Resource consumption of a diffusion model for prevention programs: the PROSPER delivery system

Abstract

Purpose: To prepare public systems to implement evidence-based prevention programs for adolescents, it is necessary to have accurate estimates of programs' resource consumption. When evidence-based programs are implemented through a specialized prevention delivery system, additional costs may be incurred during cultivation of the delivery infrastructure. Currently, there is limited research on the resource consumption of such delivery systems and programs. In this article, we describe the resource consumption of implementing the PROSPER (PROmoting School-Community-University Partnerships to Enhance Resilience) delivery system for a period of 5 years in one state, and how the financial and economic costs of its implementation affect local communities as well as the Cooperative Extension and University systems.

Methods: We used a six-step framework for conducting cost analysis, using a Cost-Procedure-Process-Outcome Analysis model (Yates, Analyzing costs, procedures, processes, and outcomes in human services: An introduction, 1996; Yates, 2009). This method entails defining the delivery System; bounding cost parameters; identifying, quantifying, and valuing systemic resource Consumption, and conducting sensitivity analysis of the cost estimates.

Results: Our analyses estimated both the financial and economic costs of the PROSPER delivery system. Evaluation of PROSPER illustrated how costs vary over time depending on the primacy of certain activities (e.g., team development, facilitator training, program implementation). Additionally, this work describes how the PROSPER model cultivates a complex resource infrastructure and provides preliminary evidence of systemic efficiencies.

Conclusions: This work highlights the need to study the costs of diffusion across time and broadens definitions of what is essential for successful implementation. In particular, cost analyses offer innovative methodologies for analyzing the resource needs of prevention systems.