University of Illinois Urbana-Champaign and OSF HealthCare are working on the computer-built model dubbed discrete event simulation.
This model allows the team to change variables and test different scenarios, as well as allows the computer to predict which types of patients might be arriving in the emergency department and what kinds of resources would be needed to treat them.
“That involves looking at past historical data, applying these machine learning prediction techniques, and suggesting that well, instead of just saying our average number of patients on a Tuesday, saying, ‘Well, this is a Tuesday in August,’ and adding as many different variables in that we think are relevant, to predict how many patients we’ll have at the door,” William Bond, MD, emergency department physician at OSF Saint Francis Medical Center, told the publication.
The research is funded through a $100,000 grant and aims to solve the problem of overcrowding in emergency departments.
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