连续远程患者监测用于出院后心力衰竭管理:使用离散事件模拟的工作流模型
Rema Padman1, Anirudh Vaidhyaa Venkatasubramanian1, Wei Ning Chi2
1Carnegie Mellon University, Pittsburgh, USA.
Studies in health technology and informatics
|January 25, 2024
概括
对心力衰竭 (HF) 患者的持续远程患者监测 (CRPM) 使用可穿戴生物传感器来预测脱补偿. 模拟建模评估了主动护理的临床工作量和工作流程,有助于扩大规模.
科学领域:
- 心脏病学 心脏病学
- 医疗信息学 医疗信息学
- 医疗保健服务研究 医疗服务研究
背景情况:
- 心力衰竭 (HF) 造成了重大负担,住院和再入院是主要问题.
- 使用可穿戴生物传感器的连续远程患者监测 (CRPM) 提供了一种有前途的方法,可以在出院后主动管理HF患者.
- 实施像Cascade-HF这样复杂的CRPM研究需要理解和解决潜在的工作流和资源挑战.
研究的目的:
- 评估参与布-高频CRPM协议的临床团队的工作量.
- 评估CRPM系统内的患者警报和升级模式.
- 为所有出院后的高频患者提供决定支持,以扩大布-高频协议的规模.
主要方法:
- 将离散事件模拟建模应用于布-HF协议.
- 利用CRPM研究软启动的试点数据.
- 评估临床团队的工作量和分析警报升级模式.
主要成果:
- 模拟提供了对CRPM协议的操作需求的见解.
- 确定了影响临床团队工作量和升级频率的关键因素.
- 生成数据以支持资源规划和人员决策,以实现可扩展性.
结论:
- 离散事件模拟是预测和解决CRPM研究中的实施挑战的宝贵工具.
- 对工作负载和工作流程的积极分析可以优化CRPM在心脏衰竭管理中的效率.
- 这些发现支持布-高频协议的扩展,以便在出院后的高频护理中得到更广泛的应用.
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