Why are the prices of new medicines so high and what can we do about it? (F8)

This blog was written during the European Health Forum Gastein 2016 (EHFG 2016

Value-based assessment of new medical technologies: towards a robust methodological framework for the application of multiple criteria decision analysis in the context of health technology assessment

In recent years, multiple criteria decision analysis (MCDA) has emerged as a likely alternative to address shortcomings in health technology assessment (HTA) by offering a more holistic perspective to value assessment and acting as an alternative priority setting tool. In this paper, we argue that MCDA needs to subscribe to robust methodological processes related to the selection of objectives, criteria and attributes in order to be meaningful in the context of healthcare decision making and fulfil its role in value-based assessment (VBA). We propose a methodological process, based on multi-attribute value theory (MAVT) methods comprising five distinct phases, outline the stages involved in each phase and discuss their relevance in the HTA process. Importantly, criteria and attributes need to satisfy a set of desired properties, otherwise the outcome of the analysis can produce spurious results and misleading recommendations. Assuming the methodological process we propose is adhered to, the application of MCDA presents three very distinct advantages to decision makers in the context of HTA and VBA: first, it acts as an instrument for eliciting preferences on the performance of alternative options across a wider set of explicit criteria, leading to a more complete assessment of value; second, it allows the elicitation of preferences across the criteria themselves to reflect differences in their relative importance; and, third, the entire process of preference elicitation can be informed by direct stakeholder engagement, and can therefore reflect their own preferences. All features are fully transparent and facilitate decision making

Multiple Criteria Decision Analysis (MCDA) for evaluating new medicines in Health Technology Assessment and beyond: the Advance Value Framework

Escalating drug prices have catalysed the generation of numerous “value frameworks” with the aim of informing payers, clinicians and patients on the assessment process of new medicines for the purpose of coverage and treatment selection decisions. Although this is an important step towards a more inclusive Value Based Assessment (VBA) approach, aspects of these frameworks are based on weak methodologies and could potentially result in misleading recommendations or decisions. A Multiple Criteria Decision Analysis (MCDA) methodological process based on Multi Attribute Value Theory (MAVT) is adopted for building a multi-criteria evaluation model. A five-stage model-building process is followed, using a top-down “value-focused thinking” approach, involving literature reviews and expert consultations. A generic value tree is structured capturing decision-makers’ concerns for assessing the value of new medicines in the context of Health Technology Assessment (HTA) and in alignment with decision theory. The resulting value tree (Advance Value Tree) spans three levels of criteria (top level criteria clusters, mid-level criteria, bottom level sub-criteria or attributes) relating to five key domains that can be explicitly measured and assessed: (a) burden of disease, (b) therapeutic impact, (c) safety profile (d) innovation level, and (e) socioeconomic impact. A number of MAVT modelling techniques are introduced for operationalising (i.e. estimating) the model, for scoring the alternative options, assigning relative weights of importance to the criteria, and combining scores and weights. Overall, the combination of these MCDA modelling techniques for the elicitation and construction of value preferences across the generic value tree provides 3 a new value framework (Advance Value Framework) enabling the comprehensive measurement of value in a transparent and structured way. Given the flexibility to meet diverse requirements and become readily adaptable across different settings, it could be tested as a decision-support tool for decision-makers to aid coverage and reimbursement of new medicines

Acquiring pharmaceutical industry assets in the UK: 1 + 1 = 1?

The recent AstraZeneca takeover bid from Pfizer puts pharmaceutical R&D once again on the public agenda. Three pertinent questions are (a) what can be expected from this acquisition, (b) what are the implications for the UK economy and science base, and (c) whether such a deal should go ahead. Although the key driver behind this acquisition would be an improvement in company performance and shareholder value, past evidence suggests that mergers and acquisitions (M&A) of large pharmaceutical companies imply a neutral net effect on productivity, if not a decline, with employment decreasing and R&D spend following a similar trend. Similarities between the two companies include dropping sales; however, relative to its size, AstraZeneca has a more promising R&D pipeline, especially in therapeutic areas where Pfizer’s strength is currently limited (e.g. oncology). Ensuring a portfolio diversification would make Pfizer’s takeover proposal a knight’s one, but history points towards a knave-like behavior

Value-based assessment of new medical technologies: towards a robust methodological framework for the application of multiple criteria decision analysis in the context of health technology assessment

In recent years, multiple criteria decision analysis (MCDA) has emerged as a likely alternative to address shortcomings in health technology assessment (HTA) by offering a more holistic perspective to value assessment and acting as an alternative priority setting tool. In this paper, we argue that MCDA needs to subscribe to robust methodological processes related to the selection of objectives, criteria and attributes in order to be meaningful in the context of healthcare decision making and fulfil its role in value-based assessment (VBA). We propose a methodological process, based on multi-attribute value theory (MAVT) methods comprising five distinct phases, outline the stages involved in each phase and discuss their relevance in the HTA process. Importantly, criteria and attributes need to satisfy a set of desired properties, otherwise the outcome of the analysis can produce spurious results and misleading recommendations. Assuming the methodological process we propose is adhered to, the application of MCDA presents three very distinct advantages to decision makers in the context of HTA and VBA: first, it acts as an instrument for eliciting preferences on the performance of alternative options across a wider set of explicit criteria, leading to a more complete assessment of value; second, it allows the elicitation of preferences across the criteria themselves to reflect differences in their relative importance; and, third, the entire process of preference elicitation can be informed by direct stakeholder engagement, and can therefore reflect their own preferences. All features are fully transparent and facilitate decision making

Advancing structured decision-making in drug regulation at the FDA and EMA

The recent benefit–risk framework (BRF) developed by the Food and Drug Administration (FDA) is intended to improve the clarity and consistency in communicating the reasoning behind the FDA's decisions, acting as an important advancement in US drug regulation. In the PDUFA VI implementation plan, the FDA states that it will continue to explore more structured or quantitative decision analysis approaches; however, it restricts their use within the current BRF that is purely qualitative. By contrast, European regulators and researchers have been long exploring the use of quantitative decision analysis approaches for evaluating drug benefit–risk balance. In this paper, we show how quantitative modelling, backed by decision theory, could complement and extend the FDA's BRF to better support the appraisal of evidence and improve decision outcomes. After providing relevant scientific definitions for benefit–risk assessment and describing the FDA and European Medicines Agency (EMA) frameworks, we explain the components of and differences between qualitative and quantitative approaches. We present lessons learned from the EMA experience with the use of quantitative modelling and we provide evidence of its benefits, illustrated by a real case study that helped to resolve differences of judgements among EMA regulators

Socio-economic burden of rare diseases: a systematic review of cost of illness evidence

Cost-of-illness studies, the systematic quantification of the economic burden of diseases on the individual and on society, help illustrate direct budgetary consequences of diseases in the health system and indirect costs associated with patient or carer productivity losses. In the context of the BURQOL-RD project (“Social Economic Burden and Health-Related Quality of Life in patients with rare diseases in Europe”) we studied the evidence on direct and indirect costs for 10 rare diseases (Cystic Fibrosis [CF], Duchenne Muscular Dystrophy [DMD], Fragile X syndrome [FXS], Haemophilia, Juvenile Idiopathic Arthritis [JIA], Mucopolysaccharidosis [MPS], Scleroderma, Prader-Willi Syndrome [PWS], Histiocytosis and Epidermolysis Bullosa [EB]). A systematic literature review of cost of illness studies was conducted using a keyword strategy in combination with the names of the 10 rare diseases. Available disease prevalence in Europe was found to range between 1-2 per 100,000 population (PWS, a sub-type of Histiocytosis, and EB) up to 42 per 100,000 population (Scleroderma). Overall, cost evidence on rare diseases appears to be very scarce (a total of 77 studies were identified across all diseases), with CF (n = 29) and Haemophilia (n = 22) being relatively well studied, compared to the other conditions, where very limited cost of illness information was available. In terms of data availability, total lifetime cost figures were found only across four diseases, and total annual costs (including indirect costs) across five diseases. Overall, data availability was found to correlate with the existence of a pharmaceutical treatment and indirect costs tended to account for a significant proportion of total costs. Although methodological variations prevent any detailed comparison between conditions, most of the rare diseases examined are associated with significant economic burden, both direct and indirect

Using health technology assessment to assess the value of new medicines: results of a systematic review and expert consultation across eight European countries

Although health technology assessment (HTA) systems base their decision making process either on economic evaluations or comparative clinical benefit assessment, a central aim of recent approaches to value measurement, including value based assessment and pricing, points towards the incorporation of supplementary evidence and criteria that capture additional dimensions of value