My main research interests are in the development, assessment and translation of statistical methodology in health economics. Supported by a MRC Early Career Fellowship, my post-doctoral research focused on developing appropriate methods for addressing missing data in health economic evaluation, particularly, when data are hierarchical, non-randomised and missing not at random. Beyond missing data methodology, my current interests includes statistical approaches for handling time-varying confounding for estimating treatment effects in health economic studies that use observational data, in particular, routinely collected data. My interests in applied research include economic evaluations alongside clinical trials and large observational studies, with particular emphasis on digital and mental health.

PhD Students

I would welcome PhD proposals in the following areas:

   - statistical/econometric methods for handling confounding, missing data or hierarchical data in health economics

   - estimation of causal effects for health interventions and policies using routinely-collected data

   - health economic evaluations of digital health innovations.

   - evaluation of health interventions for the management of chronic conditions

Current students

   Tiyi Morris - Impact of primary care digital prescribing on health and social care service use (primary supervisor)

   Keyi Li - Impact of unemployment and job insecurity on health and social care utilisation (primary supervisor)

   Nick Swart - The health economics of clinical audits in the NHS (co-supervisor)

   Elizabeth Ingram - Investigating the social determinants of multimorbidity (co-supervisor)

   Helen Buxton - Measuring quality of life in patients with intellectual disability (co-supervisor)

   Maria Nicola - Cost-effectiveness of short pathways in endovascular AAA repair (co-supervisor)

Past students 

  Jenny Shand - The economics of multi-sectoral working for health

  Baptiste Leurent - Missing data methods on trial-based cost-effectiveness analysis.