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      Big data from electronic health records for early and late translational cardiovascular research: challenges and potential

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          Abstract

          Aims

          Cohorts of millions of people's health records, whole genome sequencing, imaging, sensor, societal and publicly available data present a rapidly expanding digital trace of health. We aimed to critically review, for the first time, the challenges and potential of big data across early and late stages of translational cardiovascular disease research.

          Methods and results

          We sought exemplars based on literature reviews and expertise across the BigData@Heart Consortium. We identified formidable challenges including: data quality, knowing what data exist, the legal and ethical framework for their use, data sharing, building and maintaining public trust, developing standards for defining disease, developing tools for scalable, replicable science and equipping the clinical and scientific work force with new inter-disciplinary skills. Opportunities claimed for big health record data include: richer profiles of health and disease from birth to death and from the molecular to the societal scale; accelerated understanding of disease causation and progression, discovery of new mechanisms and treatment-relevant disease sub-phenotypes, understanding health and diseases in whole populations and whole health systems and returning actionable feedback loops to improve (and potentially disrupt) existing models of research and care, with greater efficiency. In early translational research we identified exemplars including: discovery of fundamental biological processes e.g. linking exome sequences to lifelong electronic health records (EHR) (e.g. human knockout experiments); drug development: genomic approaches to drug target validation; precision medicine: e.g. DNA integrated into hospital EHR for pre-emptive pharmacogenomics. In late translational research we identified exemplars including: learning health systems with outcome trials integrated into clinical care; citizen driven health with 24/7 multi-parameter patient monitoring to improve outcomes and population-based linkages of multiple EHR sources for higher resolution clinical epidemiology and public health.

          Conclusion

          High volumes of inherently diverse (‘big’) EHR data are beginning to disrupt the nature of cardiovascular research and care. Such big data have the potential to improve our understanding of disease causation and classification relevant for early translation and to contribute actionable analytics to improve health and healthcare.

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          Most cited references144

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          UK Biobank: An Open Access Resource for Identifying the Causes of a Wide Range of Complex Diseases of Middle and Old Age

          Cathie Sudlow and colleagues describe the UK Biobank, a large population-based prospective study, established to allow investigation of the genetic and non-genetic determinants of the diseases of middle and old age.
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            Epidemiology of multimorbidity and implications for health care, research, and medical education: a cross-sectional study.

            Long-term disorders are the main challenge facing health-care systems worldwide, but health systems are largely configured for individual diseases rather than multimorbidity. We examined the distribution of multimorbidity, and of comorbidity of physical and mental health disorders, in relation to age and socioeconomic deprivation. In a cross-sectional study we extracted data on 40 morbidities from a database of 1,751,841 people registered with 314 medical practices in Scotland as of March, 2007. We analysed the data according to the number of morbidities, disorder type (physical or mental), sex, age, and socioeconomic status. We defined multimorbidity as the presence of two or more disorders. 42·2% (95% CI 42·1-42·3) of all patients had one or more morbidities, and 23·2% (23·08-23·21) were multimorbid. Although the prevalence of multimorbidity increased substantially with age and was present in most people aged 65 years and older, the absolute number of people with multimorbidity was higher in those younger than 65 years (210,500 vs 194,996). Onset of multimorbidity occurred 10-15 years earlier in people living in the most deprived areas compared with the most affluent, with socioeconomic deprivation particularly associated with multimorbidity that included mental health disorders (prevalence of both physical and mental health disorder 11·0%, 95% CI 10·9-11·2% in most deprived area vs 5·9%, 5·8%-6·0% in least deprived). The presence of a mental health disorder increased as the number of physical morbidities increased (adjusted odds ratio 6·74, 95% CI 6·59-6·90 for five or more disorders vs 1·95, 1·93-1·98 for one disorder), and was much greater in more deprived than in less deprived people (2·28, 2·21-2·32 vs 1·08, 1·05-1·11). Our findings challenge the single-disease framework by which most health care, medical research, and medical education is configured. A complementary strategy is needed, supporting generalist clinicians to provide personalised, comprehensive continuity of care, especially in socioeconomically deprived areas. Scottish Government Chief Scientist Office. Copyright © 2012 Elsevier Ltd. All rights reserved.
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              The REporting of studies Conducted using Observational Routinely-collected health Data (RECORD) Statement

              Routinely collected health data, obtained for administrative and clinical purposes without specific a priori research goals, are increasingly used for research. The rapid evolution and availability of these data have revealed issues not addressed by existing reporting guidelines, such as Strengthening the Reporting of Observational Studies in Epidemiology (STROBE). The REporting of studies Conducted using Observational Routinely collected health Data (RECORD) statement was created to fill these gaps. RECORD was created as an extension to the STROBE statement to address reporting items specific to observational studies using routinely collected health data. RECORD consists of a checklist of 13 items related to the title, abstract, introduction, methods, results, and discussion section of articles, and other information required for inclusion in such research reports. This document contains the checklist and explanatory and elaboration information to enhance the use of the checklist. Examples of good reporting for each RECORD checklist item are also included herein. This document, as well as the accompanying website and message board (http://www.record-statement.org), will enhance the implementation and understanding of RECORD. Through implementation of RECORD, authors, journals editors, and peer reviewers can encourage transparency of research reporting.
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                Author and article information

                Journal
                Eur Heart J
                Eur. Heart J
                eurheartj
                European Heart Journal
                Oxford University Press
                0195-668X
                1522-9645
                21 April 2018
                29 August 2017
                29 August 2017
                : 39
                : 16 , Focus Issue on Atrial Fibrillation
                : 1481-1495
                Affiliations
                [1 ]Research Department of Clinical Epidemiology, The Farr Institute of Health Informatics Research, University College London, 222 Euston Road, London NW1 2DA, UK
                [2 ]The National Institute for Health Research, Biomedical Research Centre, University College London Hospitals NHS Foundation Trust, University College London, 222 Euston Road, London NW1 2DA, UK
                [3 ]Department of Cardiology, University Medical Center Utrecht, Heidelberglaan 100, Utrecht 3584 CX, The Netherlands
                [4 ]MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Worts Causeway, Cambridge CB1 8RN, UK
                [5 ]NIHR Biomedical Research Centre for Mental Health (IOP), King‘s College London, De Crespigny Park, London SE5 8AF, UK
                [6 ]European Society of Cardiology (ESC), 2035 Route des Colles, Les Templiers - CS 80179 Biot, 06903 Sophia Antipolis, France
                [7 ]Vifor Pharma Ltd, lughofstrasse 61, 8152 Glattbrugg, Zurich, Switzerland
                [8 ]Department of Epidemiology, Bayer Pharma AG, Müllerstrasse 178, 13353 Berlin, Germany
                [9 ]Division of Cardiology and Metabolism—Heart Failure, Cachexia & Sarcopenia; Department of Cardiology (CVK), Berlin-Brandenburg Center for Regenerative Therapies (BCRT), Charité University Medicine, Charitépl. 1, 10117 Berlin, Germany
                [10 ]Department of Cardiology and Pneumology, University Medicine Göttingen (UMG), Robert-Koch-Strasse 40, 37099, Göttingen, Germany
                [11 ]Julius Centre for Health Sciences and Primary Care, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
                Author notes
                Corresponding author. Tel: +44 20 3549 5329, Fax: +44 20 7813 0242, E-mail: h.hemingway@ 123456ucl.ac.uk

                Details are listed at the end of acknowledgement section.

                Article
                ehx487
                10.1093/eurheartj/ehx487
                6019015
                29370377
                f099d0b6-e22c-45f8-8387-e62153cafc23
                © The Author 2017. Published by Oxford University Press on behalf of the European Society of Cardiology

                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.

                History
                : 01 June 2017
                : 19 July 2017
                : 8 August 2017
                Page count
                Pages: 19
                Funding
                Funded by: Medical Research Council 10.13039/501100000265
                Funded by: Arthritis Research UK 10.13039/501100000341
                Funded by: British Heart Foundation 10.13039/501100000274
                Funded by: Cancer Research UK 10.13039/501100000289
                Funded by: Chief Scientist Office 10.13039/501100000589
                Funded by: Economic and Social Research Council 10.13039/501100000269
                Funded by: Engineering and Physical Sciences Research Council 10.13039/501100000266
                Funded by: Wellcome Trust 10.13039/100004440
                Award ID: MR/K006584/1
                Categories
                Clinical Review
                Prevention and Epidemiology

                Cardiovascular Medicine
                electronic health records ,health informatics ,bio-informatics ,e-health,precision medicine,translational research

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