The National ReferAll Database: An Open Dataset of Exercise Referral Schemes Across the UK

STEELE, James, WADE, Matthew, COPELAND, Robert J., STOKES, Stuart, STOKES, Rachel and MANN, Steven (2021). The National ReferAll Database: An Open Dataset of Exercise Referral Schemes Across the UK. International Journal of Environmental Research and Public Health, 18 (9).

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Open Access URL: https://www.mdpi.com/1660-4601/18/9/4831 (Published version)
Link to published version:: https://doi.org/10.3390/ijerph18094831

Abstract

In 2014, The National Institute for Health and Care Excellence (NICE) called for the development of a system to collate local data on exercise referral schemes (ERS). This database would be used to facilitate continued evaluation of ERS. The use of health databases can spur scientific investigation and the generation of evidence regarding healthcare practice. NICE’s recommendation has not yet been met by public health bodies. Through collaboration between ukactive, ReferAll, a specialist in software solutions for exercise referral, and the National Centre for Sport and Exercise Medicine, which has its research hub at the Advanced Wellbeing Research Centre, in Sheffield, data has been collated from multiple UK-based ERS to generate one of the largest databases of its kind. This database moves the research community towards meeting NICEs recommendation. This paper describes the formation and open sharing of The National ReferAll Database, data-cleaning processes, and its structure, including outcome measures. Collating data from 123 ERSs on 39,283 individuals, a database has been created containing both scheme and referral level characteristics in addition to outcome measures over time. The National ReferAll Database is openly available for researchers to interrogate. The National ReferAll Database represents a potentially valuable resource for the wider research community, as well as policy makers and practitioners in this area, which will facilitate a better understanding of ERS and other physical-activity-related social prescribing pathways to help inform public health policy and practice.

Item Type: Article
Additional Information: ** From MDPI via Jisc Publications Router ** Licence for this article: https://creativecommons.org/licenses/by/4.0/ **Journal IDs: eissn 1660-4601 **History: published 30-04-2021; accepted 27-04-2021
Uncontrolled Keywords: health database, exercise referral, physical activity, big data
Identification Number: https://doi.org/10.3390/ijerph18094831
SWORD Depositor: Colin Knott
Depositing User: Colin Knott
Date Deposited: 05 May 2021 15:32
Last Modified: 05 May 2021 15:32
URI: https://shura.shu.ac.uk/id/eprint/28598

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