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Suggested Citation:"Appendix A: Glossary." Institute of Medicine and National Research Council. 2014. Considerations in Applying Benefit-Cost Analysis to Preventive Interventions for Children, Youth, and Families: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/18708.
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Appendix A


Glossary

attrition—in the context of research studies, refers to the gradual loss of study participants, some percentage of whom often drop out.

benefit-cost analysis—a method of economic analysis in which both costs and outcomes of an intervention are valued in monetary terms, permitting a direct comparison of the benefits produced by the intervention with its costs (also referred to as cost-benefit analysis).

cost-effectiveness analysis—a method of economic analysis in which outcomes of an intervention are measured in nonmonetary terms. The outcomes and costs are compared with both the outcomes (using the same outcome measures) and the costs for competing interventions, or with an established standard, to determine if the outcomes are achieved at reasonable monetary cost.

discount rate—a factor used to estimate future costs or the value of future benefits at the current equivalent value, used with the goal of attempting to take into account likely changes in valuation, opportunity costs, and other factors.

effect size—the magnitude of results (or effects on participants) of a particular treatment or intervention that is being studied.

interrupted time series study—is a type of quasi-experiment in which measures on a sample or a series of samples from the same population are obtained several times before and after a manipulated event or a naturally occurring event.

Suggested Citation:"Appendix A: Glossary." Institute of Medicine and National Research Council. 2014. Considerations in Applying Benefit-Cost Analysis to Preventive Interventions for Children, Youth, and Families: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/18708.
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Monte Carlo simulation—the repeated drawing of uncertain parameters from assumed distributions to produce a distribution of possible outcomes. In benefit-cost analysis, Monte Carlo simulation is used to translate uncertainty in predicted resource use, impacts, and their monetizations into a distribution of predicted net benefits.

opportunity cost—the value of alternatives not chosen, calculated as part of an analysis of the costs of the alternative that was chosen.

quasi-experimental design—an experiment designed to produce evidence of causality when randomized controlled trials are not possible, using alternative statistical procedures to compensate for nonrandom factors.

randomized controlled trial—an experiment in which the participants are assigned by chance either to receive the intervention or treatment being studied or not to receive it, so the results can be compared across statistical identical groups. When this is done with a large enough number of participants, any differences among them that might influence their response to the treatment will be distributed evenly.

regression discontinuity design—a quasi-experimental analysis that can be used in program evaluation when randomized assignment is not feasible. It is based on the assumption that individuals who fall just above or below a cutoff point on a particular scale are likely to be similar, so that this group can be treated as varying randomly.

shadow price—the true value or cost of the results of a particular decision, as calculated when no market price is available; a dollar value attached to an opportunity cost.

standard error—used to refer to the standard deviation of various sample statistics such as the mean or median. The smaller the standard error, the more representative the sample will be of the overall population.

Suggested Citation:"Appendix A: Glossary." Institute of Medicine and National Research Council. 2014. Considerations in Applying Benefit-Cost Analysis to Preventive Interventions for Children, Youth, and Families: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/18708.
×
Page 67
Suggested Citation:"Appendix A: Glossary." Institute of Medicine and National Research Council. 2014. Considerations in Applying Benefit-Cost Analysis to Preventive Interventions for Children, Youth, and Families: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/18708.
×
Page 68
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Benefit-cost analyses hold great promise for influencing policies related to children, youth, and families. By comparing the costs of preventive interventions with the long-term benefits of those interventions, benefit-cost analysis provides a tool for determining what kinds of investments have the greatest potential to reduce the physical, mental, and behavioral health problems of young people. More generally, the growth of benefit-cost analysis as a field of research and practice represents an exciting and promising trend in the development and implementation of public policies.

The utility of benefit-cost analyses has been limited by a lack of uniformity in the methods and assumptions underlying these studies. For years, those who perform and those who use benefit-cost analyses have argued that the development and use of theoretical, technical, and reporting standards for benefit-cost analyses would enhance the validity of results, increase comparability across studies, and accelerate the progress of the field.

Considerations in Applying Benefit-Cost Analysis to Preventive Interventions for Children, Youth, and Families is the summary of a workshop convened by the Board on Children, Youth, and Families of the Institute of Medicine and the National Research Council in November 2013 as the first phase of a possible two-part effort directed toward guiding future benefit-cost studies and enhancing the relevance of benefit-cost analysis to governments and other organizations wanting to make sound prevention decisions. The workshop brought together leading practitioners in the field, researchers who study the methodological and analytic dimensions of benefit-cost analysis, and representatives of organizations that use the results of benefit-cost analyses to shape and implement public policies. This report discusses a wide range of issues about benefit-cost analysis, including the level of research rigor that should be met before results from an evaluation are used to estimate or predict outcomes in a cost-benefit analysis; best practices and methodologies for costing prevention interventions; prevention outcomes that currently lend themselves to monetization; processes and methodologies that should be used when linking prevention outcomes to avoided costs or increased revenues; and best methods for handling risk and uncertainty in estimates.

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