Evolution of Primary Care Workforce: Analysing the Impact of ARRS and PCNs on Job Offerings in the UK (2019-2024)

Supervisors: Dr Catia Nicodemo

For this project we are looking for a candidate with strong skills in working with text data and machine learning. The ideal candidate should have experience in natural language processing, as they'll need to analyse job descriptions and extract meaningful insights about changing skill requirements in primary care roles.

The project focuses on examining the impact of the Additional Roles Reimbursement Scheme (ARRS) and Primary Care Networks (PCNs) on job offerings in the UK healthcare sector from 2019 to 2024. It aims to quantify changes in job advertisements, analyse trends in skill requirements, and investigate geographical variations in the adoption of new roles.

The candidate will be working with a large dataset of job advertisements from Adzuna, spanning from 2017 to 2024. They should be comfortable with data cleaning, preprocessing, and applying advanced analytical techniques to extract meaningful patterns from this rich dataset.

This project would suit someone with a background in economics, data science, or a related field who has experience statistics. Familiarity with geospatial analysis would also be beneficial for examining regional variations in ARRS adoption. The ideal candidate should also have an interest in health policy and workforce development, as the project aims to provide valuable insights for policymakers and contribute to the ongoing discussions about primary care workforce planning in the NHS.

This research is part of a larger programme at the University of Oxford's Nuffield Department of Primary Care Health Sciences, offering the opportunity to collaborate with experts in the field and contribute to high-impact publications.