Using publicly available UK datasets to identify recruitment sites to maximise inclusion of under-served groups: three case studies [version 1; peer review: 2 approved]

Autor: Alison Booth, Ashley Scrimshire, Catriona McDaid, Arabella Scantlebury, Harvinder pal Singh, Catherine Hewitt
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: NIHR Open Research, Vol 4 (2024)
Druh dokumentu: article
ISSN: 2633-4402
DOI: 10.3310/nihropenres.13551.1
Popis: Background There is strong evidence that those recruited into studies are not always representative of the population for whom the research is most relevant. Development of the study design and funding decisions are points in the research process where considerations about inclusion of under-served populations may usefully be made. Current practical guidance focuses on designing and modifying participant recruitment and retention approaches but an area that has not been addressed is recruitment site selection. Methods We present case studies of three NIHR funded trials to demonstrate how publicly available UK population datasets can be used to facilitate the identification of under-served communities for inclusion in trials. The trials have different designs, address different needs and demonstrate recruitment planning across Trauma centres, NHS Trusts and special educational settings. We describe our use of national freely available datasets, such as those provided by NHS Digital and the Office for National Statistics, to identify potential recruitment sites with consideration of health status, socio-economic status and ethnicity as well as clinical and risk factors to support inclusivity. For all three studies, we produced lists of potential recruitment sites in excess of the number anticipated as necessary to meet the recruitment targets. Discussion We reflect on the challenges to our approach and some potential future developments. The datasets used are all free to use but each has their limitations. Agreeing search parameters, acceptable proxies and identifying the appropriate datasets, then cross referencing between datasets takes considerable time and particular expertise. The case studies are trials, but the methods are generalisable for various other study types. Conclusion Through these exemplars, we aim to build on the NIHR INCLUDE project, by providing trialists with a much needed practical approach to embedding EDI into trial design at the grant application stage.
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