IMPROVE will use Patient Generated Health Data (PGHD) gathered via m-health and e-health technologies to gain improved insights into the real-life behavior of, and challenges faced by, patients of all ages with complex, chronic diseases and comorbidities. Already today, a wealth of patient and citizen information is available, but fragmented, and therefore not coming to its full utility and value. These personal data will complement and improve existing approaches for Patient-Centered Outcome Measures beyond those currently available in state-of-the-art platforms. The IMPROVE platform that the consortium will build will enable the smart use of patient input and patient generated evidence to 1) advance the role of patient preference and patient experience in the context of treatment selection, 2) improve medical device design based on patient preferences and experiences, and 3) facilitate faster market entry of patient-centric and cost-effective advanced integrated care solutions. Improved clinical adoption of Value Based Health Care, and enhanced return on research and innovation investments will be demonstrated in different care settings across the EU, for 10 use cases in at least 5 different disease areas (e.g., ophthalmology, oncology, cardiovascular disease, chronic inflammation, and neurology). The use cases will be conducted using a large variety of implementation strategies, building on a design thinking approach, to optimally test the innovative framework of data gathering and translation into controlled change and action. In addition, a significant contribution from implementation science is planned to reach out to all stakeholders that are relevant for this initiative and maximise the impact to IMPROVE healthcare provision.

The first and core objective of City4Age is to enable Ambient Assisted Cities or Age-friendly Cities, where the urban communities of elderly people living in Smart Cities are provided with a range of ICT tools and services that - in a completely unobtrusive manner - will improve the early detection of risks related to cognitive impairments and frailty while they are at home or in the move within the city. The second objective is to provide a range of associated tools and services which - with the appropriate interventions - will mitigate the detected risks. The final objective of C4A is to define a model which will provide sustainability and extensibility to the offered services and tools by addressing the unmet needs of the elderly population in terms of (i) detecting risks related to other health type problems, (ii) stimulating and providing incentives to remain active, involved and engaged, (iii) creating an ecosystem for multi-sided market by matching needs and their fulfillments, (iv) contributing to the design and operation of the ultimate Age-friendly City, where the city itself provides support for detecting risks and providing interventions to those affected by mild cognitive impairment (MCI) and frailty. To achieve these objectives City4Age builds on: - behavioural, sociological and clinical research on “frailty” and MCI in the elderly population; - state of art ICT technology (i) for “sensing” personal data and exposing them as linked open data, (ii) for designing the algorithms and the API’s to extract relevant behaviour changes and correlated risks, and (iii) for designing interventions to counter the risks, - stakeholder engagement in order to be driven by relevant user needs to ensure end-user acceptance.

Ageing@Work will develop a novel ICT-based, personalized system to support ageing workers (aged 50+) into designing fit-for-purpose work environments and managing flexibly their evolving needs. Advanced dynamically adapted virtual models of workers will incorporate specificities in respect to skills, physical, cognitive and behavioral factors, being extended from the work context to personal life aspects interacting with workability, health and well-being. Virtual workplace models will encode characteristics of the workplace (factory, outdoor work site, home), at both physical and semantic, resource/process levels. On top of the models, computational intelligence will be responsible to (a) assess user specificities and needs i.r.t. work conditions, both in terms of ergonomics, health and safety issues and task assignments, and (b) perform personalized predictive simulations on workability, health and well-being. Recommendations will then be provided both to the worker and company (under strict privacy restrictions), on how the working conditions must adapt. The worker models will be populated by highly unobtrusive worker sensing, both at work, at home and on the move. To foster workability and productivity, highly personalized, intuitive, age-friendly productivity, co-design enhancement tools will be developed, including ones for AR/VR-based context-awareness and telepresence, lifelong learning and knowledge sharing. On top of these, a novel Ambient Virtual Coach (AVC) will encompass an empathic mirroring avatar for subtle notifications provision, an adaptive Visual Analytics –based personal dashboard, and a reward-based motivation system targeting positive and balanced worker behavior at work and personal life, towards a novel paradigm of ambient support into workability and well-being. The integrated system will be developed by user-centered design and will be evaluated at two pilot sites, related to core Industry 4.0 processes of mining and machines production.

The healthcare sector is hindered by several barriers that hamper the application of circular economy principles (e.g. the safety restrictions of the domain limit the use of recycled materials due to the need of materials biocompatibility, and safety in products to be used in the human body). Led by a multidisciplinary consortium of 39 partners (plus 13 industry affiliates) from 15 EU countries plus UK and USA, ENKORE aim to tackle challenges and develop an ecoDesign framework that supports the development of safe and environmental compliant devices eco-responsible packaging, which minimize the environmental impact, reduce the carbon footprint, and maximize the use and preservation of resources. The main goal is to connect the design of the medical devices packages with the end-of-life stage, thus the technologies that support circularity are taken into account at the medical device conception stage. ENKORE framework will be validated in 5 Reference Use Cases (RUCs), led by 5 different health regions that bring HPCs and policy maker, 3 large EU hospitals and the reference network for European Regional and Local Health Authorities (EUREGHA). The project developments and RUCs are supported by several associations and NGOs, a packaging manufacturer and a group of SMEs and researchers, specialists in circularity, LCA, social sciences, environment, circularity, and materials. The validation of the framework shall provide evidence to work with policymakers, creating new or revised standards and create tangible/quantitative evidence. Policy making and regulatory engagement will be strongly performed. The methods and tools comprise Environmental and Social Life Cycle Assessment (ELCA/SLCA), Circularity Calculator (CC) and Digital Product Passport (DPP) approaches, which could be adapted during the second stage of the proposal.

Head and neck cancer can take away a patient’s “right to feel human,” and its impact on physical appearance, physical functioning, psychological status and general quality of life (QoL) can be devastating. Over the past several decades, the number of patients who survive head and neck cancer (HNC) has increased; this makes lifelong surveillance critical. HNC imposes an extremely high socioeconomic burden on patients during and after cancer compared to other tumors, including costs from treatment-induced morbidities, loss of workforce participation and short-term disability. Current survivorship care plans mostly focus on functional and health conditions of treated patients, whereas socioeconomic determinants of quality of life are often neglected due to difficult data collection. The widespread technologies for social communication and unobtrusive personal monitoring embedded in smartphones and object we commonly use and in our living environments have the potential to unobtrusively collect wealth of indicators of individual QoL. BD4QoL objective is to improve HNC survivor’s Quality of Life through person-centred monitoring and follow-up plan by contribution of artificial intelligence and big data unobtrusively collected from commonly used mobile devices, in combination with multi-source clinical, -omic, socioeconomic data and patients reported outcomes, to profile HNC survivors for pBD4QoL objective is to improve HNC survivor’s Quality of Life through person-centred monitoring and follow-up plan by contribution of artificial intelligence and big data unobtrusively collected from commonly used mobile devices, in combination with multi-source clinical, -omic, socioeconomic data and patients reported outcomes, to profile HNC survivors for personalized monitoring and support. The analysis of QoL indicators collected over time will allow to early detect risks, prevent long-term effects of treatment and inform patients and caregivers for personalized interventions.