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Arch Hellen Med, 34(6), November-December 2017, 814-820


Methodology for measurement of emergency department overcrowding: A field study

M. Chouzouris,1 J. Hyosung,2 C. Kinopoulos,3 P. Xenos,1 P. Tinios,1 M. Nektarios1
1Department of Statistics and Insurance Science, School of Finance and Statistics, University of Pireus, Pireus, Greece,
2Barcelona Graduate School of Economics, Barcelona, Spain,
3Department of Informatics, Athens University of Economics and Business, Athens, Greece

OBJECTIVE Design and testing of a methodological tool for the measurement of emergency department (ED) overcrowding, using continuous quantitative variables.

METHOD Using the total time a patient spends in the emergency department, a new indicator, the overcrowding (OC) index was created and evaluated. The tool was applied for a period of three years, using patient data from eight public hospitals in Catalonia. The initial database of 2,757,780 episodes of ED visits from 1.1.2012 to 31.12.2014 was filtered for errors and duplicates to give a final dataset of 2,086,404 episodes and 1,014,646 individuals. The package STATA 13 was used for the statistical analysis.

RESULTS OC appeared to increase in the summer, at weekends and during the night. Certain categories of disease related to seasonality might be correlated with an increase in the OC index. Specifically, injuries and poisonings scored a maximum increase of approximately 167.1 visits while respiratory diseases were maximized in December (1,651.1 visits). The August peak effect was the greatest in the large hospitals while several hospitals experienced a reduced OC index in the summer. Overcrowding was heterogeneous, as in one hospital the OC index was reduced by 0.295, while in another it was increased by 0.276.

CONCLUSIONS A detailed and robust patient tracking dataset and in depth analysis of OC measurements are required for effective ED workflow management and successful alleviation of seasonal ED crises. The use of the OC index reveals temporal trends in OC and a correlation effect with time interval variables.

Key words: Emergency department, Hospital, Overcrowding, Triage level.

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