Research

My main interests are: investigating sources and effects of bias in epidemiological studies, multivariate statistical analysis and  information visualisation.

My current project involves developing methods to help researchers  make better use of primary care electronic health records. I am using data from the General Practice Database to:

1.  investigate symptoms and delays in diagnosis in patients with ovarian cancer and using free text to see how much the lack of it biases estimates,

2. develop practice-based quality scores for montioring data quality,

3. develop visualisation tools to make the information contained in the records more available to researchers.

Prior to becoming a medical statistician, I specialised in pattern recognition analysis applied to magnetic resonance spectra, and developed methods to help radiologists interpret spectra of brain tumours (latterly as scientific manager of a large EU funded project, INTERPRET http://azizu.uab.es/INTERPRET/index.html).

My work as a statistician has involved working with data from two large cohort studies (Millennium cohort and the Iraq war study). Since returning to Sussex  I have been analysing data from the General Practice research database.  Data from electronic patient records has the advantage over survey data in that it is not subject to recall or non-response bias. However there are many challenges to be overcome in order to realize the full potential of electronic patient record databases for health service research.

Current Research:

I am a co-investigator (Principal investigator at Sussex) of a Technology strategy board funded project entitled "Visualisation of the Quality of Electronic Health Records for Clinical Research" (QViz) April 2011-October 2012.

This is a collaborative project with Brighton-based Dataline Software, which has wide experience in the design and implementation of highly ergonomic IT systems; and General Practice Research Database (GPRD), which collects electronic patient records from many GP practices across the UK. My role, together with Natasha Beloff (coinvestigator) is to develop statistical pattern recognition techniques for scoring patient records with respect to data quality. These will be part of  a system (QViz) that will provide quick and effective visualisation of patient record quality. Since findings arising from patient data have potential public health and safety implications it is of crucial importance that any data used for research is of high quality. QViz will be used to help set up feasibility studies for Randomised Controlled Trials (RCTs), which are the key to proving the efficacy and safety of new medicines. QViz will allow researchers to interactively investigate and select GP practices based on data quality and the suitability of the patient base for a particular study.

I am also co-investigator of a multidisciplinary project funded by the Wellcome Trust entitled  “The ergonomics of electronic patient records: an interdisciplinary development of methodologies for understanding and exploiting free text to enhance the utility of primary care electronic patient records” under the Joint Initiative in Electronic Patient Records and Databases in Research Scheme (Jan 2009- June 2012). The project is a joint collaboration between the Brighton and Sussex Medical School (BSMS) and the School of Informatics, the General Practice Research Database and University College London. My role is to lead the statistical work and the visualisation workstream.