researching, developing and applying a new value framework for the purpose of health technology assessment

Introduction: Current evaluation approaches for new medical technologies are problematic for a plethora of reasons relating to measuring their expected costs and consequences, but also due to hurdles in turning assessed information into coverage decisions. Most adopted methodologies focus on a limited number of value dimensions, despite the fact that the value of new medicines is multi-dimensional in nature. Explicit elicitation of social value tradeoffs is not possible and decision-makers may adopt intuitive or heuristic modes for simplification purposes, based on ad hoc procedures that might lead to arbitrary decisions. Objectives: The objective of the present thesis is to develop and empirically test a methodological framework that can be used to assess the overall value of new medical technologies by explicitly capturing multiple aspects of value while allowing for their tradeoffs, through the incorporation of decision-makers’ preferences in a structured and transparent way. The research hypothesis is that Multiple Criteria Decision Analysis (MCDA) can provide a methodological option for the evaluation of new medicines in the context of Health Technology Assessment (HTA), to support decision-making and contribute to more efficient resource allocation. Methods and Empirical Evidence: The first paper proposes a conceptual methodological process, based on multi-attribute value theory (MAVT) methods comprising five distinct phases, outlining the stages involved in each phase and discusses their relevance in the HTA context. The second paper conducts a systematic literature review and expert consultation in order to investigate the practices, processes and policies of value-assessment for new medicines across eight European countries and identifies the evaluation criteria employed and how these inform coverage recommendations as part of HTA. The third paper develops a MAVT value framework for HTA, incorporating a generic value tree for new medicines composed from different levels of criteria that fall under five value domains (i.e. therapeutic, safety, burden of disease, innovation and socio-economic), together with a selection of scoring, weighting and aggregating techniques. In the fourth and fifth papers, the value framework is tested empirically by conducting two real-world case studies: in the first, the value tree is adapted for the evaluation of second-line biological treatments for metastatic colorectal cancer (mCRC) patients having received prior oxaliplatin-based chemotherapy; in the second, the value tree is conditioned for the evaluation of third-line treatments for metastatic castrate resistant prostate cancer (mCRPC) patients having received prior docetaxel chemotherapy. Both case studies were informed by decision conferences with relevant expert panels. In the mCRC decision conference multiple stakeholders participated reflecting the composition of the English National Institute for Health and Care Excellence (NICE) technology appraisal committees, whereas in the mCRPC decision conference a group of evaluators participated from the Swedish Dental and Pharmaceutical Benefits Agency (TLV), thereby adopting the TLV decision-making perspective. Policy Implications: The value scores produced from the MCDA process reflect a more comprehensive benefit metric that embeds the preferences of stakeholders and decisionsmakers across a number of explicit evaluation criteria. The incorporation of alternative treatments’ purchasing costs can then be used to derive incremental cost value ratios based on which the treatments can be ranked on ‘value-for-money’ grounds, reflecting their incremental cost relative to incremental value. Conclusion: The MCDA value framework developed can aid HTA decision-makers by allowing them to explicitly consider multiple criteria and their relative importance, enabling them to understand and incorporate their own preferences and value trade-offs in a constructed and transparent way. It can be turned into a flexible decision tool for resource allocation purposes in the coverage of new medicines by payers but could also be adapted for other decision-making contexts along their development, regulation and use.