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具有显著改善医院容量管理的潜力，尤其是在需求激增期间，此时有效的容量分配最为关键且最具挑战性。然而，要将模型以提供价值的方式整合到现有流程中，需要认识到医院管理者最终负责做出容量管理决策，并为他们精心构建可信且易于使用的工具。在本研究中，我们开发了一个交互式、用户友好的电子仪表板，用于在激增期为医院容量管理决策提供信息支持。该仪表板集成了实时医院数据、预测分析和优化模型。它允许医院管理者交互式地自定义参数，使其能够探索多种情景，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，让医院管理者加入开发团队，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大流行高峰期于约翰斯·霍普金斯医疗系统内部成功部署了该仪表板，满足了医院容量管理工具日益增长的需求。该工具被每日使用，其结果定期向医院领导层汇报。本研究展示了一种前瞻性、数据驱动、交互式的决策支持工具在医院系统容量管理中的实际应用。