Todd, OM orcid.org/0000-0001-7212-8095, Burton, JK, Dodds, RM et al. (11 more authors) (2020) New Horizons in the use of routine data for ageing research. Age and Ageing. ISSN 0002-0729
Abstract
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.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © The Author(s) 2020. Published by Oxford University Press on behalf of the British Geriatrics Society. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
Keywords: | Ageing, big data, data linkage, electronic health records, health informatics, older people |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) > Leeds Institute of Cardiovascular and Metabolic Medicine (LICAMM) > Clinical & Population Science Dept (Leeds) The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) > Leeds Institute of Health Sciences (Leeds) > Academic Unit of Elderly Care and Rehabilitation (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 17 Jan 2020 09:59 |
Last Modified: | 04 Mar 2020 16:57 |
Status: | Published online |
Publisher: | Oxford University Press |
Identification Number: | 10.1093/ageing/afaa018 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:155756 |