Background
Overcrowding in hospital emergency departments that arises from long length-of-stay is an unfortunate common occurrence. While some factors affecting length-of-stay are well known, there may be additional factors that have not yet been properly addressed. This research offers a method for emergency department managers to use available data from their departments to identify new factors that significantly influence emergency departments crowding and patient length-of-stay.
Methods
We propose an algorithm that can assist emergency department managers in determining which of these factors to address, given budgetary constraints. We implemented it in a case study which takes into account factors that are known to be influential, e.g., reason for arrival, occupancy in the emergency department, and arrival time, as well as factors that are explored for the first time in this paper, such as patient heart rate, the number of accompanying escorts, and the number of tests assigned to patients (e.g., blood tests and urinalysis).
Results
All the implemented and new factors are shown to have a significant influence on the length-of-stay and crowding. We also obtained additional support for our results by interviewing emergency departments physicians and nurses from various hospitals.
Conclusions
It is expected that, by taking all the above factors into consideration, emergency departments efficiency can be improved. The algorithm constructed here allows the choice of the most cost-effective factors to be improved, subject to a given budget. We have been able to derive practical recommendations that emergency departments managers might use to limit crowding and patient length-of-stay.
Problems related to patient scheduling and queueing in emergency departments are gaining increasing attention in theory, in the fields of operations research and emergency and healthcare services, and in practice. This paper aims to provide an extensive review of studies addressing queueing-related problems explicitly related to emergency departments. We have reviewed 229 articles and books spanning seven decades and have sought to organize the information they contain in a manner that is accessible and useful to researchers seeking to gain knowledge on specific aspects of such problems. We begin by presenting a historical overview of applications of queueing theory to healthcare-related problems. We subsequently elaborate on managerial approaches used to enhance efficiency in emergency departments. These approaches include bed management, fast-track, dynamic resource allocation, grouping/prioritization of patients, and triage approaches. Finally, we discuss scientific methodologies used to analyze and optimize these approaches: algorithms, priority models, queueing models, simulation, and statistical approaches.
Tourism is one of the largest growing industries worldwide. As the number of tourists is rapidly increasing, so too are tourist safety concerns. The increasing frequency of natural disasters along with the growth of urban areas makes it even more complex to address the resilience of tourists during such events. This article proposes a framework for collecting information about tourist locations and flows within urban areas and how to use this information for more efficient and safe evacuation routing. We define population behavior models that can be obtained from gathering empirical data and categorize them into three groups. We review the different evacuation scenarios (divided into sudden and predictable scenarios) and the types of information needed in each case. Further, we discuss the complexity of monitoring and forecasting tourists’ movements in the long term and for short-term predictions including the available data sources for doing so. The data gathering and tourist behavior are explained with examples from Kyoto, Japan, a major tourist attraction and a location that is prone to disasters. Finally, technological solutions for better guidance during the evacuation process of the population are discussed, including low-tech ones and advanced options such as websites, apps and Bluetooth Low Energy sensors, where the last one is demonstrated by a navigation experiment in a 3D environment.
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