188 research outputs found

    No exit: next steps to help promote South Pacific peace and prosperity

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    This paper explores contemporary official and scholarly thinking on aid, development, conflict prevention and strategic shaping to try to identify promising avenues to promote regional growth and stability in a tight budget environment. Overview As Australia focuses on its global interests in a changing and challenging international environment, there’s a danger that we’ll lose sight of important constants of history and geography. We don’t have an either/or choice to focus on near or distant security imperatives. While the Australian Government’s decision to lift defence funding will help with this, cutting aid to help offset that boost may prove counterproductive. We also need to further improve the quality of our aid and regional diplomacy, as well as the hard and soft aspects of our security engagement. This paper suggests some useful first steps for doing so

    Budget allocation and the revealed social rate of time preference for health

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    Appropriate decisions based on cost-effectiveness evaluations of health care technologies depend upon the cost-effectiveness threshold and its rate of growth as well as some social rate of time preference for health. The concept of the cost-effectiveness threshold, social rate of time preference for consumption and social opportunity cost of capital are briefly explored before the question of how a social rate of time preference for health might be established is addressed. A more traditional approach to this problem is outlined before a social decision making approach is developed which demonstrates that social time preference for health is revealed through the budget allocations made by a socially legitimate higher authority. The relationship between the social time preference rate for health, the growth rate of the cost-effectiveness threshold and the rate at which the higher authority can borrow or invest is then examined. We establish that the social time preference rate for health is implied by the budget allocation and the health production functions in each period. As such, the social time preference rate for health depends not on the social time preference rate for consumption or growth in the consumption value of health but on growth in the cost-effectiveness threshold and the rate at which the higher authority can save or borrow between periods. The implications for discounting and the policies of bodies such as NICE are then discussed.Economic evaluation. Discounting. Cost-effectiveness analysis

    Rights, responsibilities and NICE: a rejoinder to Harris

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    Harris' reply to our defence of the National Institute for Clinical Excellence's (NICE) current cost-effectiveness procedures contains two further errors. First, he wrongly draws a conclusion from the fact that NICE does not and cannot evaluate all possible uses of healthcare resources at any one time and generally cannot know which National Health Service (NHS) activities would be displaced or which groups of patients would have to forgo health benefits: the inference is that no estimate is or can be made by NICE of the benefits to be forgone. This is a non-sequitur. Second, he asserts that it is a flaw at the heart of the use of quality-adjusted life years (QALYs) as an outcome measure that comparisons between people need to be made. Such comparisons do indeed have to be made, but this is not a consequence of the choice of any particular outcome measure, be it the QALY or anything else

    A stitch in time: preserving peace on Bougainville

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    A decade after the successful peacekeeping mission, and a year and a half before the window opens for a referendum on Bougainville’s political status, the peace process is dangerously adrift.In this paper, Peter Jennings and Karl Claxton set out a plan to help deliver a sustainable solution for next steps in the peace process. An Australian-led preventive development effort, conducted in close cooperation with our regional partners, is needed to avoid the future requirement for a larger, costlier, riskier, and more intrusive peacekeeping mission than the limited intervention appropriate in 1997-2003.The new Government’s decision to link aid more directly to our strategic interests could assist. While the initiative would require a significant initial investment, it could create a substantial longer-term cost saving and avoid serious military, diplomatic and reputational risks

    Dimensions of design space: a decision-theoretic approach to optimal research design

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    Bayesian decision theory can be used not only to establish the optimal sample size and its allocation in a single clinical study, but also to identify an optimal portfolio of research combining different types of study design. Within a single study, the highest societal pay-off to proposed research is achieved when its sample sizes, and allocation between available treatment options, are chosen to maximise the Expected Net Benefit of Sampling (ENBS). Where a number of different types of study informing different parameters in the decision problem could be conducted, the simultaneous estimation of ENBS across all dimensions of the design space is required to identify the optimal sample sizes and allocations within such a research portfolio. This is illustrated through a simple example of a decision model of zanamivir for the treatment of influenza. The possible study designs include: i) a single trial of all the parameters; ii) a clinical trial providing evidence only on clinical endpoints; iii) an epidemiological study of natural history of disease and iv) a survey of quality of life. The possible combinations, samples sizes and allocation between trial arms are evaluated over a range of costeffectiveness thresholds. The computational challenges are addressed by implementing optimisation algorithms to search the ENBS surface more efficiently over such large dimensions.Bayesian decision theory; expected value of information; research design; costeffectiveness analysis

    Papua New Guinea at 40: Signs of a New Political Culture?

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    In April, Papua New Guinea's (PNG's) Registrar of Political Parties, Dr Alphonse Gelu, suggested that current political stability points to ' the emergence of a new political culture ' changing the face of politics for the better (Kenneth 17/4/15, 2). It's tempting to dismiss that comment as political puff; Gelu wasn't speaking as a scholar but as an official supporting a Bill to reinvigorate the Organic Law on the Integrity of Political Parties and Candidates (OLIP PAC). Many familiar features of PNG politics clearly remain. But, given Gelu's expertise, and the strange mix of sure-footed and wobbly moves by Prime Minis ter Peter O'Neill's government since the 2012 election, it's worth giving the proposition serious consideration.AusAI

    The value of implementation and the value of information: combined and uneven development

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    In a budget constrained healthcare system the decision to invest in strategies to improve the implementation of cost-effective technologies must be made alongside decisions regarding investment in the technologies themselves and investment in further research. This paper presents a single, unified framework that simultaneously addresses the problem of allocating funds between these separate but linked activities. The framework presents a simple 4 state world where both information and implementation can be either at the current level or ‘perfect’. Through this framework it is possible to determine the maximum return to further research and an upper bound on the value of adopting implementation strategies. The framework is illustrated through case studies of health care technologies selected from those previously considered by the UK National Institute for Health and Clinical Excellence (NICE). Through the case studies, several key factors that influence the expected values of perfect information and perfect implementation are identified. These factors include the maximum acceptable cost-effectiveness ratio, the level of uncertainty surrounding the adoption decision, the expected net benefits associated with the technologies, the current level of implementation and the size of the eligible population. Previous methods for valuing implementation strategies have confused the value of research and the value of implementation. This framework demonstrates that the value of information and the value of implementation can be examined separately but simultaneously in a single framework. This can usefully inform policy decisions about investment in healthcare services, further research and adopting implementation strategies which are likely to differ between technologies.Value of information analysis; value of implementation; healthcare decisionmaking, Bayesian analysis

    Mark versus Luke? Appropriate Methods for the Evaluation of Public Health Interventions

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    The purpose of this paper is to demonstrate that a social decision making approach to evaluation can be generalised to interventions such as public health and national policies which have multiple objectives and impact on multiple constraints within and beyond the health sector. We demonstrate that a mathematical programming solution to this problem is possible, but the information requirements make it impractical. Instead we propose a simple compensation test for interventions with multiple and cross-sectoral effects. However, rather than compensation based on individual preferences, it can be based on the net benefits falling on different sectors. The valuation of outcomes is based on the shadow prices of the existing budget constraints, which are implicit in existing public expenditure and its allocation across different sectors. A ‘welfarist’ societal perspective is not sufficient; rather, a multiple perspective evaluation which accounts for costs and effects falling on each sector is required.cost-effectiveness analysis, decision rules, public health

    Pharmaceutical Pricing : Early Access, The Cancer Drugs Fund and the Role of NICE

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    Defining and characterising structural uncertainty in decision analytic models

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    An inappropriate structure for a decision analytic model can potentially invalidate estimates of cost-effectiveness and estimates of the value of further research. However, there are often a number of alternative and credible structural assumptions which can be made. Although it is common practice to acknowledge potential limitations in model structure, there is a lack of clarity about methods to characterize the uncertainty surrounding alternative structural assumptions and their contribution to decision uncertainty. A review of decision models commissioned by the NHS Health Technology Programme was undertaken to identify the types of model uncertainties described in the literature. A second review was undertaken to identify approaches to characterise these uncertainties. The assessment of structural uncertainty has received little attention in the health economics literature. A common method to characterise structural uncertainty is to compute results for each alternative model specification, and to present alternative results as scenario analyses. It is then left to decision maker to assess the credibility of the alternative structures in interpreting the range of results. The review of methods to explicitly characterise structural uncertainty identified two methods: 1) model averaging, where alternative models, with different specifications, are built, and their results averaged, using explicit prior distributions often based on expert opinion and 2) Model selection on the basis of prediction performance or goodness of fit. For a number of reasons these methods are neither appropriate nor desirable methods to characterize structural uncertainty in decision analytic models. When faced with a choice between multiple models, another method can be employed which allows structural uncertainty to be explicitly considered and does not ignore potentially relevant model structures. Uncertainty can be directly characterised (or parameterised) in the model itself. This method is analogous to model averaging on individual or sets of model inputs, but also allows the value of information associated with structural uncertainties to be resolved.
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