Hosted by the Health Econimics Bristol group

Abstract: Methods have been developed for transporting evidence from Randomised Controlled Trials (RCTs) to target populations that use ‘real-world’ data for example from electronic health records (EHR). However, these approaches only allow for differences in baseline characteristics that are observed in both the RCT and the EHR data, and effect modification that is due to these observed measures (overt heterogeneity). Hence, these approaches do not recognise that treatment effects may be heterogenous due to unmeasured characteristics (essential heterogeneity).

In this talk I combine a target trial design with a local instrumental variable (LIV) approach to examine both forms of heterogeneity in assessing the comparative effectiveness of two second-line treatments for type 2 diabetes mellitus using data from the Clinical Practice Research Datalink (CPRD). These methods can provide useful new information to help target new treatments for individual patients, including subgroups excluded from RCTs. I will also discuss the role of IV methods in a future research agenda for making better use of EHR data to inform decision-making.

Biography: Richard Grieve is Professor of Health Economics Methodology London School of Hygiene and Associate Dean (Research) in the Faculty of Public Health and Policy at the London School of Hygiene and Tropical Medicine. Richard’s current research focuses on the development and application of casual inference approaches to improve the evidence available for decision-making. Richard leads a methodological study on developing instrumental variable methods for ‘personalised’ treatments, and applied studies evaluating emergency surgery, alternative treatments for type 2 diabetes mellitus, and radiotherapy for early-stage cancers.