Seeking the solution to packed, slow ERs

Lack of inpatient beds, nursing shortages, slow lab turnarounds and flu season can all contribute to overcrowding and long wait times in hospital emergency departments.

Many factors can lead to ED backups, says Dr. Richard Schwartz, chairman of the department of emergency medicine at Georgia Regents University in Augusta.

He also notes that some patients visit the ED (also known as the emergency room or ER) because they have nowhere else to get routine medical care, while others use it for genuine medical emergencies.

Recent data showed that Georgia patients spend more than two hours on average in an emergency department before they are discharged, according to the government’s Medicare website. The average wait for an ER patient to be admitted as a hospital inpatient is more than four hours.

There can be an increase in risks as well as discomfort when patients have to wait hours before receiving care.

Because emergency departments in different hospitals vary by size and operational setup, it would be hard to find a single strategy for decreasing wait times and overcrowding that could work everywhere, experts say.

But a team of researchers at Kennesaw State University and the University of Buffalo says they may have found an answer.

In the December 2012 issue of the Journal of Emergency Medicine, Jomon Paul and his colleagues described a new method for not only identifying causes of ED overcrowding and wait times but for fixing those problems as well.

“Our goal was to create a generic model that could be used for any hospital regardless of the size,” said Paul, an associate professor in the department of economics, finance, and qualitative analysis at KSU and co-author of the study.

The key element of the study is a discrete event simulation, or DES, model that was developed using data collected from a New York hospital. (The name of the hospital was withheld for confidentiality reasons.)

One of the suggestions from the DES model was to have an additional ED physician during peak hours at the unidentified hospital. When the hospital did this, the ED length of stay for discharge patients was decreased by about 18 percent. This would shave about 20 minutes off an average wait time of 2 hours.

Researchers worked closely with nurses, doctors and other ED staff to make sure that their developed model was as realistic as possible, Paul said.

This practical input is essential, said virtual environment expert Sun Joo (Grace) Ahn, an assistant professor at the University of Georgia’s Grady College of Journalism and Mass Communication.

“Ensuring that the simulation is as realistic as possible would help make it effective,” Ahn said.

The DES model allowed researchers to identify anything that might be causing overcrowding and long wait times, then test the possible solutions in the computer simulation before testing the solutions in the actual ED.

“You want to capture any kind of uncertainties,” Paul said.

Not everyone is in favor of the DES approach.

Schwartz, the emergency physician, said DES is one of many ways to find a solution for ED overcrowding, but individual hospitals have to figure out what method works best for them.

“Using a computer simulation is one way of tracking those numbers . . . but there are manual ways of coming to the same type of tracking and conclusions where you identify the bottlenecks in your process,” Schwartz said.

Those “bottlenecks” include any factors affecting performance, such as ED staff shortages or a lack of available beds for patients who need to be admitted.

Paul said the DES model takes 15 minutes to an hour to show results. The model can be used to predict how any kind of scenario, such as a natural disaster, will affect a hospital’s normal operations.

“Everybody benefits if you have a good tool,” Paul said.

April Bailey received a bachelor’s degree in print journalism, and is currently pursuing a master’s degree in health and medical journalism at the University of Georgia.