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.

通过支持技术的开发，使用在线参与者经营的在线平台（例如，这一授予的旅行和兼职护士）来有效地匹配旅行和兼职护士，从而有效地匹配了技术的发展，从而有助于改善国家卫生，从而有助于改善国家卫生，从而有助于改善国家健康。要充分有效，此类在线平台必须考虑护士可用性，护士对轮班的偏好，护士不展示和公平考虑因素而产生的不确定性。结合这些问题会导致需要开发解决方案方法的复杂数学模型。工业合作将在学者和从业人员之间创建新的沟通渠道，从而设计有效的匹配政策，以减轻护士短缺。随附的教育计划将支持研究生和本科教育，并为学生提供开发运营方法来解决重要的社会问题的机会，同时获得与现实生活数据和行业参与者一起工作的现实生活经验。这项研究项目将开发用于新颖的二元二进制和Integer多项式优化模型的解决方案方法。该项目还将为护士供求动态可用的环境制定可实施的自适应政策。开发技术的性能将使用模拟以及行业合作伙伴提供的实际数据进行测试。该数据还将用于估计护士偏好的功能表示，这些功能表示将纳入静态和动态优化和策略分析模型中。该项目的结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就业机会，或在服务经济中向客户提供商品和服务。该奖项反映了NSF的法定任务，并被认为是通过基金会的知识分子优点和更广泛的审查标准来通过评估来获得支持的。