Weiss SJ, Ernst AA, Johnson A, Sills MR. Use of the NEDOCS overcrowding scale in a pediatric ED. Society for Academic Emergency Medicine’s Annual Meeting, San Francisco, May 2006.

1. Background: Objective measures of emergency depart-
ment (ED) workload may indicate threshold values at
which ambulance diversion is requested. We hypothe-
sized that over time, the threshold for diversion might
rise as providers have become accustomed to an in-
creased workload.
Objective: To determine if the threshold for ambulance
diversion has changed over time.
Methods: Design: This was a retrospective, observational
study. We used two validated measurements of ED work-
load (Workscore and ED Work Index (EDWIN)). Setting:
An academic ED with 46,000 adult visits annually. Obser-
vations: Instances of diversion were obtained from an
independent database for 10/1/02 through 12/31/05.
Emergency department metrics were obtained every
10 minutes, and the Workscore and EDWIN score were
calculated for the time of the beginning of each instance
of ambulance diversion. Data Analysis: The data were
analyzed using a time-series regression model controlling
for time of day, day of week, and season, using an auto-
regressive correlation with a lag of 5 diversion events.
Results: Neither measure showed a significant change in
the threshold for ambulance diversion over time, and the
Workscore and EDWIN were well correlated (r = 0.58).
The slope representing the threshold trend over time
was not statistically different from zero (Workscore p =
0.827; EDWIN p = 0.355). Of the three factors controlled
for, two were significant. Time of day demonstrated a sig-
nificantly greater diversion threshold during the 2 PM-10
PM interval (Workscore p = 0.0002; EDWIN p = 0.0001).
The day-of-the-week effect was also significant, with
Tuesdays showing the greatest threshold for diversion
(Workscore p = 0.0001; EDWIN p = 0.0445).
Conclusions: The threshold for ambulance diversion in
this ED has not changed significantly over the time period
studied. This may be due to provider consistency, but fur-
ther investigations should determine how other factors
(e.g., time of day) affect the diversion threshold, and if
these results are generalizable.
54 Use of the National Emergency Department
Overcrowding Scale (NEDOCS) in a Pediatric
Emergency Department
Steven J Weiss, Amy A Ernst, Ashira Johnson,
Marian R Sill.
University of New Mexico, Albuquerque, NM,
Jackson Memorial Hospital, Miami, FL,
University of Colorado Health Sciences Center,
Denver, CO
Objective: Emergency department (ED) overcrowding
has been quantified with a scale that reflects the degree
of overcrowding (National ED Overcrowding Scale [NE-
DOCS]) in adult academic EDs. However, validity of the
5-question NEDOCS has not been established for a pedi-
atric ED (PED). The hypothesis of this study was that PED
overcrowding was (1) quantifiable, and (2) mirrored by
the NEDOCS, as a valid model.
Methods: Objective data were determined by prospec-
tively collecting 23 variables at 42 random site-sampling
times in one PED. Data were obtained by counting pa-
tients, determining patients’ times, and obtaining infor-
mation from registration, triage, and ancillary services.
The five questions needed for the NEDOCS were among
the data collected. Expert consensus (EC) was obtained
using a Likert scale completed by the charge nurse and
emergency physicians who rated the degree of over-
crowding. NEDOCS score and EC were compared to
determine predictive validity of the model for a PED.
Pearson correlation and multivariable linear regression
were used to evaluate individual variables.
Results: Overcrowding based on EC was found at 18/42
(43%) times in the PED. In the PED, NEDOCS was 28%
sensitive and 96% specific for predicting overcrowding
based on EC. High correlations existed between EC and
NEDOCS (0.68), number of patients in the waiting room
(0.74), full rooms (0.64), and total registered patients
(0.65). In a multivariable analysis, a combination of pa-
tients in the waiting room and total registered patients
had the highest correlation (0.80) with EC.
Conclusions: Overcrowding is quantifiable in a PED.
A combination of two variables, total registered patients
and patients in the waiting room, may be a better model
for PED overcrowding than the NEDOCS score.
55 Care Management Unit Impact on
Emergency Department Overcrowding
Varnada A Karriem-Norwood, Leon L Haley,
Lorie Click.
Emory University, Atlanta, GA
Background: Emergency department (ED) overcrowd-
ing is a national crisis. Frequently, admitted patients
remain boarders in the ED for more than 24 hours.
Admitted patients usually no longer require emergent
care, yet must be cared for by ED resources. Admitted
patients in the ED impede the movement of all remaining
patients.
Objectives: To evaluate how combining a clinical deci-
sion unit with case management would impact ED over-
crowding.
Methods: This was a prospective observation study. The
care management unit (CMU) consists of 7 beds, avail-
able 24/7 with ED faculty coverage. 4 case managers
were available to educate patients, arrange primary care
follow-up, maintain direct patient contact, and manage
a database. Patients were admitted with chest pain, asthma,
heart failure, or hyperglycemia. All patients were placed
on protocols developed via a collaborative effort with
emergency and internal medicine. Specific data points in-
cluded reduce short-stay admission, improve utilization
of intermediate care beds, reduce ED length of stay, and
improve referrals to primary care.
Results: Between August 2003 and April 2004 1,325 pa-
tients were admitted to the CMU. 1,147 patients, 85%,
were successfully discharged. 175 patients were subse-
quently admitted and 3 patients were transferred back
to the general ED. Potentially, we reduced hospital admis-
sions by 1,147. The average length of stay in the CMU was
18.58 hours. Average ED time fell from 5.6 hours to 5.1
hours, average waiting time for beds fell from 8 hours
to 5 hours, and average number of telemetry admissions
waiting for beds fell from 11.83 to 7.83.
Conclusions: Through a multidisciplinary approach, we
successfully combined observation medicine and case
management. We were able to decrease ED overcrowding
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