The ER wasn't overcrowded because there weren't enough doctors — it was overcrowded because there weren't enough beds, so the hospital sent the doctors to where the patients already were.

the problem

a system's bottleneck is misdiagnosed as a shortage of the expensive resource everyone assumes is scarce, when the real constraint is a cheaper, differently-scarce resource

background

what everyone would do

The standard industry response to emergency department overcrowding was hiring more physicians and nurses, treating the bottleneck as a staffing shortage the way most emergency departments nationwide diagnosed the same crowding problem.

what they saw

Kathy McCollum's team saw that adding physicians didn't fix the actual constraint, since patients still had to wait for one of a fixed number of treatment beds to open up before any physician could formally assess and treat them, meaning doctors were sitting idle relative to demand not because there weren't enough of them but because there was nowhere to put a patient for them to actually work. Rather than continuing to add the expensive resource, physician headcount, to a system whose real limit was a cheaper, differently-scarce resource, room inventory, the fix was moving physicians directly to where patients already were, working from purpose-built care pods in the waiting room itself rather than waiting for a traditional treatment bed to free up.

the move

Rather than continuing to try to add beds or staff to the traditional treatment-bay model, the hospital moved physicians and advanced practice providers directly into the waiting room itself, working from purpose-built rapid-assessment care pods so patients could be diagnosed, treated and released without ever needing a traditional treatment bed at all — treating the waiting room as clinical space rather than a holding area.

why it works

Treating the waiting room as clinical space rather than a holding area meant physicians could diagnose, treat and release patients without ever needing a traditional treatment bed at all, which addressed the actual bottleneck, bed availability, that no amount of additional hiring could have solved since more doctors couldn't create more beds. Because the fix correctly matched the intervention to the real constraint rather than the assumed one, it delivered results a staffing increase never could have: the hospital's rate of patients who left without being seen dropped significantly, and its EMS ambulance offload times became among the lowest in the state, direct measures of how much faster the actual bottleneck, not the misdiagnosed one, had been relieved. This correct diagnosis, room inventory rather than staff headcount was the real limit, is why the waiting-room care-pod model is now cited as a template for identifying which resource is truly scarce before investing in the expensive assumption everyone defaults to.

the payoff

The hospital's rate of patients who left without being seen dropped significantly after the care-pod model launched, and its EMS ambulance offload times became among the lowest in the state of Maryland, a direct measure of how much faster incoming patients could be handed off rather than queued.

where it breaks

The mechanism depends on correctly diagnosing which resource is actually the binding constraint before acting, misdiagnosing a genuine staffing shortage as a room-inventory problem, or vice versa, would lead to solving the wrong bottleneck entirely, wasting resources on a fix that doesn't touch the actual limit on throughput. It also depends on the expensive resource, here physicians, actually being redeployable to work around the real constraint, a hospital where physicians genuinely couldn't practice safely or effectively outside a formal treatment bed, due to equipment needs, patient acuity, or regulatory requirements, wouldn't have the same option to simply relocate clinical work to available space. And this fix only relieves the specific bottleneck it targets, it doesn't address other potential constraints further down the care pathway, like lab turnaround times, imaging capacity, or inpatient bed availability for admitted patients, meaning solving the waiting-room bottleneck could simply reveal the next constraint in the system rather than eliminating overcrowding altogether.

what came after

The waiting-room care-pod model is now cited among hospital operations leaders as an example of correctly diagnosing a capacity bottleneck as a room-inventory problem rather than a staffing problem, and several other health systems have since piloted similar 'provider-in-triage' or front-end assessment models explicitly built on the same room-versus-staff reframing.

references

1. [1]Health systems reengineer access to careBecker's Hospital Review, 2023beckershospitalreview.com
2. [2]Emergency DepartmentUniversity of Maryland Baltimore Washington Medical Center, 2024umms.org

keep it

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