William Henley, PhD

Professor William Henley holds a Chair of Medical Statistics at the University of Exeter Medical School and is Head of the Health Statistics Group. He has more than twenty five years of experience as an applied statistician in industry and academia. 

Professor Henley received his undergraduate training in Mathematics at the University of Oxford. He has held postdoctoral positions in statistical epidemiology at the University of Oxford and the Animal Health Trust. Prior to joining the University of Exeter, he was Associate Professor (Reader) in Statistics in the Centre for Health and Environmental Statistics at Plymouth University. In 2010, he was seconded to the National Institute for Health Research (NIHR) Collaboration for Leadership in Applied Health Research and Care for the South West Peninsula (PenCLAHRC). He is a member of the South West Regional Funding Committee for the NHS Research for Patient Benefit Programme, and a member of the NIHR Stratified Medicine Working Group for using observational studies, registries and cohorts to design stratified trials.

Professor Henley leads a programme of research on quasi-experimental analytic methods for conducting real-world evidence studies. Funded by the UK Medical Research Council Methodology Research Programme, his research group has developed extensions to the Prior Event Rate Ratio method, a promising approach to addressing hidden confounding in effectiveness studies using data from electronic medical records or large cohort studies. 

Professor Henley is Exeter Lead for the Clinical Practice Research Datalink (CPRD) and has been involved in the design, analysis and reporting of a wide range of pharmacoepidemiological studies using data from CPRD. He jointly leads a project funded by NIHR Research for Patient Benefit to evaluate whether statins modify the effectiveness of the influenza vaccine using data from primary care records. He is providing statistical leadership for several observational studies to stratify risk and assess interventions for COVID-19 and long COVID. He has authored more than 170 peer-reviewed publications and has a Google Scholar h-index of 50.