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      Factors Predicting Medicare National Coverage : An Empirical Analysis

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          Abstract

          Interventions considered to be particularly controversial or expected to significantly impact the Medicare program in the United States are considered in National Coverage Determinations. Medicare coverage for such interventions is limited to those deemed "reasonable and necessary" for the diagnosis or treatment of an illness or injury. What constitutes reasonable and necessary has not, however, been clearly defined.

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          Does NICE have a cost-effectiveness threshold and what other factors influence its decisions? A binary choice analysis.

          The decisions made by the National Institute for Clinical Excellence (NICE) give rise to two questions: how is cost-effectiveness evidence used to make judgements about the 'value for money' of health technologies? And how are factors other than cost-effectiveness taken into account? The aim of this paper is to explore NICE's cost-effectiveness threshold(s) and the tradeoffs between cost effectiveness and other factors apparent in its decisions. Binary choice analysis is used to reveal the preferences of NICE and to consider the consistency of its decisions. For each decision to accept or reject a technology, explanatory variables include: the cost per life year or per QALY gained; uncertainty regarding cost effectiveness; the net cost to the NHS; the burden of disease; the availability (or not) of alternative treatments; and specific factors indicated by NICE. Results support the broad notion of a threshold, where the probability of rejection increases as the cost per QALY increases. Cost effectiveness, together with uncertainty and the burden of disease, explain NICE decisions better than cost effectiveness alone. The results suggest a threshold somewhat higher than NICEs stated 'range of acceptable cost effectiveness' of pound 20,000-30,000 British pounds per QALY--although the exact meaning of a 'range' in this context remains unclear. Copyright 2004 John Wiley & Sons, Ltd.
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            The role of value for money in public insurance coverage decisions for drugs in Australia: a retrospective analysis 1994-2004.

            To analyze the relative influence of factors in decisions for public insurance coverage of new drugs in Australia. Evidence presented at meetings of the Australian Pharmaceutical Benefits Advisory Committee (PBAC) that makes recommendations on coverage of drugs under Pharmaceutical Benefits Scheme. All major submissions to the PBAC between February 1994 and December 2004 (n = 858) if one of the outcomes measured was life year gained (n=138) or quality-adjusted life years (QALYs) gained (n=116). Clinical significance, cost-effectiveness, cost to government, and severity of disease were significant influences on decisions. Compared to the average submission, clinical significance increased the probability of recommending coverage by 0.21 (95% confidence interval [CI] 0.02 to 0.40), whereas a drug in a life-threatening condition had an increased probability of being recommended for coverage of 0.38 (0.06 to 0.69). An increase in $A10,000 from a mean incremental cost per QALY of $A46,400 reduced the probability of listing by 0.06 (95% CI 0.04 to 0.1). The PBAC provides an example of the long-term stability and coherence of evidence-based coverage and pricing decisions for drugs that weighs up the evidence on clinical effectiveness, clinical need, and value for money. There is no evidence of a fixed public threshold value of life years or QALYs, but willingness to pay is clearly related to the characteristics of the clinical condition, perceived confidence in the evidence of effectiveness and its relevance, as well as total cost to government.
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              "Yes", "No" or "Yes, but"? Multinomial modelling of NICE decision-making.

              The National Institute for Health and Clinical Excellence (NICE) issues mandatory guidance on health technologies to the UK NHS, based on clinical evidence, cost-effectiveness and other considerations. However, the exact factors considered, their relative importance and tradeoffs between them are not made explicit. Previous research modelled NICE decisions as a binary choice (accept/reject) dependent on cost-effectiveness, amongst other variables. This paper proposes and tests an alternative model of decision-making that may better represent the "yes, but..." nature of many NICE decisions. Decisions were categorised as "recommended for routine use", "recommended for restricted use" or "not recommended". The NICE appraisal process was modelled as a single decision between the three categories. Multinomial logistic regression techniques were used to evaluate the impact of: quantity/quality of clinical evidence; cost-effectiveness; decision date; existence of alternative treatments; budget impact; technology type. Results suggest that interventions supported by more randomised trials are more likely to be recommended and endorsed for routine use. Higher cost-effectiveness ratios increased the likelihood of interventions being rejected rather than recommended for restricted use but did not significantly affect the decision between routine and restricted use. Pharmaceuticals, interventions appraised early in the NICE programme and those with more systematic reviews were also less likely to be rejected, while patient group submissions made a recommendation for routine rather than restricted use more likely. The presence of factors affecting the decision between routine and restricted use but not that between routine use and rejection suggests that modelling these three outcomes reflects NICE decision-making more closely than binary-choice analyses.
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                Author and article information

                Journal
                Medical Care
                Medical Care
                Ovid Technologies (Wolters Kluwer Health)
                0025-7079
                2012
                March 2012
                : 50
                : 3
                : 249-256
                Article
                10.1097/MLR.0b013e318241eb40
                22193418
                da35af96-70fb-4f76-8e92-5fe91fad87da
                © 2012
                History

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