GOALI: Nurse Matching to Hospitals Using Static and Dynamic Allocation through an Online Platform

GOALI：通过在线平台使用静态和动态分配将护士与医院匹配

• 批准号: 2245013
• 负责人: Seyed M. R. Iravani
• 金额: $ 45.01万
• 依托单位: Northwestern University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-01 至 2026-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2245013&HistoricalAwards=false
• 关键词: GOALI; Nurse; Matching; Hospitals; Using

This Grant Opportunity for Academic Liaison with Industry (GOALI) award contributes to the improvement of national health by supporting development of technology to efficiently match traveling and part-time nurses to vacant hospital shifts using online platforms such as that operated by the industry participant. To be fully effective such online platforms must consider uncertainty resulting from nurse availability, nurse preferences for the shifts, nurse no-show, and equity considerations. Incorporating these issues leads to complex mathematical models for which solution methodologies need to be developed. The industrial collaboration will create new channels of communications between academics and practitioners, leading to design of effective matching policies to alleviate nurse shortages. The accompanying educational plan will support graduate and undergraduate education and provide opportunities for students to develop operational methods to tackle an important societal problem, while gaining real-life experience working with real-life data and the industry participant.This research project will develop solution methods for novel binary and integer polynomial optimization models. The project will also develop implementable adaptive policies for environments where nurse supply and demand becomes available dynamically. The performance of developed techniques will be tested using simulations as well as real data provided by the industry partner. This data will also be used to estimate functional representation of nurse preferences, which will be incorporated in the static and dynamic optimization and policy analysis models. The outcomes from the project will also be useful in improving the efficiency of online platforms that offer jobs to freelancers, or offering goods and services to customers in a service economy.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

这项“与行业学术联络资助机会”（GOALI）奖通过支持技术开发，利用行业参与者运营的在线平台，有效地将旅行护士和兼职护士与空缺的医院班次匹配起来，从而有助于改善国民健康状况。为了充分发挥作用，此类在线平台必须考虑到护士可用性、护士对轮班的偏好、护士缺勤和公平性等因素带来的不确定性。合并这些问题会导致需要开发解决方法的复杂数学模型。这项产业合作将为学术界和从业人员之间创造新的沟通渠道，从而设计出有效的配套政策，以缓解护士短缺问题。配套的教育计划将支持研究生和本科教育，并为学生提供发展解决重要社会问题的操作方法的机会，同时获得与现实数据和行业参与者合作的现实经验。本研究项目将开发新的二值和整数多项式优化模型的求解方法。该项目还将制定可实施的适应性政策，以适应护士供需动态变化的环境。开发的技术的性能将通过模拟和行业合作伙伴提供的真实数据进行测试。这些数据还将用于估计护士偏好的功能表示，这将被纳入静态和动态优化和政策分析模型。该项目的成果也将有助于提高在线平台的效率，这些平台为自由职业者提供工作，或为服务经济中的客户提供商品和服务。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。