Projects Delivered

Too many young people in the UK die from asthma. Almost all of these deaths can be prevented if young people and their families know about their illness and are enabled to take the treatment that prevents attacks. Currently, children and young people are reviewed routinely either in primary or secondary care, but this may not be at a time when they are unwell. The clinic system currently doesn’t allow the flexibility to see patients when needed. We wish to use clinical data to pick out those who need to be seen, rather than waiting until they are very unwell. It is only by accessing data from many different sources that we can get a whole picture of any individual patient and then tailor their care to what they need. Accessing Dataloch provides the opportunity to use high quality data that already exists to design and develop a tool that can eventually be used by the NHS that can be used to improve care for individual patients.

New medicines for cancer are improving patient outcomes such as increased survival and quality of life. Accelerated regulatory schemes for new medicines are speeding up access. This presents challenges for reimbursement decision makers such as the Scottish Medicines Consortium. All of these factors lead to high financial risk to the NHS if an upfront fixed drug price is agreed.

“Outcomes Based Pricing” (OBP) is a flexible payment mechanism for helping the NHS managing financial risk of drug adoption with a company. Scotland has benefited from recent advances in the digitisation of healthcare records, which would support the automated rapid data capture necessary for the operation of an OBP scheme.  

We wish to propose an OBP study, as a proof of concept, by using data from NHS Lothian patients affected by Non-Hodgkin’s Lymphoma diagnosed. These patients undergo multiple treatments which would be a great example to test the above rationale, whilst placing little burden on front-line healthcare services. Treatments, medical and survival characteristics will also be described.  

The implementation of OBP for the NHS will lead to accelerated patient access to new drugs, and care improvement, in a manner that protects NHS resources from commercial exploitation by the pharmaceutical industry. The project output will enable the NHS to make safer, better informed and more timely decisions on future medicines to ensure the NHS is providing high value care to the patients it serves. The summary report from the project will be presented to the project steering group and used by Scottish Government Medicines team, Scottish Medicines Consortium and national medicines procurement services to help in the understanding of what is currently possible in NHS Scotland, and what needs to improve.

Some medicines can cause the side effect of liver injury which is the commonest cause of liver failure (organ damage).  Medicines causing liver injury are also a common cause of emergency hospital admissions and liver transplants; they are the main reasons medicines are removed from the market.  Antibiotics are the main group of medicines which cause liver injury independent of the medicine dosage.  

In this project, we are investigating whether data routinely collected by the NHS can be used to monitor liver injury caused by two antibiotics. Both amoxicillin and co-amoxiclav (antibiotics) are commonly prescribed for chest problems but the latter antibiotic causes liver injury far more frequently than the former. This means we can compare the blood test results (identifying liver injury) for these two drugs. This is beneficial because data already being collected (blood test results) can be used to measure the safety of certain drugs.  

Heart disease is the leading cause of death in women. Yet women with heart disease remain understudied, under-recognised, underdiagnosed and undertreated. There is an unmet need for novel approaches to improve prediction of heart disease in reproductive aged women and to help target effective preventative therapies and optimise treatments to prevent heart disease. There is mounting evidence that experiencing abnormal menstrual bleeding is associated with the development of heart disease in women. The impact of volume and duration on risk of heart disease remains unknown.

We hypothesize that heavy menstrual bleeding is an early predictor of heart disease and strokes and may improve prediction of future events in women. Using routine care data, we will evaluate the association between heavy menstrual bleeding and development of heart disease and strokes in women. This project will inform future studies whether heavy menstrual bleeding should be evaluated for risk assessment strategies in women to reduce heart disease burden in women.

When the heart is damaged troponin is being released in the bloodstream. High-sensitivity troponin tests measure the troponin level in the blood and are the preferred choice for the diagnosis of a heart attack. In clinical practice either a high-sensitivity troponin I or T test is being used. They are both recommended in current guidelines, but limited data is available about the agreement between the diagnostic cut offs of high-sensitivity troponin I and T.

NHS Lothian hospitals have changed from a high-sensitivity troponin I to a T test. As part of this process, it is standard laboratory practice for NHS Lothian to verify the performance of the new test. Therefore, we will evaluate in patients who present to the Emergency Department with a suspicion of a heart attack whether more patients are going to be hospitalised and the impact on cardiac investigations, care and clinical outcomes.

This project is studying people with bleeding on the brain, also called intracerebral haemorrhage (ICH). We know some of the things that put people at risk of ICH, such as high blood pressure. However, high blood pressure is common, but only a few people have brain bleeds. We don’t know why some people are affected and not others. DataLoch contains detailed information on people’s health conditions throughout their life. Using data from people who have had ICH and people who haven’t, we aim to find out more about the differences between these two groups. This will teach us more about the underlying cause of ICH, and allow us to target prevention better in future.

Inflammatory bowel disease (IBD), comprising Crohn’s disease (CD) and ulcerative colitis (UC), is a condition in which the gastrointestinal immune system responds inappropriately. It is therefore often treated with immune suppression medications to control inflammation and to prevent ‘flares’, a worsening in symptoms, which may be unpredictable.

Frailty is a description of the process in which the body loses its reserves. It generally increases with age. Frailty can be associated with many health outcomes and affect how diseases progress. 

Currently, there is limited research into how frailty interacts with inflammatory bowel disease. Therefore, we hope to measure frailty in a standardised scale and understand whether frailty affects outcomes in inflammatory bowel disease, and how patients react to treatment such as advanced biologic medications and surgery. By understanding these patterns, we can take into account frailty when tailoring treatment pathways in these patients within NHS Lothian.

Many people attend hospital with symptoms of a possible heart attack, such as chest pain or breathlessness. Getting the right diagnosis is not easy – there is a lot of information including blood results and heart traces for clinicians to consider. Advances in computing and science can now find patterns in data that are not always obvious to humans. This is sometimes called Artificial Intelligence, or AI.

In this project, we aim to develop an AI risk calculator that generates a “score” based on clinical information that is available from the patient during his/her stay at the emergency department. The score that is being calculated from the AI risk calculator will provide information about the patient’s risk of having a heart attack, and also on the future risks of that patient such as needing to come back to hospital. We expect that this approach will provide better and more individualised predictions of risk and that this application could improve the quality and safety of care delivered to patients in the emergency department.