ArticleHealthcare (Basel, Switzerland)2022
Modeling Patient Flow in an Emergency Department under COVID-19 Pandemic Conditions: A Hybrid Modeling Approach.
Article in Healthcare (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Performance indicators for evaluating and optimising hospital services during COVID-19: a scoping review.BMJ open · 2026Article
- Key performance indicators in emergency department simulation: a scoping review.Scandinavian journal of trauma, resuscitation and emergency medicine · 2025Article
- Patient flow management in biological events: a scoping review.BMC health services research · 2024Article
- Patient flow modeling and simulation to study HAI incidence in an Emergency Department.Smart health : international conference, ICSH ... ICSH (Conference : Smart Health) · 2024Article
- The Impact of Patient Infection Rate on Emergency Department Patient Flow: Hybrid Simulation Study in a Norwegian Case.Healthcare (Basel, Switzerland) · 2023Article
- The Patient Flow Effect of Pandemic Policies: A Hybrid Simulation Study in a Norwegian Emergency Department.Healthcare (Basel, Switzerland) · 2022Article
- A case study to investigate the impact of overcrowding indices in emergency departments.BMC emergency medicine · 2022Article
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Authors and funding
3 authors.
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Abstract
Emergency departments (EDs) had to considerably change their patient flow policies in the wake of the COVID-19 pandemic. Such changes affect patient crowding, waiting time, and other qualities related to patient care and experience. Field experiments, surveys, and simulation models can generally offer insights into patient flow under pandemic conditions. This paper provides a thorough and transparent account of the development of a multi-method simulation model that emulates actual patient flow in the emergency department under COVID-19 pandemic conditions. Additionally, a number of performance measures useful to practitioners are introduced. A conceptual model was extracted from the main stakeholders at the case hospital through incremental elaboration and turned into a computational model. Two agent types were mainly modeled: patient and rooms. The simulated behavior of patient flow was validated with real-world data (Smart Crowding) and was able to replicate actual behavior in terms of patient occupancy. In order to further the validity, the study recommends several phenomena to be studied and included in future simulation models such as more agents (medical doctors, nurses, beds), delays due to interactions with other departments in the hospital and treatment time changes at higher occupancies.
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