Guilkey David K, Hutchinson Paul, Lance Peter
Department of Economics and the MEASURE Evaluation Project, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA.
J Health Commun. 2006;11 Suppl 2:47-67. doi: 10.1080/10810730600973987.
This article describes methods for analyzing the cost-effectiveness of health communication programs, focusing in particular on estimating program effectiveness with econometric methods that address experimental and quasi-experimental designs (and their absence), national or subnational program coverage, and endogenously targeting of programs. Experimental designs provide a gold standard for assessing effectiveness but are seldom feasible for large-scale health communication programs. Even in the absence of such designs, however, fairly simple methods can be used to examine intermediate objectives, such as program reach, which in turn can be linked to program costs to estimate cost effectiveness. When moving beyond program reach to behavioral or other outcome measures, such as contraceptive use or fertility, or when faced with full-coverage national programs, more elaborate data and methods are required. We discuss data requirements and assumptions necessary in each case, focusing on single-equation multiple regression models, structural equations models, and fixed effects estimators for use with longitudinal data, and then describing how cost information can be incorporated into econometric models so as to get measures of the cost-effectiveness of communication interventions.
本文介绍了分析健康传播项目成本效益的方法,特别着重于运用计量经济学方法估计项目效果,这些方法涉及实验性和准实验性设计(以及缺乏此类设计的情况)、国家或次国家级项目覆盖范围以及项目的内生性目标设定。实验性设计为评估效果提供了黄金标准,但对于大规模健康传播项目而言很少可行。然而,即便没有此类设计,也可使用相当简单的方法来考察诸如项目覆盖范围等中间目标,而这反过来又可与项目成本相联系以估计成本效益。当从项目覆盖范围转向行为或其他结果指标(如避孕措施使用情况或生育率)时,或者当面对全面覆盖的国家级项目时,就需要更详尽的数据和方法。我们讨论了每种情况下所需的数据要求和假设,重点关注单方程多元回归模型、结构方程模型以及用于纵向数据的固定效应估计量,然后描述如何将成本信息纳入计量经济学模型,以便得出传播干预措施的成本效益衡量指标。