The new Joint Action on Health Information: information for action (InfAct)!

Abboud, L A; Bogaert, Petronille; Fehr, Angela; Urbanski, Dominika; Tolonen, Hanna; Noguer-Zambran, I; Padrón-Monedero, Alicia; Palmieri, Luigi; Oyen, Herman Van

doi:10.1093/eurpub/cky212.651

Cited by 3 publications

(2 citation statements)

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“…A methodological framework for federated causal inference research by re-using routinely collected observational data across different regions, was constructed based on the principles of interoperability at Legal (i.e., privacy-by-design), Organizational (i.e., analysis coordination), Semantic (i.e., built upon a common data model) and Technical (i.e., via the distribution of analyses and a reproducible environment) level [ 11 ], Open Science (i.e., transparent and accessible processes and knowledge) [ 19 , 20 ] and international cooperation driven by population-level research questions. The framework expands methodologies to leverage population health data for federated policy-oriented research proposed within the “Information for Action” Joint Action (JA-InfAct) [ 12 , 21 ] and Population Health Information Research Infrastructure (PHIRI) project [ 22 ], allowing it to address causal research questions, through applying existing methodologies (e.g., the use of Directed Acyclic Graphs) and building on literature, experience and expertise.…”

Section: Methodsmentioning

confidence: 99%

Federated causal inference based on real-world observational data sources: application to a SARS-CoV-2 vaccine effectiveness assessment

Meurisse,

Estupiñán-Romero,

González-Galindo

et al. 2023

BMC Med Res Methodol

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Introduction Causal inference helps researchers and policy-makers to evaluate public health interventions. When comparing interventions or public health programs by leveraging observational sensitive individual-level data from populations crossing jurisdictional borders, a federated approach (as opposed to a pooling data approach) can be used. Approaching causal inference by re-using routinely collected observational data across different regions in a federated manner, is challenging and guidance is currently lacking. With the aim of filling this gap and allowing a rapid response in the case of a next pandemic, a methodological framework to develop studies attempting causal inference using federated cross-national sensitive observational data, is described and showcased within the European BeYond-COVID project. Methods A framework for approaching federated causal inference by re-using routinely collected observational data across different regions, based on principles of legal, organizational, semantic and technical interoperability, is proposed. The framework includes step-by-step guidance, from defining a research question, to establishing a causal model, identifying and specifying data requirements in a common data model, generating synthetic data, and developing an interoperable and reproducible analytical pipeline for distributed deployment. The conceptual and instrumental phase of the framework was demonstrated and an analytical pipeline implementing federated causal inference was prototyped using open-source software in preparation for the assessment of real-world effectiveness of SARS-CoV-2 primary vaccination in preventing infection in populations spanning different countries, integrating a data quality assessment, imputation of missing values, matching of exposed to unexposed individuals based on confounders identified in the causal model and a survival analysis within the matched population. Results The conceptual and instrumental phase of the proposed methodological framework was successfully demonstrated within the BY-COVID project. Different Findable, Accessible, Interoperable and Reusable (FAIR) research objects were produced, such as a study protocol, a data management plan, a common data model, a synthetic dataset and an interoperable analytical pipeline. Conclusions The framework provides a systematic approach to address federated cross-national policy-relevant causal research questions based on sensitive population, health and care data in a privacy-preserving and interoperable way. The methodology and derived research objects can be re-used and contribute to pandemic preparedness.

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Section: Methodsmentioning

confidence: 99%

Federated causal inference based on real-world observational data sources: application to a SARS-CoV-2 vaccine effectiveness assessment

Meurisse,

Estupiñán-Romero,

González-Galindo

et al. 2023

BMC Med Res Methodol

View full text Add to dashboard Cite

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“…The Farr Institute facilitated the use of population-based datasets in 593 published papers between 2013 and 2018, a time of profound societal and policy change within the UK in relation to health data science [ 45 ]. In 2018, European Union (EU) Member states launched Information for Action (InfAct), a joint initiative to improve the availability of health data and strengthen health information activities across Europe [ 46 ]. An InfAct study published in 2020 reported that data linkage is performed widely across EU countries for health status monitoring, policy development, and scientific research [ 47 ].…”

Section: Barriers To Data Access and Use And Implications For Waste I...mentioning

confidence: 99%

Challenges and opportunities for using population health data to investigate cancer survivors’ quality of life in Australia

et al. 2022

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There is a recognised need for reported national data that inform health policy, health professions, and consumers about the wellbeing of Australians with cancer and other chronic conditions. International initiatives have demonstrated the viability and benefits of utilising population-based cancer registries to monitor the prevalence and trajectory of health-related quality of life (HRQOL) outcomes among people with cancer. Establishing a similar level of monitoring in Australia would require timely access to health data collected by publicly funded, population-based cancer registries, and the capacity to link this information across jurisdictions. Combining information from different sources via data linkage is an efficient and cost-effective way to maximise how data are used to inform population health and policy development. However, linking health datasets has historically been highly restricted, resource-intensive, and costly in Australia due to complex and outdated legislative requirements, duplicative approval processes, and differing policy frameworks in each state and territory. This has resulted in significant research waste due to underutilisation of existing data, duplication of research efforts and resources, and data not being translated into decision-making. Recognising these challenges, from 2015 to 2017 the Productivity Commission investigated options for improving data availability and use in Australia, considering factors such as privacy, security, and intellectual property. The inquiry report recommended significant reforms for Australian legislation, including the creation of a data sharing and release structure to improve access to data for research and policy development purposes. This paper discusses (1) opportunities in HRQOL research enabled by data linkage, (2) barriers to data access and use in Australia and the implications for waste in HRQOL research, and (3) proposed legislative reforms for improving data availability and use in Australia.

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Learning from previous work and finding synergies in the domains of public and environmental health: EU-funded projects BRIDGE Health and HBM4EU

et al. 2020

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Background During the last decade, the European Union initiated several projects in the domains of public and environmental health. Within this framework, BRIDGE Health (Bridging Information and Data Generation for Evidence-based Health policy and Research) and HBM4EU (European human biomonitoring initiative) have been implemented. Whereas, the focus of BRIDGE Health was towards a sustainable and integrated health information system (HIS), the aim of HBM4EU is to improve evidence of the internal exposure of European citizens to environmental chemicals by human biomonitoring (HBM) and the impact of internal exposure on health. As both, environmental and public health determinants are important for health promotion, disease prevention and policy, BRIDGE Health and HBM4EU have overlapping aims and outcomes. In order to improve health information regarding public health and environmental health issues, best use and exchange of respective networks and project results is necessary. Methods Both projects have implemented health information (HI) and HBM tasks in order to provide adequate environmental and public health information of the European population. Synergies of the projects were identified in the working progress and because of overlapping networks and experts a focused analysis of both projects was envisaged. This paper elaborates on the aims and outcomes of both projects and the benefit of merging and channelling research results for the use of better health information and policy making that may be of relevance for any other project in these research fields. Results The need for focused exchanges and collaborations between the projects were identified and benefits of exchanges were highlighted for the specific areas of indicator development, linkage of data repositories and the combination of HBM studies and health examination surveys (HES). Further recommendations for a European wide harmonisation among different tasks in the fields of public health and environmental health are being developed. Conclusions Lessons learned from HBM4EU and BRIDGE Health show that continuous efforts must be undertaken, also by succeeding projects, to guarantee the exchange between public health and environmental health issues. Networks covering both are essential to provide better evidence of knowledge. The experiences from BRIDGE Health and HBM4EU give a valuable input for any future activity in these domains. Avoiding overlaps and streamlining further exchange of public health and environmental health contributes to best use of research results and allows to develop new strategies and tools for improvement of health information and thus enhances people’s health and well-being.

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The new Joint Action on Health Information: information for action (InfAct)!

Cited by 3 publications

References 0 publications

Federated causal inference based on real-world observational data sources: application to a SARS-CoV-2 vaccine effectiveness assessment

Federated causal inference based on real-world observational data sources: application to a SARS-CoV-2 vaccine effectiveness assessment

Challenges and opportunities for using population health data to investigate cancer survivors’ quality of life in Australia

Learning from previous work and finding synergies in the domains of public and environmental health: EU-funded projects BRIDGE Health and HBM4EU

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