GEDMod – Towards a generic toolkit for emergency department modeling

Furian, Nikolaus; Neubacher, Dietmar; O'Sullivan, Michael J.; Walker, Cameron; Pizzera, C.

doi:10.1016/j.simpat.2018.07.010

Cited by 10 publications

(8 citation statements)

References 55 publications

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“…However, the model must t the decision-maker goals, which are classi ed either as general (runtime and visualization needs, development effort, and re-use exibility) or modelling (answering "what are the most important issues to be addressed by experimenting with the model?") (Furian et al, 2018). The generic and reusable content of the model is related to the general objectives.…”

Section: Framework For Developing Ge-des In Healthcare Systemsmentioning

confidence: 99%

Medical testing services’ quality enhancement with discrete-event simulation

Mira

Ferreira

Caldas

et al. 2023

Preprint

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In recent years, the demand for health care has increased owing to the ongoing introduction of new health problems and the intensification of existing illnesses. As research in this area progresses, knowledge becomes the primary motivation for patients to adopt a better quality of life. Consequently, many health units have struggled to develop solutions to manage excessive demand while maintaining a high quality of service to enhance patient satisfaction and boost revenues. One of these tactics is using simulation models as a method of operational research to analyze the flow of patients and predict potential solutions to enhance resource efficiency while decreasing waiting time. This work aims to develop and demonstrate a simulation model that replicates the functioning of a hospital unit. For this purpose, data derived from the health services of the Imaging Department of a private hospital, located in Lisbon, Portugal, were used. This model will replicate the daily flow that this department is subjected to by its patients and personnel and depict how the system evolves due to the management of the department's number of resources and examination rooms. At the end of the analyses, several solutions are presented and discussed, from level to level, concerning improvements in the performance of services, resources and patients. However, only the increase in one unit of examination rooms translates into a huge positive impact on waiting times in the respective queues.

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Section: Framework For Developing Ge-des In Healthcare Systemsmentioning

confidence: 99%

Medical testing services’ quality enhancement with discrete-event simulation

Mira

Ferreira

Caldas

et al. 2023

Preprint

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“…Within ED related research, many publications apply simulation as their main methodology and reviews summarise the state of the art (e.g., Salmon et al 2018;Furian et al 2018). During ORAHS 2020, several speakers presented simulation models for emergency departments (Roma et al 2020;Fabbri et al 2020;Vanbrabant et al 2020).…”

Section: Emergency Departmentsmentioning

confidence: 99%

Central European journal of operations research (CJOR) “operations research applied to health services (ORAHS) in Europe: general trends and ORAHS 2020 conference in Vienna, Austria”

Aringhieri

Hirsch

Rauner

et al. 2021

Cent Eur J Oper Res

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This articles provides a short summary of the research topics and latest research results of the European Working Group “Operations Research Applied to Health Services” (ORAHS) organized as an e-conference in Juli 2020 at the University of Vienna, Austria (https://orahs2020.univie.ac.at/). Furthermore, challenges for OR in health care including application areas, decision support systems, general trends, and modelling techniques are briefly illustrated from an European and international perspective by providing selected essential literature reviews.

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Section: In 2006 Only Half Of Reporting Laboratories In Newmentioning

confidence: 99%

“…Specimens arrive randomly throughout the day for specimen analysis and reporting. 8. Administrative tasks can occur regularly or randomly in time.…”

Section: Description Of Cytology Departmentmentioning

confidence: 99%

“…In the present study, we describe the use of a discrete event simulation (DES) model of a cytology department as a tool to evaluate the effect of different resourcing decisions on sample turnaround times. Simulation modeling is a common tool for measuring the performance of, and evaluating the impact of changes to, many health care departments, such as emergency departments, but its use has been largely ignored by decision makers in pathology labs. The authors believe the complexity inherent in modeling the activities of pathologists, given the hierarchy of priorities, has previously been a significant barrier to the use of DES for accurately estimating turnaround times of tasks in a cytology lab.…”

Section: Introductionmentioning

confidence: 99%

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Exploring trade‐offs between staffing levels and turnaround time in a pathology laboratory using discrete event simulation

Pongjetanapong

Walker

O'Sullivan

et al. 2019

Health Planning & Management

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Summary Many health delivery services have required performance targets. Typically, these targets are presented as percentiles of patients to be seen within specified timeframes. These targets present hospital administrators with a resourcing problem complicated by conflicting objectives: How to minimize costs while maximizing throughput to achieve the performance targets? In this paper, we describe the use of a simulation model to evaluate the effect of changes to staff levels in a cytology department, investigating the trade‐off between staff levels and turnaround times in light of performance targets specified by government. Standard practice for determining staffing levels in a cytology department uses average workload estimates and does not take into account target performance measures, task variability, and the interruptive nature of the workload of pathologists. We develop a simulation model for pathologist workload within a cytology department in New Zealand. We describe the model construction process that follows the hierarchical control conceptual modeling (HCCM) framework. We use the resulting simulation model to examine the trade‐offs between staffing levels (and associated rosters) and task turnaround time. The results indicate that consideration of variation in task arrivals is important when considering the effect of staffing levels on turnaround time. Furthermore, as the cytology department is required to meet performance targets that involve maximum service times for a percentile of patients, such an approach is necessary in order to estimate the performance level of a staffing roster.

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GEDMod – Towards a generic toolkit for emergency department modeling

Cited by 10 publications

References 55 publications

Medical testing services’ quality enhancement with discrete-event simulation

Medical testing services’ quality enhancement with discrete-event simulation

Central European journal of operations research (CJOR) “operations research applied to health services (ORAHS) in Europe: general trends and ORAHS 2020 conference in Vienna, Austria”

Exploring trade‐offs between staffing levels and turnaround time in a pathology laboratory using discrete event simulation

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