DECOVID V1 [COVID-19]
Research type
Research Database
IRAS ID
282225
Contact name
Elizabeth Sapey
Contact email
Research summary
De-coding COVID-19 [COVID-19]
REC name
London - City & East Research Ethics Committee
REC reference
20/HRA/1689
Date of REC Opinion
3 Apr 2020
REC opinion
Favourable Opinion
Data collection arrangements
The DECOVID database will collect in-depth, health data from patients admitted to hospital during the COVID-19 pandemic. \n\nThe health data collected will come from electronic health records and will include care processes (when people came into hospital, who they saw, what tests were ordered, and which wards people went to) acuity data ( a measure of how unwell people are which looks at how the bodies organs are working) investigations (what tests were sent and what were the results), treatments and outcomes. \n\nUniquely, this will include serial data, taking all the health data from each day of each admission, making the most complete record of COVID-19 care globally.\n\nThe health data will be pseudonymised, meaning you need to a code to the link the health data to an individual patient. This pseudonymised data will be held in a secure, private and limited access cloud system run by \nIMicrosoft Azure \n\nFor non-UHB trusts, either the data controller will pseudonymise data at the local site and provide this to UHB (who will become the data controller); or if the non-UHB trust is unable to perform pseudonymisation, identifiable data will be sent in a selected and staged manner to the private and limited access Microsoft Azure UHB cloud. At this point, UHB becomes the data controller and will perform pseudonymisation. \n\nHere the data remains until an approved request is received. The pseudonymised data will be refreshed with data up-dates to gather more longitudinal data and an increased number of patients’ data, but only data which cannot be linked to the patient will be shared with researchers to help answer critical questions about COVID-19.
Research programme
The very scale of the COVID-19 pandemic could also provide the means to quickly understand the effects of this viral illness across the population. By understanding both the acute care experience and long term health needs of patients during the COVID-19 pandemic, there is an opportunity to identify critical points in delivery pathways where new approaches, treatments and devices might revolutionise care. \n\nThis would offer significant benefits to the care of individuals, especially those admitted to hospital during the COVID-19 pandemic, when hospitals are struggling to meet the clinical needs of patients. This is especially true of patients with complex care needs and multiple health conditions, where disease outcome and course are harder to predict and outcomes following ventilation generally poor.\n\nThe potential utility of the DECOVID dataset is vast, with potential benefits including:\n1.\tBetter prognostication markers for patients on first presentation and during the course of illness while an in patient\n2.\tPathway innovation to tackle diagnostic delay \n3.\tModelling of the impact of age, multi-morbidity and poly-pharmacy within the ethnically diverse UK population \n4.\tIdentifying specific populations of risk of poorer outcomes and those most likely to respond to new therapies\n5.\tAccess outcomes of various treatment strategies employed in a new disease providing knowledge gained from a natural ‘experiment’ outside the confines of a formal clinical trial\n\nAnd to the wider community\n1.\tUp skill the workforce in health data\n2.\tEnable NHS data to solve our own healthcare challenges\n3.\tHave first access to health innovation across providers\n Lay summary of study results: DECOVID, a multi-centre research consortium, was founded in March 2020 by two United Kingdom (UK) National Health Service (NHS) Foundation Trusts (comprising three acute care hospitals) and three research institutes/universities: University Hospitals Birmingham (UHB), University College London Hospitals (UCLH), University of Birmingham, University College London and The Alan Turing Institute. The original aim of DECOVID was to share harmonised electronic health record (EHR) data from UCLH and UHB to enable researchers affiliated with the DECOVID consortium to answer clinical questions to support the COVID-19 response. The DECOVID database has now been placed within the infrastructure of PIONEER, a Health Data Research (HDR) UK funded data hub that contains data from acute care providers, to make the DECOVID database accessible to external researchers not affiliated with the DECOVID consortium. This highly granular dataset contains 256,804 spells and 165,414 hospitalised patients. The data includes demographics, serial physiological measurements, laboratory test results, medications, procedures, drugs, mortality and readmission Data access is available via the PIONEER Hub for projects which will benefit the public or patients. This can be by developing a new understanding of disease, by providing insights into how to improve care, or by developing new models, tools, treatments, or care processes. Data access can be provided to NHS, academic, commercial, policy and third sector organisations. Applications from SMEs are welcome. There is a single data access process, with public oversight provided by our public review committee, the Data Trust Committee. Contact pioneer@uhb.nhs.uk or visit https://eur03.safelinks.protection.outlook.com/?url=http%3A%2F%2Fwww.pioneerdatahub.co.uk%2F&data=05%7C02%7CTracy.Hamrang%40hra.nhs.uk%7Cbf39d9b5ae4448a4070608dd1b5890d0%7C8e1f0acad87d4f20939e36243d574267%7C0%7C0%7C638696789370448788%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&sdata=g01%2FHh3xlfp2I7Bs2cY0%2FyISvzdTQl1ufl5zslQZWCU%3D&reserved=0 for more details.
Research database title
De-coding COVID-19 [COVID-19]
Establishment organisation
University Hospitals Birmingham NHS Foundation Trust
Establishment organisation address
Mindelsohn Way
Edgbaston
Birmingham, West Midlands, UK
B15 2TH