Linked electronic health records for research on a nationwide cohort of more than 54 million people in England: data resource

CVD-COVID-UK consortium, Angela Wood, Rachel Denholm, Sam Hollings, Jennifer Cooper, Samantha Ip, Venexia Walker, Spiros Denaxas, Ashley Akbari, Amitava Banerjee, William Whiteley, Alvina Lai, Jonathan Sterne, Cathie Sudlow

Research output: Contribution to journalArticle (Academic Journal)peer-review

4 Citations (Scopus)
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Abstract

OBJECTIVE: To describe a novel England-wide electronic health record (EHR) resource enabling whole population research on covid-19 and cardiovascular disease while ensuring data security and privacy and maintaining public trust.

DESIGN: Data resource comprising linked person level records from national healthcare settings for the English population, accessible within NHS Digital's new trusted research environment.

SETTING: EHRs from primary care, hospital episodes, death registry, covid-19 laboratory test results, and community dispensing data, with further enrichment planned from specialist intensive care, cardiovascular, and covid-19 vaccination data.

PARTICIPANTS: 54.4 million people alive on 1 January 2020 and registered with an NHS general practitioner in England.

MAIN MEASURES OF INTEREST: Confirmed and suspected covid-19 diagnoses, exemplar cardiovascular conditions (incident stroke or transient ischaemic attack and incident myocardial infarction) and all cause mortality between 1 January and 31 October 2020.

RESULTS: The linked cohort includes more than 96% of the English population. By combining person level data across national healthcare settings, data on age, sex, and ethnicity are complete for around 95% of the population. Among 53.3 million people with no previous diagnosis of stroke or transient ischaemic attack, 98 721 had a first ever incident stroke or transient ischaemic attack between 1 January and 31 October 2020, of which 30% were recorded only in primary care and 4% only in death registry records. Among 53.2 million people with no previous diagnosis of myocardial infarction, 62 966 had an incident myocardial infarction during follow-up, of which 8% were recorded only in primary care and 12% only in death registry records. A total of 959 470 people had a confirmed or suspected covid-19 diagnosis (714 162 in primary care data, 126 349 in hospital admission records, 776 503 in covid-19 laboratory test data, and 50 504 in death registry records). Although 58% of these were recorded in both primary care and covid-19 laboratory test data, 15% and 18%, respectively, were recorded in only one.

CONCLUSIONS: This population-wide resource shows the importance of linking person level data across health settings to maximise completeness of key characteristics and to ascertain cardiovascular events and covid-19 diagnoses. Although this resource was initially established to support research on covid-19 and cardiovascular disease to benefit clinical care and public health and to inform healthcare policy, it can broaden further to enable a wide range of research.

Original languageEnglish
Article numbern826
Pages (from-to)n826
JournalBMJ (Clinical Research ed.)
Volume373
DOIs
Publication statusPublished - 7 Apr 2021

Bibliographical note

Funding Information:
funded co-development (with NHS Digital) of the trusted research environment, provision of linked datasets, data access, user software licences, computational usage, and data management and wrangling support, with additional contributions from the HDR UK data and connectivity component of the UK governments’ chief scientific adviser’s national core studies programme to coordinate national covid-19 priority research. Consortium partner organisations funded the time of contributing data analysts, biostatisticians, epidemiologists, and clinicians. AA is supported by Health Data Research UK (HDR-9006), which receives its funding from the UK Medical Research Council (MRC), Engineering and Physical Sciences Research Council (EPSRC), Economic and Social Research Council (ESRC), Department of Health and Social Care (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 (BHF), and Wellcome Trust; and Administrative Data Research UK, which is funded by the ESRC (grant ES/S007393/1). AB is supported by research funding from the National Institute for Health Research (NIHR), British Medical Association, Astra-Zeneca, and UK Research and Innovation. AB, AW, and SD are part of the BigData@Heart Consortium, funded by the Innovative Medicines Initiative-2 Joint Undertaking under grant agreement No 116074. AW and SI are supported by the BHF-Turing Cardiovascular Data Science Award (BCDSA\100005) and by core funding from UK MRC (MR/L003120/1), BHF (RG/13/13/30194; RG/18/13/33946), and NIHR Cambridge Biomedical Research Centre (BRC-1215-20014). JC, JS, and RD are supported by the Health Data Research (HDR) UK South West Better Care Partnership and NIHR Bristol Biomedical Research Centre. SD is supported by HDR UK London, which receives its funding from HDR UK funded by the UK MRC, EPSRC, ESRC, Department of Health and Social Care (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), BHF, and Wellcome Trust; Alan Turing Fellowship (EP/N510129/1); NIHR Biomedical Research Centre at University College London Hospital NHS Trust. VW is supported by the University of Bristol Medical Research Council Integrative Epidemiology Unit (MC_UU_00011/4). WW is supported by a Scottish senior clinical fellowship, CSO (SCAF/17/01). The views expressed are those of the authors and not necessarily those of the organisations listed. The funders of this work played no role in the collection, analysis, or interpretation of data; in the writing of the report; or in the decision to submit the article for publication. Competing interests: All authors have completed the ICMJE uniform disclosure form at www.icmje.org/coi_disclosure.pdf and declare: support from the funders listed above; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work. SH works as a data scientist and data curator for NHS Digital, which holds and processes the data.

Funding Information:
Funding: The British Heart Foundation Data Science Centre (grant No SP/19/3/34678, awarded to Health Data Research (HDR) UK)

Publisher Copyright:
©

Keywords

  • Adolescent
  • Adult
  • Aged
  • COVID-19/diagnosis
  • COVID-19 Testing
  • COVID-19 Vaccines
  • Cardiovascular Diseases/diagnosis
  • Child
  • Child, Preschool
  • Cohort Studies
  • Electronic Health Records
  • England/epidemiology
  • Female
  • Hospitalization/statistics & numerical data
  • Humans
  • Infant
  • Infant, Newborn
  • Male
  • Medical Record Linkage
  • Middle Aged
  • Primary Health Care/statistics & numerical data
  • Young Adult

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