The aim of this project is to provide a robust and adaptive computational framework for highlighting the multifaceted impact of medical device innovations in the delivery of healthcare. The proposed research will review existing evaluation techniques in the health technology assessment of medical devices field, classifying strengths, weaknesses and functionality of these computational modelling techniques across a range of clinical areas. An innovative modelling tool, consistent with best practice, will be developed that addresses the needs of health technology assessment agencies with personalised features ensuring clinically and economic plausibility but also adaptive functionality for bespoke clinical areas. Transplant technology is an emerging area where medical innovation is being applied to maximise the health benefits associated with transplantation. Cost implications however limit the feasibility of these innovations, mainly due to limitations on the modelling capacity of health technology appraisal techniques. Therefore, innovation in transplantation will be the main case study assessed in conjunction with the Oxford Transplant Centre and the Nuffield Department of Surgical Sciences, University of Oxford. The modelling tool will incorporate data collected by the Oxford Transplant Centre and the EU COPE consortium in the area of innovation in organ perfusion to validate functionality and predictive ability.
- To review the evolution of modelling frameworks in health technology assessment (HTA) of medical devices.
- To identify the strengths, weaknesses, adaptive features and functionality of current modelling techniques for predictive modelling of the costs, outcomes and benefits of medical devices.
- To develop a modelling tool that will incorporate the necessary features of HTA, consistent with best practice, that will be adaptive to a range of clinical areas.
- To validate the model with novel technologies in the field of organ transplantation.
- To provide a HTA of organ perfusion methods for transplantation from a national perspective.
This research project is grounded in applied health economics and mathematical modelling. The candidate will be expected to have an undergraduate background in one of the following: economics, mathematics, medicine, pharmaceutical science, public health, applied health sciences or a related discipline. The candidate should have a strong academic record in statistics and data analysis and should be proficient in MS Excel. A Master's degree would be preferable in a related clinical discipline or in the area of health economics, health technology assessment, data analytics, health research or a related analytical discipline. Knowledge of statistical applications in MS Excel and SPSS, STATA and R is also preferred. The candidate will also need to be available to travel to the UK for funded research placements.
to Richella Murphy [Email Address Removed] only using the application form.
Application Form / Terms of Conditions can be obtained on the website:
The closing date for receipt of applications is 5pm, (GMT) 21st February 2022