  Data-driven optimization models have the potential to significantly improve
hospital capacity management, particularly during demand surges, when effective
allocation of capacity is most critical and challenging. However, integrating
models into existing processes in a way that provides value requires
recognizing that hospital administrators are ultimately responsible for making
capacity management decisions, and carefully building trustworthy and
accessible tools for them. In this study, we develop an interactive,
user-friendly, electronic dashboard for informing hospital capacity management
decisions during surge periods. The dashboard integrates real-time hospital
data, predictive analytics, and optimization models. It allows hospital
administrators to interactively customize parameters, enabling them to explore
a range of scenarios, and provides real-time updates on recommended optimal
decisions. The dashboard was created through a participatory design process,
involving hospital administrators in the development team to ensure practical
utility, trustworthiness, transparency, explainability, and usability. We
successfully deployed our dashboard within the Johns Hopkins Health System
during the height of the COVID-19 pandemic, addressing the increased need for
tools to inform hospital capacity management. It was used on a daily basis,
with results regularly communicated to hospital leadership. This study
demonstrates the practical application of a prospective, data-driven,
interactive decision-support tool for hospital system capacity management.
