Towards a European Health Research and Innovation Cloud (HRIC)

The European Union (EU) initiative on the Digital Transformation of Health and Care (Digicare) aims to provide the conditions necessary for building a secure, flexible, and decentralized digital health infrastructure. Creating a European Health Research and Innovation Cloud (HRIC) within this environment should enable data sharing and analysis for health research across the EU, in compliance with data protection legislation while preserving the full trust of the participants. Such a HRIC should learn from and build on existing data infrastructures, integrate best practices, and focus on the concrete needs of the community in terms of technologies, governance, management, regulation, and ethics requirements. Here, we describe the vision and expected benefits of digital data sharing in health research activities and present a roadmap that fosters the opportunities while answering the challenges of implementing a HRIC. For this, we put forward five specific recommendations and action points to ensure that a European HRIC: i) is built on established standards and guidelines, providing cloud technologies through an open and decentralized infrastructure; ii) is developed and certified to the highest standards of interoperability and data security that can be trusted by all stakeholders; iii) is supported by a robust ethical and legal framework that is compliant with the EU General Data Protection Regulation (GDPR); iv) establishes a proper environment for the training of new generations of data and medical scientists; and v) stimulates research and innovation in transnational collaborations through public and private initiatives and partnerships funded by the EU through Horizon 2020 and Horizon Europe

Precision Medicine Informatics: Principles, Prospects, and Challenges

Precision Medicine (PM) is an emerging approach that appears with the impression of changing the existing paradigm of medical practice. Recent advances in technological innovations and genetics, and the growing availability of health data have set a new pace of the research and imposes a set of new requirements on different stakeholders. To date, some studies are available that discuss about different aspects of PM. Nevertheless, a holistic representation of those aspects deemed to confer the technological perspective, in relation to applications and challenges, is mostly ignored. In this context, this paper surveys advances in PM from informatics viewpoint and reviews the enabling tools and techniques in a categorized manner. In addition, the study discusses how other technological paradigms including big data, artificial intelligence, and internet of things can be exploited to advance the potentials of PM. Furthermore, the paper provides some guidelines for future research for seamless implementation and wide-scale deployment of PM based on identified open issues and associated challenges. To this end, the paper proposes an integrated holistic framework for PM motivating informatics researchers to design their relevant research works in an appropriate context.Comment: 22 pages, 8 figures, 5 tables, journal pape

Doctor of Philosophy

dissertationClinical decision support (CDS) and electronic clinical quality measurement (eCQM) are 2 important computerized strategies aimed at improving the quality of healthcare. Unfortunately, computer-facilitated quality improvement faces many barriers. One problem area is the lack of integration of CDS and eCQM, which leads to duplicative efforts, inefficiencies, misalignment of CDS and eCQM implementations, and lack of appropriate automated feedback on clinicians' performance. Another obstacle in the acceptance of electronic interventions can be the inadequate accuracy of electronic phenotyping, which leads to alert fatigue and clinicians' mistrust of eCQM results. To address these 2 problems, the research pursued 3 primary aims: Aim 1. Explore beliefs and perceptions regarding the integration of CDS and eCQM functionality and activities within a healthcare organization. Aim 2. Evaluate and demonstrate feasibility of implementing quality measures using a CDS infrastructure. Aim 3. Assess and improve strategies for human validation of electronic phenotype evaluation results. To address Aim 1, a qualitative study based on interviews with domain experts was performed. Through semistructured in-depth and critical incident interviews, stakeholders' insights about CDS and eCQM integration were obtained. The experts identified multiple barriers to the integration of CDS and eCQM and offered advice for addressing those barriers, which the research team synthesized into 10 recommendations. To address Aim 2, the feasibility of using a standards-based CDS framework aligned with anticipated electronic health record (EHR) certification criteria to implement electronic quality measurement (QM) was evaluated. The CDS-QM framework was used to automate a complex national quality measure at an academic healthcare system which had previously relied on time-consuming manual chart abstractions. To address Aim 3, a randomized controlled study was conducted to evaluate whether electronic phenotyping results should be used to support manual chart review during single-reviewer electronic phenotyping validation. The accuracy, duration, and cost of manual chart review were evaluated with and without the availability of electronic phenotyping results, including relevant patient-specific details. Providing electronic phenotyping results was associated with improved overall accuracy of manual chart review and decreased review duration per test case. Overall, the findings informed new strategies for enhancing efficiency and accuracy of computer-facilitated quality improvement

From Inception to ConcePTION: Genesis of a Network to Support Better Monitoring and Communication of Medication Safety During Pregnancy and Breastfeeding

In 2019, the Innovative Medicines Initiative (IMI) funded the ConcePTION project—Building an ecosystem for better monitoring and communicating safety of medicines use in pregnancy and breastfeeding: validated and regulatory endorsed workflows for fast, optimised evidence generation—with the vision that there is a societal obligation to rapidly reduce uncertainty about the safety of medication use in pregnancy and breastfeeding. The present paper introduces the set of concepts used to describe the European data sources involved in the ConcePTION project and illustrates the ConcePTION Common Data Model (CDM), which serves as the keystone of the federated ConcePTION network. Based on data availability and content analysis of 21 European data sources, the ConcePTION CDM has been structured with six tables designed to capture data from routine healthcare, three tables for data from public health surveillance activities, three curated tables for derived data on population (e.g., observation time and mother-child linkage), plus four metadata tables. By its first anniversary, the ConcePTION CDM has enabled 13 data sources to run common scripts to contribute to major European projects, demonstrating its capacity to facilitate effective and transparent deployment of distributed analytics, and its potential to address questions about utilization, effectiveness, and safety of medicines in special populations, including during pregnancy and breastfeeding, and, more broadly, in the general population

A decadal view of biodiversity informatics: challenges and priorities

Biodiversity informatics plays a central enabling role in the research community's efforts to address scientific conservation and sustainability issues. Great strides have been made in the past decade establishing a framework for sharing data, where taxonomy and systematics has been perceived as the most prominent discipline involved. To some extent this is inevitable, given the use of species names as the pivot around which information is organised. To address the urgent questions around conservation, land-use, environmental change, sustainability, food security and ecosystem services that are facing Governments worldwide, we need to understand how the ecosystem works. So, we need a systems approach to understanding biodiversity that moves significantly beyond taxonomy and species observations. Such an approach needs to look at the whole system to address species interactions, both with their environment and with other species. It is clear that some barriers to progress are sociological, basically persuading people to use the technological solutions that are already available. This is best addressed by developing more effective systems that deliver immediate benefit to the user, hiding the majority of the technology behind simple user interfaces. An infrastructure should be a space in which activities take place and, as such, should be effectively invisible. This community consultation paper positions the role of biodiversity informatics, for the next decade, presenting the actions needed to link the various biodiversity infrastructures invisibly and to facilitate understanding that can support both business and policy-makers. The community considers the goal in biodiversity informatics to be full integration of the biodiversity research community, including citizens’ science, through a commonly-shared, sustainable e-infrastructure across all sub-disciplines that reliably serves science and society alike