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dc.contributor.authorFagbamigbe, Adeniyi Francis
dc.contributor.authorAgrawal, Utkarsh
dc.contributor.authorAzcoaga-Lorenzo, Amaya
dc.contributor.authorMacKerron, Briana
dc.contributor.authorÖzyiğit, Eda Bilici
dc.contributor.authorAlexander, Daniel C.
dc.contributor.authorAkbari, Ashley
dc.contributor.authorOwen, Rhiannon K.
dc.contributor.authorLyons, Jane
dc.contributor.authorLyons, Ronan A.
dc.contributor.authorDenaxas, Spiros
dc.contributor.authorKirk, Paul
dc.contributor.authorMiller, Ana Corina
dc.contributor.authorHarper, Gill
dc.contributor.authorDezateux, Carol
dc.contributor.authorBrookes, Anthony
dc.contributor.authorRichardson, Sylvia
dc.contributor.authorNirantharakumar, Krishnarajah
dc.contributor.authorGuthrie, Bruce
dc.contributor.authorHughes, Lloyd
dc.contributor.authorKadam, Umesh T.
dc.contributor.authorKhunti, Kamlesh
dc.contributor.authorAbrams, Keith R.
dc.contributor.authorMcCowan, Colin
dc.identifier.citationFagbamigbe , A F , Agrawal , U , Azcoaga-Lorenzo , A , MacKerron , B , Özyiğit , E B , Alexander , D C , Akbari , A , Owen , R K , Lyons , J , Lyons , R A , Denaxas , S , Kirk , P , Miller , A C , Harper , G , Dezateux , C , Brookes , A , Richardson , S , Nirantharakumar , K , Guthrie , B , Hughes , L , Kadam , U T , Khunti , K , Abrams , K R & McCowan , C 2023 , ' Clustering long-term health conditions among 67728 people with multimorbidity using electronic health records in Scotland ' , PLoS ONE , vol. 18 , no. 11 , e0294666 .
dc.identifier.otherRIS: urn:F396EDC6D4F375277CB7C35E679D2D4D
dc.identifier.otherORCID: /0000-0002-9466-833X/work/147966765
dc.identifier.otherORCID: /0000-0003-3307-878X/work/147967359
dc.descriptionFunding: CMC: This work was supported by Health Data Research UK (HDR UK) Measuring and Understanding Multimorbidity using Routine Data in the UK (HDR-9006; CFC0110). Health Data Research UK (HDR-9006) is funded by: UK Medical Research Council, Engineering and Physical Sciences Research Council, Economic and Social Research Council, the 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.abstractThere is still limited understanding of how chronic conditions co-occur in patients with multimorbidity and what are the consequences for patients and the health care system. Most reported clusters of conditions have not considered the demographic characteristics of these patients during the clustering process. The study used data for all registered patients that were resident in Fife or Tayside, Scotland and aged 25 years or more on 1st January 2000 and who were followed up until 31st December 2018. We used linked demographic information, and secondary care electronic health records from 1st January 2000. Individuals with at least two of the 31 Elixhauser Comorbidity Index conditions were identified as having multimorbidity. Market basket analysis was used to cluster the conditions for the whole population and then repeatedly stratified by age, sex and deprivation. 318,235 individuals were included in the analysis, with 67,728 (21·3%) having multimorbidity. We identified five distinct clusters of conditions in the population with multimorbidity: alcohol misuse, cancer, obesity, renal failure, and heart failure. Clusters of long-term conditions differed by age, sex and socioeconomic deprivation, with some clusters not present for specific strata and others including additional conditions. These findings highlight the importance of considering demographic factors during both clustering analysis and intervention planning for individuals with multiple long-term conditions. By taking these factors into account, the healthcare system may be better equipped to develop tailored interventions that address the needs of complex patients.
dc.relation.ispartofPLoS ONEen
dc.subjectZA4050 Electronic information resourcesen
dc.subjectSDG 3 - Good Health and Well-beingen
dc.titleClustering long-term health conditions among 67728 people with multimorbidity using electronic health records in Scotlanden
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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