Cost-effectiveness analysis for health communication programs
David K Guilkey1, Paul Hutchinson, Peter Lance
1Department of Economics and the MEASURE Evaluation Project, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA. david-guilkey@unc.edu
This article presents econometric methods to assess the cost-effectiveness of health communication programs, even without experimental designs. It details how to link program costs with effectiveness measures for better public health intervention analysis.
Area of Science:
- Health Economics
- Econometrics
- Public Health Communication
Background:
- Assessing the cost-effectiveness of health communication programs is crucial for resource allocation.
- Experimental designs, while ideal, are often infeasible for large-scale public health initiatives.
Purpose of the Study:
- To describe econometric methods for analyzing the cost-effectiveness of health communication programs.
- To address challenges including lack of experimental designs, varying program coverage, and endogenous targeting.
Main Methods:
- Utilizes econometric approaches, including regression models and fixed effects estimators for longitudinal data.
- Incorporates cost information directly into econometric models to derive cost-effectiveness measures.
- Discusses methods for estimating program effectiveness, from intermediate objectives like reach to behavioral outcomes like contraceptive use.
Main Results:
- Demonstrates that even without experimental data, intermediate program objectives (e.g., reach) can be analyzed for cost-effectiveness.
- Highlights the need for more complex data and methods when evaluating broader outcomes or full-coverage programs.
- Provides a framework for integrating cost data with effectiveness estimates.
Conclusions:
- Econometric methods offer flexible tools for evaluating the cost-effectiveness of diverse health communication programs.
- The described methods enable robust analysis across different study designs and outcome measures.
- This work facilitates evidence-based decision-making in public health interventions.
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