Issues related to the economic analysis of genomic diagnostic technologies in the UK National Health Service: an exploration of methods

This thesis explores the empirical and methodological issues that arise when conducting economic analyses of genomic technologies in the UK National Health Service. The main focus of the thesis is the identification of the most appropriate economic evaluation approach to use in this context. Health economists are currently uncertain as to whether existing extra-welfarist approaches are sufficient to evaluate genomic technologies. Clarification is required because alternative methods, such as the welfarist approach, may lead to different adoption decisions, which will impact on population health. The advantages and disadvantages of alternative approaches are demonstrated using a clinical case study: the use of genomic testing to guide treatment decisions in chronic lymphocytic leukaemia (CLL). Two forms of extra-welfarist economic evaluation are conducted – a cost-effectiveness analysis (CEA) and a cost-utility analysis (CUA) – along with a welfarist economic evaluation which took the form of a cost-benefit analysis (CBA), informed by a discrete choice experiment (DCE). These analyses consider several test-treatment strategies, reflecting different combinations of testing and the use of both existing therapies and new treatments such as ibrutinib. Information is also generated on patient preferences in this context, via the DCE, and the results of a survey are presented in which stakeholders are asked to consider which form of economic evaluation best captures the true costs and benefits of genomic testing in CLL. The results of the CEA, CUA and CBA all indicate that the optimal strategy is to not adopt genomic testing in this context. The different approaches are then compared to assess their relative merits. The key finding – which is supported by the stakeholder survey – is that the extra-welfarist approach to economic evaluation is most appropriate when assessing genomic interventions. However, an evolution in methods is required to ensure that the results of these analyses provide decision-makers with sufficient information to facilitate the efficient allocation of scarce healthcare resources in this context.