在紧急护理系统中确定服务器位置:使用数据包裹分析和超立方体队列模型进行索引建议
Enzo Barberio Mariano1, Regiane Máximo Siqueira1, Caio Vitor Beojone2
1Department of Production Engineering, College of Engineering, São Paulo State University (UNESP), Bauru, São Paulo, Brazil.
PeerJ. Computer science
|December 11, 2023
概括
本研究引入了一个新的复合索引 (CI),以优化紧急护理系统 (ECS) 中的服务器位置. 该CI有效地对配置进行排名,帮助资源分配决策,以改善应急响应.
科学领域:
- 运营研究 运营研究
- 医疗保健管理的管理
- 公共卫生系统 公共卫生系统
背景情况:
- 优化紧急护理系统 (ECS) 服务器位置对于高效的紧急响应至关重要.
- 现有的方法可能缺乏确定最有效配置的精度.
- 资源分配决策需要强大的分析工具.
研究的目的:
- 提出一种新的复合指数 (CI),用于确定紧急护理系统 (ECS) 内的最佳服务器位置.
- 整合超立方体队列模型和数据包围分析 (DEA) /怀疑的好处 (BoD) 进行综合分析.
- 为评估不同ECS配置提供一个排名系统.
主要方法:
- 数学分区和顺序被用来定义潜在的ECS配置.
- 应用了超立方体队列模型来确定每个配置的性能参数.
- 数据包围分析 (DEA) /怀疑的好处 (BoD) 用于构建CI和排名配置.
- 来自两个巴西案例的现实世界数据被用于验证.
主要成果:
- 超立方体模型有效地确定了配置参数.
- DEA/BoD的方法在排序ECS配置时提供了有效的歧视.
- 确定了救护车度和配置有效性之间的相关性.
- 拟议的CI证明了ECS管理人员在资源定位决策中的实用性.
结论:
- 开发的复合指数 (CI) 为优化紧急护理系统 (ECS) 服务器配置提供了有价值的工具.
- 排队理论和DEA/BoD的整合为绩效评估提供了一个强大的框架.
- 结果支持数据驱动的决策,以改善紧急医疗服务.
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