An Interactive Modeling Tool for Projecting the Health and Direct Medical Cost Impact of Changes in the Sexually Transmitted Diseases Prevention Program Budgets

Abstract

Context: Estimating the return on investment for public health services, tailored to the state level, is critical for demonstrating their value and making resource allocation decisions. However, many health departments have limited staff capacity and expertise to conduct economic analyses in-house. Program: We developed a user-friendly, interactive Excel-based spreadsheet model that health departments can use to estimate the impact of increases or decreases in sexually transmitted infection (STI) prevention funding on the incidence and direct medical costs of chlamydia, gonorrhea, syphilis, and STI-attributable HIV infections. Users tailor results to their jurisdictions by entering the size of their population served; the number of annual STI diagnoses; their prior annual funding amount; and their anticipated new funding amount. The interface was developed using human-centered design principles, including focus groups with 15 model users to collect feedback on an earlier model version and a usability study on the prototype with 6 model users to finalize the interface. Implementation: The STI Prevention Allocation Consequences Estimator (“SPACE Monkey 2.0”) model will be publicly available as a free downloadable tool. Evaluation: In the usability testing of the prototype, participants provided overall positive feedback. They appreciated the clear interpretations, outcomes expressed as direct medical costs, functionalities to interact with the output and copy charts into external applications, visualization designs, and accessible information about the model's assumptions and limitations. Participants provided positive responses to a 10-item usability evaluation survey regarding their experiences with the prototype. Discussion: Modeling tools that synthesize literature-based estimates and are developed with human-centered design principles have the potential to make evidence-based estimates of budget changes widely accessible to health departments.