Valeurs seuils pour le rapport coût-efficacité en soins de santé - KCE

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38 ICER Thresholds KCE Reports 100 • The most commonly mentioned facilitators were: personal contact between researchers and policymakers; timeliness and relevance of the research; research that included a summary and clear recommendations; research that confirmed current policy or endorsed self-interest; community or client demand for the research; and research that included effectiveness data. • The most commonly mentioned barriers were: absence of personal contact between researchers and policy makers; lack of timeliness or relevance of research; mutual mistrust; power and budget struggles; poorquality research and political instability or high turnover of policymaking staff. The review also clarifies that "Use" of research can be viewed in three different ways: 1) direct use (research directly affects the decision); 2) selective use (research is selected to legitimate pre-determined positions); and 3) enlightening use (research helps to set new benchmarks for what is possible and deepens understanding). Lavis et al. 123 distinguish four broad categories or models for developing evidence-based policy making. These models are presented as a typology, but can be applied either alone or in combination. • Enhancing push factors (Model A) - “Push” efforts are generally led by researchers, or communications staff of research institutes and aim to increase awareness of research evidence among policy makers and civil society. Such efforts are well suited to situations where the potential research users are unaware they should be considering a particular message or in some cases would prefer to continue to disregard evidence. HTA and evidence based research agencies operate most of the time within this model. • Enhancing pull factors (Model B) - User-pull and/or demand for research evidence are critical for research evidence uptake. It occurs when policy and decision makers identify an information gap and request evidence or commission research to fill this gap. These kinds of demands are often handled by policy advisory units within Ministries of Health and/or other policy making or technical support units (sometimes also applied research by universities or research institutes) • Supporting exchange efforts (Model C) - Exchange efforts occur when producers and users of research work in partnerships and establish links. • Supporting implementation of an integrated model (Model D) - integrated models combine elements of the three models described above. Key points • Decisions are in most of the cases not taken on the basis of scientific or technical information only, but on a mix of information sources. • Several barriers and facilitators have been identified for developing scientifically informed decision making. • Knowledge and research evidence can be used by decision makers in three different ways: direct, selective and enlightening. • Knowledge brokering is an important topic to be further explored in order to support decision makers. • The process of ‘knowledge brokering’ for policy makers can be summarized in four models: an information push model, an information pull model, an exchange model and an integrated model.
KCE reports 100 ICER Thresholds 39 3.3 EMPIRICAL EVIDENCE ON THE USE OF ECONOMIC EVALUATIONS IN HEALTH CARE DECISION MAKING “…, the results of rigorous clinical trials and sensitive modelling techniques tell us little about how data on clinical and cost effectiveness are interpreted at the level of national policy formulation”. 124 It has been repeatedly argued in this report that health care decision making is assumed, in an ideal situation, to be focussing on an optimal allocation of available resources with the purpose of maximising health. Decision makers are expected to focus on interventions that provide the most health gains for a given expenditure of resources. 114 Moreover, a systematic approach is expected to increase transparency and consistency in the decisions taken. 125 A particular branch of empirical research has been studying the impact of economic evaluation studies on the policy making processes. The successful application of costeffectiveness principles has been documented as being a problem in different health care systems. 114, 126-128 Several barriers to the use of the results of economic evaluations have been observed. 129 The barriers have been summarized as issues of accessibility of research evidence and (scientific, structural/institutional and ethical/political) acceptability of research evidence. 17 A systematic review on the use of economic evaluations in the UK revealed that a number of features of the decision making process hamper the use of cost-effectiveness analysis, such as capacity to understand economic analysis, attitudes to economic evaluations including concerns on the basis of analysis and its use, the scope of the research questions and the scope of the policy question. 130 A survey in nine European countries documents that decision makers use different sources of economic information, but that many decision makers also believe that a lot of the information obtained can be biased through sponsorship. 112 Despite the widespread use of modelling and cost-effectiveness ratios for health care decision support, there are concerns with regard to the quality of the models: 131 concerns exist about the transparency and validity of the models, the lack of high level clinical data, possible bias when observational data are used and difficulties with extrapolation. In order to deal with these perceptions and increase the legitimacy of research findings major efforts are being devoted to the development of guidelines on how to perform economic evaluation. Moreover, decision makers do not fully understand health economics outcomes statements such as in particular incremental cost-effectiveness ratios, willingness to pay, QALYs etc. 77 or consider them to be irrelevant. 132 Decision makers are convinced that although economic evaluations can be useful in principle, in practice their usefulness is considered limited as the studies do not always apply to the particular decision making context. 133-136 Economic evaluations seldom take contextual factors into consideration 137 although health care systems and health insurance regimes differ, and particular cultural, social, economic and political conditions are important background variables to understand decision making procedures. A recent comparison of drug reimbursement decisions between the UK, Australia and New Zealand concluded that different factors might drive reimbursement decisions in different countries. 138 Drugs that have the potential to save lives (e.g. leukaemia) or alleviate particularly complex diseases (e.g. multiple sclerosis) were reimbursed in all three countries. For other drugs, severity of the disease becomes important in the elements considered during the decision making process. Perceptions of disease severity might differ between countries. Raftery (2008) suggests that “the perception of ‘dread’ diseases depends on social factors, such as patient lobbying and public perceptions. Decisions on which drugs to fund, in the final analysis, depend on their political and social acceptability”. 138 Timeliness of information is a particular issue. Cost-effectiveness analyses crucially depend on evidence of effectiveness and therefore always come later in the life cycle of a technology. Healthcare decisions, however, are frequently needed in the early stages of a technology’s life cycle.
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Valeurs seuils pour le rapport coût-efficacité en soins de santé - KCE

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