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Dr Elizabeth Ford

Dr Elizabeth Ford (MA, DPhil)

Senior Lecturer in Primary Care Research
E: E.M.Ford@bsms.ac.uk
T: +44 (0)1273 641974
Location: Watson Building, University of Brighton, Falmer, Brighton, BN1 9PH

Area of expertise: GP patient records, mental health, epidemiology

Research areas: Primary Care and Public Health, Dementia

BACKGROUND IMAGE FOR PANEL

Biography

Elizabeth Ford is Senior Lecturer in Primary Care Research. After studying for an undergraduate degree in Psychology from Oxford University, Elizabeth came to the University of Sussex in 2004 to take up a DPhil in clinical health psychology investigating the influences on women’s perceptions of childbirth and their development of post-traumatic stress disorder as a result of traumatic birth.

Elizabeth held postdoctoral positions at University of Sussex, Barts and the London Medical School, and at SHORE-C in BSMS. She worked as Research Fellow in Primary Care Epidemiology in the Department of Primary Care and Public Health at BSMS from 2011 to 2016, and as Lecturer in Research Methodology from 2016 to 2018. Her research focuses on mental health and dementia in primary care and community settings, with a particular focus on novel methods for using electronic health data such as patient records.

Research

Elizabeth’s current research uses electronic GP patient records as data for epidemiological studies in dementia and mental health. She works with epidemiologists, data scientists and social scientists to understand how clinicians interact with patient record systems, and to work out ways of extracting the most useful and accurate information from these records. Her work focuses on the interface between human and computer in the clinical environment, enabling better understanding of data quality and developing appropriate analytical methods for dealing with complex, multi-dimensional clinical data. She also carries out studies to understand the public’s opinions on the use of NHS patient data for research.

See her current project on dementia here >

Elizabeth’s previous research focussed on postnatal mental health and family relationships, and the influence of social relationships (at home and work) on common mental disorders such as anxiety and depression. In addition, she looked at how care received during diseases, such as cancer, can influence mental health.

BACKGROUND IMAGE FOR PANEL

Teaching

Elizabeth supports research methodology, ethics and data governance for Module 404 “Individual Research Project” in the medical undergraduate curriculum. She supports students and supervisors in all aspects of research project design, navigating ethics and governance, and data analysis (statistical or qualitative).

She also teaches research methods and statistics in year 2 and 3 of the undergraduate medical curriculum, and on postgraduate courses. She regularly supervises individual research projects for fourth year medical students as well as masters and PhD students.

Selected Publications

Ford E., Sheppard, J., Oliver, S., Rooney, P., Banerjee, S., Cassell. J. (2021) Automated detection of patients with dementia whose symptoms have been identified in primary care but have no formal diagnosis: a retrospective case–control study using electronic primary care records. BMJ Open 2021;11:e039248. doi:10.1136/bmjopen-2020-039248

Ford E, Starlinger J, Rooney P et al. (2020) Could dementia be detected from UK primary care patients’ records by simple automated methods earlier than by the treating physician? A retrospective case-control study. Wellcome Open Res 2020, 5:120 (https://doi.org/10.12688/wellcomeopenres.15903.1)

Ford, E., Rooney, P., Hurley, P., Oliver, S., Bremner, S., and Cassell, J. (2020) Can the use of Bayesian analysis methods correct for incompleteness in electronic health records diagnosis data? Development of a novel method using simulated and real-life clinical data. Front. Public Health 8:54. doi:10.3389/fpubh.2020.00054

Ford, E., Rooney, P., Oliver, S. et al. (2019) Identifying undetected dementia in UK primary care patients: a retrospective case-control study comparing machine-learning and standard epidemiological approaches. BMC Med Inform Decis Mak 19, 248 doi:10.1186/s12911-019-0991-9

Ford, E., Greenslade, N., Paudyal, P., Bremner, S., Smith, H.E., Banerjee, S., Sadhwani, S., Rooney, P., Oliver, S. and Cassell, J. (2018). Predicting dementia from primary care records: a systematic review and meta-analysis. PLoS ONE 13(3): e0194735.

Ford E, Curlewis K, Squires E, Griffiths LJ, Stewart R and Jones KH (2021) The Potential of Research Drawing on Clinical Free Text to Bring Benefits to Patients in the United Kingdom: A Systematic Review of the Literature. Frontiers in Digital Health 3:606599. doi: 10.3389/fdgth.2021.606599

Ford E, Shepherd S, Jones K and Hassan L (2021) Toward an Ethical Framework for the Text Mining of Social Media for Health Research: A Systematic Review. Frontiers in Digital Health 2:592237. doi: 10.3389/fdgth.2020.592237

Ford, E., Kazempour, Y., Cooper, M., Katikireddi, SV., Boyd, A. (2020) Media content analysis of general practitioners’ reactions to care.data expressed in the media: what lessons can be learned for future NHS data sharing initiatives? BMJ Open 10(9), e038006

Jones KH, Ford, E., Lea NC, Griffiths LJ, Hassan L, Squires EL, Heys SM and Nenadic G (2020) Towards the development of data governance standards for using clinical free-text data in health research. J Med Internet Res 2020; 22(6):e16760, DOI:10.2196/16760

Ford, E., Oswald, M., Hassan, L., Bozentko, K., Nenadic, G., and Cassell, J. (2020) Should free text data in electronic medical records be shared for research? A citizens’ jury study in the United Kingdom. Journal of Medical Ethics 46(6), pp.367-377. doi:10.1136/medethics-2019-105472