The EHDEN Academy, in collaboration with our guest lecturers, Kees van Bochove and Jolanda Strubel, The Hyve are pleased to announce the launch of our next course: Open Science & FAIR Principles. The Academy is free, used in more than 60 countries, and only requires a participant to set up an account and log in.
This course explains the initiatives and principles developed to improve the (re) use of medical data and advance medical evidence generation. Beyond this, it also demonstrates how dataset levels can be increased by participating in the EHDEN project. It also gives an example of how to put Open Science into practice by organising a study-a-thon.
"This course is the perfect starting point to gain a deeper understanding of what each and everyone of us can do to support open science. From the high level, conceptual helicopter view to the nitty gritty details of implementation of the FAIR guidelines. Our guest lecturers walk you through the theoretical background as explained in core, high-impact publications and illustrate value and impact through practical examples of how the OMOP CDM and the OHDSI ecosystem are leveraged today to generate real world reproducible evidence and to facilitate open science," said Julia Kurps, Team Lead - Real World Data at The Hyve, Co-Lead Technical Work Package, EHDEN
In this first section, Open Science and the FAIR Principles are explored, and how these are used in EHDEN and OHDSI. It initially outlines the concept of Open Science, and then the principles of Findable, Accessible, Interoperable and Reusable (FAIR) data principles in more detail down to their attribute level, before covering a large international OHDSI study, LEGEND, (Large-scale Evidence Generation and Evaluation across a Network of Databases) as an example of Open Science in EHDEN and OHDSI. In this large, systematic, multinational analysis of comparative effectiveness and safety of first-line antihypertensive study by Suchard, et al1, ten LEGEND principles were established and are discussed further.
Following on from this, the next section discusses how to increase the FAIR level of datasets. It provides guidance on how transforming data to the OMOP common data model improves data FAIR-ness (interoperability and reusability), and what limitations there are in transforming data to the OMOP CDM on making data more FAIR. Utilising the FAIR attributes and principles, it illustrates the advantages the OMOP CDM provides in specific aspects of, for instance, attributing metadata to your data.
In the second part of this section, the EHDEN Data Partner Catalogue and its use of metadata, as well as some current limitations in this approach are described. Again, using the FAIR attributes and principles, the utilisation of the EHDEN Catalogue to enhance findability and accessibility are expanded upon. Incidentally, the EHDEN Data Partner Catalogue, via the EHDEN Portal, will be made available for free to the research community on Friday 24th June 2022.
The final section discusses the use of the study-a-thon approach, focusing on the OHDSI/EHDEN COVID-19 study-a-thon in March 2020. The study-a-thon concept is explained, and the tools, skills, methods and international network of datasets described further, in particular the role of characterisation, effect estimation and prediction studies in addressing rapid network analysis of the COVID-19 pandemic at that time, from patient phenotyping, to treatment outcomes and safety, through to prediction modelling for clinical and public health decision-making. The COVID-19 study-a-thon is one more example of international open science in action, reliant on FAIR datasets and open, transparent methodology to generate reliable evidence.
“Open science is at the fundamental core of EHDEN and OHDSI, focusing on transparent, high quality evidence generation that is reproducible and based on collaboration and methods that support large scale network studies. Underpinning this all is ensuring datasets interacted with are FAIR, and this course is a great introduction into these basic concepts, providing colleagues with a deeper understanding of how they can be applied in rapid network studies, and study-a-thons,” said Nigel Hughes, Scientific Director, Epidemiology, Global R&D, Janssen (Co-Lead EHDEN).
We hope many more of you will also find this course beneficial and will add this to your existing portfolio of EHDEN Academy courses, or if new, add more to this one. You can enrol on the Academy via this link.
Please keep an eye out for new courses we will be adding throughout this year:
Marc A Suchard, Martijn J Schuemie, et al, Comprehensive comparative effectiveness and safety of first-line antihypertensive drug classes: a systematic, multinational, large-scale analysis, The Lancet, Volume 394, Issue 10211, 2019, 1816-1826, https://doi.org/10.1016/S0140-6736(19)32317-7