University of Oxford

Academic Institute

No

CCU070

Because of the impact of COVID-19 there is strain on research staff doing diabetes research in hospitals and GP surgeries across the UK. Using new trial methods, in which the trial coordinating office communicates directly with trial participants by telephone, mail or online, rather than using staff in local sites, could help diabetes research to recover from COVID-19 and ensure that more patients are given the opportunity to participate in the research studies that are an essential part of of the UK’s recovery from the COVID-19 pandemic. This should be more convenient for patients, as well as reducing the costs and improving the efficiency of diabetes research. Healthcare data can be used to identify people with diabetes to invite them to join clinical trials and can be used to find out whether clinical trial participants have had a heart attack, stroke or mini-stroke, but it is not known how accurate these methods are. In this project, we will use data available via the BHF Data Science Centre (DSC) (including national registries and data from primary care), which are not currently used across the UK for trial recruitment and follow-up, to assess the algorithms (rules and logic used to work out whether someone has or doesn’t have a condition based on items recorded in the health data) used to find and follow the health of people with diabetes for a diabetes clinical trial. We will compare how well these algorithms work when run on the data currently used (hospital admissions data and prescribing data) versus the more extensive data now available via the BHF DSC. The UK Government’s Clinical Research Recovery, Resilience and Growth (RRG) programme emphasises the crucial role of more efficient and inclusive research studies – in particular clinical trials – in the UK’s recovery from the impact of the COVID-19 pandemic.

This study will directly inform trials like ASCEND PLUS, a new direct-to-participant trial which aims to test new treatments in 20,000 patients with type 2 diabetes, and will benefit researchers more widely including contributing potential algorithms to the BHF DSC SCORE-CVD programme. Visit the BHF Data Science Centre website for more detailed information about project outputs. https://bhfdatasciencecentre.org/projects/ccu070/

This project accessed the following datasets within the Trusted Research Environment(s) for CVD-COVID-UK / COVID-IMPACT: - ENGLAND: - Civil Registration - Deaths - Emergency Care Data Set (ECDS) - GPES Data for Pandemic Planning and Research (COVID-19) - Hospital Episode Statistics Admitted Patient Care - Hospital Episode Statistics Outpatients - Medicines dispensed in Primary Care (NHSBSA data) - Mental Health Services Data Set - NICOR – MINAP: Myocardial Ischaemia National Audit Project - NICOR – NHFA: National Heart Failure Audit - NICOR – PCI: Percutaneous Coronary Interventions - Secondary Care Prescribed Medicines (EPMA) - Sentinel Stroke National Audit Programme Clinical Dataset

10/06/2024

De-Personalised

TRE