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心胸外科重症监护路径建模。

Modeling the critical care pathway for cardiothoracic surgery.

机构信息

Department of Management Science, University of Strathclyde, Glasgow, UK.

Golden Jubilee National Hospital, Clydebank, UK.

出版信息

Health Care Manag Sci. 2018 Jun;21(2):192-203. doi: 10.1007/s10729-017-9401-y. Epub 2017 May 16.

Abstract

The west of Scotland heart and lung center based at the Golden Jubilee National Hospital houses all adult cardiothoracic surgery for the region. Increased demand for scheduled patients and fluctuations in emergency referrals resulted in increasing waiting times and patient cancellations. The main issue was limited resources, which was aggravated by the stochastic nature of the length of stay (LOS) and arrival of patients. Discrete event simulation (DES) was used to assess if an enhanced schedule was sufficient, or more radical changes, such as capacity or other resource reallocations should be considered in order to solve the problem. Patients were divided into six types depending on their condition and LOS at the different stages of the process. The simulation model portrayed each patient type's pathway with sufficient detail. Patient LOS figures were analyzed and distributions were formed from historical data, which were then used in the simulation. The model proved successful as it showed figures that were close to actual observations. Acquiring results and knowing exactly when and what caused a cancellation was another strong point of the model. The results demonstrated that the bottleneck in the system was related to the use of High Dependency Unit (HDU) beds, which were the recovery beds used by most patients. Enhancing the schedule by leveling out the daily arrival of patients to HDUs reduced patient cancellations by 20%. However, coupling this technique with minor capacity reallocations resulted in more than 60% drop in cancellations.

摘要

位于金禧国家医院的苏格兰西部心肺中心负责该地区所有成人心胸外科手术。计划患者的需求增加和急诊转诊的波动导致等待时间和患者取消手术增加。主要问题是资源有限,而住院时间(LOS)和患者到达的随机性加剧了这一问题。离散事件模拟(DES)用于评估增强计划是否足够,或者是否应考虑更多激进的更改,例如容量或其他资源重新分配,以解决问题。患者根据病情和在治疗过程不同阶段的 LOS 分为六类。模拟模型详细描述了每个患者类型的路径。对患者 LOS 数据进行分析,并根据历史数据形成分布,然后将其用于模拟。该模型非常成功,因为它显示的数字与实际观察结果非常接近。获取结果并确切了解何时以及是什么导致取消手术是模型的另一个优势。结果表明,系统的瓶颈与高依赖病房(HDU)床位的使用有关,大多数患者都在这些病房中恢复。通过使 HDU 中患者的每日到达量均衡,增强日程安排可将患者取消手术减少 20%。但是,将这种技术与少量的容量重新分配结合使用,可使取消手术的比例降低 60%以上。

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