🛑Stop Modeling the ED Like a Clinic: It Doesn’t End at Bed Placement
When modeling an emergency department (ED) using discrete event simulation, it’s tempting to treat “bed placement” as the final step for admitted patients. After all, once a bed is assigned, isn’t the job done? Not quite. Bed placement is just a decision point — not the end of the patient’s ED journey.
What comes next — boarding delays, inpatient bed unavailability, transport lags — has a massive impact on ED crowding, length of stay, and even patient outcomes. Ignoring that final stretch means your model is skipping over the part where the system often breaks down.
💡 The Biggest Opportunities Are Often After “Admit”
Across many hospitals and real-world models, the most valuable improvement opportunities emerge after the admit decision. Why? Because that’s when the ED starts feeling the weight of the inpatient system’s inefficiencies.
Patients board for hours while inpatient beds are cleaned, staffed, or simply opened up. Observation units run near full, and delays in inpatient discharges cause ripple effects that choke ED flow. The result? Bottlenecks that can't be fixed no matter how efficient the front-end ED processes become.
📈 Planning for Growth? You Need to Model What’s Next
Even if boarding times are low, that doesn’t mean your system is in the clear. If you're using simulation to test future volumes, expansions, or surge scenarios, you’re going to stress the system and inpatient and observation capacity will likely become the new limiting factors.
It might be tempting to model the ED alone, just as you might model a clinic because a clinic is a closed system. In a clinic, patients are seen, treated, and discharged all within the same setting. But the ED isn't like that. It’s tightly coupled to the rest of the hospital. Simulating it like a clinic is a category error that can lead to dangerously incomplete results.
Without modeling what happens after admission, you risk generating false positives: results that look promising in simulation, but fall apart in the real world. That could lead to misplaced investments, ineffective policies, and frustrated teams wondering why nothing improved.
🤔 But What If You’re Just Improving Fast-Track or Discharge-Eligible Patients?
A common question is: “If our focus is on patients who are likely to be discharged, like fast-track, low-acuity, or rapid assessment areas, do we really need to model the inpatient side?”
It’s tempting to think you can skip it, but here’s why that can backfire.
Your ED is a shared system. Even patients who are quick to discharge still rely on the same beds, staff, and physical space as patients who are boarding. When admitted patients get stuck waiting for inpatient beds, they tie up resources and create downstream congestion that impacts everyone — including the fast-track population.
So you can build the best triage or rapid treatment process in the world, but if hallway beds are full of boarders or your nurses are tied up managing admitted patients waiting hours for an inpatient bed, those low-acuity patients will still get stuck.
Boarding delays hurt everyone. They slow down throughput, create backups in triage, and extend wait times. If your simulation doesn’t account for that reality, your projected gains from front-end improvements will likely be overly optimistic.
✅ When might it be okay to skip it? If you’re modeling a truly separate, dedicated unit with its own space and staff — with guaranteed capacity not shared with boarded patients — you might get away with it. But for most real-world EDs, the flow is interconnected. If you’re testing future volume or surge scenarios, ignoring the inpatient side is almost always a mistake.
🤦♂️ The Common Pitfall: Modeling Only the ED
I can’t tell you how many times I’ve gone to simulation conferences and seen detailed, impressive ED models — that stop cold at the admit decision. It’s common, especially for newer modelers or academic projects. The ED feels bounded. The data is accessible. And yes, the inpatient side can feel messy and hard to model.
But here’s the deal:
You can’t fix the ED without fixing how patients get out of it.
A model that ends at bed placement may look clean, but it won’t reflect reality. It risks misleading leadership and producing recommendations that don’t solve the actual constraint.
🧠 Yes, It Takes More Time — But It’s Worth It
Sure, including inpatient and observation logic takes more effort. It adds complexity. And stakeholders unfamiliar with simulation might not immediately understand why it's necessary. But that’s where your role as a modeler becomes strategic, not just technical.
If your goal is real-world impact, the extra time is worth it. A more complete model, even a simplified inpatient abstraction helps ensure your insights are valid, your scenarios realistic, and your decisions aligned with how hospitals actually operate.
✅ Final Word
Simulation isn’t just about visualizing the present. It’s about pressure-testing the future. And that only works if you model the full story — not just the clean parts. So, if you're serious about change, whether it’s fixing today's ED bottlenecks or preparing for tomorrow’s demand, don’t stop at bed placement. Model what happens next. That’s where the system really starts to speak.
This article was collaboratively written with the help of artificial intelligence, with human oversight and editing to ensure accuracy and coherence.
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