Experimental designs in clinical research are commonly focused upon demonstrating that a particular treatment is better on average than an alternative treatment. The reporting of an average treatment effect is typical of this literature. Yet treatment response for some patients will differ markedly from the average. Observed characteristics at a patient level, such as age, sex, ethnicity and severity of disease, may all determine a patient’s response to treatment as well as influencing their cost of care. Identifying baseline covariates in which treatment response may differ markedly from the population average treatment effect is of central interest to policy makers, reimbursement agencies as well as informing clinical decision making in an age of precision medicine. Recent innovations in healthcare have provided greater opportunities for clinical decision-making through the tailoring of treatment towards individual patients. This process of personalisation of care, moving from an average to an individual patient, for clinical outcomes remains elusive in the economic evidence used to support decision-making for the adoption of new innovations across healthcare systems. The disconnect between economic outcomes and the information required by clinicians, patients and policymakers can be mitigated by deriving more individualised cost-effectiveness results for use in healthcare. This PhD will apply advanced econometric and big data methods for heterogeneous treatment effects to generate economic results that move beyond simple averages of costs and health outcomes. The different candidate methods will be evaluated at specific stages relevant to all healthcare innovations, reflecting key challenges in the life-cycle of economic evidence. This will include the i) Early-phase evaluation of novel therapeutics where important clinical and economic information may be imprecise, missing or undefined; and ii) Late-stage evaluation where decision-makers are required to make a choice among alternatives based on the best available clinical and economic evidence at that point in time. The PhD will also extend on the results from the early and late-stage evaluation by accommodating patient heterogeneity into distributional cost-effectiveness analysis across multiple outcomes of interest to reduce existing health inequalities. Project design, analysis and dissemination strategies will be co-produced with the Office of Health Economics (OHE), a UK-based registered charity and independent research organisation in global health economics. By partnering with OHE, there will be distinct opportunities for disseminating and contextualising research results into global health systems from different stakeholder perspectives, including clinical, policy and industry assessments. This will also be supported through mentoring activities within OHE during the PhD through access to experts in value-based pricing, stratified healthcare, innovation and decision-making in healthcare. The PhD candidate will be invited to undertake a three-month internship with OHE to facilitate knowledge exchange and support developmental training opportunities.
For more information including how to apply please click here: PhD studentship opportunities | Faculty of Medicine | Imperial College London