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This paper provides an educational review covering the consideration of costs for cost-effectiveness analysis (CEA), summarising relevant methods and research from the published literature. Cost data are typically generated by applying appropriate unit costs to healthcare resource-use data for patients. Trial-based evaluations and decision analytic modelling represent the two main vehicles for CEA. The costs to consider will depend on the perspective taken, with conflicting recommendations ranging from focusing solely on healthcare to the broader 'societal' perspective. Alternative sources of resource-use are available, including medical records and forms completed by researchers or patients. Different methods are available for the statistical analysis of cost data, although consideration needs to be given to the appropriate methods, given cost data are typically non-normal with a mass point at zero and a long right-hand tail. The choice of covariates for inclusion in econometric models also needs careful consideration, focusing on those that are influential and that will improve balance and precision. Where data are missing, it is important to consider the type of missingness and then apply appropriate analytical methods, such as imputation. Uncertainty around costs should also be reflected to allow for consideration on the impacts of the CEA results on decision uncertainty. Costs should be discounted to account for differential timing, and are typically inflated to a common cost year. The choice of methods and sources of information used when accounting for cost information within CEA will have an effect on the subsequent cost-effectiveness results and how information is presented to decision makers. It is important that the most appropriate methods are used as overlooking the complicated nature of cost data could lead to inaccurate information being given to decision makers. [ABSTRACT FROM AUTHOR]

This paper resolves several controversies in CEA. Generalizing [Garber, A.M., Phelps, C.E., 1997. Economic foundations of cost-effectiveness analysis. Journal of Health Economics 16 (1), 1–31], the paper shows accounting for unrelated future costs distorts decision making. After replicating [Meltzer, D., 1997. Accounting for future costs in medical cost-effectiveness analysis. Journal of Health Economics 16 (1), 33–64] quite different conclusion that unrelated future costs should be included in CEA, the paper shows that Meltzer''s findings result from modeling the budget constraint as an annuity, which is problematic. The paper also shows that related costs should be included in CEA. This holds for a variety of models, including a health maximization model. CEA should treat costs in the manner recommended by Garber and Phelps. [Copyright &y& Elsevier]

Where prioritization and selection process of large-scale construction projects is concerned, governments should consider various quantitative and qualitative criteria when choosing the best project alternative. The traditional benefit–cost (BC) analysis has some drawbacks in terms of analyzing qualitative attributes that cannot be easily expressed in monetary terms. To eliminate this limitation, multicriteria decision-making techniques are proposed for the solution of project prioritization problems. In this paper, an analytic network process (ANP) model is developed to demonstrate how the project selection process can be carried out by considering both quantitative and qualitative factors, as well as their interrelations. The decision network is grouped under four subnetworks, namely benefits, costs, opportunities, and risks. The selected alternatives are real highway projects that are in the investment agenda of the Turkish government. Using the proposed network model, four investment alternatives are assessed by a team of experts and achieved results demonstrate that the ranking of project alternatives may significantly change when the ANP model is used instead of the classical B/C approach. [ABSTRACT FROM AUTHOR]

The product with the highest unit profit may not be the product with the highest profit per unit of resource consumed. The Theory of Constraints (TOC), with its emphasis on throughput costing, offers one possible approach to profitability analysis, but it is focused on the short term. The authors discuss why throughput costing, in combination with ABC, is a better option to guide long-term, strategic decision making. [ABSTRACT FROM PUBLISHER]

Health administrators are searching for ways to decide how best to use and manage their limited resources as well as to identify what combination of strategies will result in the most effective production and delivery of health-care services. To assist in this dilemma, decision makers are increasingly using two analytical tools, benefit-cost analysis and cost-effectiveness analysis. Cost-effectiveness analysis is a subset of benefit-cost analysis. The key distinction between benefit-cost analysis and cost-effectiveness analysis is that benefit-cost analysis requires all project outcomes to be valued in monetary terms, whereas cost-effectiveness analysis requires only that the outcomes be expressed in commensurate units.

El artículo enfoca en el cálculo de costos para la toma de decisiones en contextos corporativos. El autor utiliza ejemplos de la vida cotidiana para describir el proceso de calcular los costos y su relación con tomar decisiones. Arguye que el costo relevante asociado con una decisión depende de que dicha decisión sea el causante del gasto o del ahorro.