HOD2: Instrumental Variable approaches for estimating heterogeneity of treatment effects to inform personalisation using electronic health records

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Personalised medicine aims to provide the right treatment for the right patient at the right time. The evidence to inform personalised medicine can come from patient's electronic health records. However, there are several problems with using these data to compare outcomes for groups of patients who receive alternative treatments. First, the patients in the two groups may differ according to characteristics that are not measured (for example, the patient's frailty). Second, the extent to which an intervention leads to an improvement in the patients' outcome (or harm) may differ according to these unmeasured characteristics. Third, it is often unknown which patient groups benefit from which interventions. Methods for addressing these three problems are currently unavailable. This project will develop new methods that resolve these problems and provide more accurate estimates of the effectiveness and harms of new treatments that apply to individual patients. In particular, we will develop new methods that make more realistic assumptions. Instead of assuming that we know which patient groups benefit from which treatment, we will develop approaches that can learn from the data about which subgroups benefit from which treatment. We will examine how well these new methods work in practice by testing them as part of new studies. One of these studies will examine which patients benefit from emergency surgery for common acute conditions (e.g. appendicitis), and uses data from 1.5 million hospital episodes. The other study considers which patients with type 2 Diabetes Mellitus benefit from new, more costly oral treatments, and uses prescription data from General Practice databases for 25,000 patients. Our new methods will enable us to provide more accurate, relevant evidence about which interventions work best for which patients with these two conditions. We will provide a general framework for these methods that can be applied across many different disease areas and countries. To help future studies, we will provide tutorials and guidance on using and adapting these methods in different contexts. We will run short courses and workshops to assist those designing, analysing and interpreting studies that use electronic health records to inform treatment decisions for individual patients.