A data-driven model of an emergency department. (March 2017)

• Record Type: Journal Article
• Authors: Whitt, Ward; Zhang, Xiaopei
• Is Part Of: Operations research for health care. Volume 12(2017:Mar.)
• Page Start: 1
• Page End: 15
• Publication Date: 2017-03
• Subjects: Emergency departments -- Nonstationary stochastic models -- Queueing models -- Nonhomogeneous Poisson process -- Time-varying length-of-stay distribution -- Two-time-scale arrival process model; Medical care -- Mathematical models -- Periodicals; Medical policy -- Mathematical models -- Periodicals; Health services administration -- Mathematical models -- Periodicals; Operations research -- Periodicals; Operations Research -- Periodicals; Health Services Research -- Periodicals; Health Policy -- Periodicals; Delivery of Health Care -- Periodicals; 362.106805
• DOI: 10.1016/j.orhc.2016.11.001
• Languages: English
• ISSNs: 2211-6923

Abstract

Abstract: This paper develops an aggregate stochastic model of an emergency department (ED) based on a careful study of data on individual patient arrival times and length of stay in the ED of the Rambam Hospital in Israel, which was used in a large-scale exploratory data analysis by Armony et al. (2015). This data set is of special interest because it has been made publicly available, so that the experiments are reproducible. Our analysis confirms the previous conclusions about the time-varying arrival rate and its consequences, but we also find that the probability of admission to an internal ward from the ED and the patient length-of-stay distribution should be time varying as well. Our analysis culminates in a new time-varying infinite-server aggregate stochastic model of the ED, where both the length-of-stay distribution and the arrival rate are periodic over a week.