Overview of retrospective data harmonisation in the MINDMAP project: process and results

Life course of retrospective harmonization initiatives: key elements to consider

Optimizing research on the developmental origins of health and disease (DOHaD) involves implementing initiatives maximizing the use of the available cohort study data; achieving sufficient statistical power to support subgroup analysis; and using participant data presenting adequate follow-up and exposure heterogeneity. It also involves being able to undertake comparison, cross-validation, or replication across data sets. To answer these requirements, cohort study data need to be findable, accessible, interoperable, and reusable (FAIR), and more particularly, it often needs to be harmonized. Harmonization is required to achieve or improve comparability of the putatively equivalent measures collected by different studies on different individuals. Although the characteristics of the research initiatives generating and using harmonized data vary extensively, all are confronted by similar issues. Having to collate, understand, process, host, and co-analyze data from individual cohort studies is particularly challenging. The scientific success and timely management of projects can be facilitated by an ensemble of factors. The current document provides an overview of the 'life course' of research projects requiring harmonization of existing data and highlights key elements to be considered from the inception to the end of the project.

Harmonising electronic health records for reproducible research: challenges, solutions and recommendations from a UK-wide COVID-19 research collaboration

BACKGROUND

The CVD-COVID-UK consortium was formed to understand the relationship between COVID-19 and cardiovascular diseases through analyses of harmonised electronic health records (EHRs) across the four UK nations. Beyond COVID-19, data harmonisation and common approaches enable analysis within and across independent Trusted Research Environments. Here we describe the reproducible harmonisation method developed using large-scale EHRs in Wales to accommodate the fast and efficient implementation of cross-nation analysis in England and Wales as part of the CVD-COVID-UK programme. We characterise current challenges and share lessons learnt.

METHODS

Serving the scope and scalability of multiple study protocols, we used linked, anonymised individual-level EHR, demographic and administrative data held within the SAIL Databank for the population of Wales. The harmonisation method was implemented as a four-layer reproducible process, starting from raw data in the first layer. Then each of the layers two to four is framed by, but not limited to, the characterised challenges and lessons learnt. We achieved curated data as part of our second layer, followed by extracting phenotyped data in the third layer. We captured any project-specific requirements in the fourth layer.

RESULTS

Using the implemented four-layer harmonisation method, we retrieved approximately 100 health-related variables for the 3.2 million individuals in Wales, which are harmonised with corresponding variables for > 56 million individuals in England. We processed 13 data sources into the first layer of our harmonisation method: five of these are updated daily or weekly, and the rest at various frequencies providing sufficient data flow updates for frequent capturing of up-to-date demographic, administrative and clinical information.

CONCLUSIONS

We implemented an efficient, transparent, scalable, and reproducible harmonisation method that enables multi-nation collaborative research. With a current focus on COVID-19 and its relationship with cardiovascular outcomes, the harmonised data has supported a wide range of research activities across the UK.

Neighbourhood walkability in relation to cognitive functioning in patients with disorders along the heart-brain axis

This study examined associations of neighbourhood walkability with cognitive functioning (i.e., global cognition, memory, language, attention-psychomotor speed, and executive functioning) in participants without or with either heart failure, carotid occlusive disease, or vascular cognitive impairment. Neighbourhood walkability at baseline was positively associated with global cognition and attention-psychomotor speed. These associations were stronger in patients with vascular cognitive impairment. Individuals who live in residential areas with higher walkability levels were less likely to have impairments in language and executive functioning at two-year follow-up. These findings highlight the importance of the built environment for cognitive functioning in healthy and vulnerable groups.

HUNT for better public health

Aims:

The Trøndelag Health Study (HUNT) has collected population data through comprehensive decennial surveys over the last four decades and has so far collected data from 240,000 participants. The participants are identified with the unique Norwegian birth number, which enables them to be followed throughout different life stages, from survey to survey, and to endpoint measures in Norwegian national health registers without attrition bias.

Methods:

The study design of HUNT offers several advantages: it provides an overview of the public health development in the population over decades, the data can be used in health services research, clinical epidemiology, studies of causation, trajectories, and consequences of diseases, and to study gene × environment interactions.

Results:

HUNT data have shown major shifts in public health trends, such as decreasing mean blood pressure and resting heart rate among adults, increasing prevalence of obesity, geographical and socioeconomic inequalities in health, increasing mental health distress among adolescents and young adults with an opposite development among the elderly. Data from HUNT have been used in several major international research projects, where data harmonization with several other population cohorts internationally has been done. HUNT has placed great emphasis on safeguarding research ethics, privacy, and data security. The Norwegian authorities established national regulations for the surveys from the time General Data Protection Regulation was introduced in 2018.

Conclusions:

Researchers can apply for HUNT data access from HUNT Research Centre provided they have obtained project approval from the Regional Committee for Medical and Health Research Ethics. Researchers not affiliated to a Norwegian research institution must collaborate with and apply through a Norwegian principal investigator. Information on the application and conditions for data access is available at www.ntnu.edu/hunt/data.

Position paper on management of personal data in environment and health research in Europe

Management of datasets that include health information and other sensitive personal information of European study participants has to be compliant with the General Data Protection Regulation (GDPR, Regulation (EU) 2016/679). Within scientific research, the widely subscribed'FAIR' data principles should apply, meaning that research data should be findable, accessible, interoperable and re-usable. Balancing the aim of open science driven FAIR data management with GDPR compliant personal data protection safeguards is now a common challenge for many research projects dealing with (sensitive) personal data. In December 2020 a workshop was held with representatives of several large EU research consortia and of the European Commission to reflect on how to apply the FAIR data principles for environment and health research (E&H). Several recent data intensive EU funded E&H research projects face this challenge and work intensively towards developing solutions to access, exchange, store, handle, share, process and use such sensitive personal data, with the aim to support European and transnational collaborations. As a result, several recommendations, opportunities and current limitations were formulated. New technical developments such as federated data management and analysis systems, machine learning together with advanced search software, harmonized ontologies and data quality standards should in principle facilitate the FAIRification of data. To address ethical, legal, political and financial obstacles to the wider re-use of data for research purposes, both specific expertise and underpinning infrastructure are needed. There is a need for the E&H research data to find their place in the European Open Science Cloud. Communities using health and population data, environmental data and other publicly available data have to interconnect and synergize. To maximize the use and re-use of environment and health data, a dedicated supporting European infrastructure effort, such as the EIRENE research infrastructure within the ESFRI roadmap 2021, is needed that would interact with existing infrastructures.