Emergency Department overcrowding is a problem that even appears to increase the death rate for patients.
The study does have its limitations, but it is logically consistent with being so busy that we are occasionally distracted from what we are doing and having that result in mistakes. The study does not track mistakes, but does compares outcomes of patients adjusted for the severity of triage category.
Look below at the distribution among the triage categories. The first graph shows that very few patients are triaged as 1 (very critical), while a large number are triaged as 5 (not so critical).
The next graph shows that most deaths are in triage category 3. Green is the NOC (Not OverCrowded) group and blue/gray is the OC (OverCrowded) group.
The last graph shows that even though there were only a tiny number of patients in triage category 1, they are much more likely to die than everyone else. This is not quite a Pareto distribution (rather than the allegedly normal distribution of a Gaussian bell curve), where 20% of people are responsible for 80% of what is being measured (20% of employees produce 80% of problems or 20% of employees produce 80% of revenue)., 
So what can we do to reduce overcrowding and possibly improve our ability to save lives?
I walked in to the emergency department (ED) about 10 minutes early for my 3 pm shift and as I signed into my computer I stared disbelieving at the screen. “Only 10 people in the waiting room?” I said to the charge nurse, who was casually flipping through some paperwork, and the off-going attending, who had assumed a relaxed pose in his chair, knowing his day was over. “It’s the Ebola,” they replied in unison.
The night before, our hospital had admitted a patient suspected of having Ebola directly to the critical care unit, and the news of this event had spread rapidly over the local news by early morning.
We should take advantage of the Ebola outbreak, while it lasts.
EMS can proudly announce that we are transporting these Ebola patients.
An added benefit will be that employees might actually pay attention to isolation precautions.
It could work.
“Sixty-year-old female with right-sided facial droop, right-arm and right-leg weakness, started 4 hours ago,” stated the lead female paramedic to me as I watched my senior resident and the neurology resident start their evaluation. Then she leaned over and whispered in my ear, “She says she didn’t call for help right away because she didn’t want to be brought to the Ebola hospital.”
OK. It is not a perfect plan, but it might be worth announcing today.
Subgroup analysis shows that mortality was higher even after accounting for triage differences, and suggests that there may even have been an element of “under-triage” on OC shifts, as the mortality rate was 70% higher in Triage Category 4, but the analysis method lacked sufficient power to properly distinguish the relative effects of presenting condition and ED treatment. Controlling for triage will be challenging in future studies if under-triage is an issue at times of overcrowding.
 Power laws, Pareto distributions and Zipf’s law
M. E. J. Newman
Department of Physics and Center for the Study of Complex Systems, University of Michigan, Ann Arbor,
MI 48109. U.S.A.
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