Investigators across the six HDR UK sites have mobilised to provide the research community with the tools they need to address urgent clinical questions related to the COVID-19 pandemic.

Phenotype Portal: Developing an open-access catalogue of codes for defining COVID-19-related phenotypes

In order for research into COVID-19 to be carried out consistently across the whole of the UK, it is important that the research community is open and transparent about how the condition has been defined for research. We enhanced the Phenotype Portal to provide a comprehensive, open-access resource providing the research community with information, tools and phenotyping algorithms for defining COVID-19 related phenotypes in UK electronic health records (EHR). The Portal currently hosts 336 phenotyping phenotypes, 909 codelists and curates 25000 controlled clinical terminology terms. Many of the disease conditions covered in the Portal are from conditions which have been flagged as high-risk in relation to COVID-19 such as cancer, chemotherapy, immunosuppression and others. This resource contains information on controlled clinical terminology codes used to record COVID-19 related events (ICD-10 and ICD-11, Clinical Terms Version 3 (CTV3), EMIS, Vision, UK SNOMED-CT, International SNOMED-CT, LOINC and openEHR), reporting templates and proformas, prevalence estimates and information about the Public Health England high risk definition or populations at increased risk of severe illness from COVID-19. All algorithms can be downloaded directly from the Portal in a machine readable format (as CSV files).

Understanding and protecting vulnerable groups

Researchers harnessed the Phenotype Portal to address the wider impact of the COVID-19 pandemic by identifying high-risk vulnerable groups.

Estimating excess 1-year mortality from COVID-19 according to underlying conditions and age in England (published in The Lancet, 2020)

Vulnerable people, including people aged over 70 and those who have high blood pressure, heart disease or asthma, make up 20 per cent of the British population. Early models of population mortality during the COVID pandemic did not include information on such common high-risk conditions or their longer-term pre-COVID-19 mortality. Researchers at UCL, Oxford and Cambridge estimated the excess number of deaths over one year under different COVID-19 incidence scenarios based on varying levels of transmission suppression and differing mortality impacts for different relative risks for the disease. The study used linked electronic health records of 3.8M people from England and the Health Data Research (HDR) UK–CALIBER open online portal to define underlying conditions at different ages in women and men. Findings show that the risk of death from COVID-19 for someone with heart disease is five times higher than a healthy person and 10 times higher for someone with heart disease and diabetes. The research won the Health Data Research UK Impact of the Year Award 2020

Estimating Excess Mortality in People with Cancer and Multimorbidity in the COVID-19 Emergency (published as a pre-print)

UCL-led research along with DATA-CAN: The Health Data Research Hub for Cancer used data from hospitals in London, Leeds and Northern Ireland and the health records of nearly 4 million patients in England (CALIBER) to look at changes in cancer service provision and model excess deaths in the COVID-19 emergency in patients with cancer and other underlying health conditions. Researchers estimated there could be 6,270 more deaths among newly diagnosed cancer patients over the next year – a 20% increase in deaths among people newly diagnosed with cancer. This number could rise to an estimated 17,915 additional deaths if all people currently living with cancer are considered. More than three quarters of these excess deaths will occur in people who are also suffering from one or more other underlying health condition, including cardiovascular diseases, hypertension, obesity and diabetes. Dr Alvina Lai, lead researcher, won the Health Data Research UK Early Career Lightning Talk Award 2020

Development of public-facing COVID-19 prediction models: OurRisk online risk calculator for patients and the public

In response to the UK Government Chief Medical Officer's announcements on 16 and 22 March 2020 on underlying conditions we wanted to identify an individual's risk of dying based on their underlying conditions using the best possible evidence. This is important to help people understand how government policies around 'social distancing' affect them. We also wanted to find out how COVID-19 will affect the health system by estimating the number of excess deaths which might occur due to COVID-19. Thirty-nine members of the public worked with researchers to produce the OurRisk online risk calculator for patients and the public which provides 1-year COVID-19 mortality risks for common conditions by age and sex in the context of current guidelines and facilitate people's conversations with their family and health professionals. The risk calculator has had 1.3 million pageviews from 636K users across the world (64% of users were from the UK, 21% were from the United States and 5% from Australia).

National COVID-19 Datamart for Research (DECOVID)

HDR London entered into a major collaboration with the Alan Turing Institute and others to establish DECOVID - a scalable, national data repository and data analytics centre providing clinicians with real-time actionable intelligence into patient care and operational planning during the COVID-19 pandemic. The resource will be used to answer clinically pertinent questions on the acute management of inpatients who are at risk of, or are suspected or confirmed to have COVID-19.