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GOALI/Collaborative Research: Improving Patient Flow in Hospitals

GOALI/Collaborative Research: Improving Patient Flow in Hospitals
GOALI/合作研究:改善医院的患者流动
批准号:
1762544
负责人:
Jing Dong
金额:
$4.72万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-08-15 至 2022-07-31

项目摘要

项目成果

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中文摘要
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英文摘要
This Grant Opportunity for Academic Liaison with Industry (GOALI) Program award will advance the national health by reducing congestion and improving patient flow within hospital units and between hospitals. By developing models that predict flow dynamics and address sources of congestion, this project will improve patient safety and satisfaction, and at the same time reduce staffing and equipment costs to the hospital. Reduced congestion will also improve occupancy prediction, thus reducing ambulance diversions within the hospital network. This research employs novel modeling techniques that are informed by a close collaboration between the PIs and the GOALI partner, Northwestern Memorial Hospital (NMH). Models will be developed that are easy to calibrate and sufficiently general, so that their analyses and insights are applicable in a broad range of clinical settings within the hospital. The award provides support for graduate students to engage in research that will be of direct benefit to healthcare operations. The PIs will incorporate the results of their research in courses on queueing and service engineering. The outcomes of the research will be disseminated to both the operations research and the healthcare practitioner communities.This award supports research on multi-server queueing models, tailored specifically to hospital operations, that address key features of patient-flow dynamics. These features include bursty departures due to periodic discharge windows and non-stationary arrival processes. Because of the complexity of the dynamics, the research develops appropriate approximations for queueing phenomena based on fluid approximations during peak loads and infinite server approximations during lightly loaded periods. These methods, in conjunction with high-fidelity simulations, will be used to characterize long-run behavior of the patient-flow process, such as the maximum throughput of hospital units, and their (periodic) time-dependent equilibria behavior under different operational policies.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.
期刊论文(5)
专著(0)
科研奖励(0)
会议论文
Managing Queues with Different Resource Requirements
管理具有不同资源要求的队列
DOI: 10.1287/opre.2022.2284
发表时间: 2022
期刊: Operations Research
影响因子: 2.7
作者: [Zychlinski, Noa, Chan, Carri W., Dong, Jing]
通讯作者: Dong, Jing
DOI: 10.1287/msom.2022.0377
发表时间: 2024
期刊: Manufacturing & Service Operations Management
影响因子: --
作者: [Dong, Jing, Görgülü, Berk, Sarhangian, Vahid]
通讯作者: Sarhangian, Vahid
Queueing Models for Patient-Flow Dynamics in Inpatient Wards
住院病房患者流动动态的排队模型
DOI: 10.1287/opre.2019.1845
发表时间: 2020
期刊: Operations Research
影响因子: 2.7
作者: [Dong, Jing, Perry, Ohad]
通讯作者: Perry, Ohad
DOI: 10.1007/s11134-020-09669-5
发表时间: 2020-10-04
期刊: QUEUEING SYSTEMS
影响因子: 1.2
作者: [Chen, Jinsheng, Dong, Jing, Shi, Pengyi]
通讯作者: Shi, Pengyi
CAREER: Improving Operational Decision Making with Predictive Information and Data
  • 批准号:
    1944209
  • 项目类别:
    Standard Grant
  • 资助金额:
    $50.0万
  • 财政年份:
    2020
  • 负责人:
    Jing Dong
  • 依托单位:
Collaborative Research: Tolerance-Enforced Simulation of Stochastic Processes
  • 批准号:
    1720433
  • 项目类别:
    Standard Grant
  • 资助金额:
    $8.94万
  • 财政年份:
    2017
  • 负责人:
    Jing Dong
  • 依托单位:
海外基金