Why we're building the world's biggest cancer database

Picture a population pyramid. At the top are people with multiple chronic conditions. At the second level are those with single-disease problems. At the third level are people who are currently quite healthy but are at risk of developing diseases in five to 10 years. What steps can we take today to prevent them from becoming ill tomorrow?

This is a challenge we are embracing at Leeds Teaching Hospitals Trust, one of the largest acute trusts in the country. We are working with colleagues in primary, community, and social care to harness the power of huge datasets and make timely interventions to improve people’s lives, tackle health inequalities, and reduce pressure on public services.

To illustrate the problem we are facing, consider the NHS treatment of people whose kidneys have stopped working properly because of high blood pressure. Without mitigation, we expect demand to increase by 400 per cent over the next decade. To meet that, the UK would need to build new hospitals just to provide renal dialysis.

Instead, we are working with GPs and local authorities to identify people at risk and intervene early to monitor and manage their blood pressure, preventing the deterioration of their renal function. Moreover, because kidney disease and heart failure run side by side, we are looking at linking our renal physicians with cardiologists to get further ahead of the curve.

People in poverty find it harder to lead healthy lives and access NHS services; they live with more illness and die younger than the rest of the population, according to the King’s Fund think tank

As well as extending healthy life expectancies for individual patients, this kind of collaboration can also drive down health inequalities. People in poverty find it harder to lead healthy lives and access NHS services; they live with more illness and die younger than the rest of the population, according to the King’s Fund think tank. By combining health and care data, we can target our resources at people in the poorest postcodes (who tend to be more likely to suffer from high blood pressure) and help enhance their wellbeing.

Leeds was also one of the early pioneers in early detection of cancer through the Yorkshire Lung Screening Trial, a groundbreaking project for lung cancer screening funded by Yorkshire Cancer Research. Launched in 2018, the trial identified smokers of a certain age from primary care records, triaged them and invited those at higher risk for a CT scan at a mobile clinic. The trial helped to prove the case for lung cancer screening at a national level. By co-delivering smoking cessation interventions alongside screening, the team has also demonstrated the benefit of combining prevention with earlier diagnosis.

Taking this approach further, the team behind the lung trial has used primary care records to identify cohorts of patients with mild, moderate, and severe frailties. Based on analysis of this information, we can predict the likelihood of nursing home admission, hospitalisation or mortality. This project is at an early stage but could be used to refine screening processes in future.

Knowledge is power, especially when it comes to combating cancer. The Leeds-based National Pathology Imaging Cooperative is collaborating with Genomics England to build the biggest cancer data repository in the world. The initiative combines multimodal datasets in an effort to increase understanding of the characteristics of cancer. The hope is these breakthroughs will better inform diagnoses and best direct treatment.

Coming back to today, we know our high service users and the time spent at appointments, attendances, and admissions. At present, we can predict within a 5-10 per cent degree of accuracy, the workload on any given day of the year. Increasingly, we are using near real-time data to analyse what’s happening with our beds. This insight helps us to plan our services and run our hospitals more efficiently in the short term. What we want to do is predict who the high service users will be in five to 10 years. Then we will know who to focus on today.

Undeniably, linking datasets is difficult but we are making great progress as these examples illustrate. If we don’t pursue this approach to data in healthcare, it is highly likely we will see more admissions and, as a consequence, we will need more beds and more clinicians. Instead, we need to peer beyond our hospital walls and work across the boundaries of the traditional health and care sector to look after our population in the future.