Hospital Systems Occupancy Prediction and Control to Increase Access, Smooth Provider Workload, and Reduce Cost

医院系统占用预测和控制，以增加访问、平稳提供者工作负载并降低成本

• 批准号: 1068638
• 负责人: MARK VAN OYEN
• 金额: $ 23.97万
• 依托单位: Regents of the University of Michigan - Ann Arbor
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-06-01 至 2014-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1068638&HistoricalAwards=false
• 关键词: Hospital; Systems; Occupancy; Prediction; Control

This research project creates an innovative methodology based upon enterprise-wide patient flow modeling to guide operational admission and scheduling practices to smooth hospital census/occupancy. Our research will provide theoretical foundations as well as a practical decision support methodology incorporating (1) the stochasticity of unscheduled/emergent patient arrivals, (2) scheduled elective surgical and medical inpatients, (3) the stochastic system dynamics of bed block and occupancy by bed unit/ward and (4) the patient's treatment trajectory through the bed units and (5) other critical hospital resources (i.e. physicians, nurses, equipment, specialized beds, operating time etc.). Analytical models will be developed to approximate the hospital beds as a dynamically controlled queueing network. A theoretical patient flow modeling methodology will be used to capture the stochastic evolution of the patient's bed resource needs and thereby census. New optimization/control models will provide methods for (1) elective admission planning and (2) census recourse/control. Hospitals frequently lack rigorous, accurate enterprise level planning and daily census management tools developed from a systems perspective. This research will provide the theoretical foundations, practical methodologies, and proof of concept for a novel online decision support approach to achieve increased access by reducing turnaways and delays to access, better matching of the care workload to the scheduled staff for improved quality of patient care, and reduced hospital operating costs. This research engages partner hospitals that are recognized as leaders in innovation. Outcomes will be disseminated to engineering and public health communities through publications targeting highly visible journals in engineering, and medicine/healthcare. Graduate and undergraduate students in engineering, business, and public health will benefit through classroom instruction (including teaching tools) and involvement in the research. The highly relevant application will equip students to be change agents in improving hospital operations.

该研究项目创建了一种基于企业范围内的患者流建模的创新方法，以指导运营入院和调度实践，以顺利进行医院普查/入住。我们的研究将提供理论基础以及实用的决策支持方法，包括（1）计划外/紧急患者到达的随机性，（2）计划的择期手术和内科住院患者，（3）床位单元/病房的床位区和占用率的随机系统动力学;（4）患者通过床位单元的治疗轨迹;（5）其他关键医院资源（即医生、护士、设备、专用病床、手术时间等）。将开发分析模型，以将医院病床近似为动态控制的网络。一个理论上的病人流量建模方法将被用来捕捉随机演变的病人的病床资源需求，从而普查。新的优化/控制模型将为（1）选修入学计划和（2）普查资源/控制提供方法。医院经常缺乏严格、准确的企业级规划和从系统角度开发的日常人口普查管理工具。这项研究将提供一种新的在线决策支持方法的理论基础，实用的方法和概念证明，以实现通过减少周转和延迟访问，更好地匹配的护理工作量，以提高患者护理质量的预定工作人员，并降低医院的运营成本，以增加访问。这项研究涉及被公认为创新领导者的合作医院。成果将通过针对工程和医学/医疗保健领域知名期刊的出版物传播给工程和公共卫生界。工程，商业和公共卫生的研究生和本科生将通过课堂教学（包括教学工具）和参与研究而受益。高度相关的应用程序将使学生成为改善医院运营的变革推动者。