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Applying advanced analytics to guide emergency department operational decisions: A proof-of-concept study examining
R Andrew Taylor1, Arjun Venkatesh1, Vivek Parwani1
1Yale University School of Medicine, Department of Emergency Medicine, United States.
Background:
Emergency Department (ED) leaders are increasingly confronted with large amounts of data with the potential to inform and guide operational decisions. Routine use of advanced analytic methods may provide additional insights.
Objectives:
To examine the practical application of available advanced analytic methods to guide operational decision making around patient boarding.
Methods:
Retrospective analysis of the effect of boarding on ED operational metrics from a single site between 1/2015 and 1/2017. Times series were visualized through decompositional techniques accounting for seasonal trends, to determine the effect of boarding on ED performance metrics and to determine the impact of boarding "shocks" to the system on operational metrics over several days.
Results:
There were 226,461 visits with the mean (IQR) number of visits per day was 273 (258-291). Decomposition of the boarding count time series illustrated an upward trend in the last 2-3 quarters as well as clear seasonal components. All performance metrics were significantly impacted (p<0.05) by boarding count, except for overall Press Ganey scores (p<0.65). For every additional increase in boarder count, overall length-of-stay (LOS) increased by 1.55min (0.68, 1.50). Smaller effects were seen for waiting room LOS and treat and release LOS. The impulse responses indicate that the boarding shocks are characterized by changes in the performance metrics within the first day that fade out after 4-5days.
Conclusion:
In this study regarding the use of advanced analytics in daily ED operations, time series analysis provided multiple useful insights into boarding and its impact on performance metrics.
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