University of St Andrews

Population and Behavioural Science Research Division

PBS 5 Research 5 Health data science

Health data science

Health Data Science is an interdisciplinary field in which clinicians, statisticians, data scientists and other specialists collaborate to answer important clinical questions and improve health outcomes using statistical, computational and data science methods. 

In the digital age, healthcare systems generate vast amounts of data that often remain underused. Advances in computing and Health Data Science methodologies now present opportunities to analyse these large and complex datasets in new ways, uncovering patterns and insights that, with expert interpretation, can be translated into clinical practice and contribute to meaningful improvements in healthcare delivery. 

Our research makes use of high-quality routinely collected healthcare data accessed through secure research platforms. This includes comprehensive Scottish health datasets covering hospital admissions, emergency department attendances, pregnancies, cancer registrations, laboratory tests, and prescriptions as well as other UK and international health data sources, enabling our research teams to address clinically important questions across different populations and health systems, delivering internationally relevant and impactful research. 

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Why is health data science important?

Making sense of the large amounts of data we produce can provide earlier insights to diseases and health conditions. Using tools and methods, data can be turned into useful information that can be analysed to detect patterns which help clinicians offer patients the best care. For example, data on individual patients can be combined and analysed in order to learn more about how conditions develop in populations, and who is more likely to develop these. Analysing data can help us learn more about causes and symptoms so that we can learn to spot diseases and conditions earlier and plan how best to manage the care of patients.

Where does the health data come from?

The data used by health data scientists comes from many sources and can also come in a variety of formats, such as text, numeric and images. Sources include:

  • Health care records on primary care and hospital attendance, such as doctors’ records — both notes and codes— prescriptions and social care provision, records of hospital admission and A & E visits
  • Mobile phone applications, smart watches and other tracker devices that collect information on heart rate, physical activity, sleep, age and menstrual cycle.

Who has access to health data?

The ethical and legal responsibility of using data is closely controlled in the UK, each project is assessed by the relevant governing body and data is provided in an anonymous format in order to protect patient confidentiality. Health Data Research UK suggested best practice is that access to data is given for a specific use and provided through a data safe haven. A data safe haven is a platform that holds electronic records in a secure environment, providing restricted access in a de-identifiable format for analysis to enable research.

Who are the data scientists?

Data scientists come from a broad range of disciplines such as: Computer Science, Mathematics, Statistics, Biomedical Science, Physical Science and Social Science. Multidisciplinary teams work particularly well in health data research, as each expert, brings a different perspective and approach to how they interpret the research. Through sharing their thoughts, opinions and expertise, better results can be achieved.

What are some of our current research interests?

Health Data Research UK enhance our research through their funding, support and endeavours to combine health data from across the UK through their national implementation projects.

Multimorbidity resource — defined as two or more long-term conditions — identifying which conditions are commonly found together, how these develop with age and what challenges are faced by these people and the health services that are supporting them.

Principal Investigators

Alun Hughes

Prof Colin McCowan

Head of Division

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Dr Sarah Mills

Clinical Senior Lecturer

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Dr Cicely Macnamara

Lecturer in Medical Statistics

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Professor Frank Sulliavn

Professor of Primary Care Medicine

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Dr Keith Moffat

Academic Fellow in General Practice

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Ms Robin Alexander

Research Fellow in Medical Statistics

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Dr Desy Nuryunarsih

Research Fellow in Medical Statistics/Health Data Science

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Mr Benedict Leonard-Hawkead

Research Fellow in Medical Statistics/Health Data Science

Current Projects

Multimorbidity is defined as two, or more, existing conditions which may affect health outcomes.

Research study to improve patient care in Sepsis.

To improve care in the last year of life.

This project uses epidemiological methods to identify patients at greater risk of infection

The NOMAD study aims to determine whether paternal use of sodium valproate is associated with an increased risk of adverse neurodevelopmental outcomes in children.

Supporting earlier identification of people who may benefit from palliative care in unscheduled NHS care settings.

Past Projects

Developing research to study and improve maternity care for pregnant women who are managing two or more long-term health conditions.

Developing a Learning Health System for NHS Fife.

Research Interests and Opportunities

We are interested in all areas of health data science, medical statistics, artificial intelligence (machine learning/deep learning), and mixed methods related to health data analysis. We support funded PhD students, taught MSc and MSc by Research projects and undergraduate summer projects. 

Contact Us

If you have a question or would like further information, please email us [email protected] and we will get back to you as soon as possible. 

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