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Researchers develop model to help ERs predict and minimize long wait times


When every second counts, the last thing you want to see is a line. Yet, all too often, emergency room patients are confronted with delays that prevent them from receiving care in a timely manner.

The Stanford Graduate School of Business explored this issue in a recent story about a research team that developed a way to use predictions of emergency room congestion to send patients to less busy ERs.

As the story explains, hospitals already use data on waiting room congestion to divert patients, but this data relies on how busy the emergency department is at that moment. The new model, which was developed by Stanford assistant professor Kuang Xu, PhD, and Carri Chan, PhD, an associate professor at Columbia Business School, takes existing congestion models one step further by incorporating predictions of how busy the emergency room is likely to be in the future. This, the researchers say, could help hospitals reduce wait times and prevent further congestion.

“Delays can have significant, life-changing ramifications,” Xu said. “Imagine a situation where a hospital gauges its own level of business and puts a notice on the website that says, ‘We’re really busy right now; if you’re not that sick, don’t come in.’ That simple change could improve delays significantly.”

Previously: Emergency room efficiency could rise by empowering doctors, new study findsImproving patient satisfaction and turn-around time in an emergency department and Speed it up: Two programs help reduce length of stay for emergency-room visitors
Photo by iStock/abalcazar

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