Multi-objective Robust Stochastic Planning and Scheduling of Healthcare Service Providers

医疗服务提供者的多目标鲁棒随机规划和调度

• 批准号: 0928936
• 负责人: Sanjay Mehrotra
• 金额: $ 45.5万
• 依托单位: Northwestern University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-01 至 2014-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0928936&HistoricalAwards=false
• 关键词: Multi; objective; Robust; Stochastic; Planning

This grant provides funding for developing novel models and methods for planning, scheduling, staffing, and assignment (PSSA) problems that have multiple objectives and are unpredictable because of future uncertainty. Such problems arise frequently in the healthcare industry, which would be the focus application area. Examples of multiple, often competing, objectives are: patient safety and satisfaction, cost of service, continuity of care, educational goals of the residents, and staff satisfaction. Examples of uncertainty are patient workload and service times. Realistic mathematical models will be developed for such problems for healthcare professionals incorporating the unique features of this setting. A particular focus will be on medical resident scheduling. Computational methods will be developed for solving these models. In particular, heuristic methods will be developed for quickly identifying good candidate solutions for such problems. These methods will be tested on realistic data from the healthcare setting.If successful, the results of this research will enable healthcare providers to improve work flow and to make utilize the skills of the provider's medical staff. Improved training schedules of medical school residents would be possible, while meeting their residency requirements. Patient satisfaction will improve as continuity of care is enhanced. The computational methods developed for solving problems arising in healthcare will also be useful for stochastic multi-objective integer programming models arising in a wide variety of application areas including production planning, supply chain management and vehicle.

该补助金为开发新的模型和方法提供资金，用于规划，调度，人员配备和分配（PSSA）问题，这些问题具有多个目标，并且由于未来的不确定性而不可预测。 这些问题经常出现在医疗保健行业，这将是重点应用领域。 多个，往往是相互竞争的，目标的例子是：病人的安全和满意度，服务成本，护理的连续性，居民的教育目标，工作人员的满意度。 不确定性的例子是病人的工作量和服务时间。 现实的数学模型将开发这样的问题，为医疗保健专业人员结合这种设置的独特功能。 一个特别的重点将是医疗住院医生的时间安排。 将开发计算方法来解决这些模型。 特别是，启发式方法将开发快速识别良好的候选解决方案，这些问题。 这些方法将在来自医疗环境的真实数据上进行测试。如果成功，这项研究的结果将使医疗服务提供者能够改善工作流程，并利用提供者医务人员的技能。 改善医学院住院医师的培训时间表是可能的，同时满足他们的住院要求。随着护理连续性的提高，患者满意度将提高。 为解决医疗保健中出现的问题而开发的计算方法也将用于随机多目标整数规划模型，这些模型在各种应用领域中产生，包括生产计划，供应链管理和车辆。