GOALI/Collaborative Research: Consistent Nursing Home Staff Planning under Heterogeneous Service Demand
GOALI/Collaborative Research: Consistent Nursing Home Staff Planning under Heterogeneous Service Demand
批准号:
1825725
负责人:
Nan Kong
金额:
$24.3万
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:
2018-09-01 至 2023-08-31
中文摘要
点击翻译按钮获取中文摘要
英文摘要
This Grant Opportunities for Academic Liaison with Industry (GOALI) award will advance the national health by improving the delivery of health-care to the growing sector of the population served by nursing homes. Nursing homes are responsible for caring for the frail and vulnerable population of older adults who suffer from diverse chronic diseases, functional limitations and impairments. They must coordinate distinct caregivers to provide patients with round-the-clock physical and emotional care and assistance. Because of growing demand due to immutable population demographics, rapidly increasing health-care costs, and escalating nursing staff shortage, proper care for nursing home residents is at-risk. The goal of this project is to improve long-term nursing home quality of care and reduce costs using analytical methods and tools to realize proactive, resident-centered staffing plans. This project will improve workforce planning, recruitment and allocation decisions for nursing home managers, reduce stress and burn-out by better balancing workloads for nursing home staff, and enhance health outcomes for nursing home residents by better meeting their diverse care needs. The close involvement of the engineering team with a nursing home operator and national aging health policy experts will also help transform nursing home culture into delivering more resident-centered and home-like care. The research objectives will be achieved through the development of a set of innovative models, algorithms, and decision tools. A predictive data analytics model and efficient estimation algorithms will be developed to characterize heterogeneous service need trajectories and length-of-stays of nursing home residents for service demand prediction improvement at the resident level. A two-stage stochastic programming model and efficient numerical optimization algorithms will be developed for consistent nursing home staff planning under service demand fluctuation and uncertainty. To maximize the practical relevance of research deliverables, a decision support system will be also developed to evaluate and validate the work in a real-world nursing home setting through our academic-industrial partnership with Greystone Healthcare Management Corporation and industry-scale solution deployment in their facilities.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
登录
查看更多内容
Optimal Nursing Home Service Scheduling Under covid-19 Related Probabilistic Staff Shortage: A Two-stage Stochastic Programming Approach
covid-19相关概率性人员短缺下的最佳疗养院服务调度:两阶段随机规划方法
DOI:
--
发表时间:
2021
期刊:
2021 Industrial and Systems Engineering Research Conference
影响因子:
--
作者:
[Jiang, S., Kong, N., Abrahamson, K., Yih, Y.]
通讯作者:
Yih, Y.
DOI:
10.1109/lra.2021.3140056
发表时间:
2022-04
期刊:
IEEE Robotics and Automation Letters
影响因子:
5.2
作者:
[Jingyuan Feng;Xiangpei Hu;N. Kong]
通讯作者:
Jingyuan Feng;Xiangpei Hu;N. Kong
Optimal Nursing Home Shift Scheduling: A Two-Stage Stochastic Programming Approach
最佳疗养院轮班安排:两阶段随机规划方法
DOI:
--
发表时间:
2020
期刊:
CASE 2020
影响因子:
--
作者:
[Shujin Jiang, Mingyang Li]
通讯作者:
Shujin Jiang, Mingyang Li
Heterogeneous length-of-stay modeling of post-acute care residents in the nursing home with competing discharge dispositions
具有竞争性出院处置的疗养院急性后护理居民的异质住院时间模型
DOI:
10.1007/s42524-022-0203-7
发表时间:
2022
期刊:
Frontiers of Engineering Management
影响因子:
7.4
作者:
[Sakib, Nazmus, Sun, Xuxue, Kong, Nan, Masterson, Chris, Meng, Hongdao, Smith, Kelly, Li, Mingyang]
通讯作者:
Li, Mingyang
DOI:
--
发表时间:
2019
期刊:
Proceedings of the 2019 IISE Annual Conference
影响因子:
--
作者:
[Sakib, Nazmus, Hyer, Kathryn, Dobbs, Debra, Peterson, Lindsay, Jester, Dylan J., Kong, N]
通讯作者:
Kong, N
Collaborative Research: Optimizing Trauma Care Network Design
-
批准号:1761022
-
项目类别:Standard Grant
-
资助金额:$24.96万
-
财政年份:2018
-
负责人:Nan Kong
-
依托单位:
Research Initiation: Enhancing the Learning Outcomes of Empathic Innovation in Longevity Engineering
-
批准号:1738214
-
项目类别:Standard Grant
-
资助金额:$19.98万
-
财政年份:2017
-
负责人:Nan Kong
-
依托单位:
GOALI/Collaborative Research: Optimal Inpatient Discharge Planning under Uncertainty
-
批准号:1405357
-
项目类别:Standard Grant
-
资助金额:$22.28万
-
财政年份:2014
-
负责人:Nan Kong
-
依托单位:
GOALI/Collaborative Research: Warehouse Integration in Enterprise-Wide Supply Chain Planning under Uncertainty
-
批准号:1235283
-
项目类别:Standard Grant
-
资助金额:$18.0万
-
财政年份:2012
-
负责人:Nan Kong
-
依托单位:
海外基金