使用随机模拟建模来研究挪威分散的入院规避单位的占用水平
Meetali Kakad1,2, Martin Utley3, Fredrik A Dahl1,2,4
1Health Services Research Unit, Akershus University Hospital Trust, Lørenskog, Norway.
Health systems (Basingstoke, England)
|October 20, 2023
概括
挪威的市政急性病房 (MAU) 旨在减少住院人数. 这些单位的合并可能会使床位容量减少20%而不会影响护理,尽管由于未满足的需求较低,占用率的增加是最小的.
科学领域:
- 医疗保健管理的管理
- 医疗保健服务研究 医疗服务研究
- 公共卫生政策 公共卫生政策
背景情况:
- 挪威建立了市级分散的急性病房 (MAU),以从医院转移低急性患者.
- 经销商联盟面临着一些挑战,包括低占用率和对医院压力的有限影响.
- 确定MAU优化的有效策略对于医疗保健系统至关重要.
研究的目的:
- 开发一个模拟模型来测试增加MAU占用率的场景.
- 估计由于缺乏容量而被拒绝的患者数量.
- 评估合并MAU对床位容量和服务提供的影响.
主要方法:
- 开发了一个离散时间模拟模型来表示MAU的入院和出院情况.
- 测试了各种场景,以评估提高绝对平均占用率的策略.
- 该模型用于估计在没有历史数据的情况下对床位的不受约束的需求.
主要成果:
- 仅靠合并不太可能显著增加MAU的绝对平均占用率,因为未满足的需求通常很低.
- 合并MAU可以使床位容量减少多达20%.
- 这些产能减少不会对服务提供产生负面影响.
结论:
- 合并MAU为资源优化和床位容量减少提供了潜力.
- 开发的模拟模型提供了一种方法来估计数据稀缺环境中的需求.
- 这些发现与其他入院规避单位和医疗保健规划有关.
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