Abstract for: From static to dynamic, the transformation of a health care program cost data into an open-source decision support tool

Introduction: Health care systems are slow to adopt effective Community Health Worker (CHW) programs, and decision makers may benefit from additional support to translate CHW program evidence to make it relevant to their practices and health systems. This study used agent-based modeling (ABM) to transform empirical Return on Investment (ROI) data from a CHW asthma program to develop a decision support tool that can inform program adoption. Methods: Using published data from an 11-year follow-up to a CHW asthma intervention, we simulated common program variants and adaptations that can have a negative, neutral, or positive impact on ROI. Results: The model showed that the time to breakeven (ROI = 1.0) can vary widely and nearly doubled depending on the scenarios presented (2.8 - 7.7 years). Sensitivity analysis of isolated variables, such as staffing, offered insight into underlying and model-specific impacts. Conclusion: These results present variation on ROI reporting and how an agent-based model may be a useful and practical approach to reporting and research. The results demonstrate how sustained programs and common variation in programming can impact financial outcomes. As an open-source decision support tool, the model is available to reuse or repurpose for new studies.