Factors Predicting Overcrowding in Emergency Room of a University Hospital
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Abstract
The aim of this cross-sectional predictive study was to identify the predicted factors of emergency room (ER) overcrowding. The 4,039 patients who visited ER during March to May 2019 were selected. National Emergency Department Overcrowding Study (NEDOCS) was used to measure the degree of crowding. Every 4 hour, ER overcrowding was assessed by NEDOCS 273 times and patient’s information was retrieved from patient’s folder. Multiple logistic regression analysis was used to identify factors predicted ER overcrowding.
In conclusion according to research findings, decreasing waiting time of laboratory result report, decreasing boarding time in ER, and guideline or policy development may improve overcrowding in ER.
The research found that factors predicting ER overcrowding were number of patients who used ventilator (ORadj = 3.75, 95%CI: 2.19-6.44), number of patients who waited to be boarding from ER more than 2 hours (ORadj = 2.75, 95%CI: 1.15-6.55), number of patients who waited to triage (ORadj = 2.43, 95%CI: 1.82-3.24), number of patients who waited for laboratory result more than 2 hours (ORadj = 1.81, 95%CI: 1.38-2.38), number of patient in ER (ORadj = 1.79, 95%CI: 1.42-2.26), number of patients who waited to see doctor (ORadj = 1.48, 95%CI: 1.28-1.71), and number of doctors who delivered care in ER (ORadj = 1.45, 95%CI: 1.20-1.74)
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References
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