Tendering for low cost generics in Australia

An Australian federal government committee recently proposed, as a cost-saving measure, the introduction of sealed-bid competitive tendering to exclusively supply the Pharmaceutical Benefits Scheme with specific generic medicines. A similar plan involved an open tender to supply generic products below a government set price, also linked with a reduced patient co-payment as an incentive. These proposals represented an opportunity to encourage the price of generic pharmaceuticals to move closer to the marginal cost of production—a process that could be subsequently applied to innovative (or brand-name) patented medicines in a therapeutic class with many competitors. This article examines these tendering proposals, particularly in relation to the potential for increased involvement of generic pharmaceutical manufacturers in the Australian market.

Effectiveness, costs, and cost-effectiveness of recruitment strategies for a mammographic screening program to detect breast cancer

BACKGROUND AND PURPOSE: Since effective and affordable recruitment methods are essential for the widespread implementation of mammographic screening for detection of breast cancer, we studied the effectiveness, the costs, and the cost-effectiveness of various recruitment strategies in the population targeted by a pilot Australian program that offered free mammography screening between 1988 and 1990. METHODS: We evaluated three public recruitment strategies--local newspaper articles, community promotion, and promotion to physicians--and five personal strategies--invitation letters with or without specified appointment times, either alone or with a follow-up letter, or telephone call to nonattenders. The effectiveness of public recruitment strategies was estimated from monthly attendance rates by Poisson regression analysis, while the probability of attendance in response to personal strategies was calculated using logistic regression analysis. Costs were determined by resource usage studies. The cost-effectiveness ratios for personal strategies were determined using decision analysis. RESULTS: The costs in 1988-1989 Australian dollars per woman recruited were $22 for local newspaper articles and $106 for community promotion. No detectable increase in attendance resulted from promotion to physicians. When the cost of reserving an appointment was considered, the most cost-effective personal recruitment strategy was an invitation letter without a specified appointment time, followed by a second letter to nonattenders. This strategy recruited 35.6% of women in the sample targeted and cost $10.52 per attendee. In comparison, the most effective personal recruitment strategy was a letter with a specified appointment time followed by a second letter to nonattenders, which recruited 44.1% of women at an average cost of $19.99 and a marginal cost of $59.71 per additional attendee. CONCLUSIONS: Personal recruitment strategies were more cost-effective than public strategies. The most cost-effective personal strategy was an invitation letter without a specified appointment time, followed by a second letter to nonattenders.

Inter-firm knowledge diffusion, market power, and welfare

We propose an infinite-horizon quantity-setting differential game with learning spillovers and organizational forgetting to analyze the optimal management decisions affecting the evolution of the stock of know-how, and, in turn, the dynamics of productive efficiency. Specifically, we study the long run impact of inter-firm knowledge diffusion on market power, i.e. the ability of a firm to raise the price above the marginal cost, and welfare. We consider two types of processes through which knowledge is acquired: (i) passive learning, or learning-by-doing, where managers do not actively invest in information and (ii) active learning, or learning-by-investing, where managers acquire new and additional information through specific investments in human capital. We show that: under (i), knowledge diffusion reduces market power; under (ii), knowledge diffusion reduces market power as long as learning spillovers are sufficiently important. From a welfare viewpoint, we also show that: under (i), knowledge diffusion is always welfare-enhancing; under (ii), weak spillovers are required in order for knowledge diffusion to be welfare-enhancing.

Byzantine-resilient secure software-defined networks with multiple controllers

Software-defined network (SDN) is the next generation of networking architecture that is dynamic, manageable, cost-effective, and adaptable, making it ideal for the high-bandwidth, dynamic nature of today's applications. In SDN, network management is facilitated through software rather than low-level device configurations. However, the centralized control plane introduced by SDN imposes a great challenge for the network security. In this paper, we present a secure SDN structure, in which each device is managed by multiple controllers rather than a single one as in a traditional manner. It can resist Byzantine attacks on controllers and the communication links between controllers and SDN switches. Furthermore, we design a cost-efficient controller assignment algorithm to minimize the number of required controllers for a given set of switches. Extensive simulations have been conducted to show that our proposed algorithm significantly outperforms random algorithms. © 2014 IEEE.

Water security through scarcity pricing and reverse osmosis: a system dynamics approach

Water supply and demand planning is often conducted independently of social and economic strategies. There are presently no comprehensive life-cycle approaches to modelling urban water balances that incorporate economic feedbacks, such as tariff adjustment, which can in turn create a financing capacity for investment responses to low reservoir levels. This paper addresses this gap, and presents a system dynamics model that augments the usual water utility representation of the physical linkages of water grids, by adding inter-connected feedback loops in tariff structures, demand levels and financing capacity. The model, applied in the south-east Queensland region in Australia, enables simulation of alternatives and analysis of stocks and flows around a grid or portfolio of bulk supplies including an increasing proportion of rain-independent desalination plants. Such rain-independent water production plants complement the rain-dependent sources in the region and can potentially offer indefinite water security at a price. The study also shows how an alternative temporary drought pricing regime not only defers costly bulk supply infrastructure but actually generates greater price stability than traditional pricing approaches. The model has implications for water supply planners seeking to pro-actively plan, justify and finance portfolios of rain-dependent and rain-independent bulk water supply infrastructure. Interestingly, the modelling showed that a temporary drought pricing regime not only lowers the frequency and severity of water insecurity events but also reduces the long-run marginal cost of water supply for the region when compared to traditional reactive planning approaches that focus on restrictions to affect demand in scarcity periods.

The new Keynesian Phillips curve in a small open economy: empirical evidence from Australia

This study estimates the new Keynesian Phillips curve (NKPC) ofGali and Monacelli for a small open economy using Australian data.Our detailed investigation hinges on estimating the structuralparameters in five different variants of the Gali–Monacelli NKPC,which relates the inflation process to terms of trade and the realexchange rate; the marginal cost and output gap as proxies for realeconomic activity and the hybrid version incorporating bothforward- and backward-looking inflation expectations. The analysisand extensive robustness checks overwhelmingly establish that theGali–Monacelli NKPC cannot explain the dynamics of inflation andis rejected by the Australian data.

Dynamic regime marginal structural mean models for estimation of optimal dynamic treatment regimes, Part I: main content

Dynamic treatment regimes are set rules for sequential decision making based on patient covariate history. Observational studies are well suited for the investigation of the effects of dynamic treatment regimes because of the variability in treatment decisions found in them. This variability exists because different physicians make different decisions in the face of similar patient histories. In this article we describe an approach to estimate the optimal dynamic treatment regime among a set of enforceable regimes. This set is comprised by regimes defined by simple rules based on a subset of past information. The regimes in the set are indexed by a Euclidean vector. The optimal regime is the one that maximizes the expected counterfactual utility over all regimes in the set. We discuss assumptions under which it is possible to identify the optimal regime from observational longitudinal data. Murphy et al. (2001) developed efficient augmented inverse probability weighted estimators of the expected utility of one fixed regime. Our methods are based on an extension of the marginal structural mean model of Robins (1998, 1999) which incorporate the estimation ideas of Murphy et al. (2001). Our models, which we call dynamic regime marginal structural mean models, are specially suitable for estimating the optimal treatment regime in a moderately small class of enforceable regimes of interest. We consider both parametric and semiparametric dynamic regime marginal structural models. We discuss locally efficient, double-robust estimation of the model parameters and of the index of the optimal treatment regime in the set. In a companion paper in this issue of the journal we provide proofs of the main results.

Dynamic regime marginal structural mean models for estimation of optimal dynamic treatment regimes, Part II: proofs of results

In this companion article to "Dynamic Regime Marginal Structural Mean Models for Estimation of Optimal Dynamic Treatment Regimes, Part I: Main Content" [Orellana, Rotnitzky and Robins (2010), IJB, Vol. 6, Iss. 2, Art. 7] we present (i) proofs of the claims in that paper, (ii) a proposal for the computation of a confidence set for the optimal index when this lies in a finite set, and (iii) an example to aid the interpretation of the positivity assumption.

Dynamic on-the-fly minimum cost benchmarking for storing generated scientific datasets in the cloud

Massive computation power and storage capacity of cloud computing systems enable users to either store large generated scientific datasets in the cloud or delete and then regenerate them whenever reused. Due to the pay-as-you-go model, the more datasets we store, the more storage cost we need to pay, alternatively, we can delete some generated datasets to save the storage cost but more computation cost is incurred for regeneration whenever the datasets are reused. Hence, there should exist a trade-off between computation and storage in the cloud, where different storage strategies lead to different total costs. The minimum cost, which reflects the best trade-off, is an important benchmark for evaluating the cost-effectiveness of different storage strategies. However, the current benchmarking approach is neither efficient nor practical to be applied on the fly at runtime. In this paper, we propose a novel Partitioned Solution Space based approach with efficient algorithms for dynamic yet practical on-the-fly minimum cost benchmarking of storing generated datasets in the cloud. In this approach, we pre-calculate all the possible minimum cost storage strategies and save them in different partitioned solution spaces. The minimum cost storage strategy represents the minimum cost benchmark, and whenever the datasets storage cost changes at runtime in the cloud (e.g. new datasets are generated and/or existing datasets' usage frequencies are changed), our algorithms can efficiently retrieve the current minimum cost storage strategy from the partitioned solution space and update the benchmark. By dynamically keeping the benchmark updated, our approach can be practically utilised on the fly at runtime in the cloud, based on which the minimum cost benchmark can be either proactively reported or instantly responded upon request. Case studies and experimental results based on Amazon cloud show the efficiency, scalability and practicality of our approach.

A new second-order method for blind signal separation from dynamic mixtures

This paper presents a new approach to separate colored stationary signals mixed by convolutive channels. A cost function is proposed by employing linear constraint to the demixing vectors. The linear constraint is shown to be sufficient for avoiding trivial solution. The minimization of the cost function is performed using the Lagrangian method. Simulation results demonstrate the performance of the algorithm.

Estimating the user cost of soil erosion in tea smallholdings in Sri Lanka

Soil erosion in developing countries is a widespread problem causing considerable economic damage. It still remains an intractable problem in many countries. Available research findings on costs of soil erosion indicate them to be high. Soil erosion continues to be a problem due to the difficulties of estimating the economic damages and attendant difficulties in developing effective control policies. This paper considers soil to be a nonrenewable resource and estimates the marginal user costs using a yield damage function. Results indicate user costs to be low for individual farms. The low user costs are due to some of the assumptions made with respect to a number of parameters such as prices of tea, costs, and technological developments. The results also indicate that marginal user costs are sensitive to prices, soil depth and soil loss.

An evolutionary computing approach to minimize dynamic hedging error

The objective of our present paper is to derive a computationally efficient genetic pattern learning algorithm to evolutionarily derive the optimal rebalancing weights (i.e. dynamic hedge ratios) to engineer a structured financial product out of a multiasset, best-of option. The stochastic target function is formulated as an expected squared cost of hedging (tracking) error which is assumed to be partly dependent on the governing Markovian process underlying the individual asset returns and partly on
randomness i.e. pure white noise. A simple haploid genetic algorithm is advanced as an alternative numerical scheme, which is deemed to be
computationally more efficient than numerically deriving an explicit solution to the formulated optimization model. An extension to our proposed scheme is suggested by means of adapting the Genetic Algorithm parameters based on fuzzy logic controllers.

Generic medicines in Australia : business dynamics and recent policy reform

This article describes the role of generics in the Australian prescription drug market and patterns of business activity in this dynamic market segment. The Pharmaceutical Benefits Scheme (PBS) is the central mechanism for the supply of prescription medicines. PBS prices are arrived at through cost-effectiveness analyses comparing new products against already available products and therapies. In this system, prices do not operate effectively as incentives for consumers or prescribers to choose generics, and their market share was historically marginal. In recent years, generics suppliers achieved a growing market share through discounts (trading terms) to pharmacists. It is estimated that around 30% of PBS scripts, representing around 15% of PBS sales by value, are now filled with generics. Complex changes to the PBS were introduced in 2007, to be phased in over the period to 2012, aimed at increasing the scope for cost benefits to the government, and to lesser extent consumers, from the expanding availability of generic medicines.

Cost-effectiveness of adult circumcision in a resource-rich setting for HIV prevention among men who have sex with men

Background.  We examined the effects and cost‐effectiveness of 4 strategies of circumcision in a resource‐rich setting (Australia) in a population of men who have sex with men (MSM).

Method.  We created a dynamic mathematical transmission model and performed an economic analysis to estimate the costs, outcomes, and cost‐effectiveness of different strategies, compared with those of the status quo. Strategies included circumcision of all MSM at age 18 years, circumcision of all MSM aged 35–44 years, circumcision of all insertive MSM aged 18 years, and circumcision of all MSM aged 18 years . All costs are reported in US dollars, with a cost‐effectiveness threshold of $42,000 per quality‐adjusted life‐year.

Results.  We find that 2%–5% of human immunodeficiency virus (HIV) infections would be averted per year, with initial costs ranging from $3.6 million to $95.1 million, depending on the strategy. The number of circumcisions needed to prevent 1 HIV infection would range from 118 through 338. Circumcision of predominately insertive MSM would save $21.7 million over 25 years with a $62.2 million investment. Strategies to circumcise 100% of all MSM and to circumcise MSM aged 35–44 years would be cost‐effective; the latter would require a smaller investment. The least cost‐effective approach is circumcision of young MSM close to their sexual debut. Results are very sensitive to assumptions about the cost of circumcision, the efficacy of circumcision, sexual preferences, and behavioral disinhibition.

Conclusions.  Circumcision of adult MSM may be cost‐effective in this resource‐rich setting. However, the intervention costs are high relative to the costs spent on other HIV prevention programs.