Patient Streaming to Improve Flow and Safety in Hospital Emergency Departments

Time, Date, Venue

July 1, 2011 Friday 11.00-12.00

University College London

1st floor Exec-ed room, Engineering Front Building
("Malet place" in Google maps)


Crisis level overcrowding conditions in Emergency Departments (ED's) have led hospitals to seek out new patient flow designs to improve both responsiveness and safety.   In this talk we discuss two promising approaches for separating patients into streams to achieve these objectives.

First, we analyze a  new patient streaming mechanism that has attracted attention and experimentation in the emergency medicine community in which ED beds and care teams are segregated and patients are “streamed” based on predications of patient disposition (i.e., whether they will be discharged or admitted to the hospital). We use a combination of analytic and simulation models to determine whether such a streaming policy can improve ED performance, where it is most likely to be effective, and how it should be implemented for maximum performance. Our results suggest that the concept of streaming can indeed improve patient flow, but only in some situations.  We also find that, to take full advantage of streaming, physicians assigned to admit patients should prioritize upstream (new) patients, while physicians assigned to discharge patients should prioritize downstream (old) patients.

Second, because we observe that streaming based on patient disposition is most effective when the difference between Admit and Discharge patients is greatest, we develop and discuss an entirely new streaming mechanism that separates patients on the basis of complexity.  That is, in addition to classifying patients on the basis of clinical urgency, the triage nurse classifies patients on the basis of the estimated number of interactions as a proxy for complexity.   Experimental data from the literature indicate that such classifications can be made with reasonable accuracy.  Results from our analytic and simulation models suggest that, even with some misclassification error, adding complexity information to conventional urgency triage classification can be used to achieve substantial improvements in patient length of stay and risk of adverse events. 


Professor Hopp joined the Ross School in 2007 after 23 years on the faculty of Northwestern University. His research focuses on the design, control and management of production, supply chain and work systems. He has published widely in the academic literature in these areas and was Editor-in-Chief of the journal Management Science from 2003 to 2008. Hopp is co-author of the text Factory Physics, which was named the IIE Book of the Year, and author of a new book Supply Chain Science. He has won a number of teaching and research awards, including being named a Fellow of INFORMS, IIE, MSOM and POMS. He is also an active industry consultant, whose clients have included Abbott Laboratories, Bell & Howell, Black & Decker, Case, Dell, Ford, Eli Lilly, Emerson Electric, General Motors, John Deere, IBM, Intel, Motorola, Owens Corning, Texas Instruments, Whirlpool, Zenith, and others.