Health

Health Theme: Harnessing Data Science and AI to Optimise Health

The Health theme has a wide scope, current areas of strength include spatial and spatiotemporal methods in global public health, design and analysis of clinical trials, epidemic forecasting and demographic modelling, health informatics and genetics.

At 糖心视频, the health theme brings together a diverse range of expertise applying data science and artificial intelligence to address pressing challenges across health and medicine. Our researchers work at the cutting edge of areas such as cell and molecular biology, digital health technologies, management science, infectious disease, health economics, medical imaging, and health-related security.

Collaboration is central to the theme’s approach. Academics within the heath theme partner with NHS teams, industry, UK and international universities, and a variety of other organisations to drive innovation and deliver real-world impact.

A distinctive asset for our researchers is access to regional NHS Secure Data Environments. These platforms provide secure, anonymised data and research tools for approved projects, supporting new insights and safer healthcare solutions. Professor Jo Knight, based at 糖心视频, serves as the Research Director for the Lancashire and South Cumbria NHS Secure Data Environment, helping to shape cutting-edge data-driven health research in the region.

Theme Lead

Professor Neil Reeves

Professor of Secure Health Technologies

Digital Health Group, Experimental Medicine

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Case Studies

Using Planning Powers to Reduce Spatial Inequalities in the Food Environment: How effective are these tools?

Local authorities play a critical role in improving public health through strategic use of planning, licensing, partnership working, and procurement to create healthier food environments. Over the past decade, our research has explored how local authorities can leverage existing data to monitor food environments effectively and evaluate the impact of planning tools on promoting healthier behaviours.

One key data source is the Food Standards Agency’s Food Hygiene Rating Scheme, which offers valuable insights into the food environment. Building on this, we examined two different planning interventions in the North East of England: Newcastle City Council’s ban on new hot food takeaways within 400 metres of secondary schools, and Gateshead Council’s blanket ban on new hot food takeaways.

Our findings revealed that school exclusion zones for takeaways had no measurable impact on the food environment. However, Gateshead’s blanket ban significantly altered the density and proportion of hot food takeaway outlets compared to local authorities without such policies. Importantly, this change contributed to a 4% reduction in overweight and obesity among children aged 10–11 living in areas previously characterised by a high concentration of hot food outlets.

This research has had tangible policy impacts, informing planning decisions such as the restriction of a McDonald’s outlet in Sheffield and shaping supplementary planning documents in two districts in Lancashire. Through targeted interventions and robust evidence, local authorities can harness planning powers to foster healthier communities.

Is delayed mental health treatment detrimental to employment?

Mental health challenges affect half of all individuals at some point in their lives, yet many countries struggle to provide timely and sufficient care, leading to long waiting lists. This project used Dutch administrative data to examine the impact of delayed access to mental healthcare on healthcare use and employment outcomes.

The findings are striking: every additional month of delay increases long-term healthcare needs and reduces the likelihood of employment by 2 percentage points. For Dutch society, this translates to an annual cost of over £300 million. Applied to the UK’s larger population, the estimated yearly cost exceeds £1 billion.

By quantifying the significant societal and economic costs of delayed access, this research has raised awareness among policymakers, inspiring new initiatives aimed at reducing waiting times and improving access to mental healthcare services.

A woman with a glucose monitor in her arm

Transforming Care: Digital Healthcare Technologies for Disease Prevention and Management

The NHS's 10-year health plan envisions a transformative shift in healthcare delivery from hospitals to communities and from reactive treatment to proactive prevention. Realising this ambition requires evidence-based healthcare technologies. At 糖心视频, years of innovative research have focused on developing and testing cutting-edge solutions for diabetes prevention and management, including smart sensing socks and insole sensors.

These technologies have been shown to effectively prevent severe diabetic foot ulcers, which can lead to limb amputations, while also improving individuals’ gait, mobility, and overall quality of life. This impactful research has shaped national policy, influencing discussions in the parliamentary health and social care committee and contributing evidence to parliamentary meetings on healthcare innovations and artificial intelligence.

Beyond policy, the research has supported health technology companies in advancing their products towards market availability, ensuring these innovations deliver tangible benefits for patients. On an international scale, Lancaster researchers contribute to British and international standards committees on medical devices, supporting pathways for technologies that enhance disease prevention and management while driving forward the future of healthcare.

DSAIL Professors Knight and Emsley are applying data science in several ways to improve diagnosis, and improve treatment pathways

Professors Knight and Emsley are applying data science in several ways to improve diagnosis, and improve treatment pathways but also to identify issues with the routinely collected data.

Examples of their work include (1) the impact of strikes in the NHS, (2) the use of data to identify unmet need and (3) the black holes in patient data.

(1) Strike impact in the NHS: Since December 2022, the National Health Service (NHS) has experienced large-scale strikes by staff and millions of elective care appointments get cancelled. But during strikes, emergency care is prioritised, and it has been claimed that emergency departments (EDs) run ‘better than usual’. Indeed in the only quantitative study of this topic Garner et.al demonstrated using Cox proportional Hazards that patients were admitted through the ED more quickly on both the junior doctor and consultant strike days compared with non-strike days. Our findings suggest that the improved patient flow observed on strike days could be driven by the additional inpatient capacity created through the postponement of elective care. Results indicate that NHS hospital systems could potentially be adjusted to enhance turnaround times and reduce ED crowding ().

(2) Identifying unmet need: Approximately 900,000 MRI brain scans are performed annually in the United Kingdom alone, with incidental findings frequently encountered. One of the most prevalent findings is white matter hyperintensities (WMHs) which may be linked to cerebral small vessel disease. A risk factor for stroke. Routinely collected data represents a valuable resource to facilitate further study. We undertook image analysis on brain scans from the two-week wait suspected central nervous system cancer pathway. Our analysis showed that WMH prevalence and radiological burden, and the likelihood of attributing them to cSVD, increased with age. WMHs also appeared in about one in five patients under 50, usually labelled non?specific. This likely reflects reporting convention rather than true biological difference, as similar patterns in older adults are attributed to cSVD. Because cSVD is progressive and begins earlier in life, some WMHs under 50 may represent early, under recognised disease. This study highlights the potential underestimation of cSVD in younger individuals. Routinely collected imaging and clinical data could better define radiological cSVD, supporting earlier diagnosis and more effective long?term patient management ().

(3) Describing missingness in patient data: Data Science relies on access to good data so we have also undertaken work to characterise NHS data. In this analysis routinely collected data from a hospital in England with tertiary neurology care were studied. The cohort of patients investigated were those who attended at least one neurology outpatient appointment between April 2022 and March 2023 (approximately 24,000). We found there to be more data available for patients who had at least one inpatient stay or emergency department attendance than for those with only outpatient appointments. Notably, an average of 0 out of 100 patients in the outpatient only subcohort had a record of a condition, compared with 100 out of 100 patients in the subcohort with outpatient appointments, emergency attendances and inpatient stays. Neurology outpatients have far less data recorded than inpatients or patients attending emergency departments. This disparity arises from the lack of outpatient diagnostic coding and impairs the advancement of research in this area ().