How to correctly calculate discounted healthcare costs and benefits

A feature of a healthcare policy (such as screening) with interventions at specific ages is that when it is introduced, part of the population is too old to participate in the full programme. This fact changes the formulae to be used for cost and benefit discounting in a non-intuitive way. General formulae are derived for the expected discounted costs and benefits of such health promotion policies, for a stationary population. Correct ways to calculate discounted costs and benefits via simulation are also described. The formulae have some surprising properties, for example the relative cost of two health policies does not depend on the discounting rate. They are also relevant to the ongoing debate over the correct discounting rate for benefits. It is shown that when health benefits follow quickly on treatments, varying the discounting rate for health benefits is merely equivalent to rescaling the cash value of a benefit. It is only when benefit follows long after treatment that the problem of choosing an appropriate discount rate for benefits cannot be simplified.     

Optimal track class assignment for a railroad network

The track class and speed for North American railroads are governed by regulations from the Federal Railroad Administration. Better quality of track permits greater operational speeds and lower transportation cost but also requires greater maintenance expenditure. In this study, we considered the trade-off between maintenance and transportation costs, and developed an optimization framework determining the optimal assignment for track class based upon the characteristics of the track, traffic demand, and maintenance budget. We also presented a solution algorithm by using Lagrangian Relaxation techniques to improve the solution efficiency. This tool can help railroads maintain tracks at their most appropriate level so as to provide reliable and cost-effective services.     

Magnitude adjustment for AHP benefit/cost ratios

A feature of the Analytic Hierarchy Process (AHP) that has not been subject to close scrutiny is its use for benefit/cost analysis. If benefit priorities are divided by project costs to yield benefit points per dollar, then the resulting numbers can be used to allocate program budgets. But if benefit priorities and cost priorities are derived from two separate hierarchies, then it is likely that the ratio of benefit priorities to cost priorities produces misleading results. To correct the situation, adjustments must be made to put the numerator and denominator priorities into commensurate terms.     

Economic implications of poor access to antenatal care in rural and remote Western Australian Aboriginal communities: An individual sampling model of pregnancy

Background

Australian Aboriginal women attend antenatal care less frequently and experience poorer pregnancy outcomes than non-Aboriginal women. Improving access to antenatal care is recognised as a means to improve pregnancy outcomes for mother and baby.

Objective

To estimate the costs of inadequate antenatal care and provide baseline measurements and implications for policy that targets improving access to care in rural and remote Western Australian (WA) Aboriginal communities.

Methods

An individual sampling model of pregnancy was developed that simulated hypothetical women with pregnancy events and outcomes observed in the WA Aboriginal population. Weekly pregnancy events were modelled via logistic regression according to maternal characteristics, events during pregnancy and current gestation, with adequate and inadequate care (?4 and <4 antenatal visits) to reflect differences in outcomes reported in the literature. The pregnancy model simulated clinical management including antenatal visits, hospitalisations, and transfers to tertiary care.

Results

The mean cost of pregnancy was AUD$8985, with a large difference depending on access to antenatal care (AUD$7635 and AUD$10,216 for adequate and inadequate care respectively). The main difference in costs resulted from neonatal care (AUD$1021 vs AUD$3205 for adequate and inadequate care respectively). In a rural community with 150 births per year, up to AUD$123,082 may be spent to improve access to care at no extra cost to the total current expenditure (AUD$1,347,733).

Conclusions

The large difference in pregnancy costs between those receiving adequate and inadequate care demonstrates that additional expenditure on improving access to antenatal care may be cost-effective and should be further investigated.     

Fuzzy pricing,marketing and service planning in a fuzzy inventory model: A geometric programming approach

In the real world markets, demand is influenced by different parameters. Recently, many researchers have been interested in integrated production and marketing planning strategies in inventory models where demand depends on different parameters such as price and/or marketing expenditure. The quality of services that are offered to customers of a product is one of the most important parameters that affects demand in the real markets and has not been considered in development of inventory models. On the other hand, the cost parameters in real inventory systems and other parameters such as price, marketing and service elasticity to demand are imprecise and uncertain in nature. So, the notion of fuzziness can be applied to cope with this uncertainty. In this paper, a new fuzzy profit maximization inventory model with shortages is proposed. The demand is considered as a power function of price, marketing expenditure and service expenditure. Furthermore, unit cost is determined as a power function of order quantity. Since the proposed model is in a fuzzy environment, a fuzzy decision should be made to meet the decision criteria, and the results should be fuzzy. Therefore, the proposed model is formulated and solved using geometric programming and fuzzy optimization techniques to derive an approximation of the results’ membership functions. The model is illustrated with a numerical example and finally a case study is provided for evaluation and validation of the results of model.     

Optimal design of a hoist structure frame

In an attempt to find the most cost effective design of a multipurpose hoisting device that can be easily mounted on and removed from a regular farm vehicle, cost optimisation including both material and manufacturing expenditure, is performed on the main frame supporting the device. The optimisation is constrained by local and global buckling and fatigue conditions. Implementation of Snyman’s gradient-based LFOPC optimisation algorithm to the continuous optimisation problem, results in the economic determination of an unambiguous continuous solution, which is then utilised as the starting point for a neighbourhood search within the discrete set of profiles available, to attain the discrete optimum.

This optimum is further investigated for a different steel grade and for the manufacturing and material cost pertaining to different countries. The effect of variations in the formulation of the objective function for optimisation is also investigated. The results indicate that considerable cost benefits can be obtained by optimisation, that costing in different countries do not necessarily result in the same most cost effective design, and that accurate formulation of the objective function, i.e. realistic mathematical modelling, is of utmost importance in obtaining the intended design optimum.     

Structural database for reducing cost in materials design and complexity of multiscale computations

Computational complexity of multiscale methods based on the first‐principles energetics is analyzed. Computational cost of such methods is dominated by expensive first‐principles determination of structural energies and atomic forces, including structural relaxations. Information integration is an opportunity to eliminate recalculation of known data, and, consequently, to reduce the total cost of multiscale calculations. We propose the Structural Database as a universal tool for structural data integration, and explain its conceptual design and functionality, including data mining options. To exemplify benefits provided by the Structural Database, we consider search for new ground states, construction of a phase diagram for a bulk material, and prediction of surface patterning. We show that the Structural Database is a powerful tool for information integration and data mining, which can greatly reduce the cost of multiscale computations and materials design. © 2006 Wiley Periodicals, Inc. Complexity 11: 36–42, 2006     

Enriched workflow modelling and Stochastic Branch-and-Bound

Workflow systems provide means and techniques for modelling, designing, performing and controlling repetitive (business) processes. The quality of commercial workflow systems is usually determined to a large extent by their versatility and multi-purpose application. One of the current trends in improving workflow systems lies in enriching modelling methods and techniques in order to enlarge design alternatives.The need for such advanced methods is particularly apparent in those fields in which the process duration can be determined only vaguely, but whose completion schedules are at the same time strictly enforced by a highly competitive market by means of fines and penalties. The risk of an overrun has to be weighed against the expected costs and benefits of certain measures reducing turn-around time and their combinations. Because they can help to avoid such penalties—or, at least, keep any potential losses low by identifying critical subprocesses and evaluate appropriate measures—modelling and evaluation techniques are becoming essential features of workflow systems.Methodologically, we use Stochastic Branch-and-Bound as a technique for finding “optimal” bundles of measures. A numerical study shows the benefits of this meta-approach by means of five stepwise-developed decision scenarios requiring rich modelling. Petri nets as a modelling tool and Stochastic Branch-and-Bound as an optimization technique determine for multi-mode resource constrained workflows of varying complexity an optimal workforce strategy with respect to the number of workers and their qualification.     

基于学习效应的质量经济性动态最优化模型

随着市场竞争的日益加剧,企业越来越关注质量作为竞争武器所带来的经济效益.然而目前关于质量经济性的研究多集中于质量成本的概念和理论.为了克服质量成本模型的局限性,将产品制造过程中的学习效应引入质量经济性模型中,通过分析产品质量的提高所带来的学习效应,研究了产品质量与利润现值之间的定量关系,得出最优产品质量水平及相应的最优产量和最优价格随时间的变化轨迹,说明了在竞争条件下企业逐步改进质量降低价格的合理性.     

Using DEA to assess NATO burden-sharing

As the member making many of the most visible contributions to NATO, the USA has often claimed that they shoulder the heaviest ‘burden’ in maintaining the objectives of the alliance. This claim has been backed by research which has concentrated on contributions such as defence expenditure and benefits such as protection from external threats. However, modern alliances entail the exchange of multiple forms of alliance benefits and liabilities and therefore the study of ‘burden-sharing’ in these alliances is a more complicated accounting problem than has been acknowledged by previous research. In this paper, burden-sharing is studied using Data Envelopment Analysis (DEA). This is a novel application of DEA. Instead of calculating relative ‘efficiencies’, the analysis produces a ‘net-burden index’ for each member nation of NATO. The results of the analysis indicate that whilst the USA shoulders a heavy burden, some other member nations, including Canada and Spain, may in fact shoulder a heavier burden.     

HOP: A software tool for production scheduling at Bridgestone/Firestone off-the-road

We describe the development of the Heater Optimization Program (HOP), a software tool for scheduling the curing operation at Bridgestone/Firestone Off-The-Road (BFOR). The company produces large tires for heavy off-the-road machines such as trucks, tractors and earthmoving equipment used in the construction, lumber and mining industries. The huge tires, having different priorities, are built in molds and put into heaters for the curing process. The problem is to find a feasible assignment of tires to molds and molds to heaters to achieve a maximum total priority. HOP produces about 7% more tires per shift compared to the previous manual way of developing schedules and moves the company towards its goal of quick response manufacturing with low inventories. A user-friendly Windows interface, written around our custom made optimization routines, allows for easy retrieval of the data from the company's data bases and provides for a graphical representation of the optimization results.     

Implications of population change on social insurance systems providing old-age benefits

General agreement, although not completely universal, exists in North America that cost analysis of programs providing old-age retirement benefits should be conducted over the long range, and not merely over the next few years. The actuarial cost estimates for what is now the U.S. Old-Age, Survivors, and Disability Insurance program have always been made over a long period of future years. Initially, for the 1935 Act, this period was 44 years (up through 1980), but most subsequent valuations of the program have used a 75-year period. The justification for this length of time is that it covers essentially the entire lifetime of every person in covered employment on the valuation date.It must be recognized that outside of North America — but with the exception of the United Kingdom — long-range social insurance programs providing retirement benefits are not generally considered over long future periods. The argument made in support of this short-sighted approach is that it is impossible to predict with any precision such long-range future operations. Countering this is the point that an estimate prepared by well-qualified persons is far better for policy planning and analysis than nothing at all.     

An evaluation of the applicability of system dynamics to patient flow modelling

The objective of this research is to determine whether Systems Dynamics (SD) is a beneficial method for modelling hospital patient flow from a strategic planning perspective. While discrete event simulation has frequently been used as a tool for analysing and improving patient flow in health care settings, the desire to assess and understand patient flow and resource demand from a more strategic, and therefore aggregate, perspective led to the use of SD. To evaluate the suitability of such an approach, a model was developed in collaboration with the General Campus at The Ottawa Hospital with particular attention paid to the delays experienced by patients in the emergency department. The modelling techniques used, model validation and scenarios tested with the model are discussed, accompanied by comments regarding the appropriateness of SD for such a model.     

Pricing public health care services using DEA: Methodology versus politics

The New Zealand public health sector has used DEA since 1997 to identify efficient expenditure levels to set prices for hospital services at the DRG level. Given the size of the expenditure (NZ$ 2.6 billion), considerable robustness was required for the results and sophistication of the models/process. While the model development and application appeared to be successful, politics overturned the results in the short run. In the longer term, the results have been shown to be reasonably robust and have become a base-line reference for future developments. As such, this paper reports a relatively successful transfer of theory into practice.     

OPTIMAL DISCOUNTING OF BENEFITS FROM CLEANUP AT WASTE SITES

Abstract This paper uses a general equilibrium optimal growth model to discuss the role of optimal discounting of future benefits from cleanup at high‐level toxic waste sites. Cleanup simultaneously generates two streams of benefits. One of these is directly from utility and the other is indirectly from the added productivity of workers. We note that the optimal discount rate is different for these two types of benefits. Along the optimal path, the former are discounted at the rate of time preference and the latter at the market rate of interest. We achieve this by identifying four components of the shadow value of the stock of toxic waste. These are the utility, productivity, cost, and abundance effects. The distinction between discount rates appears to have been overlooked in the literature but has significant implications for environmental cost‐benefit analysis due to the growing interest in applying zero time preference to environmental problems, (like waste cleanup) whose consequences extend many generations into the future. A numerical example is included to illustrate these concepts.     

A production–inventory model in an imperfect production process

The paper develops a model to determine the optimal product reliability and production rate that achieves the biggest total integrated profit for an imperfect manufacturing process. The basic assumption of the classical Economic Manufacturing Quantity (EMQ) model is that all manufacturing items are of perfect quality. The assumption is not true in practice. Most of the production system produces perfect and imperfect quality items. In some cases the imperfect quality (non conforming) items are reworked at a cost to restore its quality to the original one. Rework cost may be reduced by improvements in product reliability (i.e., decreasing in product reliability parameter). Lower value of product reliability parameter results in increase development cost of production and also smaller quantity of nonconforming products. The unit production cost is a function of product reliability parameter and production rate. As a result, higher development cost increases unit production cost. The problem of optimal planning work and rework processes belongs to the broad field of production–inventory model which deals with all kinds of reuse processes in supply chains. These processes aim to recover defective product items in such a way that they meet the quality level of ‘good item’. The benefits from imperfect quality items are: regaining the material and value added on defective items and improving the environment protection. In this point of view, a model is introduced here to guide a firm/industry in addressing variable product reliability factor, variable unit production cost and dynamic production rate for time-varying demand. The paper provides an optimal control formulation of the problem and develops necessary and sufficient conditions for optimality of the dynamic variables. In this purpose, the Euler–Lagrange method is used to obtain optimal solutions for product reliability parameter and dynamic production rate. Finally, numerical examples are given to illustrate the proposed model.     

New differentiated consensus problem with topology cost constraints

A new differentiated consensus problem is studied. The problem is, given a system with multiple classes, consensus is targeted for each class and the consensus values can be different among the classes. Specifically, differentiated consensus is studied in a distributed stochastic network of nodes (or agents), where tasks assigned with different priorities are serviced. The network is assumed to have a switching topology and involves noises, delays in measurements, and topology cost constraints. The goal is to reach a balanced load (i.e., consensus) across the network and, at the same time, to satisfy the topology cost constraint, both for each priority class. A new control protocol is proposed, with which the network resources are allocated in a randomized way with a probability assigned to each priority class. It is shown that the control protocol meets the topology cost constraint and can be used to reach an approximate consensus for each of the priority classes in the network.     

Measuring the value of information: The case of data on the cost of producing cotton

Operational measurement methods may be developed to measure the value of information in the data reported by the U.S. Government. Illustrative measures for cost of cotton production statistics indicate that the benefits from these data in certain important uses may far exceed their costs. If similar measures could be provided for major Government data programmes, it would facilitate the development of a national data policy that is oriented toward decision making and improvements in economic growth, national well-being, and quality of life. Making these estimates would begin to provide the dollar values in important uses of information in the nation's data bases. These values are needed for allocating resources to maintain, refine, and develop fundamental data series. Cutting data expenditure in the absence of these value measures may be false economy indeed; because, reducing data series with very high benefit/cost ratios might well limit, if not reduce, living standards for many generations to come.Robert R. Nathan Associates, Inc.     

A Multiple-criteria Approach to Dynamic Cold-ingot Substitution

Bethlehem Steel's plant at Bethlehem, Pennsylvania uses a computer-based mill-providing procedure to plan ingot requirements for the production of structural shapes and pilings. When not enough hot steel is available to meet all the ingot requirements, cold steel ingots from inventory must be substituted in order to meet the production plan. A computer system was developed that dynamically selects cold ingots to use when hot steel is not available. This system selects cold ingots based first on ingot-selection priorities, and secondly, within priorities, on several criteria. An approach was developed that assigns a penalty to each feasible cold ingot such that the priorities and multiple criteria are addressed by simply ranking the ingots based on their penalty values. Ingots are selected from the top of the ranked list, and the results are consistently acceptable to the steel-providers at the Bethlehem plant. The system improves yield and reduces material-handling costs.     

Progressive Basic Decision CPM

PERT and CPM are two valuable tools for the planning, scheduling and controllingof projects, but they do not on their own deal with the interdependence between planning resource utilization or direct cost expenditure and sclheduling with its overhead cost (penalty cost and/or reward bonus) implications. Several approaches to overcome this deficiency are possible, this paper dealing with one known as Decision CPM. The most recent approach to the Decision CPM problem known to the authors leads to relatively large integer programming problems which are solved as such. This paper considers a restricted formulation of the Decision CPM problem in an integer programming framework, and shows how it may be solved relatively easily witlhout resort to integer programming methods. Extensions of the restricted model are also considered briefly, some of which pose no difficulties, while others suggest the need for a hybrid of other approaches and that described here.