Socioeconomic outcomes measurement in survivors of major illness using public sector data

This studentship offers an exciting opportunity for a PhD candidate to be at the forefront of data science, epidemiology and economics research. It will bring together a range of public sector datasets in novel linkages to explore the consequences of surviving a major illness.

Individuals who survive a major illness, such as cancer or critical illness, report ongoing problems with their health and wellbeing for months or years after the acute event. Clinical care and research has focussed on helping patients survive their acute illness. However, there is a need to better understand how illness exerts its burden in the longer term, not only on the NHS and healthcare services, but also on social care services, welfare services and other sectors. This broader, longer- term perspective is particularly important when new treatments and interventions are evaluated in patients with major illness. Furthermore, broadening the outcomes measures used in national healthcare audits offers the opportunity to improve quality of care in survivors of major illness through development of new policy or service design.

Rich public sector datasets in Scotland provide a unique and underexploited opportunity to measure socioeconomic outcomes over a wide scope. Using Scotland’s unique person-specific identifier to link datasets, and recent efforts by the Scottish Government to improve data availability, we are now able to bring together variables not previously obtainable that can help us to measure financial, clinical and social outcomes.

The project will use established, high quality Scottish Cancer and Intensive Care registries to identify cohorts of patients diagnosed with major illness. With support from the Farr Institute Scotland, eDRIS and ADRC, a bespoke national research dataset will be extracted and used as a basis for analysis. The analysis will use health economic costing methods to quantify the burden of disease on society including the relative burden between public services and sectors. Econometric modelling will be used to identify predictors of excess cost. There will be an opportunity to use simulation methods to forecast future socioeconomic consequences of changes in disease epidemiology and treatment effectiveness.

Academically strong candidates with a background in economics, epidemiology and statistics or relating subject areas such as informatics, computer science, clinical sciences, health services research, machine learning, are particularly encouraged to apply.
The successful candidate will be based in the Usher Institute of Population Health Sciences and Informatics (www.ed.ac.uk/usher) in close collaboration with Edinburgh Cancer Centre (http://www.ed.ac.uk/cancer-centre) and will benefit greatly from the strong inter-disciplinary environment offered by the Farr Institute (www.farrinstitute.org).

Application Procedure
Please provide a CV, a personal statement detailing your research interests and reasons for applying, a referenced outline of your research plan (maximum of 2 pages), degree certificate(s), marks for your degree(s) and 2 academic references in electronic format and email to:

Dr Nazir Lone
email: [Email Address Removed]

Interviews will take place on 1st August 2017.

Following interview, the selected candidate will need to apply and be accepted for a place on the Usher Institute Medical Informatics PhD programme; details can be found here http://www.ed.ac.uk/studying/postgraduate/degrees/index.php?r=site/view&id=924