Towarzystwo Pielegniarskie), 1 nurse education centre (Osrodek Ksztalcenia Podyplomowego Pielegniarek i Poloznych) and 2 hospitals (Hospital of Lithuanian University of Health Sciences, Kaunas Clinics, SIHTASUTUS TARTU ULIKOOLI KLIINIKUM).Project activities: The project analysed the current state of education in the above mentioned areas and transferred an innovative VET program to 4 countries. Seminars for trainers were carried out and the innovative M&H educational program was then pilot tested. Afterwards, dissemination events took place mainly through the implementation of local workshops and small scale meetings. Within the project, several transnational project meetings were held. At the end of the project the impacts of the program on the target group were evaluated. In general, the target group stated that the use of these new manipulation techniques with patients greatly facilitates their current work, and the transfer and enforcement of these techniques in the educational processes are seen as entirely breakthrough. The nurses evaluated the training course as very beneficial and the target group agreed that the implementation of the project will increase the effectiveness of the education, the education process will be significantly upgraded and the implementation of these techniques among the medical personnel will reduce the number of injuries of the musculoskeletal system at the nursing staff. Outputs of the project: As a result of the implementation of the project a detailed analysis of the state of the art of the above-mentioned issues was carried out in individual countries. There was also carried out a research of the impact of the educational program, which served as input for the final creation of 4 local versions of the training course.The project ran in line with the scheduled timetable and was successfully completed in September 2017.

There is a growing recognition that health and wellness apps need to play a much stronger role in health care systems, self-care and health prevention than they do today. However, health care systems, health professionals, patients and citizens lack means to adequately assess the quality and reliability of the many apps to choose from, for every purpose, in each app store. Suppliers experience the varying national approval processes as confusing and unclear as to what is expected and the depth of evidence that is required by each approval body. We intend to break through the impasse by leveraging the golden opportunity of the publication in July 2021 of the ISO 82304?2 Technical Specification (TS) and its health app quality label. Work is now needed to turn this globally endorsed quality assessment and health app quality label into the EU assessment and EU mHealth label, embed it within the approval and reimbursement processes of European countries and foster cross-country alignment of these approval processes. The objective of Label2Enable is threefold: achieve trust, use and adoption. We will pursue: 1. trust with an EU certification scheme that results in consistent compliant inclusive app assessments 2. use with: - a more detailed health app quality report that enables health professionals to recommend apps and insurers to speed up decisions on reimbursements - supporting communication that enables all patients, citizens and carers to use the label in considering health apps - social experimentation to promote app stores, app libraries and other routinely used trusted sources that (seek to) offer health apps to effectively publish the label alongside them 3. adoption of the TS and cross-country recognition with pilots, use stories, advocacy, mass communication and targeted multi-stakeholder engagement, affordable app assessments and a sustainable non-profit entity that will maintain the scheme, accredit app assessors and promote the TS after the project.

Most cases of gastric cancer (GC) are detected at a late stage, when patients have a median life expectancy of about a year. Diagnosing people at risk of developing GC at the pre-symptomatic stage, typically chronic gastric inflammation, could significantly improve the outlook. Artificial intelligence (AI) can help clinicians make sense of their own data by automating much of the treatment and analysis, which require manual work and years of experience. But it can do more: it can bring together available data from various sources into a vast data lake and cross-correlate the data to derive a ‘risk score’ for gastric cancer and shed light on the mechanisms of its evolution. Aida aims to do just that. It helps researchers understand the mechanisms that trigger gastric oncogenesis, helps clinicians diagnose precancerous inflammation at the earliest possible stage, suggests personalised therapeutic strategies for treatment and follow-up, and makes personalised recommendations for monitoring patient health status, thus contributing to gastric cancer prevention. This places Aida squarely on Europe’s agenda of ‘Staying healthy in a rapidly changing society’. Aida unites some of Europe’s leading authorities in the field of gastric inflammation, gastric cancer, leading AI and machine learning experts, experts on data governance and privacy, representatives of the public administration and patient advocates. Aida also has strong ties with the industry. After the project, the results will live on in an association that acts as a transnational focal point for chronic gastric inflammation — and GC in general. We hope that the solid, inclusive design principles of Aida, its societal relevance and its durability will spawn a vigorous ecosystem around chronic gastric inflammation, its understanding and its treatment. And we hope that it will inspire other data collaboratives in health — for other chronic inflammations, other forms of cancer or other ailments altogether.

The goal of EuCanImage is to build a highly secure, federated and large-scale European cancer imaging platform, with capabilities that will greatly enhance the potential of artificial intelligence (AI) in oncology. Firstly, the EuCanImage platform will be populated with a completely new data resource totaling over 25,000 single subjects, which will allow to investigate unmet clinical needs like never before, such as for the detection of small liver lesions and metastases of colorectal cancer, or for estimating molecular subtypes of breast tumours and pathological complete response. Secondly, the cancer imaging platform, built by leveraging the well-established Euro-Bioimaging infrastructure, will be cross-linked to biological and health repositories through the European Genome-phenome Archive, allowing to develop multi-scale AI solutions that integrate organ-level, molecular and other clinical predictors into dense patient-specific cancer fingerprints. To deliver this platform, the consortium will build upon several key European initiatives in data sharing for personalised medicine research, including EUCANCAn (cancer genomics and health data sharing), euCanSHare (cardiac imaging and omics data sharing) and EUCAN-Connect (federated data analytics). Furthermore, to foster international cooperation and leverage existing success stories, the consortium comprises the coordinators of The Cancer Imaging Archive (TCIA), the US cancer imaging repository funded by the National Cancer Institute. This will allow EuCanImage to leverage a unique 10-year long experience in cancer imaging storage, anonymisation, curation and management. Finally, a close collaboration between world renown clinical, radiomics, AI and legal experts within the consortium and beyond will establish well-needed guidelines for AI development and validation named FUTURE, for delivering Fair, Universal, Traceable, Usable, Robust and Explainable decision support systems for future cancer care.