國立虎尾科技大學 |

Optimizing Task Scheduling in Emergency Departments.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Optimizing Task Scheduling in Emergency Departments./
作者:	Centeno, Ana Paula Bluhm.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2019,
面頁冊數:	111 p.
附註:	Source: Dissertations Abstracts International, Volume: 80-12, Section: B.
Contained By:	Dissertations Abstracts International80-12B.
標題:	Computer science. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13426399
ISBN:	9781392224816

Optimizing Task Scheduling in Emergency Departments.
Centeno, Ana Paula Bluhm.

Optimizing Task Scheduling in Emergency Departments. - Ann Arbor : ProQuest Dissertations & Theses, 2019 - 111 p.

Source: Dissertations Abstracts International, Volume: 80-12, Section: B.

Thesis (Ph.D.)--Rutgers The State University of New Jersey, School of Graduate Studies, 2019.

This item must not be sold to any third party vendors.

An Emergency Department (ED) is a health care service that delivers time-critical care to unscheduled patient arrivals. Due to an ever increasing number of arrivals, the number of patients often exceed the physical and staffing capacity resulting in long waiting times, patients leaving without being seen by medical staff and higher mortality levels. In this work we investigate the scheduling of staff and equipment resources in EDs. We propose a spatial agent-based simulation framework to quantify the impacts of staff decision processes, such as patient selection, on patient length of stay and waiting times. To explore the ED administration intuition that patient throughput could be increased by prioritizing short patient visits, and corroborate our findings from our simulations that the order in which providers see their next patient affects the length of time patients spend in the ED, we proposed a real-time scheduler that prioritizes short visits. We concluded that Emergency Departments need an online system that is constantly adapting to find an optimal scheduling of patient tasks to available resources. To that effect we propose a mixed-integer linear programming model (MILP) to find an optimal schedule of tasks to resources that minimizes the time spent in the ED for every patient. Our findings show a large fraction of unaccounted tasks on the JSUMC Electronic Health Records (EHR), and that time and motion studies would be needed to complement EHR's to accurately model ED scheduling.

ISBN: 9781392224816Subjects--Topical Terms:

573171
Computer science.
Subjects--Index Terms:

Emergency department

Optimizing Task Scheduling in Emergency Departments.
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