Global Cost Savings Research Articles

Cost-minimization Analysis in Iron-deficiency Anemia Comparing Intravenous Ferric Carboxymaltose to Standard of Care in Pregnant Women in Algeria

Abstract INTRODUCTION: Anemia due to iron deficiency is frequent during pregnancy and increases morbidity and mortality of mothers and infants. The objective of this study was to assess the economic consequences of intravenous ferric carboxymaltose (FCM) in anemic pregnant women in Algeria. METHODS: The economic analysis was a cost-minimization model comparing the strategy for treating pregnant women with intravenous iron sucrose to FCM. The perspective of Algerian health-care providers was adopted to calculate costs savings. Cost related to treatment of iron-deficiency anemia included infusion, iron workup, medical time, iron vials acquisition, and absenteeism. Data were obtained mostly from available scientific literature and public health data and were validated by expert opinion. A budget impact model was also developed for the population of Algerian women needing intravenous iron treatment to evaluate the gross impact on payers’ budget if FCM treatment was prescribed. RESULTS: Treatment of pregnant women with iron-deficiency anemia (mean weight, 65 kg; hemoglobin 7.5 g/dL) needed 7 hospital visits and 14.9 doses for iron sucrose treatment to be compared to 2 hospital visits and 2 doses for FCM treatment. Total cost was Algerian dinar (DZD) 69,222 per patient for iron sucrose and DZD 57,452 for FCM (cost savings per patient: DZD 11,769, i.e., 17%). If all 192,000 pregnant Algerian anemic women eligible for injectable iron treatment received FCM, global cost savings would be DZD 2,259,820,627 per year. CONCLUSION: This economic model suggests that FCM is a cost-saving treatment compared to standard iron sucrose treatment in pregnant women with iron-deficiency anemia in Algeria.

Evaluation of drug cost savings related to clinical trials from the perspective of a university hospital

ObjectivesClinical trials are an opportunity for patients to access innovative therapy, but patient inclusion in clinical trials can also result in cost savings for hospitals. Our objective was to evaluate...

A break-even analysis of orbital debris and space preservation through monetization

While NASA and European Space Agency (ESA) publicly recognize space debris imposes high costs on space economies, they have not published monetized space debris costs. This study monetizes the increasing costs of orbital debris and costs of space preservation through Monte Carlo simulations using a break-even analysis. Orbital debris imposes satellite fortification, avoidance, and early replacement costs on satellite owners. This paper assigns values to NASA published space debris mitigation models for an estimate of space preservation costs. Estimating space debris costs has been hampered by a lack of information largely due to commercial proprietary information. This study shows how simple-realistic assumptions can turn sparse data into the basis of a robust analysis. Further, by conducting a break-even analysis of these cost streams, this study identifies the global cost savings after the costs of space debris equals the costs of space preservation. Using alternative inputs, this study conducts sensitivity analyses to identify the effectiveness of mitigation and remediation options. At a 90% success rate of post-mission disposal (PMD) and an active removal of as few as 5 defunct spacecraft per year are the sufficient and effective space preservation measures if spacefaring communities are in compliance with them sooner rather than later. Phases and timelines for global practicing measures of mitigation and remediation are sensitive to the outcome of break-even analysis. In conclusion, spacefaring communities need to stabilize the space debris environment for cost-savings and space sustainability. A simple solution is post-mission disposal and a worldwide orbital user sinking fund per launch to finance future debris removal and hedge preservation timeline uncertainty.active debris removal missions per year that proposed by NASA ODPO would cost less than one third the costs of space debris under the status quo.

THF: 3-Way Hierarchical Framework for Efficient Client Selection and Resource Management in Federated Learning

Federated learning (FL) is a promising technique for collaboratively training machine-learning models on massively distributed clients data under privacy constraints. However, the existing FL literature focuses on speeding up the learning process and ignores minimizing the communication cost which is critical for resource-constrained clients. To this end, in this article, we propose a novel 3-way hierarchical framework (THF) to promote communication efficiency in FL. Using the proposed framework, only a cluster head (CH) communicates with the cloud server through edge aggregation in order to minimize the communication cost of clients. In particular, the clients upload their local models to their respective CHs, which are responsible to forward them to the corresponding edge server. The edge server averages the local models and iterates until it achieves the edge accuracy. Afterward, each edge server uploads the edge models to the cloud server for global aggregation. In this way, model downloading and uploading requires less bandwidth due to the short distance from source to destination that makes an efficient 3-way hierarchical network structure. In addition, we formulate a joint communication and computation resource management scheme through efficient client selection in order to achieve global cost minimization in FL. We conduct extensive empirical evaluations on diverse data learning tasks on multiple data sets to signify that THF achieves global cost savings and converges within fewer communication rounds compared to other FL approaches.

A real industrial building: Modeling, calibration and Pareto optimization of energy retrofit

An existing industrial building ubicated in South Italy is investigated by applying a tailored approach to optimize energy retrofit. The baseline provides high energy consumption, which needs to be tackled to promote the transition towards more sustainable buildings. Accordingly, after a detailed energy audit, the building is modeled and simulated under EnergyPlus environment using DesignBuilder® to characterize geometry and HVAC (heating, ventilating and air conditioning) systems. The model is calibrated against metered data as concerns the trends of indoor temperatures. Different retrofit measures are investigated, i.e., replacement of windows, implementation of solar screens, use of heat recovery, optimization of HVAC operation and installation of photovoltaics of different sizes. Thus, a large domain of solutions is explored by conducting an exhaustive research through the coupling between EnergyPlus and MATLAB®. The research provides the Pareto optimization of building retrofit minimizing primary energy consumption and global cost for two different scenarios as regards the access to public incentives. The utopia point criterion is used to pick a solution from the Pareto front. Such solution can yield energy and global cost savings up to 81% and 45%, respectively, ensuring the same comfort level compared to the baseline. The primary energy consumption of the whole facility can be reduced up to 40.1 kWhp/m2a. The outcomes can give precious guidelines to refurbish industrial and office buildings in Mediterranean areas with a view to energy-efficiency and cost-effectiveness.

Retrofit of villas on Mediterranean coastlines: Pareto optimization with a view to energy-efficiency and cost-effectiveness

A comprehensive multi-objective optimization framework is proposed to address the energy retrofit of typical villas on Mediterranean coastlines. Primary energy consumption and global cost are minimized using a Pareto approach. Two different construction technologies (i.e., a lightweight house in reinforced concrete and a massive tuff-made villa), in two different climates (i.e., Greek and Italian coasts), are investigated to provide robust optimal retrofit strategies according to two different criteria, i.e., the achievement of the nearly zero energy standard and the cost-optimality, respectively. The optimal energy retrofit strategies are achieved by coupling transient energy simulations and a genetic algorithm. They address all main factors affecting energy performance, i.e., building envelope (thermal insulation, reflectance of coatings, windows and solar shading), active energy systems (space conditioning devices) and renewable energy sources (solar photovoltaics). The investigation findings can provide useful generic guidelines for the retrofit of houses on the Mediterranean coastlines with a view to energy-efficiency and cost-effectiveness. The implementation of the suggested retrofit strategies to the case studies can yield substantial primary energy savings, up to 125 kWh/m2a, and global cost savings, up to 140 €/m2. The most energy-efficient and cost-effective retrofit solutions are the improvement of energy systems’ efficiency, the installation of full-roof photovoltaic systems, the replacement of windows and the roof thermal insulation.

Thermodynamic and economic analysis of the integration of high-temperature heat pumps in trigeneration systems

Polygeneration energy systems are proven to be a reliable, competitive and efficient solution for energy production. The recovery of otherwise wasted energy is the primary reason for the high efficiency of polygeneration systems. In this paper, the integration of a high-temperature heat pump within a trigeneration system is investigated. The heat pump uses the low-temperature heat from the condenser of the absorption chiller as heat source to produce hot water. A numerical model of the heat pump cycle is developed to evaluate the technical viability of current heat pump technology for this application and assess the performance of different working fluids. An exergy analysis is performed to show the advantages of the novel trigeneration system with respect to traditional systems for energy production. Moreover, a levelized cost of electricity method is applied to the proposed energy system to show its generic economic feasibility. Finally, actual energy demand data from an Italian pharmaceutical factory are considered to evaluate the economic savings obtainable with the integrated system, implemented in a case study. A two-level algorithm is proposed for the economic optimization of the investment. The synthesis/design problem is addressed by a genetic algorithm and the optimal operation problem is solved by a linear programming method. Results show that the integration of a high-temperature heat pump within a trigeneration system provides flexibility to cover variable energy demands and achieve valuable economic and energy performances, with global cost savings of around 40% with respect to separate production and around 10% with respect to traditional cogeneration and trigeneration systems.

Solving a large multi-product production-routing problem with delivery time windows

Even though the joint optimization of sequential activities in supply chains is known to yield significant cost savings, the literature concerning optimization approaches that handle the real-life features of industrial problems is scant. The problem addressed in this work is inspired by industrial contexts where vendor-managed inventory policies are applied. In particular, our study is motivated by a meat producer whose supply chain comprises a single meat processing centre with several production lines and a fleet of vehicles that is used to deliver different products to meat stores spread across the country. A considerable set of characteristics, such as product family setups, perishable products, and delivery time windows, needs to be considered in order to obtain feasible integrated plans. However, the dimensions of the problem make it impossible to be solved exactly by current solution methods. We propose a novel three-phase methodology to tackle a large Production-Routing Problem (PRP) combining realistic features for the first time. In the first phase, we attempt to reduce the size of the original problem by simplifying some dimensions such as the number of products, locations and possible routes. In the second phase, an initial PRP solution is constructed through a problem decomposition comprising several inventory-routing problems and one lot-sizing problem. In the third phase, the initial solution is improved by different mixed-integer programming models which focus on small parts of the original problem and search for improvements in the production, inventory management and transportation costs. Our solution approach is tested both on simpler instances available in the literature and on real-world instances containing additional details, specifically developed for a European company’s case study. By considering an integrated approach, we achieve global cost savings of 21.73% compared to the company’s solution.

Resilience of robust cost-optimal energy retrofit of buildings to global warming: A multi-stage, multi-objective approach

The climate evolution towards a progressive increase of Earth's temperature is leading to many worrying consequences, involving different aspects of World life. Among them, a specific focus should be given to the resilience of building energy design to global warming, since the efficiency and effectiveness of energy conservation measures over time can be highly affected by climate change. In this vein, the paper applies a multi-stage, multi-objective approach to find robust cost-optimal energy retrofit solutions and to assess their resilience to global warming. The approach combines the software EnergyPlus and MATLAB® to implement an optimization genetic algorithm and a smart research strategy. This framework allows to explore a huge solution domain by investigating sundry performance indicators, such as energy needs, polluting emissions and global costs, thereby ensuring a robust assessment of cost-optimality. Different cost-optimal retrofit solutions are found for different global warming and economic scenarios. Finally, a careful decision-making is performed to identify a recommended solution that provides the highest resilience to the cited scenarios, yielding the best trade-off among energy, environmental and economic performances. The approach is applied to a typical Mediterranean building, located in South Italy. The recommended solution includes the energy retrofit of the whole building envelope and the replacement of energy systems. It requires an investment around 100€/m2 and, in most scenarios, produces high potential benefits in terms of primary energy savings (42÷44kWh/m2a), polluting emission reductions (11.5÷12.0kgCO2-eq/m2a) and global cost savings (5÷78€/m2).

Addressing Large-Scale Energy Retrofit of a Building Stock via Representative Building Samples: Public and Private Perspectives

Scientific literature about energy retrofit focuses on single buildings, but the investigation of whole building stocks is particularly worthy because it can yield substantial energy, environmental and economic benefits. Hence, how to address large-scale energy retrofit of existing building stocks? The paper handles this issue by employing a methodology that provides a robust energy analysis of building categories. This is denoted as SLABE, “Simulation-based Large-scale uncertainty/sensitivity Analysis of Building Energy performance”. It was presented by the same authors and is here enhanced to investigate a whole and heterogeneous building stock that includes various categories. Each category is represented via a Representative Building Sample (RBS), which is defined through Latin hypercube sampling and uncertainty analysis. Hence, optimal retrofit packages are found in function of building location, intended use and construction type. Two families of optimal solutions are achieved. The first one collects the most energy-efficient (and thus sustainable) solutions, among the ones that produce global cost savings, thereby addressing the public perspective. The second one collects cost-optimal solutions thereby addressing the private perspective. EnergyPlus is employed as a simulation tool and coupled with MATLAB® for data analysis and processing. The methodology is applied to a significant share of the Italian public administration building stock, which includes several building categories depending on location, use destination and construction type. The outcomes show huge potential energy and economic savings, and could support a deep energy renovation of the Italian building stock.

CASA, cost-optimal analysis by multi-objective optimisation and artificial neural networks: A new framework for the robust assessment of cost-optimal energy retrofit, feasible for any building

The cost-optimal analysis provides the most cost-effective energy retrofit solutions. This can strongly support the deep renovation of buildings. However, an outstanding question arises: How to achieve the robust assessment of cost-optimal solutions, feasible for any building? The paper answers this question by proposing a new multi-stage framework for cost-optimal analysis by multi-objective optimisation and artificial neural networks, called CASA. It couples EnergyPlus and MATLAB®. A genetic algorithm allows to select recommended retrofit packages by minimizing energy consumption and thermal discomfort. Among these packages, the cost-optimal solution is identified. It is robust because the algorithm explores a wide domain of retrofit scenarios. The optimization procedure uses artificial neural networks to predict building performance. Large-scale uncertainty and sensitivity analyses are conducted to support the generation of the networks. These latter are tested against data provided by current literature with excellent results. The networks’ applicability to whole building categories and rapidity of evaluation make the procedure feasible for any building. For demonstration, CASA is applied to a reference office building located in South Italy, by investigating the related category. The achieved cost-optimal solution produces global cost savings around 42.4€/m2, and significant reductions of energy consumption, discomfort hours and polluting emissions.

A new comprehensive approach for cost-optimal building design integrated with the multi-objective model predictive control of HVAC systems

A new comprehensive approach is proposed to support cost-optimal design of building envelope’s thermal characteristics and HVAC (heating, ventilating and air-conditioning) systems in presence of a simulation-based model predictive control (MPC) for heating and cooling operations. The cost-optimal solution is identified through a main mono-objective genetic algorithm (GA) that minimizes global costs for space conditioning. The explored solutions represent building thermal designs integrated with the MPC of HVAC systems. For defining the MPC strategies, the main GA launches two secondary bi-objective GAs that optimize heating and cooling operations, respectively. These secondary GAs perform Pareto optimizations by minimizing operating costs and thermal discomfort. They provide the optimal hourly set point temperatures for heating and cooling operations, with a day-ahead planning horizon, by considering the forecasts of weather conditions and building use. The optimal control strategies are found based on requirements of users, who set a minimum comfort level to be fulfilled. The GAs are implemented by coupling MATLAB® with EnergyPlus. The methodology is applied to a new multi-zone residential building in Naples (Southern Italy). It yields primary energy savings around 35.4kWh/m2a and global cost savings around 7000€, ensuring the same satisfying comfort level, compared to a standard design approach.

Why are there large differences in performances when the same carbon emission reductions are achieved in different countries?

Great interest has been in unilateral climate policies, given present difficulty of establishing stable global coordinated agreements. In this paper, we investigate underlining factors explaining large differences in performances, when the same carbon emission reductions are achieved in different abating countries. To this end, we develop a new multi-country general equilibrium model, incorporating six countries (or world regions), two goods, six production inputs, capital mobility, energy mobility and international trade. Meanwhile, we adopt two performance indicators, with carbon leakage representing environmental efficiency and carbon emission abatement costs revealing cost-effectiveness. Our findings are as follows. Firstly, there are large differences in performances among these unilateral climate policies, as evidenced by large differences in leakage rates and carbon emission abatement costs. Secondly, the new global climate treaties to replace the Kyoto Protocol should be able to induce more carbon emission reductions in countries with low carbon emission reduction costs, since such setting contributes to global cost savings. Finally, developed countries have high carbon emission abatement costs compared with large developing countries (China and India in this paper), implying that there should be trade-off mechanisms between efficiency and equity regarding how to allocate carbon emission reductions among countries.

The potential contribution of the shipping sector to an efficient reduction of global carbon dioxide emissions

Abstract In this paper, we analyze how much the shipping sector could contribute to global CO2 emission reductions from an efficiency point of view. To do this, a marginal abatement cost curve (MACC) for the shipping sector is generated that can be combined with a MACC for conventional CO2 abatement in the production and consumption sectors around the world. These two MACCs are used to assess the following as regards the various global reduction targets: (a) what the maximum global cost savings would be that could be achieved by abating emissions in the shipping sector, (b) how much the shipping sector could contribute to abating emissions cost efficiently, and (c) what the potential additional costs of implementing a separate solution for the shipping sector would be. The focus is on the year 2020. We find that the shipping sector could always contribute to efficient global emission reductions and thus could always achieve global cost savings, but also that the size of the contribution and the size of cost savings depend heavily on the MACC case assumed, i.e., on how the existence of negative abatement costs is treated in a MACC, and on the reduction potentials and costs of measures assumed.

Comparing conventional and organic citrus grower efficiency in Spain

This paper compares the organic and conventional citriculture systems in Spain from the perspective of their technical efficiency. The primary objective of the research is to compare the relative efficiency of these two systems in relation to a metafrontier that envelops both technologies. In addition, the article analyses how efficient each growing system is at using its own technology, that is, when farms’ efficiency is benchmarked in relation to the best practices in their group. Contrary to conventional practice, farms’ performance is analyzed in terms of specific growing tasks: soil and plant cover management, pruning, fertilization and phytosanitary treatments. The results obtained highlight that both organic and conventional orchards would be able to achieve substantial global cost savings if they reached the maximum level of efficiency that their technological restrictions permit. They also reveal that the gap between the levels of efficiency on the frontier of each of the systems and the metafrontier is much wider in the case of organic citriculture than in conventional growing systems. Consequently, there is evidence that the limitations imposed on organic citriculture by regulatory and technological determinants have a significant impact on the relative efficiency of organic orchards in citrus fruit production, with potential consequences as regards their financial viability.

The role of border carbon adjustment in unilateral climate policy: Overview of an Energy Modeling Forum study (EMF 29)

Issues of emission leakage and competitiveness are at the fore of the climate policy debate in all the major economies implementing or proposing to implement substantial emission cap-and-trade programs. Unilateral climate policy cannot directly impose emission prices on foreign sources, but it can complement domestic emission pricing with border carbon adjustment to reduce leakage and increase global cost-effectiveness. While border carbon adjustment has a theoretical efficiency rationale, its practical implementation is subject to serious caveats. This article summarizes the results of an Energy Modeling Forum study (EMF 29) on the efficiency and distributional impacts of border carbon adjustment. We find that border carbon adjustment can effectively reduce leakage and ameliorate adverse impacts on energy-intensive and trade-exposed industries of unilaterally abating countries. However, the scope for global cost savings is small. The main effect of border carbon adjustment is to shift the economic burden of emission reduction to non-abating countries through implicit changes in international prices.

Unilateral climate policy design: Efficiency and equity implications of alternative instruments to reduce carbon leakage

Global cost-effectiveness of unilateral emission abatement can be seriously hampered by carbon leakage. We assess three widely discussed proposals for leakage reduction: carbon-motivated border tax adjustments, industry exemptions from carbon regulation, and output-based allocation of emission allowances. We find that none of these measures amounts to a “magic bullet” when both efficiency and equity criteria matter. Compared to unilateral emission pricing alone, border carbon adjustments are most effective in leakage reduction and promotion of global cost-effectiveness but can markedly exacerbate regional inequality; exemptions and output-based allocation tend to avoid distributional pitfalls but are less effective in leakage reduction and global cost savings; exemptions may even decrease global cost-effectiveness of unilateral emission abatement.

Unilateral Climate Policy and Competitiveness: Economic Implications of Differential Emission Pricing

AbstractUnilateral climate policy raises concerns about international competitiveness and emission leakage that result in preferential regulatory treatment of domestic energy‐intensive and trade‐exposed (EITE) industries. Our applied analysis of unilateral EU abatement illustrates the potential pitfalls of climate policy design which narrowly focuses on competitiveness concerns about EITE industries. The sector‐specific gains of differential emission pricing in favour of these branches must be traded off with the additional burden imposed on other industries. From the perspective of the unilaterally abating region preferential EITE emission pricing can induce non‐negligible excess cost as policy concedes (too) low emission prices to EITE industries and thereby foregoes relatively cheap abatement options in these sectors. With respect to global cost‐effectiveness of unilateral climate policy, we find that differential emission pricing in favour of EITE industries can reduce emission leakage and thereby provide global cost savings compared with uniform pricing. However, the scope for cost savings is limited and may change into substantial cost increases if unilateral reduction targets are moderate and EITE industries get close to exemptions.

Evaluation of cost savings with ferric carboxymaltose in anemia treatment through its impact on erythropoiesis-stimulating agents and blood transfusion: French healthcare payer perspective

Objective:To evaluate the economic impact of intravenous iron (in the form of intravenous iron preparation of ferric carboxymaltose) in three different clinical settings of iron deficiency anemia: chemotherapy-induced anemia in breast cancer, chemotherapy-induced anemia in digestive cancer, and perioperative anemia in knee and hip surgery.Methods:The economic model compared the usual therapeutic strategies of anemia without intravenous iron and strategies including intravenous iron, in each of the three clinical settings selected. Costs related to anemia treatment by erythropoiesis-stimulating agents (ESA), blood transfusion, and intravenous iron were estimated and compared inside each setting. Cost savings were calculated from the French healthcare payer perspective. Data included in the economic model were obtained from scientific literature, public health agencies, and medical experts.Results:The most prominent annual cost savings were observed in chemotherapy-induced anemia in breast cancer (€997 and €360 per patient for metastatic and non-metastatic breast cancers, respectively; global cost saving, €33.6 million). This large impact of intravenous iron on costs was mainly explained by both a lower number of women treated and lower ESA dosing. Mean annual cost saving in digestive cancers and knee and hip surgery were estimated to €168 and €216 per patient and global cost savings of €7.5 and €12.1 million, respectively. Overall, annual cost savings in these three settings were estimated to €53 million including €39 million for ESA cost savings. Sensitivity analysis showed that strategies including intravenous iron remained cost-effective even with wide variations in the assumptions, particularly for cost savings on ESA.Limitations:Economic model based on literature data and expert opinions.Conclusions:The present economic model suggests that use of intravenous iron, according to recommendations of international guidelines, is cost saving, particularly in chemotherapy-induced anemia in breast cancers.

Cost-effective environmental policy: implications of induced technological change

Cost-effective environmental policy generally requires that all emission sources are faced with the same tax. In this paper I discuss how the existence of induced technological change may alter this result, if at least some of the effect is external to the firm. Focusing on Learning by doing (LBD) effects in abatement activities, it is shown that emission sources with external learning effects should be faced with a higher tax than emission sources with only autonomous technological change. By using simple numerical simulations, it is further investigated to what degree a cost-effective climate policy differs from a free quota market, under various assumptions about learning effects, diffusion of technology and environmental targets. The results indicate that optimal taxes may be significantly higher in the industrial world than in the developing world. Moreover, the industrial world's share of global abatement may be much higher in a cost-effective solution than in a free quota market. The global cost savings of a fully flexible implementation of the Kyoto Protocol are further questioned, as potential spillover effects of technological growth in the industrial world are not internalised in the market.