Journal Article

Protocol for the development of the Wales Multimorbidity e-Cohort (WMC): data sources and methods to construct a population-based research platform to investigate multimorbidity

McCowan, Colin, Dezateux, Carol, Gallacher, John, Davies, Jan, Akbari, Ashley, Rafferty, James, Gale, Chris P, Azcoaga-Lorenzo, Amaya, Lyons, Ronan A, Lyons, Jane, Richardson, Sylvia, Davies, Chris, Peek, Niels, Abrams, Keith R, Harper, Gill, John, Ann, Chess, James, Brookes, Anthony J, Cross, Lynsey, Fry, Richard, Bailey, Rowena, O"Reilly, Dermot, Owen, Rhiannon, Denaxas, Spiros, Watkins, Alan, Robson, John P, Hall, Marlous, Holmes, Chris, Agrawal, Utkarsh

2021

Overview

IntroductionMultimorbidity 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 analysisThe 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 disseminationThe 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.

• Publisher: British Medical Journal Publishing Group,BMJ Publishing Group LTD,BMJ Publishing Group
• Subject: Age groups / Cohort Studies / Comorbidity / Datasets / Demography / Design / Disease / Epidemiologic Studies / Epidemiology / Female / geriatric medicine / Health care policy / health policy / Health services utilization / Humans / Information Storage and Retrieval / Machine learning / Male / Mortality / Multimorbidity / Older people / Population / Population-based studies / Primary care / Privacy / public health / State Medicine / Wales - epidemiology