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 under‑used. 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.
Principal Investigators
Prof Colin McCowan
Head of Division
Dr Sarah Mills
Clinical Senior Lecturer
Dr Cicely Macnamara
Lecturer in Medical Statistics
Professor Frank Sulliavn
Professor of Primary Care Medicine
Dr Keith Moffat
Academic Fellow in General Practice
Ms Robin Alexander
Research Fellow in Medical Statistics
Dr Desy Nuryunarsih
Research Fellow in Medical Statistics/Health Data Science
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.








