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dc.contributor.authorLyons, Jane
dc.contributor.authorAkbari, Ashley
dc.contributor.authorAgrawal, Utkarsh
dc.contributor.authorHarper, Gill
dc.contributor.authorAzcoaga-Lorenzo, Amaya
dc.contributor.authorBailey, Rowena
dc.contributor.authorRafferty, James
dc.contributor.authorWatkins, Alan
dc.contributor.authorFry, Richard
dc.contributor.authorMcCowan, Colin
dc.contributor.authorDezateux, Carol
dc.contributor.authorRobson, John P
dc.contributor.authorPeek, Niels
dc.contributor.authorHolmes, Chris
dc.contributor.authorDenaxas, Spiros
dc.contributor.authorOwen, Rhiannon
dc.contributor.authorAbrams, Keith R
dc.contributor.authorJohn, Ann
dc.contributor.authorO'Reilly, Dermot
dc.contributor.authorRichardson, Sylvia
dc.contributor.authorHall, Marlous
dc.contributor.authorGale, Chris P
dc.contributor.authorDavies, Jan
dc.contributor.authorDavies, Chris
dc.contributor.authorCross, Lynsey
dc.contributor.authorGallacher, John
dc.contributor.authorChess, James
dc.contributor.authorBrookes, Anthony J
dc.contributor.authorLyons, Ronan A
dc.identifier.citationLyons , J , Akbari , A , Agrawal , U , Harper , G , Azcoaga-Lorenzo , A , Bailey , R , Rafferty , J , Watkins , A , Fry , R , McCowan , C , Dezateux , C , Robson , J P , Peek , N , Holmes , C , Denaxas , S , Owen , R , Abrams , K R , John , A , O'Reilly , D , Richardson , S , Hall , M , Gale , C P , Davies , J , Davies , C , Cross , L , Gallacher , J , Chess , J , Brookes , A J & Lyons , R A 2021 , ' Protocol for the development of the Wales multimorbidity e-Cohort (WMC) : data sources and methods to construct a population-based research platform to investigate multi-morbidity ' , BMJ Open , vol. 11 , no. 1 , e047101 .
dc.identifier.otherRIS: urn:1873E51A445BCD2A26709B66FADD8C42
dc.identifier.otherRIS: urn:1873E51A445BCD2A26709B66FADD8C42
dc.identifier.otherORCID: /0000-0002-9466-833X/work/90112642
dc.identifier.otherORCID: /0000-0003-3307-878X/work/90112719
dc.descriptionThis work was supported by Health Data Research UK (HDR-9006; CFC0110) and the Medical Research Council (MR/S027750/1). Health Data Research UK is funded by: UK Medical Research Council; Engineering and Physical Sciences Research Council; Economic and Social Research Council; National Institute for Health Research (England); Chief Scientist Office of the Scottish Government Health and Social Care Directorates; Health and Social Care Research and Development Division (Welsh Government); Public Health Agency (Northern Ireland); British Heart Foundation and Wellcome Trust.en
dc.description.abstractIntroduction  Multimorbidity is widely recognised as the presence of two or more concurrent long-term conditions, yet remains a poorly understood global issue despite increasing in prevalence. We have created the Wales Multimorbidity e-Cohort (WMC) to provide an accessible research ready data asset to further the understanding of multimorbidity. Our objectives are to create a platform to support research which would help to understand prevalence, trajectories and determinants in multimorbidity, characterise clusters that lead to highest burden on individuals and healthcare services, and evaluate and provide new multimorbidity phenotypes and algorithms to the National Health Service and research communities to support prevention, healthcare planning and the management of individuals with multimorbidity. Methods and analysis  The WMC has been created and derived from multisourced demographic, administrative and electronic health record data relating to the Welsh population in the Secure Anonymised Information Linkage (SAIL) Databank. The WMC consists of 2.9 million people alive and living in Wales on the 1 January 2000 with follow-up until 31 December 2019, Welsh residency break or death. Published comorbidity indices and phenotype code lists will be used to measure and conceptualise multimorbidity. Study outcomes will include: (1) a description of multimorbidity using published data phenotype algorithms/ontologies, (2) investigation of the associations between baseline demographic factors and multimorbidity, (3) identification of temporal trajectories of clusters of conditions and multimorbidity and (4) investigation of multimorbidity clusters with poor outcomes such as mortality and high healthcare service utilisation. Ethics and dissemination  The SAIL Databank independent Information Governance Review Panel has approved this study (SAIL Project: 0911). Study findings will be presented to policy groups, public meetings, national and international conferences, and published in peer-reviewed journals.
dc.relation.ispartofBMJ Openen
dc.subjectRA0421 Public health. Hygiene. Preventive Medicineen
dc.subjectZA4050 Electronic information resourcesen
dc.subjectSDG 3 - Good Health and Well-beingen
dc.titleProtocol for the development of the Wales multimorbidity e-Cohort (WMC) : data sources and methods to construct a population-based research platform to investigate multi-morbidityen
dc.typeJournal articleen
dc.contributor.institutionUniversity of St Andrews. School of Medicineen
dc.contributor.institutionUniversity of St Andrews. Sir James Mackenzie Institute for Early Diagnosisen
dc.contributor.institutionUniversity of St Andrews. Population and Behavioural Science Divisionen
dc.description.statusPeer revieweden

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