Cookies on this website

We use cookies to ensure that we give you the best experience on our website. If you click 'Accept all cookies' we'll assume that you are happy to receive all cookies and you won't see this message again. If you click 'Reject all non-essential cookies' only necessary cookies providing core functionality such as security, network management, and accessibility will be enabled. Click 'Find out more' for information on how to change your cookie settings.

amanda nicholson.jpg


- BA Medical Science, University of Cambridge.
- MB BS, St Bartholomew's Hospital, University of London.
- MSc Epidemiology, London School of Hygiene and Tropical Medicine.
- Clinical Lecturer in Epidemiology & Public Health, University College London.
- PhD Epidemiology, University College London.
- Clinical Research Fellow, Central and Eastern Europe Research Group, University College London.

Current post:

- Research Fellow in Primary Care Epidemiology. Brighton & Sussex Medical School

Research focus:

As an epidemiologist specialising in social inequalities in health and psychosocial influences on health, my focus has recently shifted to the potential of using primary care electronic patient records as a research resource. My current research activity concentrates on developing skills to access and use these data for research. I am using the GPRD (a large UK-based primary care database) to examine the incidence and management of two diverse health conditions : pelvic inflammatory disease and rheumatoid arthritis. I will examine patient and practice factors associated with suboptimal management of these conditions. Because patient data are collected for clinical care rather than research, there is considerable methodological work to be done to ensure that the data can be reliably used for research. One major issue is the balance between coded data and data entered as free text. I am involved in a project funded by the Wellcome Trust (PI: Prof. J Cassell) which aims to use natural language processing techniques to access textual data that are not usually available to researchers.