A Data-Driven Discrete Event Simulation Model to Improve Emergency Department Logistics

Abourraja, Mohamed Nezar; Marzano, Luca; Raghothama, Jayanth; Asl, Arsineh Boodaghian; Darwich, Adam S.; Meijer, Sebastiaan; Lethvall, Sven; Falk, Nina

doi:10.1109/wsc57314.2022.10015465

Cited by 2 publications

(3 citation statements)

References 24 publications

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“…The Uppsala University Hospital's (Sweden) ED data from 2019 were analysed (n = 33,881 patients for n = 49,938 total event logs). Previously, these data were used to inform a simulation study aimed to improve the ED acute ows testing which kind of interventions the hospital needed to reach a 4-hour length of stay target 70 .…”

Section: Hospital Emergency Department Production Datamentioning

confidence: 99%

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How to diagnose an overcrowded emergency department from its EHRs? Enhancing opportunities and challenges of real-world data from a whole-system perspective

Marzano,

Darwich,

Jayanth

et al. 2023

Preprint

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Emergency department overcrowding is a complex problem that persists globally. Data of visits constitute an opportunity to understand it. However, the gap between the collected information and the real-life clinical processes, and the lack of a whole-system perspective, still constitutes a relevant limitation. An analytical pipeline was developed to analyse one-year of production data following the patients that came from the ED (n = 49,938) at Uppsala University Hospital (Uppsala, Sweden) by involving clinical experts in all the steps of the analysis. The key internal issues to the ED were the high volume of generic or non-specific diagnoses from non-urgent visits, and the delayed decision regarding hospital admission caused by several imaging assessments and lack of hospital beds. Furthermore, the external pressure of high frequent re-visits of geriatric, psychiatric, and patients with unspecified diagnoses dramatically contributed to the overcrowding. Our work demonstrates that through analysis of production data of the ED patient flow and participation of clinical experts in the pipeline, it was possible to identify systemic issues and directions for solutions. A critical factor was to take a whole systems perspective, as it opened the scope to the boundary effects of inflow and outflow in the whole healthcare system.

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Section: Hospital Emergency Department Production Datamentioning

confidence: 99%

“…The geriatric ow was the one connected to external processes to the hospital that concerned mostly the clinicians. The urgent care ow management in competition with non-urgent and complex patients was studied in the previous simulation work 70 .…”

Section: Analytical Pipelinementioning

confidence: 99%

How to diagnose an overcrowded emergency department from its EHRs? Enhancing opportunities and challenges of real-world data from a whole-system perspective

Marzano,

Darwich,

Jayanth

et al. 2023

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…Apart from reducing patient waiting time, evaluating staff strength and overcrowding, etc., simulation models have also been utilized by researchers for emergency department evacuation, logistics optimization, layout design, etc. [41][42][43].…”

Section: Introductionmentioning

confidence: 99%

Simulation and Goal Programming Approach to Improve Public Hospital Emergency Department Resource Allocation

Rehman,

Usmani,

Mian

et al. 2023

Systems

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Efficient and effective operation of an emergency department is necessary. Since patients can visit the emergency department without making an appointment, the emergency department always treats a lot of critical patients. Moreover, the severity of the ailment determines which patients should be prioritized. Therefore, the patients are greatly impacted as a consequence of longer waiting times caused primarily by incorrect resource allocation. It frequently happens that patients leave the hospital or waiting area without treatment. Certainly, the emergency department’s operation can be made more effective and efficient by examining its work and making modifications to the number of resources and their allocation. This study, therefore, investigates the emergency department of a public hospital to improve its functioning. The goal of this research is to model and simulate an emergency department to minimize patient wait times and also minimize the number of patients leaving the hospital without service. A comprehensive simulation model is developed using the Arena simulation platform and goal programming is undertaken to conduct simulation optimization and resource allocation analysis. Hospital management should realize that all resources must be prioritized rather than just focusing on one or two of them. The case scenario (S3) in this study that implements goal programming with variable weights yields the most favorable results. For example, it is observed in this instance that the number of patients leaving the system without service drops by 61.7%, and there is also a substantial drop in waiting times for various types of patients.

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A Data-Driven Discrete Event Simulation Model to Improve Emergency Department Logistics

Cited by 2 publications

References 24 publications

How to diagnose an overcrowded emergency department from its EHRs? Enhancing opportunities and challenges of real-world data from a whole-system perspective

How to diagnose an overcrowded emergency department from its EHRs? Enhancing opportunities and challenges of real-world data from a whole-system perspective

Simulation and Goal Programming Approach to Improve Public Hospital Emergency Department Resource Allocation

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