Health Data Science: Fully Funded Health and Care Research Wales-NIHR PhD studentship in Statistical Modelling in Multiple Long-Term Conditions for Healthcare Policy (RS820)

Darperir y cynnwys hwn o ffynhonnell allanol yn Saesneg yn unig.

Key Information

Project start date: 1 October 2025 

Supervisors: Professor Rhiannon Owen, Dr James Rafferty, Professor Keith Abrams (University of Warwick) 

Aligned programme of study: PhD Population Data Science 

Mode of study: Full-time 

Project description:

Healthcare decision-making has previously focused on developing recommendations for single conditions. However, standardised care for each chronic condition in isolation can be inappropriate for individuals living with multiple long-term conditions known as multimorbidity, and may lead to unnecessary polypharmacy. This PhD studentship aims to develop a Bayesian modelling framework to identify clusters of multiple long-term conditions resulting in increased risk of hospitalisations, polypharmacy and/or mortality using population-scale, linked, electronic health records from the Secure Anonymised Information Linkage (SAIL) Databank Wales Multimorbidity e-Cohort. This approach will be extended to explore potential genetic, environmental, or demographic risk factors associated with cluster membership and/or the outcomes of interest. 

This PhD studentship is funded as part of the Re-thinking Health Policy in Multimorbidity (REMIT) project. The REMIT project aims to develop new methods to assess emerging treatments for people living with multiple long-term conditions. This project will utilise the SAIL Databank’s rich anonymised population-scale, individual-level, linked data sources to answer important population-level questions that will inform health technology assessment, policy, and practice. The successful PhD student will be embedded within an interdisciplinary team across academia and healthcare policy.  

Find out more and apply.

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Population Data Science - Swansea University