Data Simulations Reduce ED Crowding

By Katie Wike, contributing writer

Harnessing the power of data to simulate patient flow through the emergency department shows how to reduce ED crowding.

Researchers from the University of Florida have found that, through the use of data-driven simulations, they can better predict and prevent emergency department crowding. According to iHealth Beat , UF team analyzed data from both an average ED and an average academic hospital ED.

“We investigated two qualitatively distinct ED environments and found that similar changes to process of care – such as adding resources implementing fast track mechanisms, or systematically reducing boarding times – had very different effects on patient flow,” said researchers in the report, published by BioMed Central.

They studied the effects of factors like door-to-event times per patient, rates of patients leaving without receiving care, occupancy level, resource use, and staffing. “With a shortage of ED physicians, finding more appropriate sources of care for patients with less acute issues could help more than reducing wait times. A shortage of beds is a bigger problem at academic hospitals, however, so adding doctors doesn't necessarily improve patient flow at those facilities,” explains Fierce Health IT.

“The model was also able to identify a point of diminishing returns. It found that adding one doctor in the average ED reduces mean length of stay by one hour, but adding a second doctor provides no further improvement.”

Overall, researchers found that using data to predict the changes in emergency department flow was a helpful tool for hospitals seeking to avoid overcrowding while not wanting to experiment in their ED.