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  Population and Health Data Science: Fully Funded Health Data Research UK PhD Scholarship: Use of Real-World Evidence in Health Technology Assessment for Multiple Long-term Conditions


   Swansea University Medical School

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  Prof Rhiannon Owen  No more applications being accepted  Funded PhD Project (Students Worldwide)

About the Project

Funding provider: Health Data Research (HDR) UK

Subject areas: Population Data Science

Project start date:

  • 1 October 2024 (Enrolment open from mid-September)

Project supervisors:

  • Professor Rhiannon Owen ([Email Address Removed])
  • Dr James Rafferty
  • Professor Hamish Laing
  • Professor Keith Abrams (University of Warwick)

Aligned programme of study: PhD in Population and Health Data Science

Mode of study: Full-time

Project description:

Healthcare decision-making has previously focussed 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 modelling framework to estimate the natural history of disease in individuals living with multiple long-term conditions using population-scale, linked, electronic health records from the Secure Anonymised Information Linkage (SAIL) Databank Wales Multimorbidity e-Cohort (Lyons et al, 2021). This approach will allow estimation of the potential adverse effects (such as hospitalisations) of drug-on-drug interactions for the treatment of multiple conditions and associated genetic, environmental, or demographic risk factors. Further this PhD project will compare the efficacy of different combinations of treatments used in people with multiple long-term conditions, and assess potential health inequalities.  

Facilities 

The PhD student will be based in Population Data Science at Swansea University with visiting PhD Student Status at the Department of Statistics at the University of Warwick, benefiting from the stimulating and supportive environment and bespoke training programmes. The successful candidate will receive training to develop their knowledge and expertise in statistical modelling, epidemiology, population data science and health technology assessment, with the opportunity for their research to directly inform healthcare policy and practice. The successful student will have the opportunity to present their work at national and international conferences and workshops.  

This PhD is funded as part of the HDR UK Medicines in Acute and Chronic Care Driver Programme, which is a national collaboration that aims to understand and transform the use of medicines for patient benefit, and reduce medicines-associated harm. The Driver Programme has a particular focus on vulnerable populations including people living with multiple long-term conditions and those experiencing health inequalities. The successful candidate will be one of several PhD students contributing to the wider HDR UK Driver Programmes and will have the opportunity to collaborate with the wider HDR UK Driver Programme Team as well as access additional training and associated events hosted by HDR UK. 

Eligibility

Candidates must hold an Upper Second Class (2.1) honours degree. Candidates will need an MSc in Statistics/Biostatistics or Epidemiology/Health Data Science (with a strong analytical component) plus programming and data analysis skills/experience in R and/or Python. 

Experience of analysing large-scale linked electronic health record data and knowledge of Bayesian methods would be an advantage.

If you are eligible to apply for the scholarship but do not hold a UK degree, you can check our comparison entry requirements. Please note that you may need to provide evidence of your English Language proficiency. 

This scholarship is open to candidates of any nationality.

Computer Science (8) Medicine (26) Nursing & Health (27)

Funding Notes

This scholarship covers the full cost of tuition fees and an annual stipend of £19,237.
Additional research expenses will also be available.

Where will I study?