Facilitating virtual networking for Design for All in Europe: The HERMES platform

This paper reports on HERMES, the virtual networking platform of the European Design for All eAccessibility Network (EDeAN) that was established in 2002 by the European Commission in order to stimulate European network activities within the area of Design for All, with particular focus on ICT and e-Accessibility. The paper reports on the development and utilisation of the networking platform developed to enable the cooperation of EDeAN members through an accessible interface over the World Wide Web. HERMES is available at http://www.edean.or

A Data-informed Public Health Policy-Makers Platform

Hearing loss is a disease exhibiting a growing trend due to the number of factors, including but not limited to the mundane exposure to the noise and ever-increasing amount of older population. In the framework of a public health policymaking process, modeling of the hearing loss disease based on data is a key factor in alleviating the issues related to the disease issuing effective public health policies. First, the paper describes the steps of the data-driven policymaking process. Afterward, a scenario along with the part of the proposed platform, responsible for supporting policymaking are presented. With the aim of demonstrating the capabilities and usability of the platform for the policy-makers, some initial results of preliminary analytics are presented in a framework of a policy-making process. Ultimately, the utility of the approach is validated throughout the results of the survey which was presented to the health system policy-makers professionals involved in the policy development process in Croatia

A Modelling Framework for Evidence-Based Public Health Policy Making

It is widely recognised that the process of public health policy making (i.e., the analysis, action plan design, execution, monitoring and evaluation of public health policies) should be evidenced based, and supported by data analytics and decision-making tools tailored to it. This is because the management of health conditions and their consequences at a public health policy making level can benefit from such type of analysis of heterogeneous data, including health care devices usage, physiological, cognitive, clinical and medication, personal, behavioural, lifestyle data, occupational and environmental data. In this paper we present a novel approach to public health policy making in a form of an ontology, and an integrated platform for realising this approach. Our solution is model-driven and makes use of big data analytics technology. More specifically, it is based on public health policy decision making (PHPDM) models that steer the public health policy decision making process by defining the data that need to be collected, the ways in which they should be analysed in order to produce the evidence useful for public health policymaking, how this evidence may support or contradict various policy interventions (actions), and the stakeholders involved in the decision-making process. The resulted web-based platform has been implemented using Hadoop, Spark and HBASE, developed in the context of a research programme on public health policy making for the management of hearing loss called EVOTION, funded by the Horizon 2020

Pseudonymisation in the context of GDPR-compliant medical research

Pseudonymisation is a data protection technique often used to protect the privacy of individuals when their personal data are being used for research purposes. Not only is it a key ingredient of the General Data Protection Regulation (GDPR) that requires organisations to ensure that the personal data they process is handled in a secure manner, but it is particularly important in assisting medical research given that often relies on sensitive personal data, since it reduces the risk that medical data could be misused or mishandled. For managing their medical data, it is important to ensure that such data are protected against unauthorised access, and can be reutilised in an anonymous fashion, while still authorised personnel is able to identify the study participant that some data belong to (e.g., for personalised interventions, technical alerts, technical support). In addition, the re-identification of a study participant is a pre-requisite for exercising their rights under the GDPR, since it assists organisations in meeting GDPR requirements (such as the right to access, rectify and portability of data). We argue that the application of pseudonymisation is particularly effective when considered during the early stages (Privacy by Design) of digital services implementation, as well as when defining the complementary to these organizational procedures. Aim of this paper is to present the way in which the pseudonymisation mechanism of the SMART BEAR H2020 project supports the triptych of research activities conducted within the context of an observational medical study, legal obligations arising from the regulatory framework for the protection of personal data, and reutilisation of data for research purposes. Evidence-based security and privacy assessments will be conducted on two different H2020 projects to evaluate such privacy practice

RAMA: a risk assessment solution for healthcare organizations

Recent cyber-attacks targeting healthcare organizations underscore the growing prevalence of the sector as a prime target for malicious activities. As healthcare systems manage and store sensitive personal health information, the imperative for robust cyber security and privacy protocols becomes increasingly evident. Consequently, healthcare institutions are compelled to actively address the intricate cyber security risks inherent in their digital ecosystems. In response, we present RAMA, a risk assessment solution designed to evaluate the security status of cyber systems within critical domain, such as the healthcare one. By leveraging RAMA, both local stakeholders, such as the hospital’s IT personnel, and global actors, including external parties, can assess their organization’s cyber risk profile. Notably, RAMA goes beyond risk quantification; it facilitates a comparative analysis by enabling organizations to measure their performance against average aggregated mean scores, fostering a culture of continuous improvement in cyber security practices. The practical efficacy of RAMA is demonstrated through its deployment across four real-world healthcare IT infrastructures. This study not only underscores the significance of addressing cyber security risks within healthcare but also highlights the value of innovative solutions like RAMA in safeguarding sensitive health information and enhancing the sector’s overall cyber resilience

Healthier and Independent Living of the Elderly: Interoperability in a Cross-Project Pilot

The ageing of the population creates new heterogeneous challenges for age-friendly living. The progressive decline in physical and cognitive skills tends to prevent elderly people from performing basic instrumental activities of daily living and there is a growing interest in technology for aging support. Digital health today can be exercised by anyone owning a smartphone and parameters such as heart rate, step counts, calorie intake, sleep quality, can be collected and used not only to monitor and improve the individual’s health condition but also to prevent illnesses. However, for the benefits of e-health to take place, digital health data, either Electronic Health Records (EHR) or sensor data from the IoMT, must be shared, maintaining privacy and security requirements but unlocking the potential for research an innovation throughout EU. This paper demonstrates the added value of such interoperability requirements, and a form of accomplishing them through a cross-project pilot

Visualization of postoperative anterior cruciate ligament reconstruction bone tunnels: Reliability of standard radiographs, CT scans, and 3D virtual reality images

Background and purpose: Non-anatomic bone tunnel placement is the most common cause of a failed ACL reconstruction. Accurate and reproducible methods to visualize and document bone tunnel placement are therefore important. We evaluated the reliability of standard radiographs, CT scans, and a 3-dimensional (3D) virtual reality (VR) approach in visualizing and measuring ACL reconstruction bone tunnel placement. Methods: 50 consecutive patients who underwent single-bundle ACL reconstructions were evaluated postoperatively by standard radiographs, CT scans, and 3D VR images. Tibial and femoral tunnel positions were measured by 2 observers using the traditional methods of Amis, Aglietti, Hoser, Stubli, and the method of Benereau for the VR approach. Results: The tunnel was visualized in 50-82% of the standard radiographs and in 100% of the CT scans and 3D VR images. Using the intraclass correlation coefficient (ICC), the inter- and intraobserver agreement was between 0.39 and 0.83 for the standard femoral and tibial radiographs. CT scans showed an ICC range of 0.49-0.76 for the inter- and intraobserver agreement. The agreement in 3D VR was almost perfect, with an ICC of 0.83 for the femur and 0.95 for the tibia. Interpretation: CT scans and 3D VR images are more reliable in assessing postoperative bone tunnel placement following ACL reconstruction than standard radiographs. Copyright

Overview of the SMART-BEAR Technical Infrastructure

This paper describes a cloud-based platform that offers evidence-based, personalised interventions powered by Artificial Intelligence to help support efficient remote monitoring and clinician-driven guidance to people over 65 who suffer or are at risk of hearing loss, cardiovascular diseases, cognitive impairments, balance disorders, and mental health issues. This platform has been developed within the SMART-BEAR integrated project to power its large-scale clinical pilots and comprises a standards-based data harmonisation and management layer, a security component, a Big Data Analytics system, a Clinical Decision Support tool, and a dashboard component for efficient data collection across the pilot sites