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Creating A Research Ready Data Asset and Empowering Dynamic and Efficient Research: The Sail Dementia E-Cohort (SDEC)

Authors :
Ashley Akbari
Laura North
Chris Orton
Simon Thompson
Christian Schnier
Tim Wilkinson
John Gallacher
Ronan Lyons
Source :
International Journal of Population Data Science, Vol 5, Iss 5 (2020)
Publication Year :
2020
Publisher :
Swansea University, 2020.

Abstract

Introduction Research can often be slow to start and require duplication of effort which in lots of cases has previously been completed to generate research-ready-data-assets (RRDA). Within the UK, two programmes: Dementias Platform UK (DPUK) that brings together over 50 different dementia-related cohorts and Secure Anonymised Information Linkage (SAIL) Databank, which provides access to longitudinal population-scale person-level data for every person in Wales have tried to tackle this challenge of creation, use and management of RRDA’s. Objectives and Approach Combining clinical, data and management expertise from DPUK and SAIL, we hoped to construct a RRDA that was easily accessible and well described for a dementia e-cohort. Welsh residents with available primary care records were included, with clinical and demographic information including follow-up times, several dementia indicators using validated diagnostic code lists, information on every dementia-related diagnostic event and several covariates and co-morbidities. SDeC was made available to researchers and can be modified according to appropriate study designs, with learning from projects used to update the SDeC to improve future uses. Interactive visualisations effectively summarise cohort characteristics, aiding researchers to quickly determine cohort eligibility for dementia studies. Results SDeC contains data from 4.6 million participants in SAIL, with 1.5 million meeting cohort inclusion criteria, resulting in 24.3 million person-years of follow-up. Of these, 146,323 (10%) developed all-cause dementia during follow-up, with 90,150 (60%) having dementia subtype codes. We made this resource available to researchers who had never used SAIL before, with limited experience of population-scale routine-data, and projects have proceeded with one managing to proceed from point of initial access to submission of publication in less than 6-months. Conclusion / Implications SDeC provides a reproducible dynamic method for completing dementia research, and expediting learning and understanding of the use of these data, with further developments and maintenance planned to increase the complexity and detail available to researchers over time.

Details

Language :
English
ISSN :
23994908
Volume :
5
Issue :
5
Database :
Directory of Open Access Journals
Journal :
International Journal of Population Data Science
Publication Type :
Academic Journal
Accession number :
edsdoj.9d4f8b81fcfd43ebac32913e7b513a7c
Document Type :
article
Full Text :
https://doi.org/10.23889/ijpds.v5i5.1518