A Simulation Study for a Safe Reopening and Operation of the Trager Institute Optimal Aging Clinic During the COVID-19 Pandemic

IF 1.1 4区 管理学 Q4 MANAGEMENT Informs Journal on Applied Analytics Pub Date : 2023-08-24 DOI:10.1287/inte.2022.0032
Shahab Sadri, Arsalan Paleshi, Lihui Bai, Monica Gentili
{"title":"A Simulation Study for a Safe Reopening and Operation of the Trager Institute Optimal Aging Clinic During the COVID-19 Pandemic","authors":"Shahab Sadri, Arsalan Paleshi, Lihui Bai, Monica Gentili","doi":"10.1287/inte.2022.0032","DOIUrl":null,"url":null,"abstract":"In this study, we develop a discrete-event simulation model to aid the Trager Institute, an outpatient clinic for optimal aging located in Louisville, Kentucky, in determining their safe reopening strategies during the COVID-19 pandemic and operational strategies beyond the pandemic. The model studies the movement of several groups of people (e.g., healthcare providers, navigators, patients, staff) and the operations of the clinic’s primary and ancillary services. The main objective is to ensure that the clinic operates safely while COVID-19 restrictions are in place and to improve its providers’ utilization rate. The model simulates people’s movement in the clinic, monitors the congestion level in four common areas, and identifies the peak hours during a day. We also study various overbooking and telehealth policies to overcome high cancelation or no-show rates and low utilization for providers. Simulation results using AnyLogic have helped the management decide to reopen the in-person services during the COVID-19 pandemic based on the safe congestion level demonstrated by the simulation. Insights on optimal overbooking and telehealth policies can shed a broader light on other healthcare organizations. History: This paper was refereed.","PeriodicalId":53206,"journal":{"name":"Informs Journal on Applied Analytics","volume":"28 1","pages":""},"PeriodicalIF":1.1000,"publicationDate":"2023-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Informs Journal on Applied Analytics","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1287/inte.2022.0032","RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"MANAGEMENT","Score":null,"Total":0}
引用次数: 0

Abstract

In this study, we develop a discrete-event simulation model to aid the Trager Institute, an outpatient clinic for optimal aging located in Louisville, Kentucky, in determining their safe reopening strategies during the COVID-19 pandemic and operational strategies beyond the pandemic. The model studies the movement of several groups of people (e.g., healthcare providers, navigators, patients, staff) and the operations of the clinic’s primary and ancillary services. The main objective is to ensure that the clinic operates safely while COVID-19 restrictions are in place and to improve its providers’ utilization rate. The model simulates people’s movement in the clinic, monitors the congestion level in four common areas, and identifies the peak hours during a day. We also study various overbooking and telehealth policies to overcome high cancelation or no-show rates and low utilization for providers. Simulation results using AnyLogic have helped the management decide to reopen the in-person services during the COVID-19 pandemic based on the safe congestion level demonstrated by the simulation. Insights on optimal overbooking and telehealth policies can shed a broader light on other healthcare organizations. History: This paper was refereed.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
新冠肺炎大流行期间特拉格研究所优化老年门诊安全重开运营模拟研究
在本研究中,我们开发了一个离散事件模拟模型,以帮助位于肯塔基州路易斯维尔的特拉格研究所(Trager Institute)确定其在COVID-19大流行期间的安全重新开放策略和大流行之后的运营策略。该模型研究了几组人群(例如,医疗保健提供者、导航员、患者、工作人员)的移动以及诊所主要和辅助服务的运营。主要目标是确保诊所在COVID-19限制措施实施期间安全运营,并提高其提供者的利用率。该模型模拟了人们在诊所的活动,监测了四个公共区域的拥堵程度,并确定了一天中的高峰时间。我们还研究了各种超额预订和远程医疗政策,以克服高取消或缺席率和提供者的低利用率。使用AnyLogic的仿真结果帮助管理层根据仿真显示的安全拥塞水平决定在COVID-19大流行期间重新开放现场服务。关于最佳超额预订和远程医疗政策的见解可以为其他医疗保健组织提供更广泛的启示。历史:本文被审稿。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
21.40%
发文量
51
期刊最新文献
Alleviating Court Congestion: The Case of the Jerusalem District Court Data-Driven Order Fulfillment Consolidation for Online Grocery Retailing In Memoriam: Srinagesh Gavirneni, 1967–2023 Applying Analytics to Design Lung Transplant Allocation Policy Introduction: 2022 Daniel H. Wagner Prize for Excellence in the Practice of Advanced Analytics and Operations Research
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1