News Release

Utilizing data to predict hospital wait times – it can save more than your patience!

New research streamlines emergency departments, saves money and improves patient satisfaction

Peer-Reviewed Publication

Institute for Operations Research and the Management Sciences

INFORMS Journal Manufacturing & Service Operations Management New Study Key Takeaways:

  • Researchers develop a method to more accurately predict and showcase hospital wait times to patients and emergency personnel by using new information that is learned in the intake process.
  • This method provides more up-to-date wait times allowing patients and paramedics to make choices about which emergency department to go to.
  • This process streamlines patient flow, creates more uniform spread of patients and lowers congestion across emergency departments, and could improve patient outcomes and satisfaction.


BALTIMORE, MD, June 8, 2023 – Headed to the emergency department (ED)? How should you decide which nearby ED to go to so that you can get in and out? New research in the INFORMS journal Manufacturing & Service Operations Management uncovers how best to showcase hospital wait times to not only save your patience, but increase efficiency, more accurately route emergency vehicles and save money.

“By showcasing anticipated waiting-time estimates, patients and ambulance staff can be better informed in selecting an ED from a group of EDs, which can lead to a more uniform spread of patients across the system,” says Ho-Yin Mak of Georgetown University and one of the study’s authors.

“It’s no secret that waiting-time estimates can help improve patients’ overall satisfaction, but current methods focus on point forecasts, thereby completely ignoring several underlying factors. Communicating only a point forecast to patients can be uninformative and potentially misleading.”

In this study, “Probabilistic Forecasting of Patient Waiting Times in an Emergency Department,” the authors consider calendar effects, demographics, staff count, ED workload resulting from patient volumes and the severity of the patient condition.

“Our model allows for dynamic updating and refinement of waiting-time estimates as patient- and ED-specific information (e.g., patient condition, ED congestion levels) is revealed during the waiting process,” says study co-author Siddharth Arora of the University of Oxford.

The authors also reiterate that this method gives low-acuity patients and first responders a more comprehensive picture of the possible waiting trajectory and provides more reliable inputs for them to make a well-informed decision.

“For emergency healthcare service providers, probabilistic waiting-time estimates could assist in ambulance routing, staff allocation and managing patient flow, which could facilitate efficient operations and cost savings, and aid in better patient care and outcomes,” says co-author James Taylor, also of the University of Oxford.


Link to full study.


About INFORMS and Manufacturing & Service Operations Management

INFORMS is the leading international association for operations research and analytics professionals. Manufacturing & Service Operations Management, one of 17 journals published by INFORMS, is a premier academic journal that covers the production and operations management of goods and services including technology management, productivity and quality management, product development, cross-functional coordination and practice-based research. More information is available at or @informs.




Ashley Smith



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