A national initiative in data science for health: an evaluation of the UK Farr Institute.


Journal

International journal of population data science
ISSN: 2399-4908
Titre abrégé: Int J Popul Data Sci
Pays: Wales
ID NLM: 101737740

Informations de publication

Date de publication:
08 Apr 2020
Historique:
entrez: 16 9 2020
pubmed: 17 9 2020
medline: 17 9 2020
Statut: epublish

Résumé

To evaluate the extent to which the inter-institutional, inter-disciplinary mobilisation of data and skills in the Farr Institute contributed to establishing the emerging field of data science for health in the UK. We evaluated evidence of six domains characterising a new field of science:defining central scientific challenges,demonstrating how the central challenges might be solved,creating novel interactions among groups of scientists,training new types of experts,re-organising universities,demonstrating impacts in society.We carried out citation, network and time trend analyses of publications, and a narrative review of infrastructure, methods and tools. Four UK centres in London, North England, Scotland and Wales (23 university partners), 2013-2018. 1. The Farr Institute helped define a central scientific challenge publishing a research corpus, demonstrating insights from electronic health record (EHR) and administrative data at each stage of the translational cycle in 593 papers with at least one Farr Institute author affiliation on PubMed. 2. The Farr Institute offered some demonstrations of how these scientific challenges might be solved: it established the first four ISO27001 certified trusted research environments in the UK, and approved more than 1000 research users, published on 102 unique EHR and administrative data sources, although there was no clear evidence of an increase in novel, sustained record linkages. The Farr Institute established open platforms for the EHR phenotyping algorithms and validations (>70 diseases, CALIBER). Sample sizes showed some evidence of increase but remained less than 10% of the UK population in primary care-hospital care linked studies. 3.The Farr Institute created novel interactions among researchers: the co-author publication network expanded from 944 unique co-authors (based on 67 publications in the first 30 months) to 3839 unique co-authors (545 papers in the final 30 months). 4. Training expanded substantially with 3 new masters courses, training >400 people at masters, short-course and leadership level and 48 PhD students. 5. Universities reorganised with 4/5 Centres established 27 new faculty (tenured) positions, 3 new university institutes. 6. Emerging evidence of impacts included: > 3200 citations for the 10 most cited papers and Farr research informed eight practice-changing clinical guidelines and policies relevant to the health of millions of UK citizens. The Farr Institute played a major role in establishing and growing the field of data science for health in the UK, with some initial evidence of benefits for health and healthcare. The Farr Institute has now expanded into Health Data Research (HDR) UK but key challenges remain including, how to network such activities internationally.

Identifiants

pubmed: 32935051
doi: 10.23889/ijpds.v5i1.1128
pii: 5:1:20
pmc: PMC7480324
doi:

Types de publication

Journal Article

Langues

eng

Pagination

1128

Subventions

Organisme : Medical Research Council
ID : MR/S004041/1
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/K006665/1
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/K006584/1
Pays : United Kingdom
Organisme : Medical Research Council
ID : MC_PC_13042
Pays : United Kingdom
Organisme : Department of Health
ID : RP-PG-0407-10314
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/K006525/1
Pays : United Kingdom
Organisme : Wellcome Trust
Pays : United Kingdom
Organisme : Department of Health
ID : 05/40/04
Pays : United Kingdom
Organisme : Medical Research Council
ID : MC_PC_13041
Pays : United Kingdom

Déclaration de conflit d'intérêts

Conflict of interest statement: The authors report no conflicts of interest.

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Auteurs

H Hemingway (H)

HDR UK London.
UCL Institute of Health Informatics, 222 Euston Road, London NW1 2DA.

R Lyons (R)

HDRUK Wales/Northern Ireland.
Swansea University Medical School, Fourth Floor, Data Science Building, Singleton Campus, Swansea, SA2 8PP.

Q Li (Q)

West China Hospital, Chengdu, China.
UCL Institute of Health Informatics, 222 Euston Road, London NW1 2DA.

I Buchan (I)

University of Liverpool, Liverpool L69 3BX.

J Ainsworth (J)

Division of Informatics, Imaging & Data Sciences, The University of Manchester, Oxford Rd, Manchester M13 9PL.

J Pell (J)

Institute of Health and Wellbeing, University of Glasgow, 1 Lilybank Gardens, Glasgow G12 8RZ.

A Morris (A)

University of Edinburgh.
HDR UK.

Classifications MeSH