Enhancement of Intra-hospital patient transfer in medical center hospital using discrete event system simulation

被引:1
|
作者
Meephu, Ekkarat [1 ]
Arwatchananukul, Sujitra [1 ]
Aunsri, Nattapol [1 ,2 ]
机构
[1] Mae Fah Luang Univ, Sch Informat Technol, Chiang Rai, Thailand
[2] Mae Fah Luang Univ, Comp & Commun Engn Capac Bldg Res Ctr CCC, Chiang Rai, Thailand
来源
PLOS ONE | 2023年 / 18卷 / 04期
关键词
CRITICALLY-ILL PATIENTS; EMERGENCY-DEPARTMENT; HEALTH-CARE; TRANSPORT; PERFORMANCE; IMPROVEMENT;
D O I
10.1371/journal.pone.0282592
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
The intra-hospital transfer of critically ill patients are associated with complications at up to 70%. Numerous issues can be avoided with optimal pre-transport planning and communication. Simulation models have been demonstrated to be an effective method for modeling processes and enhancing on-time service and queue management. Discrete-event simulation (DES) models are acceptable for general hospital systems with increased variability. Herein, they are used to improve service effectiveness. A prospective observational study was conducted on 13 official day patient transfers, resulting in a total of 827 active patient transfers. Patient flow was simulated using discrete-event simulation (DES) to accurately and precisely represent real-world systems and act accordingly. Several patient transfer criteria were examined to create a more realistic simulation of patient flow. Waiting times were also measured to assess the efficiency of the patient transfer process. A simulation was conducted to identify 20 scenarios in order to discover the optimal scenario in which where the number of requests (stretchers or wheelchairs) was increased, while the number of staff was decreased to determine mean waiting times and confidence intervals. The most effective approach for decreasing waiting times involved prioritizing patients with the most severe symptoms. After a transfer process was completed, staff attended to the next transfer process without returning to base. Results show that the average waiting time was reduced by 21.78% which is significantly important for emergency cases. A significant difference was recorded between typical and recommended patient transfer processes when the number of requests increased. To decrease waiting times, the patient transfer procedure should be modified according to our proposed DES model, which can be used to analyze and design queue management systems that achieve optimal waiting times.
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页数:19
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