Department of Industrial Management, Agroindustry and Operations, Universidad de la Costa CUC, Barranquilla 081001, Colombia.
Research Centre on Production Management and Engineering, Universitat Politècnica de València, 46022 Valencia, Spain.
Int J Environ Res Public Health. 2020 Apr 13;17(8):2664. doi: 10.3390/ijerph17082664.
The most commonly used techniques for addressing each Emergency Department (ED) problem (overcrowding, prolonged waiting time, extended length of stay, excessive patient flow time, and high left-without-being-seen (LWBS) rates) were specified to provide healthcare managers and researchers with a useful framework for effectively solving these operational deficiencies. Finally, we identified the existing research tendencies and highlighted opportunities for future work. We implemented the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology to undertake a review including scholarly articles published between April 1993 and October 2019. The selected papers were categorized considering the leading ED problems and publication year. Two hundred and three (203) papers distributed in 120 journals were found to meet the inclusion criteria. Furthermore, computer simulation and lean manufacturing were concluded to be the most prominent approaches for addressing the leading operational problems in EDs. In future interventions, ED administrators and researchers are widely advised to combine Operations Research (OR) methods, quality-based techniques, and data-driven approaches for upgrading the performance of EDs. On a different tack, more interventions are required for tackling overcrowding and high left-without-being-seen rates.
本研究旨在为医疗保健管理者和研究人员提供一个有用的框架，以有效地解决这些运营缺陷，为此，我们针对每个急诊科（ED）问题（过度拥挤、等待时间延长、住院时间延长、患者流量时间过长和高未就诊率）最常使用的技术进行了规定。最后，我们确定了现有研究趋势，并强调了未来工作的机会。我们采用了系统评价和荟萃分析的首选报告项目（PRISMA）方法，对 1993 年 4 月至 2019 年 10 月期间发表的学术文章进行了综述。所选论文根据主要 ED 问题和出版年份进行了分类。共发现 203 篇论文分布在 120 种期刊上，符合纳入标准。此外，计算机模拟和精益制造被认为是解决急诊科主要运营问题的最突出方法。在未来的干预措施中，ED 管理人员和研究人员被广泛建议将运筹学（OR）方法、基于质量的技术和数据驱动方法结合起来，以提高 ED 的绩效。另一方面，需要采取更多的干预措施来解决过度拥挤和高未就诊率的问题。
