Suppr超能文献

以少获多:使用离散事件模拟软件提高新德里一家顶级三级护理医院新冠病毒筛查检测设施通量的研究

More from less: Study on increasing throughput of COVID-19 screening and testing facility at an apex tertiary care hospital in New Delhi using discrete-event simulation software.

作者信息

Gowda Naveen R, Khare Amitesh, Vikas H, Singh Angel R, Sharma D K, Poulose Ramya, John Dhayal C

机构信息

Department of Hospital Administration, All India Institute of Medical Sciences (AIIMS), India.

All India Institute of Medical Sciences (AIIMS), India.

出版信息

Digit Health. 2021 Sep 27;7:20552076211040987. doi: 10.1177/20552076211040987. eCollection 2021 Jan-Dec.

Abstract

BACKGROUND

One of the challenges has been coping with an increasing need for COVID-19 testing. A COVID-19 screening and testing facility was created. There was a need for increasing throughput of the facility within the existing space and limited resources. Discrete event simulation was used to address this challenge.

METHODOLOGY

A cross-sectional interventional study was done from September 2020 to October 2020. Detailed process mapping with all micro-processes was done. Patient arrival patterns and time taken at each step were measured by two independent observers at random intervals over two weeks. The existing system was simulated and a bottleneck was identified. Two possible alternatives to the problem were simulated and evaluated.

RESULTS

Scenario 1 showed a maximum throughput of 316. The average milestone times of all the processes after the step of "Preparation of sampling kits" jumped 62%; from 82 to 133 min. Staff state times also showed that staff at this step was stretched and medical lab technicians were underutilized. Scenario 2 simulated the alternative with lesser time spent on sampling kit preparation with a 22.4% increase in throughput, but could have led to impaired quality check. Scenario 3 simulated with increased manpower at the stage of bottleneck with 26.5% increase in throughput and was implemented on-ground.

CONCLUSION

Discrete event simulation helped to identify the bottleneck, simulate possible alternative solutions without disturbing the ongoing work, and finally choose the most suitable intervention to increase throughput, without the need for additional space allocation. It therefore helped to optimally utilize resources and get "more from less."

摘要

背景

其中一项挑战是应对新冠病毒检测需求的不断增加。于是设立了一个新冠病毒筛查与检测设施。需要在现有空间和有限资源的条件下提高该设施的吞吐量。采用离散事件模拟来应对这一挑战。

方法

于2020年9月至2020年10月开展了一项横断面干预研究。对所有微观流程进行了详细的流程映射。由两名独立观察员在两周内随机间隔测量患者到达模式以及每个步骤所花费的时间。对现有系统进行了模拟并识别出一个瓶颈。对该问题的两种可能替代方案进行了模拟和评估。

结果

方案1显示最大吞吐量为316。在“准备采样试剂盒”步骤之后,所有流程的平均里程碑时间跃升了62%;从82分钟增至133分钟。员工状态时间也表明该步骤的员工工作紧张,而医学实验室技术人员未得到充分利用。方案2模拟了减少采样试剂盒准备时间的替代方案,吞吐量提高了22.4%,但可能导致质量检查受损。方案3模拟了在瓶颈阶段增加人力的情况,吞吐量提高了26.5%,并在实际中实施。

结论

离散事件模拟有助于识别瓶颈,在不干扰正在进行的工作的情况下模拟可能的替代解决方案,最终选择最合适的干预措施来提高吞吐量,而无需额外的空间分配。因此,它有助于优化资源利用并“以少博多”。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验