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.

翻译：数据驱动的优化模型有潜力显著改善医院容量管理，尤其是在需求激增时期，此时容量的有效分配最为关键且具挑战性。然而，要将这些模型整合到现有流程中并创造价值，必须认识到医院管理者最终对容量管理决策负责，并为他们精心构建值得信赖且易用的工具。在本研究中，我们开发了一款交互式、用户友好的电子仪表板，用于在激增期间为医院容量管理决策提供信息支持。该仪表板整合了实时医院数据、预测分析和优化模型，允许医院管理者以交互方式自定义参数，探索一系列场景，并提供关于推荐最优决策的实时更新。该仪表板通过参与式设计流程创建，医院管理者作为开发团队成员参与其中，以确保其实用性、可信度、透明度、可解释性和可用性。我们在COVID-19疫情高峰期间成功将该仪表板部署于约翰·霍普金斯卫生系统，以应对医院容量管理工具需求的增长。该仪表板每日使用，其结果定期向医院领导层汇报。本研究展示了面向医院系统容量管理的前瞻性、数据驱动、交互式决策支持工具的实际应用。