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基于一种新的启动模式建模技术,预测未来十年的全地区重症监护能力需求
Tom Lawton1, Aaron Corp1, Claire Horsfield2
1Bradford Institute for Health Research, Bradford, UK.
Future healthcare journal
|October 3, 2023
概括
这项研究使用开源数据驱动技术模拟了重症监护网络中的患者流动和资源使用情况. 该方法为未来的重症监护资源提供提供单位级建议,考虑到人口变化.
科学领域:
- 医疗保健服务研究 医疗服务研究
- 计算流行病学计算流行病学
- 医疗保健管理的管理
背景情况:
- 已经建立了一个开源数据驱动的建模技术,用于提供重症监护资源.
- 该技术已成功扩展到模拟选择性手术和整个医院系统.
研究的目的:
- 将数据驱动的建模技术应用于西约克郡重症监护网络内的患者流动和资源使用.
- 为未来的重症监护资源提供提供单位级推.
- 为了预测关键护理能力需求,考虑未来十年的人口变化.
主要方法:
- 使用开源,数据驱动的建模方法.
- 在重症监护网络中建模患者流动和资源利用.
- 将人口数据和人口变化纳入模型.
主要成果:
- 建模技术可以在单个单位层面上提出建议.
- 该方法考虑了人口数量和人口统计数据的预测变化.
- 该研究表明,该模型对预测未来重症监护能力的有用性.
结论:
- 数据驱动的建模技术对于优化重症监护资源配置是有效的.
- 这种方法可以指导面对人口变化的医疗保健系统的战略规划.
- 该方法可扩展到英国其他地区的应用,以预测关键护理需求.
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