Yawo M. Kobara, Felipe F. Rodrigues, Camila P. E. de Souza, David Stanford
{"title":"ICU patient flow: To premature step-down or not? A simulation analysis","authors":"Yawo M. Kobara, Felipe F. Rodrigues, Camila P. E. de Souza, David Stanford","doi":"10.1080/20479700.2023.2266637","DOIUrl":null,"url":null,"abstract":"ABSTRACTA Step-Down Unit (SDU) provides an intermediate Level of Care for patients from an Intensive Care Unit (ICU) as their condition becomes less acute. SDU congestion and upstream patient arrivals force ICU administrators to incur costs, either in the form of overstays or premature step-downs. Based on a proxy for patient acuity level called the ‘Nine Equivalents of Nursing Manpower Score (NEMS)’, patients were classified into high-acuity and low-acuity. Two patient flow policies were developed and simulated: one allowing for premature step-down actions when the system is congested and the other allowing for patient rejection actions when the system is congested. The results show that the patient-rejection policy has a net health service benefit that significantly exceeds the premature step-down policy. Based on these results, it can be concluded that premature step-down contributes to congestion downstream. Counter-intuitively, premature step-down should therefore be discouraged and patient diversion actions should be further explored as viable options for congested ICUs.KEYWORDS: Healthcarepatient flowICUSDUcongestionpremature step-down Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThe author(s) reported there is no funding associated with the work featured in this article.Notes on contributorsYawo M. KobaraYawo M. Kobara is an Assistant Professor in the Odette School of Business, University of Windsor.Felipe F. RodriguesFelipe F. Rodrigues is an Assistant Professor of Operations Management and Analytics at King's University College.Camila P. E. de SouzaCamila P. E. de Souza is Assistant Professor in Statistics and Data Science at the Department of Statistical and Actuarial Sciences at Western University in London, Ontario.David StanfordDavid Stanford is a Professor in Statistics and Data Science at the Department of Statistical and Actuarial Sciences at Western University in London.","PeriodicalId":46911,"journal":{"name":"International Journal of Healthcare Management","volume":"2 1","pages":"0"},"PeriodicalIF":1.4000,"publicationDate":"2023-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Healthcare Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/20479700.2023.2266637","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"HEALTH POLICY & SERVICES","Score":null,"Total":0}
引用次数: 0
Abstract
ABSTRACTA Step-Down Unit (SDU) provides an intermediate Level of Care for patients from an Intensive Care Unit (ICU) as their condition becomes less acute. SDU congestion and upstream patient arrivals force ICU administrators to incur costs, either in the form of overstays or premature step-downs. Based on a proxy for patient acuity level called the ‘Nine Equivalents of Nursing Manpower Score (NEMS)’, patients were classified into high-acuity and low-acuity. Two patient flow policies were developed and simulated: one allowing for premature step-down actions when the system is congested and the other allowing for patient rejection actions when the system is congested. The results show that the patient-rejection policy has a net health service benefit that significantly exceeds the premature step-down policy. Based on these results, it can be concluded that premature step-down contributes to congestion downstream. Counter-intuitively, premature step-down should therefore be discouraged and patient diversion actions should be further explored as viable options for congested ICUs.KEYWORDS: Healthcarepatient flowICUSDUcongestionpremature step-down Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThe author(s) reported there is no funding associated with the work featured in this article.Notes on contributorsYawo M. KobaraYawo M. Kobara is an Assistant Professor in the Odette School of Business, University of Windsor.Felipe F. RodriguesFelipe F. Rodrigues is an Assistant Professor of Operations Management and Analytics at King's University College.Camila P. E. de SouzaCamila P. E. de Souza is Assistant Professor in Statistics and Data Science at the Department of Statistical and Actuarial Sciences at Western University in London, Ontario.David StanfordDavid Stanford is a Professor in Statistics and Data Science at the Department of Statistical and Actuarial Sciences at Western University in London.
降压病房(SDU)为重症监护病房(ICU)的患者提供中间水平的护理,因为他们的病情变得不那么严重。SDU的拥挤和上游患者的到来迫使ICU管理员承担费用,要么以逾期居留的形式,要么过早降级。根据一种名为“护理人力九等量评分(NEMS)”的患者视力水平代理,将患者分为高视力和低视力。开发并模拟了两个患者流策略:一个允许在系统拥挤时采取过早的降压行动,另一个允许在系统拥挤时采取患者排斥行动。结果表明,患者排斥政策的净卫生服务效益显著超过过早退步政策。基于这些结果,可以得出过早降压导致下游拥堵的结论。因此,与直觉相反,应不鼓励过早降压,并应进一步探索患者转移行动,作为拥挤的icu的可行选择。关键词:医疗保健患者流量;充血;过早退出披露声明作者未报告潜在的利益冲突。其他信息资金作者报告没有与本文所述工作相关的资金。作者简介:yawo M. Kobara,温莎大学奥德特商学院助理教授。Felipe F. Rodrigues,国王大学学院运营管理与分析助理教授。Camila P. E. de Souza,安大略省伦敦西部大学统计与精算科学系统计与数据科学助理教授。大卫·斯坦福(David Stanford)是伦敦西部大学统计与精算科学系的统计与数据科学教授。