Cardiovascular disease (CVD, including heart attacks and strokes) remains one of the leading causes of death in the UK. There are a number of conditions that commonly increase an individual’s risk of developing CVD. Some of these conditions, such as diabetes and having high circulating levels of cholesterol in the blood, can be controlled by using medicines.
However, these conditions need to be diagnosed before an individual can be prescribed the medicines to control them. Because of disruption from the COVID-19 pandemic resulting in changes in health care services and fewer face-to-face medical appointments, it is likely that the number of conditions being diagnosed has fallen. Therefore, some individuals are not being prescribed the medicines to control the condition.
One way to investigate this problem is to look at what changes there have been in the prescriptions for these conditions. This involves looking at new and repeat prescriptions that have been issued by the GP, and also the amount of prescriptions dispensed by the pharmacy.
We already know that the COVID-19 pandemic caused a disruption to the usual pattern of prescribing of medicines for these conditions. For example, there was a significant increase in the number of repeat prescriptions issued in March 2020, presumably as doctors and patients ensured they had sufficient medication for the first lockdown. Subsequent patterns in the prescribing of medicines for these conditions during 2020 have not yet been adequately studied.
The number of GP appointments also fell during Spring-Summer 2020, presumably resulting in a reduced number of individuals being diagnosed with CVD. It is also presumed that there would be a reduction in the diagnosis in new patients of conditions that can increase their risk of developing CVD, and therefore a decrease in the amount of prescriptions for medicines to control these conditions.
For this project, we therefore propose to examine patterns in the prescription of medicines for these conditions. This will enable us to understand how the COVID-19 pandemic has had an impact on the control of CVD and its related conditions in the UK population. We will use this information to understand how many people are likely to be affected by cardiovascular disease in the future. It is hoped that this will enable more accurate planning for better patient care.
Extension to understand the impact of COVID-19 on a number of clinical pathways using medicines as an approach
We previously proposed that medicines could be used to estimate how risk factors for CVD have been managed through the pandemic. This work has yielded important findings demonstrating that medicines used to treat major CVD risk factors, e.g. blood pressure and cholesterol, have fallen over the course of the pandemic and have not yet recovered. This has major implications on how CVD should be managed in the months and years to come and how this may be able to facilitate targeting of treatment e.g. working with NICE, Public Health bodies.
We would now like to extend this work to other disease pathways. During the COVID-19 pandemic health care was disrupted due to increased demands on the NHS. Many long-term conditions and emergency health problems were not diagnosed or treated. To address this, we aim to harmonise medicines data, link this to health outcomes and create a medicines dashboard to understand changes to clinical pathways during COVID-19. If we are unable to create a dashboard to answer these questions, we will carry out select use cases to demonstrate the utility of the national data in parallel to creating a useful medicines dashboard which could then carry this work out in the future.
The public health benefits include monitoring change of medicines use, targeting treatments to high risk or neglected groups, ensuring equity of access, assessing value for money, informing guidance on the use of medicines and capturing harms linked to medicines. If sustained the medicines dashboard can be embedded within health care agencies for ongoing benefit.
The issues outlined above will be addressed in outputs from a number of related sub-projects. Follow the links below to view repositories containing the protocol, data curation and analysis code, and phenotyping algorithms and codelists for each sub-project:
Links to repositories for additional outputs will follow in due course.
This project has been approved by the CVD-COVID-UK/COVID-IMPACT Approvals & Oversight Board (Project ID: CCU014). It also successfully received funding through a funding call by Health Data Research UK working in partnership with The Alan Turing Institute and the Office of National Statistics, as part of the wider Data and Connectivity National Core Study.