New Horizons in the use of routine data for ageing research.

ageing big data data linkage electronic health records health informatics older people

Journal

Age and ageing
ISSN: 1468-2834
Titre abrégé: Age Ageing
Pays: England
ID NLM: 0375655

Informations de publication

Date de publication:
24 08 2020
Historique:
received: 29 10 2019
revised: 02 12 2019
accepted: 16 01 2020
pubmed: 12 2 2020
medline: 29 7 2021
entrez: 12 2 2020
Statut: ppublish

Résumé

The past three decades have seen a steady increase in the availability of routinely collected health and social care data and the processing power to analyse it. These developments represent a major opportunity for ageing research, especially with the integration of different datasets across traditional boundaries of health and social care, for prognostic research and novel evaluations of interventions with representative populations of older people. However, there are considerable challenges in using routine data at the level of coding, data analysis and in the application of findings to everyday care. New Horizons in applying routine data to investigate novel questions in ageing research require a collaborative approach between clinicians, data scientists, biostatisticians, epidemiologists and trial methodologists. This requires building capacity for the next generation of research leaders in this important area. There is a need to develop consensus code lists and standardised, validated algorithms for common conditions and outcomes that are relevant for older people to maximise the potential of routine data research in this group. Lastly, we must help drive the application of routine data to improve the care of older people, through the development of novel methods for evaluation of interventions using routine data infrastructure. We believe that harnessing routine data can help address knowledge gaps for older people living with multiple conditions and frailty, and design interventions and pathways of care to address the complex health issues we face in caring for older people.

Identifiants

pubmed: 32043136
pii: 5733068
doi: 10.1093/ageing/afaa018
pmc: PMC7444666
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

716-722

Subventions

Organisme : The Dunhill Medical Trust
ID : RTF107/0117
Pays : United Kingdom
Organisme : Wellcome Trust
ID : 206,470/Z/17/Z
Pays : United Kingdom

Informations de copyright

© The Author(s) 2020. Published by Oxford University Press on behalf of the British Geriatrics Society.

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Auteurs

Oliver M Todd (OM)

Academic Unit of Elderly Care and Rehabilitation, Bradford Teaching Hospitals NHS Trust, University of Leeds, Bradford, UK.
Leeds Institute for Data Analytics, University of Leeds, Leeds, UK.

Jennifer K Burton (JK)

Academic Section of Geriatric Medicine, Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow G4 OSF, UK.

Richard M Dodds (RM)

AGE Research Group, Translational and Clinical Research Institute, Newcastle University, Newcastle, UK.

Joe Hollinghurst (J)

Health Data Research UK (HDR-UK), Swansea University, Swansea, UK.

Ronan A Lyons (RA)

Health Data Research UK (HDR-UK), Swansea University, Swansea, UK.

Terence J Quinn (TJ)

Academic Section of Geriatric Medicine, Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow G4 OSF, UK.

Anna Schneider (A)

School of Health & Social Care, Scottish Centre for Administrative Data Research, Edinburgh Napier University, Edinburgh, UK.

Katherine E Walesby (KE)

Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh EH8 9JZ, UK.

Chris Wilkinson (C)

Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK.
Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne, UK.

Simon Conroy (S)

Department of Health Sciences, University of Leicester, Leicester, UK.

Chris P Gale (CP)

Leeds Institute for Data Analytics, University of Leeds, Leeds, UK.
Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK.

Marlous Hall (M)

Leeds Institute for Data Analytics, University of Leeds, Leeds, UK.
Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK.

Kate Walters (K)

Centre for Ageing Population Studies, Department of Primary Care & Population Health, Institute of Epidemiology & Health Care, University College, London, UK.

Andrew P Clegg (AP)

Academic Unit of Elderly Care and Rehabilitation, Bradford Teaching Hospitals NHS Trust, University of Leeds, Bradford, UK.

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Classifications MeSH