The role of economic modelling in informing the allocation of scarce resources through health technology and health research impact assessment: a critical review

Abstract

Over the last 30 years, economic evaluation has increasingly been used as a tool to inform the allocation of scarce healthcare resources. For an economic evaluation of healthcare interventions to inform optimal decisions, it is often necessary to understand the effects and costs of an intervention across the lifetime of a patient. In the absence of primary data to inform this, economic models are required to extrapolate beyond observed data, collate best available evidence from disparate sources and conduct experiments that could not be performed in a real-life setting. As well as allocating resources to the provision of existing interventions, public monies help conduct medical research into potential new interventions that may deliver future health benefits. Given the opportunity cost of investing in research into new interventions, over the provision of existing interventions, policymakers and funders have shown interest in understanding the economic value, or impact, of publicly funded medical research. Based on logic models developed in the research impact literature, the outputs of economic evaluations can be used in models to assess the return on investment from bodies of medical research. This thesis presents a critical review alongside a portfolio of seven published works concerned with assessing the value of: (a) healthcare interventions; and (b) funding health research. Chapter 1 presents background to contextualise the works and outline the central themes. Chapter 2 explores the overarching methods and contribution to knowledge and Chapter 3 assesses the impact of the portfolio. The critical review demonstrates the extensive role the methods developed for health technology assessment can play in research impact assessment and the remaining boundaries and challenges. Self-reflection on the contribution to knowledge and impact of the works, combined with formal bibliometric techniques suggest the work has made significant contribution and had identifiable impact across targeting of future research (by centrality or significant contribution to other research), influencing policy (including clinical guidelines), and potential impact on health outcomes (through implemented interventions).