Emergency departments are often assessed by the number of treatment bays they have, the number of patients they attend, or the time patients spend waiting. These measures are useful, but they do not always explain why a department with apparently sufficient resources can still become overwhelmed.
To understand this, we need to look beyond the number of patients and examine how they move through the system.
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From space to flow
The Descompresión del Flujo en Urgencias (DFU) model — which can be translated as Emergency Department Flow Decompression — was developed as part of my research into the loss of operational capacity in hospital emergency departments.
Its starting point is simple: patients do not occupy emergency department resources in isolation. They move through a sequence of clinical and operational stages, from initial assessment and treatment to observation, discharge or admission.
When this progression is interrupted, patients remain in spaces that may be needed by others. A treatment bay can remain occupied after its main clinical purpose has been fulfilled. A patient awaiting an inpatient bed can prevent the department from completing the next stage of care. Gradually, the accumulation spreads, reducing the system’s ability to receive and treat new arrivals.
The problem is therefore not always a shortage of space in itself. It can also be a loss of continuity in patient flow.
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What does the DFU model do?
The DFU model is a configurable simulation tool designed to explore how demand, patient characteristics, resource availability and time interact within an emergency department.
It allows different scenarios to be tested by changing parameters such as the number of treatment bays, patient arrival patterns, time spent occupying resources, observation capacity, access to diagnostic tests and the availability of inpatient beds.
The purpose is not simply to count how many patients enter the department. It is to examine what happens to the system as those patients progress through it — and what happens when that progression slows or stops.
By changing one or more conditions, the model allows us to explore questions such as:
- Can a department lose effective capacity even when demand remains unchanged?
- Does adding treatment bays resolve congestion, or does the bottleneck move elsewhere?
- How does limited observation or inpatient capacity affect the rest of the department?
- What happens to patients who no longer need a treatment bay but have not yet completed their journey through the system?
These questions help shift the discussion from isolated resources towards the interaction between the different stages of care.
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Why decompression matters
The DFU approach also explores whether the patient pathway can be reorganised to reduce unnecessary occupation of high-demand spaces.
One concept is a dedicated clinical transit area for patients who have left the treatment phase but remain within the emergency care process. Such a space could allow treatment bays to become available earlier, provided that patient selection, staffing, monitoring and clinical safety requirements are appropriately addressed.
This is not a universal solution, nor does the model establish that a particular intervention will work in every hospital. Its value lies in making assumptions explicit and allowing alternative configurations to be explored before decisions are made.
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A tool for asking better questions
The DFU model does not replace clinical judgement, operational data or the expertise required to design and manage an emergency department. Nor should its simulated results be interpreted as direct predictions of what will happen in a particular hospital.
It offers a way to examine relationships that are difficult to understand by looking at individual indicators alone.
Ultimately, the central question is not just how many patients an emergency department can receive, or how many treatment bays it contains.
It is how effectively the system can move each patient through the different stages of care.
That is the perspective behind the DFU model: understanding capacity not simply as a quantity of space or resources, but as the ability to sustain the flow of patients through the system.
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From Simulation to Strategic Decisions
The real potential of the DFU model lies not only in understanding why emergency departments become congested, but in exploring what could be done differently.
What if we could test a new configuration before building it? What if we could compare different numbers of treatment bays, observation places or patient pathways, and examine how each alternative affects the system as a whole? What if we could explore the consequences of changing one resource without simply assuming that more capacity will solve the problem?
Simulation makes it possible to explore these questions in a controlled environment, test alternative scenarios and identify potential bottlenecks before committing to costly or difficult-to-reverse decisions.
This opens the door to a more ambitious development: a digital twin of a specific emergency department, informed by real operational data and capable of representing how that particular system behaves. The DFU model is not, by itself, a fully integrated digital twin. But its approach to modelling patient flow provides a foundation on which such a tool could be developed.
The ambition is to move from reacting to overcrowding to testing alternatives before it happens. From making isolated decisions based on pressure or intuition to comparing options using data, simulation and a clearer understanding of their consequences.
Otherwise, we risk continuing to build what I call Frankenstein emergency departments: facilities expanded and modified piece by piece, with each intervention addressing an immediate problem but not necessarily improving the system as a whole.
The question is no longer simply how much space an emergency department needs. It is how we can design and organise that space to make the entire system work better — before we build, expand or change it.
About this research
This article draws on a four-month research project conducted as part of my Master’s Final Project in Hospital Engineering and Architecture at the University of Cádiz, Spain, which received a grade of 9.5/10.
The research examines demographic trends, hospital designs and functional plans, emergency care processes, and the perspectives of emergency department professionals gathered through surveys. It culminates in the development of a digital twin simulation model designed to explore multiple scenarios and analyse how different factors affect emergency department operational capacity.