University of Oxford

Academic Institute

No

CCU069

Heart and diabetes related problems are the number one cause of death in the world. Also known as cardiometabolic diseases, many of them are common and well-known. Some however are rare or found in less than 1 in 2,000 people. Rare conditions are hard to diagnose and treat. Over 4 million people in the UK live with unmet health and social needs for rare conditions. We know that often rare conditions have a genetic link and can affect certain ethnicities more than others. The COVID-19 pandemic disproportionally affected individuals from ethnically and socio-economically diverse backgrounds. We do not know how the healthcare and outcomes of the “invisible minority” suffering from rare conditions was impacted. Overall, there is a gap in our understanding of rare diseases that are related to or co-occur with heart disease and diabetes. We also don’t know the impact of intersectional health disparities compounded by the COVID-19 pandemic on those living with rare diseases. To help people receive earlier and correct diagnosis of their condition and appropriate care, we need to learn more about rare diseases and related health inequalities. Anonymous electronic health records offer a unique opportunity to discover rare conditions by studying the whole population. We will study the largest set of records in the UK containing over 58 million English people spanning 250+ ethnicities and including more than 1 million who suffer from at least one of 331 rare conditions. To understand the link between rare conditions related to or co-occur with heart disease and diabetes. We will look for sub-groups that may be distinguishable by their medical history. We will further see if COVID-19 pandemic negatively impacted the health of those with rare conditions who may also be marginalized with regards to where they live, their age and gender, their ethnicity and their socioeconomic status. To do so we will select a few exemplar rare conditions related to heart and diabetes. We use techniques that make this approach scalable to study other conditions. We have a successful history of working closely with patients, carers and public members to design and deliver research in a way that is culturally appropriate and relevant to patients from all backgrounds. We will also take input from related national rare disease collaborative networks (NHS RCDNs).

Improved understanding of rare heart disease and diabetes groups and sub-groups, how their health risks and health care use has been impacted by COVID-19, and how this information can be used to provide targeted care can ultimately help reduce health gaps and ensure those with rare conditions are no longer “invisible”. Visit the BHF Data Science Centre website for more detailed information about project outputs. https://bhfdatasciencecentre.org/projects/ccu069/

This project accessed the following datasets within the Trusted Research Environment(s) for CVD-COVID-UK / COVID-IMPACT: - ENGLAND: - Civil Registration - Deaths - COVID-19 SARI-Watch (formerly CHESS) - Covid-19 Second Generation Surveillance System - Covid-19 UK Non-hospital Antibody Testing Results - Covid-19 UK Non-hospital Antigen Testing Results - COVID-19 Vaccination Adverse Reaction - COVID-19 Vaccination Status - Emergency Care Data Set (ECDS) - GPES Data for Pandemic Planning and Research (COVID-19) - Hospital Episode Statistics Admitted Patient Care - Hospital Episode Statistics Critical Care - ICNARC: Intensive Care National Audit and Research Centre - Medicines dispensed in Primary Care (NHSBSA data) - NICOR – MINAP: Myocardial Ischaemia National Audit Project - NICOR – NACRM: National Audit of Cardiac Rhythm Management - NICOR – NACSA: National Adult Cardiac Surgery Audit - NICOR – NCHDA: National Congenital Heart Disease Audit - NICOR – NHFA: National Heart Failure Audit - NICOR – PCI: Percutaneous Coronary Interventions - NICOR – TAVI: Transcatheter Aortic Valve Implantation - Secondary Care Prescribed Medicines (EPMA) - Secondary Uses Services Payment By Results - Sentinel Stroke National Audit Programme Clinical Dataset - Uncurated Low Latency Hospital Data (Admitted Patient Care, Outpatients, Critical Care)

29/06/2023

De-Personalised

TRE