NHS – University of Liverpool and NHSE

Innovation Placement 3 with the NHS/University of Liverpool

In collaboration with the University of Liverpool and their partnership with NHSE and HDRUK, DiRAC is pleased to invite applications for a 6-month Innovation Placement focussing on the link between healthcare data and medication data and outcomes.

Host organisation: University of Liverpool
Location: University of Liverpool or remote


Medicines are the most common intervention in human health. In the UK we spend £20 billion per annum on medicines, however it is not known if these medicines are used as intended or if they are having the effects they are intended to have. This is because health care outcome data is not routinely linked to medicines data. Moreover, medicines data is not all stored in the same place, rather is siloed across primary and secondary specialist care.  

To overcome this we are working with partners including but not limited to NHS England (NHSE), Health Data Research UK (HDRUK) to begin to address these limitations by identifying and linking medicines and health care data.  

This work includes a number of work streams:

  • Identification of data sets and governance around their use 
  • Permissions and transfer of data sets into a secure data environment 
  • Curation of medicines data so they are available to be readily used for healthcare and research 
  • Linkage of medicines to primary and secondary health outcome data 

We will then use the above to build tools for health care professionals and researchers to assess how medicines are being used across the health care system and with specific examples begin to show if they are being used as intended and if they are cost-effective and safe.  

The Project

The Project will model the effect of medicines based on the prescription histories of medicines and linked health care data. 

The project will use both ML and statistical models to assess how changes of uses of medicines occur through a patient period and patterns of common and rare medicines evolve. 

  • This will require creation/adaption of dashboards, general and disease specific to determine how and where medicines are being used for both individual patients and groups of patients. 
  • The prescription and patient health care data will need to be linked and then used to train a Deep Learning Neural Networks so that (i) heuristics can be generated and (ii) they can be retrained with each new data update. 
  • Proto-heuristics on the following two areas; the effects of medicines on new patients, and poly-pharmacy on patients will be generated for both specific patients and groups of patients for further study. 
  • The proto heuristics generated above will then be compared with the results of current statistics methods used in the above areas to determine their potential efficacy and to suggest improvements. 

These investigations will take place in a secure Health care data TRE and the data will be anonymised for the purposes of this project. 

Candidate profile

The successful candidate will posses the following experience:

  • Good understanding of data and data structures and models 
  • Good working knowledge of data bases 
  • Coding skills in python and other languages 
  • Statistical skills and use of relevant packages e.g R 

This placement is now closed to applications.