过度拥挤
急诊科
调度(生产过程)
医疗急救
医疗保健
启发式
还原(数学)
医学
计算机科学
工作(物理)
运营管理
运筹学
护理部
工程类
人工智能
数学
经济
经济增长
机械工程
几何学
作者
David Sinreich,Ola Jabali,Nico Dellaert
出处
期刊:Iie Transactions
[Taylor & Francis]
日期:2012-01-10
卷期号:44 (3): 163-180
被引量:44
标识
DOI:10.1080/0740817x.2011.609875
摘要
Reducing Emergency Department (ED) overcrowding in the hope of improving the ED's operational efficiency and health care delivery ranks high on every health care decision maker's wish list. The current study concentrates on developing efficient work shift schedules that make the best use of current resource capacity with the objectives of reducing patient waiting time and leveling resource utilization as much as possible. The study introduces two iterative heuristic algorithms, which combine simulation and optimization models for scheduling the work shifts of the ED resources: physicians, nurses and technicians. The algorithms are distinctive because they account for patients being treated by multiple care providers, possibly over the course of several hours, often with interspersed waiting. In such instances, patient arrival time is not a good indicator of when the various care providers are needed. The algorithms were tested using a detailed simulation based on data from five general hospital EDs. A patient's Length of Stay (LOS) is measured as the time a patient spends in the ED until being admitted to the hospital or discharged. The first algorithm achieved an average reduction of between 20 and 45% in the total patient waiting time, which led to a reduction of between 7 and 17% in the combined average patient LOS. By allowing a restructure of the ED resource capacities, the second algorithm achieved an average reduction of between 20 and 64% in the total patient waiting time, leading to an 11 to 29% reduction in the combined average patient LOS.
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