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Session Title: Money Talks: Including Costs in Your Evaluation
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Panel Session 809 to be held in Liberty Ballroom Section B on Saturday, November 10, 1:50 PM to 3:20 PM
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Sponsored by the Quantitative Methods: Theory and Design TIG
and the Costs, Effectiveness, Benefits, and Economics TIG
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| Chair(s): |
| Patricia Herman,
University of Arizona,
pherman@email.arizona.edu
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| Discussant(s):
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| Brian Yates,
American University,
brian.yates@mac.com
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| Abstract:
This panel presents an overview of three types of cost-based evaluation techniques that can be added to existing evaluation plans to increase the usefulness of results. The three methods are basic cost-effectiveness analysis, Monte Carlo simulation, and threshold analysis. Each is applied, as an illustration, to a different component of a tobacco control program. This panel will attempt to illustrate that cost-based evaluation is possible across a number of types of programs where these techniques might not typically be considered. None of the programs evaluated had a previous cost evaluation, and the methods here were conducted, together with an experienced practitioner, by program evaluators with little direct experience with cost-based techniques. All results are preliminary, and each panelist will discuss what they learned from adding a cost analysis to their evaluations. The panel will end with a discussion intended to ensure generalization of the approaches to all types of programs.
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Overview of Cost-based Evaluation
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| Patricia Herman,
University of Arizona,
pherman@email.arizona.edu
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This short presentation will provide a quick overview of cost-based evaluation and its benefits, and allow for an introduction to the other speakers, their program components, and the cost-based evaluation technique each will demonstrate.
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Cost-effectiveness of Smoking Cessation Programs: A Preliminary Analysis
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| Dee Dee Avery,
University of Arizona,
davery@email.arizona.edu
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| Patricia Herman,
University of Arizona,
pherman@email.arizona.edu
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Arizona, like many states, has in place a series of programs targeting smoking cessation. An estimate of the quit rate is available for each as a result of regular program evaluation activities. In this case all that is required is to assemble the resources used by each program from program documentation and to compare these costs to the effects seen. This paper presents an example of a straightforward cost-effectiveness analysis. Challenges involved in gathering cost data, in getting program manager by-in for the analysis, and in performing a sensitivity analysis will also be discussed.
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Costs and Effects From Several Sources? Putting it All Together With a Monte Carlo Simulation
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| Michele Walsh,
University of Arizona,
mwalsh@u.arizona.edu
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| Patricia Herman,
University of Arizona,
pherman@email.arizona.edu
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Put broadly, Monte Carlo methods are useful for modeling phenomena with significant uncertainty in inputs. For campaigns offering free nicotine replacement therapy (NRT) there is often an increase in cessation efforts by smokers, a proportion of that increase (and of those who would have tried to quit anyway) that obtain the free NRT, an increase in the proportion of those efforts that are successful at the end of the intervention, and an increase in the proportion of those who remain successful at longer-term follow up-the measured effect of the program. In addition to overall administrative costs, the costs of these programs depend on the number of smokers who must be screened for eligibility, the number receiving free NRT vouchers, and the number who actually redeem those vouchers. Each of these inputs is uncertain. Monte Carlo simulation allows an estimate of program cost-effectiveness takes these uncertainties into account.
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Threshold Analysis: How Much Reduced Exposure Does it Take to Make a Secondhand Smoke Media Campaign Worthwhile?
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| Crystal Schemp,
University of Arizona,
csg@email.arizona.edu
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| Patricia Herman,
University of Arizona,
pherman@email.arizona.edu
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Every year millions are spent by tobacco control programs using media campaigns to prevent smoking initiation, to promote cessation, and to reduce exposure to secondhand smoke. Because of their wide exposure and the number of concurrent program components, the effect of these campaigns is difficult to determine. Although other cost-based evaluations require that effects be measured prior to (or in parallel with) the cost analysis, a threshold analysis uses campaign cost and the dollar value of smoking reduction to provide a lower-limit for effects for the program to be cost-effective. This threshold value can oft-times indicate without further evaluation a high likelihood of cost-effectiveness (the lower limit is so low that it is highly likely actual measured effects will exceed that value) or a high likelihood that the program is not cost-effective (the lower limit is so high as to preclude the likelihood that actual effects will exceed that value).
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